34 Commits

Author SHA1 Message Date
steve d44d11e4fe Bump engine version to 3.2.2 2026-04-14 21:48:55 +01:00
steve 574370e8d1 Remove AMD ROCm support — CPU and NVIDIA only
BREAKING: Remove Dockerfile.rocm, compose.rocm.yaml, and ROCm image
build/push from the release pipeline. Remove AMD quick-start and ROCm
references from README and DEVELOPER docs. Update docker-deployment
and developer-docs specs to reflect CPU + NVIDIA only.

The ROCm variant added significant complexity (4.2GB torch wheel,
>20GB container) with limited usage. Users on AMD GPUs should stay
on engine v3.2.x or switch to CPU mode.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-06 16:39:37 +01:00
steve 17b19999de Switch nvidia and rocm Dockerfiles from onnxruntime to torch
Nvidia: install torch+torchvision from PyTorch cu130 index, drop
onnxruntime-gpu. ROCm: use local torch wheel with rocm6.4 index for
torchvision, clean up nvidia remnants from the venv.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-06 16:13:41 +01:00
steve bb78f4ea80 Fix 500 error on notes with slashes in title, bump engine to 3.2.1
Sanitize / and \ in note titles and filenames when writing to the
staging directory — a title like "/reset skill" was interpreted as a
path separator, causing a FileNotFoundError and a 500 from the jobs
endpoint. Also add PRAGMA busy_timeout=5000 to SQLite connections to
prevent immediate failure under concurrent write load.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-06 16:12:58 +01:00
steve 223ff2cf5d Latest changes all archived 2026-04-04 22:50:19 +01:00
steve e9a282ddb1 Document KB_BULK_SAFETY_PERCENT in README, DEVELOPER, MCP, and SKILL docs
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-04 22:43:42 +01:00
steve b5a203d2aa Add bulk operations and remove collections abstraction
- Add bulk delete, bulk tags, and bulk set-tags engine endpoints
  (POST /api/v1/bulk/delete, /bulk/tags, /bulk/set-tags)
- Filter-based selection: by tags, doc_type, ID list, ID range
- Safety threshold (KB_BULK_SAFETY_PERCENT, default 70%) prevents
  accidental mass operations unless force=true
- Synchronous execution with audit trail via jobs table
- Add kb_bulk_delete, kb_bulk_tags, kb_bulk_set_tags MCP tools
- Add kb bulk-remove, bulk-tag, bulk-set-tags CLI commands
- Remove collection abstraction from MCP server (use tags instead)
- Remove kb_set_collection MCP tool
- Update SKILL.md, MCP.md, README.md documentation

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-04 22:34:47 +01:00
steve 0c124c4ab7 Bump engine version to 3.0.1 2026-04-04 12:42:32 +01:00
steve da5b8435bc Add configurable allowed hosts for MCP remote access (KB_MCP_ALLOWED_HOSTS)
The MCP SDK's DNS rebinding protection rejects remote clients with 421
when the Host header isn't in the allowlist. Add KB_MCP_ALLOWED_HOSTS env
var (comma-separated IPs/FQDNs) to configure additional allowed hosts
while keeping localhost always permitted.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-04 12:39:43 +01:00
steve e39e00a2c0 Add MCP auth status to kb_status and update server instructions
- kb_status now returns authenticated: true/false so clients can verify auth
- Server instructions mention Bearer token auth requirement
- Add .env, .venv/, test_mcp_client.py to .gitignore

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-04 12:04:12 +01:00
steve d078af9ad3 Split MCP docs into MCP.md with AI tool setup examples
Move MCP server documentation from README into dedicated MCP.md.
Add configuration examples for Claude Code, VS Code, Cursor,
Windsurf, and JetBrains IDEs.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-02 22:03:41 +01:00
steve b3dce188e1 Fix version check failing on non-200 status responses
When the engine returns 401 (auth required) or other non-200 responses,
the version check was parsing the error body, getting an empty version
string, and fatally exiting. Now skips the check on non-200 responses
and lets the actual API call surface the real error.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-02 21:52:24 +01:00
steve 0dc3065979 Update README for v3.0.0 — add MCP server docs, updatenote, fix version refs
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-02 21:45:31 +01:00
steve e7136a4a20 Add MCP server, note mutation endpoint, and updated_at tracking (v3.0.0)
New MCP server (mcp/) exposes kb operations as native MCP tools over
Streamable HTTP with Bearer token auth. Supports collections via tag
conventions, chunked file uploads, and agent-side search patterns.

Engine gains PATCH /api/v1/notes/{id} for in-place note updates with
transactional re-chunk/re-embed, and updated_at column on documents.

Go client adds updatenote command and Patch HTTP method.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-02 21:34:55 +01:00
steve adeba21712 Bump client version to 2.2.1 2026-04-02 16:18:06 +01:00
steve 2d179af557 Fix search human-mode output to match engine API response
The Go client struct expected a nested document object and top-level
page/section fields, but the engine returns flat results with metadata
in chunk_metadata. This caused empty display for title, type, tags,
page, and section in human output mode.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-02 16:17:35 +01:00
steve a6bab5e55e Add CPU-only Docker image and fix release tag naming
- Add Dockerfile.cpu and compose.cpu.yaml for CPU-only deployments
- Use sentence-transformers[onnx] + CPU-only torch for ~4x smaller image
- Fix release script: separate git tags (engine-v*) from Docker tags (v*)
- Add CPU image to release build/push pipeline
- Update README with CPU deployment instructions

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-02 16:02:00 +01:00
steve c5191df9c0 Bump client version to 2.2.0 2026-03-31 20:50:17 +01:00
steve afbe270181 Replace implicit note shorthand with explicit addnote command and split README
Two changes:

1. structured-add-commands: The implicit note shorthand (kb "text") caused
   accidental note creation from mistyped commands. Replaced with explicit
   kb addnote <text> command. Root command reverts to standard Cobra
   behaviour. Updated examples, tests, SKILL.md, and specs.

2. split-readme-developer-docs: Moved build-from-source instructions, release
   process, API reference, and ROCm migration notes from README.md into a
   new DEVELOPER.md. README now links to DEVELOPER.md for dev workflows.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 20:48:22 +01:00
steve 9e957f1a9a Added pycache to gitignore 2026-03-30 07:26:16 +01:00
steve bbe6a5e909 Add dev-up script and archive kb-title-in-chunks change
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-30 07:25:22 +01:00
steve 743102aee4 Bump client version to 2.1.1 2026-03-29 21:09:55 +01:00
steve 0f3b3be59f Bump engine version to 2.1.0 2026-03-29 21:06:04 +01:00
steve 2fa2ac1134 Reject single bare word as implicit note shorthand
Single unrecognized words now print an error with usage hint instead of
being submitted as a note. Prevents typos from creating junk notes.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-29 21:03:52 +01:00
steve b2176c36ea Chunk enrichment: prepend document title to embeddings
Adds enriched_text column to chunks table that prepends document title
(and section header when present) to chunk text. Embeddings and FTS now
use enriched text for better search relevance. Includes schema migration
with backfill for existing data.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-29 21:03:48 +01:00
steve 5f9946efc9 Added manual download to README 2026-03-29 14:03:35 +01:00
steve ea3d5707e1 Bump client version to 2.1.0 2026-03-29 13:58:42 +01:00
steve 7f4decee26 Reindex command, implicit note shorthand, add→addfile rename
- Add `kb reindex` command with confirmation prompt and --yes flag
- Add implicit note shorthand: `kb "my note"` submits a note directly
- Rename `add` to `addfile`, remove --note/--title/--type flags
- Add client-side file extension validation before upload
- Add `kb examples` command for common usage patterns
- Update README, SKILL.md, and main specs
- Archive completed changes and sync delta specs

BREAKING: `kb add` renamed to `kb addfile`, `kb add --note` replaced by `kb "text"`

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-29 13:58:04 +01:00
steve 528a09ca90 Independent client/engine versioning with compatibility check
Split release.sh into release-client.sh and release-engine.sh for
independent release cadences. Client checks engine version on first
API call and hard-fails if engine is below MinEngineVersion.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-28 15:59:16 +00:00
steve b04823e67b Store original documents for download after ingestion
Persist uploaded files to {data_dir}/documents/{content_hash}{ext} after
successful ingestion. Add GET /documents/{id}/file endpoint for retrieval,
delete stored files on document deletion, and add `kb export` client command.
Includes schema migration, tests, and spec updates.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-28 15:16:27 +00:00
steve 6a4bce4659 Bump version to 2.0.5 2026-03-26 23:08:48 +00:00
steve 4590c124ad Merge pull request 'Upload-time dedup, FTS5 query sanitization, release guard' (#1) from 2.0.5 into main
Reviewed-on: #1
2026-03-26 23:06:08 +00:00
steve 6fec627503 Upload-time duplicate detection, FTS5 query sanitization, release guard
- Reject duplicate uploads at the API boundary (HTTP 409) instead of
  silently skipping in the background worker. Checks both ingested
  documents and in-flight jobs via content_hash on the jobs table.
- Go client handles 409 with distinct messages for already-imported
  documents vs already-queued jobs.
- Sanitize FTS5 search queries by quoting each token to prevent syntax
  errors from special characters like ?, *, ", (), AND, OR, NOT.
- Add try/except safety net around FTS5 execute for edge cases.
- Add main branch guard to release.sh to prevent releasing from
  feature branches.
- Update specs and README to reflect new behaviour.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 23:05:07 +00:00
steve 63654a59b8 Fix tea asset upload syntax in release script
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 22:10:48 +00:00
152 changed files with 8623 additions and 508 deletions
+8
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@@ -1 +1,9 @@
examples/
.claude/
__pycache__/
engine/data/
TMP/
.env
.venv/
test_mcp_client.py
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@@ -0,0 +1,96 @@
# Developer Guide
Instructions for building from source, releasing, and contributing to kb.
## Building from source
### Engine
```bash
cd engine
# NVIDIA GPU
KB_DATA_PATH=~/kb-data docker compose -f compose.nvidia.yaml up -d
```
### Client
```bash
cd client
make build # produces ./kb binary
make all # or cross-compile: dist/kb-{os}-{arch}
```
## Building and releasing
Client and engine are versioned independently via `client/VERSION` and `engine/VERSION`. Each has its own release script and git tag prefix.
### Release client
```bash
./release-client.sh --gitea # patch bump, release via Gitea
./release-client.sh --github --minor # minor bump, release via GitHub
./release-client.sh --gitea --no-increment # release current version as-is
./release-client.sh --gitea --dry-run # preview without doing anything
```
Creates tag `client-vX.Y.Z`, builds Go binaries for all platforms, and creates a Gitea/GitHub release with binaries attached.
The client embeds a `MinEngineVersion` (from `client/MIN_ENGINE_VERSION`) and will hard-fail if the connected engine is too old.
### Release engine
```bash
./release-engine.sh --gitea # patch bump, release via Gitea
./release-engine.sh --github --minor # minor bump, release via GitHub
./release-engine.sh --gitea --no-increment # release current version as-is
./release-engine.sh --gitea --dry-run # preview without doing anything
```
Creates tag `engine-vX.Y.Z`, builds NVIDIA and CPU Docker images, creates a Gitea/GitHub release, and pushes images to the registry.
### Checking versions
```bash
# Client
kb --version
# Engine
curl http://localhost:8000/api/v1/status | jq .version
```
### Docker images
Images are pushed to `docker.dcglab.co.uk/dcg/kb/engine` with tags:
- `engine-v2.0.6-nvidia` / `engine-v2.0.6-cpu` — versioned
- `latest-nvidia` / `latest-cpu` — latest release
Override the registry and org via environment variables:
```bash
REGISTRY=ghcr.io IMAGE_ORG=myorg ./release-engine.sh --github
```
## API reference
All endpoints are under `/api/v1/`. Requires `Authorization: Bearer <key>` header when `KB_API_KEY` is set.
| Method | Endpoint | Description |
|---|---|---|
| `GET` | `/health` | Health check (bypasses auth) |
| `POST` | `/search` | Hybrid search (JSON body) |
| `POST` | `/jobs` | Upload file/note for ingestion (multipart, returns 202 or 409 if duplicate) |
| `GET` | `/jobs` | List ingestion jobs |
| `GET` | `/jobs/{id}` | Job details |
| `GET` | `/documents` | List documents |
| `GET` | `/documents/{id}` | Document details with chunks |
| `GET` | `/documents/{id}/file` | Download original file |
| `DELETE` | `/documents/{id}` | Remove a document (and stored file) |
| `PUT` | `/documents/{id}/tags` | Add/remove tags |
| `GET` | `/tags` | List all tags |
| `GET` | `/status` | Engine status, GPU info, DB stats |
| `POST` | `/reindex` | Re-embed all chunks |
| `POST` | `/bulk/delete` | Bulk delete documents by filter |
| `POST` | `/bulk/tags` | Bulk add/remove tags by filter |
| `POST` | `/bulk/set-tags` | Bulk replace tags by filter |
+174
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@@ -0,0 +1,174 @@
# MCP Server (Agent Integration)
The MCP server exposes kb operations as native MCP tools, so agents can search, add notes, upload files, and manage documents without shelling out to the CLI.
## Start the MCP server
The compose files include a `kb-mcp` service alongside the engine. Set `KB_MCP_API_KEY` to require Bearer token auth from connecting agents:
```bash
KB_API_KEY=your-engine-key KB_MCP_API_KEY=your-agent-key \
docker compose -f engine/compose.nvidia.yaml up -d
```
Or run the MCP server standalone:
```bash
docker run -d --name kb-mcp \
-p 3000:3000 \
-e KB_ENGINE_URL=http://your-engine-host:8000 \
-e KB_API_KEY=your-engine-key \
-e KB_MCP_API_KEY=your-agent-key \
--restart unless-stopped \
docker.dcglab.co.uk/dcg/kb/mcp:latest
```
## MCP tools
| Tool | Description |
|---|---|
| `kb_search` | Hybrid search with optional tag/type filters |
| `kb_addnote` | Add a text note (queued for async ingestion) |
| `kb_update_note` | Update an existing note in place |
| `kb_get` | Get document details by ID or source path |
| `kb_delete` | Permanently delete a document by ID |
| `kb_status` | Engine health and statistics |
| `kb_jobs` | Ingestion queue status |
| `kb_upload_start` | Start a chunked file upload |
| `kb_upload_chunk` | Upload a base64-encoded file chunk |
| `kb_upload_finish` | Finish upload and submit for ingestion |
| `kb_bulk_delete` | Delete multiple documents matching a filter |
| `kb_bulk_tags` | Add/remove tags on multiple documents |
| `kb_bulk_set_tags` | Replace all tags on multiple documents |
## Organising with tags
Use tags to separate agent data from user documents. For example, an agent can tag all its notes with `agent:mybot` and filter by that tag when searching. This is a naming convention — configure it in your agent's system prompt. No special server-side enforcement is needed.
Bulk tools accept filter-based selection (by tags, doc_type, ID list, or ID range) so agents can manage thousands of documents in a single call instead of looping. A safety threshold (default 70%, configurable via engine env var `KB_BULK_SAFETY_PERCENT`) prevents accidental mass operations unless `force: true` is set.
## MCP server configuration
| Variable | Default | Description |
|---|---|---|
| `KB_ENGINE_URL` | `http://localhost:8000` | Engine API URL |
| `KB_API_KEY` | (none) | Engine API key |
| `KB_MCP_API_KEY` | (none) | Bearer token required from agents (disabled if unset) |
| `KB_MCP_PORT` | `3000` | Port to listen on |
## Connecting AI coding tools
The kb MCP server uses **Streamable HTTP** transport at `http://your-host:3000/mcp`. Below are configuration examples for popular AI coding tools.
### Claude Code (CLI / Desktop / Web)
Add the server to your project or user settings:
```bash
claude mcp add kb-server --transport http http://localhost:3000/mcp
```
Or add it manually to `.claude/settings.json` (project) or `~/.claude/settings.json` (global):
```json
{
"mcpServers": {
"kb-server": {
"type": "http",
"url": "http://localhost:3000/mcp",
"headers": {
"Authorization": "Bearer your-agent-key"
}
}
}
}
```
### VS Code (GitHub Copilot)
Add to your `.vscode/settings.json` (workspace) or user settings:
```json
{
"mcp": {
"servers": {
"kb-server": {
"type": "http",
"url": "http://localhost:3000/mcp",
"headers": {
"Authorization": "Bearer your-agent-key"
}
}
}
}
}
```
Or add to `.vscode/mcp.json` in your workspace:
```json
{
"servers": {
"kb-server": {
"type": "http",
"url": "http://localhost:3000/mcp",
"headers": {
"Authorization": "Bearer your-agent-key"
}
}
}
}
```
### Cursor
Add to `.cursor/mcp.json` in your project root:
```json
{
"mcpServers": {
"kb-server": {
"type": "streamable-http",
"url": "http://localhost:3000/mcp",
"headers": {
"Authorization": "Bearer your-agent-key"
}
}
}
}
```
### Windsurf
Add to `~/.codeium/windsurf/mcp_config.json`:
```json
{
"mcpServers": {
"kb-server": {
"serverUrl": "http://localhost:3000/mcp",
"headers": {
"Authorization": "Bearer your-agent-key"
}
}
}
}
```
### JetBrains IDEs (IntelliJ, WebStorm, PyCharm, etc.)
Add to `.junie/mcp.json` in your project root, or configure via **Settings > Tools > AI Assistant > MCP Servers**:
```json
{
"servers": {
"kb-server": {
"type": "http",
"url": "http://localhost:3000/mcp",
"headers": {
"Authorization": "Bearer your-agent-key"
}
}
}
}
```
+88 -93
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@@ -1,34 +1,63 @@
# kb-search
# kb
Personal knowledge base with hybrid search (full-text + semantic vector search).
v2 uses a client-server architecture: a **FastAPI engine** running in Docker (with GPU acceleration) and a lightweight **Go CLI client** that talks to it over HTTP.
Client-server architecture: a **FastAPI engine** running in Docker (with optional GPU acceleration), a lightweight **Go CLI client**, and an **MCP server** for native agent integration.
## Architecture
```
Go CLI (kb) ──HTTP──▶ FastAPI Engine (Docker) ──▶ SQLite + GPU
MCP Agents ──MCP/HTTP──▶ MCP Server (Docker) ──┘
```
- **Engine**: Keeps the embedding model warm in GPU memory. Handles search, ingestion, and document management via REST API. Runs in Docker with NVIDIA or AMD GPU support.
- **Engine**: Keeps the embedding model warm in memory. Handles search, ingestion, document management, and note mutation via REST API. Runs in Docker with NVIDIA GPU or CPU-only support.
- **Client**: Single static Go binary. No Python, no ML dependencies, instant startup. Talks to the engine over HTTP.
- **MCP Server**: Exposes kb operations as native MCP tools over Streamable HTTP. Runs as a separate Docker container alongside the engine. Use tags to scope agent data from user documents.
- **Storage**: Single SQLite database with FTS5 (keyword search) and sqlite-vec (vector search). Portable via bind mount — just copy the data directory between hosts.
## Quick start
### 1. Start the engine
**From pre-built images** (recommended):
```bash
cd engine
# NVIDIA GPU
KB_DATA_PATH=~/kb-data docker compose -f compose.nvidia.yaml up -d
docker run -d --name kb-engine \
--gpus all \
-p 8000:8000 \
-v ~/kb-data:/data \
-e KB_MODEL=all-MiniLM-L6-v2 \
-e KB_DEVICE=auto \
-e KB_API_KEY=your-secret-key \
--restart unless-stopped \
docker.dcglab.co.uk/dcg/kb/engine:latest-nvidia
# AMD GPU (ROCm)
KB_DATA_PATH=~/kb-data docker compose -f compose.rocm.yaml up -d
# CPU only (no GPU required — smaller image)
docker run -d --name kb-engine \
-p 8000:8000 \
-v ~/kb-data:/data \
-e KB_MODEL=all-MiniLM-L6-v2 \
-e KB_API_KEY=your-secret-key \
--restart unless-stopped \
docker.dcglab.co.uk/dcg/kb/engine:latest-cpu
```
The engine will download the embedding model on first start (~90MB) and load it onto the GPU. Check readiness:
Or use a compose file from the repo:
```bash
# NVIDIA GPU
KB_DATA_PATH=~/kb-data docker compose -f engine/compose.nvidia.yaml up -d
# CPU only
KB_DATA_PATH=~/kb-data docker compose -f engine/compose.cpu.yaml up -d
```
See [DEVELOPER.md](DEVELOPER.md) to run the engine from source.
The engine will download the embedding model on first start (~90MB) and load it into memory (GPU or CPU). Check readiness:
```bash
curl http://localhost:8000/api/v1/health
@@ -37,18 +66,32 @@ curl http://localhost:8000/api/v1/health
### 2. Install the client
Build from source:
**From a release** (recommended):
Check [releases](https://gitea.dcglab.co.uk/steve/kb/releases) for the latest client tag, then:
```bash
cd client
make build # produces ./kb binary
# Set the version tag
TAG=client-v3.0.0
# Linux (amd64)
curl -L -o kb https://gitea.dcglab.co.uk/steve/kb/releases/download/${TAG}/kb-linux-amd64
# Linux (arm64)
curl -L -o kb https://gitea.dcglab.co.uk/steve/kb/releases/download/${TAG}/kb-linux-arm64
# macOS (Apple Silicon)
curl -L -o kb https://gitea.dcglab.co.uk/steve/kb/releases/download/${TAG}/kb-darwin-arm64
# macOS (Intel)
curl -L -o kb https://gitea.dcglab.co.uk/steve/kb/releases/download/${TAG}/kb-darwin-amd64
# Then install
chmod +x kb
sudo mv kb /usr/local/bin/
```
Or cross-compile for all platforms:
```bash
make all # produces dist/kb-{os}-{arch} binaries
```
See [DEVELOPER.md](DEVELOPER.md) to build the client from source.
### 3. Configure the client
@@ -65,10 +108,13 @@ Override via environment variables (`KB_ENGINE_URL`, `KB_API_KEY`) or CLI flags
### 4. Use it
```bash
# Add documents (async — uploads and exits immediately)
kb add ~/docs/manual.pdf --tags admin
kb add ~/notes/ --recursive
kb add --note "Always restart nginx after config changes" --tags ops
# Add notes
kb addnote "Always restart nginx after config changes"
kb addnote "Server room is building 3, floor 2" --tags ops
# Add files (async — uploads and exits immediately)
kb addfile ~/docs/manual.pdf --tags admin
kb addfile ~/notes/ --recursive
# Check ingestion progress
kb jobs
@@ -77,13 +123,22 @@ kb jobs
kb search "how to install git"
kb search "deploy process" --tags ops --type pdf
# Update a note in place
kb updatenote 42 "revised note content"
# Manage
kb list
kb info 1
kb tags
kb tag 1 --add important
kb export 1 -o manual.pdf # download original file
kb remove 3 --yes
kb status
# Bulk operations
kb bulk-remove --tags "draft,old" --type note --yes
kb bulk-tag --type note --add "archived" --yes
kb bulk-set-tags --tags "old-scheme" --set "new-scheme" --yes
```
## How it works
@@ -100,12 +155,15 @@ The engine is configured via environment variables (set in the compose file or v
|---|---|---|
| `KB_DATA_DIR` | `/data` | Data directory inside the container (bind-mounted) |
| `KB_MODEL` | `all-MiniLM-L6-v2` | HuggingFace embedding model name |
| `KB_DEVICE` | `auto` | Embedding device: `auto`, `cpu`, or `cuda` |
| `KB_INGEST_DEVICE` | `auto` | Docling layout detection device |
| `KB_DEVICE` | `auto` | Embedding/search device: `auto`, `cpu`, or `cuda` |
| `KB_INGEST_DEVICE` | `auto` | Docling layout detection device: `auto`, `cpu`, or `cuda` |
| `KB_API_KEY` | (none) | Optional Bearer token for API authentication |
| `KB_SEARCH_THRESHOLD` | `0.01` | Minimum score for search results (filters noise) |
| `KB_BULK_SAFETY_PERCENT` | `70` | Bulk operations affecting more than this % of documents are rejected unless `force` is set (0 disables) |
| `KB_PORT` | `8000` | Port to expose |
| `KB_DATA_PATH` | `./data` | Host path for bind mount (compose variable) |
| `KB_HOST` | `0.0.0.0` | Host to bind to |
| `HF_HUB_OFFLINE` | (none) | Set to `1` to prevent model downloads (use cached only) |
| `KB_DATA_PATH` | `./data` | Host path for bind mount (compose variable, not used by engine) |
## Data portability
@@ -119,77 +177,14 @@ rsync -a ~/kb-data/ user@target:/home/user/kb-data/
KB_DATA_PATH=~/kb-data docker compose -f compose.nvidia.yaml up -d
```
Data is GPU-vendor-agnostic — you can ingest on NVIDIA and serve from AMD (or vice versa) with the same data directory.
Data is device-agnostic — you can ingest on NVIDIA and serve from CPU (or vice versa) with the same data directory.
## API reference
## MCP server (agent integration)
All endpoints are under `/api/v1/`. Requires `Authorization: Bearer <key>` header when `KB_API_KEY` is set.
The MCP server exposes kb operations as native MCP tools over Streamable HTTP, so agents can search, add notes, upload files, and manage documents without shelling out to the CLI. Includes setup guides for Claude Code, VS Code, Cursor, Windsurf, and JetBrains IDEs.
| Method | Endpoint | Description |
|---|---|---|
| `GET` | `/health` | Health check (bypasses auth) |
| `POST` | `/search` | Hybrid search (JSON body) |
| `POST` | `/jobs` | Upload file/note for ingestion (multipart, returns 202) |
| `GET` | `/jobs` | List ingestion jobs |
| `GET` | `/jobs/{id}` | Job details |
| `GET` | `/documents` | List documents |
| `GET` | `/documents/{id}` | Document details with chunks |
| `DELETE` | `/documents/{id}` | Remove a document |
| `PUT` | `/documents/{id}/tags` | Add/remove tags |
| `GET` | `/tags` | List all tags |
| `GET` | `/status` | Engine status, GPU info, DB stats |
| `POST` | `/reindex` | Re-embed all chunks |
See **[MCP.md](MCP.md)** for full details — server setup, available tools, tag-based organisation, configuration, and client examples.
## Building and releasing
## Agent skill
Versioning is managed via `client/VERSION` and `engine/VERSION` files. The release script bumps these, builds all artifacts, tags, and publishes in one step.
### Release
```bash
./release.sh --gitea # patch bump (e.g. 2.0.0 → 2.0.1), release via Gitea
./release.sh --github --minor # minor bump (e.g. 2.0.1 → 2.1.0), release via GitHub
./release.sh --gitea --major # major bump (e.g. 2.1.0 → 3.0.0)
./release.sh --gitea --no-increment # release current version as-is
./release.sh --gitea --dry-run # preview without doing anything
```
The script will:
1. Bump the version in both `client/VERSION` and `engine/VERSION` (unless `--no-increment`)
2. Build Go client binaries for all platforms (linux/darwin/windows, amd64/arm64)
3. Build Docker engine images for NVIDIA and ROCm
4. Commit the version bump, create an annotated git tag, and push
5. Create a release (with client binaries attached) via `tea` or `gh`
6. Push Docker images to the registry
### Checking versions
```bash
# Client
kb --version
# Engine
curl http://localhost:8000/api/v1/status | jq .version
```
### Docker images
Images are pushed to `docker.dcglab.co.uk/dcg/kb/engine` with tags:
- `v2.1.0-nvidia` / `v2.1.0-rocm` — versioned
- `latest-nvidia` / `latest-rocm` — latest release
Override the registry and org via environment variables:
```bash
REGISTRY=ghcr.io IMAGE_ORG=myorg ./release.sh --github
```
## Future: ROCm runtime migration
The `onnxruntime-rocm` execution provider was removed from onnxruntime as of v1.23. AMD is pushing toward the **MIGraphX execution provider** as the replacement for ROCm GPU inference. When upgrading onnxruntime beyond v1.22, the ROCm Dockerfile will need to switch from `onnxruntime-rocm` to `onnxruntime` with the MIGraphX EP and install the `migraphx` runtime libraries instead.
## Claude Code skill
This tool is designed to be wrapped as a Claude Code skill. See `SKILL.md` for the skill definition.
If you are restricted from using MCP server, or you just prefer to utilise Agent SKILLS, please also see `SKILL.md` for the skill definition.
+141 -27
View File
@@ -1,6 +1,6 @@
# kb-search skill
Search the user's personal knowledge base containing PDFs, markdown documents, code snippets, and text notes.
Search, manage, and add to the user's personal knowledge base containing PDFs, Word docs, HTML, markdown, code files, and text notes.
## When to use
@@ -8,10 +8,18 @@ Search the user's personal knowledge base containing PDFs, markdown documents, c
- User explicitly says "check my notes", "search kb", "look in my knowledge base", "what do my docs say about..."
- User references documents or notes they've previously stored
- User asks "how do I..." style questions that their knowledge base likely covers
- User wants to save a note, add a file, or manage their knowledge base
## Available commands
## Adding notes
### Search (primary)
```bash
kb addnote "remember to update DNS records" # add a note
kb addnote "server room is building 3, floor 2" --tags ops # add a tagged note
```
The note text must be a single quoted argument.
## Search (primary use case)
```bash
kb search "<query>" --top 10 --format json
@@ -20,25 +28,109 @@ kb search "<query>" --top 10 --format json
Returns JSON with ranked results combining full-text and semantic search.
**Flags:**
- `--top N` — number of results (default: 10)
- `-n, --top N` — number of results (default: 10)
- `--tags tag1,tag2` — filter by tags (AND logic)
- `--type pdf|markdown|code|note` — filter by document type
- `--format json|human` — output format (always use json)
- `--format json|human` — output format (always use json for parsing)
- `--fts-only` — keyword search only (skip semantic)
- `--vec-only` — semantic search only (skip keyword)
- `--threshold FLOAT` — minimum score cutoff
### Other useful commands
## Adding files
```bash
kb list --format json # List all documents
kb list --type pdf --format json # List only PDFs
kb tags --format json # List tags with counts
kb info <doc_id> --format json # Document details
kb status --format json # DB stats
kb addfile report.pdf # single file
kb addfile report.pdf --tags admin,reference # with tags
kb addfile ~/docs/ --recursive # directory (recursive)
kb addfile ~/docs/ --recursive --tags reference # directory with tags
```
## Output format (search)
Supported file types: `.pdf`, `.docx`, `.html`, `.md`, `.txt`, `.py`, `.sh`, `.go`. Unsupported extensions are rejected before upload.
**Flags:**
- `--tags tag1,tag2` — tags (comma-separated)
- `-r, --recursive` — recursively add directory contents
## Document management
```bash
kb list --format json # list all documents
kb list --type pdf --format json # filter by type
kb list --tags admin --format json # filter by tags
kb info <doc_id> --format json # document details with chunks
kb export <doc_id> -o file.pdf # download original file
kb remove <doc_id> # remove (prompts for confirmation)
kb remove <doc_id> --yes # remove without confirmation
```
## Tag management
```bash
kb tags --format json # list all tags with counts
kb tag <doc_id> --add important,ops # add tags to a document
kb tag <doc_id> --remove draft # remove tags from a document
```
## Bulk operations
Operate on multiple documents at once using filter-based selection. Filters combine with AND logic.
**Filter flags (shared across all bulk commands):**
- `--tags tag1,tag2` — match documents with ALL specified tags
- `--type pdf|note|...` — match by document type
- `--ids 1,5,12` — match specific document IDs
- `--from-id N` — match documents with id >= N
- `--to-id N` — match documents with id <= N
- `--force` / `-f` — override safety threshold (blocks operations affecting >70% of all documents)
- `--yes` / `-y` — skip confirmation prompt
```bash
# Bulk delete
kb bulk-remove --tags "draft,old" --type note --yes # delete matching docs
kb bulk-remove --from-id 10 --to-id 50 --yes # delete by ID range
kb bulk-remove --ids "3,7,12" --yes # delete specific IDs
# Bulk tag add/remove
kb bulk-tag --tags "agent:mybot" --add "reviewed" --remove "pending" --yes
kb bulk-tag --type note --add "archived" --yes # tag all notes
# Bulk replace tags
kb bulk-set-tags --tags "old-scheme" --set "new-scheme,migrated" --yes
```
All bulk commands return a summary: matched count, succeeded count, failed count, and errors.
A safety threshold prevents accidentally affecting more than 70% of documents unless `--force` is used.
The threshold is configurable on the engine via `KB_BULK_SAFETY_PERCENT` (integer 0-100, default 70; 0 disables).
## Jobs (ingestion queue)
```bash
kb jobs --format json # list recent jobs
kb jobs --status failed --format json # filter by status
kb jobs <job_id> --format json # job details
```
## Examples
```bash
kb examples # show common usage examples
```
## Engine status and maintenance
```bash
kb status --format json # engine status, GPU info, DB stats
kb reindex --yes # re-embed all chunks (skip confirmation)
```
## Global flags
All commands support:
- `--format json|human` — output format (always use `json` for machine parsing)
- `--engine <url>` — engine API URL (default: http://localhost:8000)
- `--api-key <key>` — API key for authentication
## Search output format
```json
{
@@ -47,18 +139,14 @@ kb status --format json # DB stats
{
"chunk_id": 1423,
"score": 0.031,
"score_breakdown": {"fts": 0.016, "vector": 0.015},
"text": "To install the latest version of git from source...",
"source": {
"document_id": 42,
"title": "Git Admin Guide",
"path": "/home/user/docs/git-admin.pdf",
"type": "pdf",
"page": 12,
"chunk_index": 3,
"total_chunks": 28,
"tags": ["git", "admin"]
}
"chunk_index": 3,
"chunk_metadata": {"page": 12},
"title": "Git Admin Guide",
"doc_type": "pdf",
"source_path": "/home/user/docs/git-admin.pdf",
"created_at": "2026-03-15T10:30:00",
"tags": ["git", "admin"]
}
],
"total_matches": 47,
@@ -66,7 +154,7 @@ kb status --format json # DB stats
}
```
## How to answer
## How to answer search queries
1. Run `kb search "<query>" --top 10 --format json`
2. Read the returned chunks
@@ -93,7 +181,7 @@ Query 2: kb search "git merge explanation" --top 5 --format json
Query 3: kb search "git rebase vs merge" --top 5 --format json
```
## Filtering
## Filtering tips
Use filters when the question implies a specific domain:
@@ -101,10 +189,36 @@ Use filters when the question implies a specific domain:
- From a specific topic → `--tags <topic>`
- Check available tags first: `kb tags --format json`
## Updating notes
```bash
kb updatenote 42 "revised note content" # update note by ID
```
Updates the text of an existing note in place, preserving its ID, creation timestamp, and tags. Re-chunks and re-embeds the new text.
## MCP server (agent integration)
For agent-to-agent integration, kb provides an MCP server alongside the CLI. The MCP server
exposes the same operations as native MCP tools over Streamable HTTP transport, which agents
can connect to directly without subprocess overhead.
**MCP tools:** `kb_search`, `kb_addnote`, `kb_update_note`, `kb_get`, `kb_delete`, `kb_status`,
`kb_jobs`, `kb_upload_start`, `kb_upload_chunk`, `kb_upload_finish`, `kb_bulk_delete`,
`kb_bulk_tags`, `kb_bulk_set_tags`.
Use tags to separate agent data from user documents (e.g. tag all agent notes with
`agent:mybot` and filter by that tag when searching). This convention is communicated
via system prompt — no special server-side enforcement needed.
If the kb engine is already running via Docker Compose, add the MCP server by deploying the
`kb-mcp` service from the same compose file. Agents connect to it on port 3000 (default).
## Important notes
- Always use `--format json` for machine parsing
- The `score` field is relative, not absolute — compare scores within a result set
- `source.page` is only present for PDF documents
- `source.section_header` is only present for markdown documents with headers
- `chunk_metadata.page` is only present for PDF documents
- `chunk_metadata.section_header` is only present for markdown documents with headers
- Results are already ranked by relevance (hybrid FTS + vector search)
- Duplicate files are detected at upload time (HTTP 409) — the client handles this gracefully
+1
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@@ -0,0 +1 @@
3.2.0
+2 -1
View File
@@ -1,5 +1,6 @@
VERSION ?= $(shell cat VERSION 2>/dev/null || echo "dev")
LDFLAGS := -ldflags "-s -w -X github.com/kb-search/kb/cmd.Version=$(VERSION)"
MIN_ENGINE_VERSION ?= $(shell cat MIN_ENGINE_VERSION 2>/dev/null || echo "dev")
LDFLAGS := -ldflags "-s -w -X github.com/kb-search/kb/cmd.Version=$(VERSION) -X github.com/kb-search/kb/cmd.MinEngineVersion=$(MIN_ENGINE_VERSION)"
PLATFORMS := linux/amd64 linux/arm64 darwin/amd64 darwin/arm64 windows/amd64
+1 -1
View File
@@ -1 +1 @@
2.0.4
3.2.0
+85 -69
View File
@@ -1,9 +1,12 @@
package cmd
import (
"encoding/json"
"fmt"
"net/http"
"os"
"path/filepath"
"sort"
"strings"
"github.com/kb-search/kb/internal/api"
@@ -11,6 +14,21 @@ import (
"github.com/spf13/cobra"
)
type uploadResult struct {
Raw interface{}
Duplicate bool
DocID float64
JobID float64
Title string
}
func (r *uploadResult) duplicateMsg() string {
if r.DocID > 0 {
return fmt.Sprintf("Already imported: %s (doc ID: %.0f)", r.Title, r.DocID)
}
return fmt.Sprintf("Already queued: %s (job ID: %.0f)", r.Title, r.JobID)
}
var supportedExts = map[string]bool{
".pdf": true,
".docx": true,
@@ -22,73 +40,25 @@ var supportedExts = map[string]bool{
".go": true,
}
var addCmd = &cobra.Command{
Use: "add <path>",
Short: "Add a document or directory to the knowledge base",
Args: cobra.MaximumNArgs(1),
RunE: runAdd,
var addfileCmd = &cobra.Command{
Use: "addfile <path>",
Short: "Upload a file or directory to the knowledge base",
Args: cobra.ExactArgs(1),
RunE: runAddfile,
}
func init() {
addCmd.Flags().String("tags", "", "tags (comma-separated)")
addCmd.Flags().String("type", "", "document type")
addCmd.Flags().BoolP("recursive", "r", false, "recursively add directory contents")
addCmd.Flags().String("note", "", "add a text note instead of a file")
addCmd.Flags().String("title", "", "title for the note")
rootCmd.AddCommand(addCmd)
addfileCmd.Flags().String("tags", "", "tags (comma-separated)")
addfileCmd.Flags().BoolP("recursive", "r", false, "recursively add directory contents")
rootCmd.AddCommand(addfileCmd)
}
func runAdd(cmd *cobra.Command, args []string) error {
func runAddfile(cmd *cobra.Command, args []string) error {
tags, _ := cmd.Flags().GetString("tags")
docType, _ := cmd.Flags().GetString("type")
recursive, _ := cmd.Flags().GetBool("recursive")
note, _ := cmd.Flags().GetString("note")
title, _ := cmd.Flags().GetString("title")
client := api.NewClient()
// Note mode
if note != "" {
fields := map[string]string{
"note": note,
}
if title != "" {
fields["title"] = title
}
if tags != "" {
fields["tags"] = tags
}
if docType != "" {
fields["type"] = docType
}
resp, err := client.PostMultipart("/api/v1/jobs", fields, nil)
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if err := api.CheckError(resp); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
var result interface{}
if err := api.DecodeJSON(resp, &result); err != nil {
return fmt.Errorf("failed to decode response: %w", err)
}
if output.IsJSON() {
output.PrintJSON(result)
} else {
fmt.Println("Queued: note")
}
return nil
}
if len(args) == 0 {
return fmt.Errorf("path argument is required (or use --note)")
}
path := args[0]
info, err := os.Stat(path)
if err != nil {
@@ -96,15 +66,28 @@ func runAdd(cmd *cobra.Command, args []string) error {
}
if !info.IsDir() {
// Validate extension
ext := strings.ToLower(filepath.Ext(path))
if !supportedExts[ext] {
supported := make([]string, 0, len(supportedExts))
for e := range supportedExts {
supported = append(supported, e)
}
sort.Strings(supported)
return fmt.Errorf("unsupported file type %q — supported: %s", ext, strings.Join(supported, ", "))
}
// Single file upload
result, err := uploadFile(client, path, tags, docType)
result, err := uploadFile(client, path, tags)
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if output.IsJSON() {
output.PrintJSON([]interface{}{result})
output.PrintJSON([]interface{}{result.Raw})
} else if result.Duplicate {
fmt.Println(result.duplicateMsg())
} else {
fmt.Printf("Queued: %s\n", filepath.Base(path))
}
@@ -135,27 +118,39 @@ func runAdd(cmd *cobra.Command, args []string) error {
}
var results []interface{}
queued := 0
duplicates := 0
for _, f := range files {
result, err := uploadFile(client, f, tags, docType)
result, err := uploadFile(client, f, tags)
if err != nil {
fmt.Fprintf(os.Stderr, "Error uploading %s: %v\n", f, err)
continue
}
results = append(results, result)
if !output.IsJSON() {
fmt.Printf("Queued: %s\n", filepath.Base(f))
results = append(results, result.Raw)
if result.Duplicate {
duplicates++
if !output.IsJSON() {
fmt.Println(result.duplicateMsg())
}
} else {
queued++
if !output.IsJSON() {
fmt.Printf("Queued: %s\n", filepath.Base(f))
}
}
}
if output.IsJSON() {
output.PrintJSON(results)
} else if duplicates > 0 {
fmt.Printf("Queued: %d files, %d duplicates skipped\n", queued, duplicates)
} else {
fmt.Printf("Queued: %d files\n", len(results))
fmt.Printf("Queued: %d files\n", queued)
}
return nil
}
func uploadFile(client *api.Client, path, tags, docType string) (interface{}, error) {
func uploadFile(client *api.Client, path, tags string) (*uploadResult, error) {
f, err := os.Open(path)
if err != nil {
return nil, fmt.Errorf("cannot open %s: %w", path, err)
@@ -166,9 +161,6 @@ func uploadFile(client *api.Client, path, tags, docType string) (interface{}, er
if tags != "" {
fields["tags"] = tags
}
if docType != "" {
fields["type"] = docType
}
upload := &api.FileUpload{
FieldName: "file",
@@ -180,6 +172,29 @@ func uploadFile(client *api.Client, path, tags, docType string) (interface{}, er
if err != nil {
return nil, err
}
if resp.StatusCode == http.StatusConflict {
var raw json.RawMessage
if err := api.DecodeJSON(resp, &raw); err != nil {
return nil, fmt.Errorf("failed to decode response: %w", err)
}
var dupResp struct {
DocumentID float64 `json:"document_id"`
JobID float64 `json:"job_id"`
Title string `json:"title"`
}
json.Unmarshal(raw, &dupResp)
var rawIface interface{}
json.Unmarshal(raw, &rawIface)
return &uploadResult{
Raw: rawIface,
Duplicate: true,
DocID: dupResp.DocumentID,
JobID: dupResp.JobID,
Title: dupResp.Title,
}, nil
}
if err := api.CheckError(resp); err != nil {
return nil, err
}
@@ -188,5 +203,6 @@ func uploadFile(client *api.Client, path, tags, docType string) (interface{}, er
if err := api.DecodeJSON(resp, &result); err != nil {
return nil, fmt.Errorf("failed to decode response: %w", err)
}
return result, nil
return &uploadResult{Raw: result}, nil
}
+88
View File
@@ -0,0 +1,88 @@
package cmd
import (
"fmt"
"net/http"
"os"
"github.com/kb-search/kb/internal/api"
"github.com/kb-search/kb/internal/output"
"github.com/spf13/cobra"
)
var addnoteCmd = &cobra.Command{
Use: "addnote <text>",
Short: "Add a text note to the knowledge base",
Args: func(cmd *cobra.Command, args []string) error {
if len(args) == 0 {
return fmt.Errorf("requires a note text argument\n\n Usage: kb addnote \"your note text here\"")
}
if len(args) > 1 {
return fmt.Errorf("accepts 1 arg but received %d — quote your note text, e.g. kb addnote \"your note text here\"", len(args))
}
return nil
},
RunE: runAddnote,
}
func init() {
addnoteCmd.Flags().String("tags", "", "tags (comma-separated)")
rootCmd.AddCommand(addnoteCmd)
}
func runAddnote(cmd *cobra.Command, args []string) error {
tags, _ := cmd.Flags().GetString("tags")
client := api.NewClient()
return submitNote(client, args[0], tags)
}
func submitNote(client *api.Client, note, tags string) error {
fields := map[string]string{
"note": note,
}
if tags != "" {
fields["tags"] = tags
}
resp, err := client.PostMultipart("/api/v1/jobs", fields, nil)
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if resp.StatusCode == http.StatusConflict {
var result interface{}
if err := api.DecodeJSON(resp, &result); err != nil {
return fmt.Errorf("failed to decode response: %w", err)
}
if output.IsJSON() {
output.PrintJSON(result)
} else {
if m, ok := result.(map[string]interface{}); ok {
if docID, ok := m["document_id"].(float64); ok {
fmt.Printf("Already imported: %s (doc ID: %.0f)\n", m["title"], docID)
} else if jobID, ok := m["job_id"].(float64); ok {
fmt.Printf("Already queued: %s (job ID: %.0f)\n", m["title"], jobID)
}
}
}
return nil
}
if err := api.CheckError(resp); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
var result interface{}
if err := api.DecodeJSON(resp, &result); err != nil {
return fmt.Errorf("failed to decode response: %w", err)
}
if output.IsJSON() {
output.PrintJSON(result)
} else {
fmt.Println("Queued: note")
}
return nil
}
+186
View File
@@ -0,0 +1,186 @@
package cmd
import (
"bufio"
"fmt"
"os"
"strconv"
"strings"
"github.com/kb-search/kb/internal/api"
"github.com/kb-search/kb/internal/output"
"github.com/spf13/cobra"
)
var bulkRemoveCmd = &cobra.Command{
Use: "bulk-remove",
Short: "Delete multiple documents matching a filter",
RunE: runBulkRemove,
}
func init() {
addBulkFilterFlags(bulkRemoveCmd)
rootCmd.AddCommand(bulkRemoveCmd)
}
func runBulkRemove(cmd *cobra.Command, args []string) error {
body, err := buildBulkBody(cmd)
if err != nil {
return err
}
yes, _ := cmd.Flags().GetBool("yes")
if !yes {
desc := describeBulkFilter(cmd)
fmt.Printf("This will delete documents matching: %s\nProceed? [y/N] ", desc)
reader := bufio.NewReader(os.Stdin)
answer, _ := reader.ReadString('\n')
answer = strings.TrimSpace(strings.ToLower(answer))
if answer != "y" && answer != "yes" {
fmt.Println("Cancelled.")
return nil
}
}
client := api.NewClient()
resp, err := client.Post("/api/v1/bulk/delete", body)
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if err := api.CheckError(resp); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
var result map[string]interface{}
if err := api.DecodeJSON(resp, &result); err != nil {
return fmt.Errorf("failed to decode response: %w", err)
}
if output.IsJSON() {
output.PrintJSON(result)
} else {
printBulkResult("Deleted", result)
}
return nil
}
// ---------------------------------------------------------------------------
// Shared helpers for all bulk commands
// ---------------------------------------------------------------------------
func addBulkFilterFlags(cmd *cobra.Command) {
cmd.Flags().String("tags", "", "filter by tags (comma-separated)")
cmd.Flags().String("type", "", "filter by document type")
cmd.Flags().String("ids", "", "filter by document IDs (comma-separated)")
cmd.Flags().Int("from-id", 0, "filter by id >= value")
cmd.Flags().Int("to-id", 0, "filter by id <= value")
cmd.Flags().BoolP("force", "f", false, "override safety threshold")
cmd.Flags().BoolP("yes", "y", false, "skip confirmation prompt")
}
func buildBulkBody(cmd *cobra.Command) (map[string]interface{}, error) {
body := map[string]interface{}{}
tagsStr, _ := cmd.Flags().GetString("tags")
if tagsStr != "" {
body["tags"] = splitTags(tagsStr)
}
docType, _ := cmd.Flags().GetString("type")
if docType != "" {
body["doc_type"] = docType
}
idsStr, _ := cmd.Flags().GetString("ids")
if idsStr != "" {
ids, err := parseIntList(idsStr)
if err != nil {
return nil, fmt.Errorf("invalid --ids: %w", err)
}
body["document_ids"] = ids
}
fromID, _ := cmd.Flags().GetInt("from-id")
if fromID > 0 {
body["from_id"] = fromID
}
toID, _ := cmd.Flags().GetInt("to-id")
if toID > 0 {
body["to_id"] = toID
}
force, _ := cmd.Flags().GetBool("force")
if force {
body["force"] = true
}
// Ensure at least one filter
hasFilter := tagsStr != "" || docType != "" || idsStr != "" || fromID > 0 || toID > 0
if !hasFilter {
return nil, fmt.Errorf("at least one filter is required (--tags, --type, --ids, --from-id, --to-id)")
}
return body, nil
}
func describeBulkFilter(cmd *cobra.Command) string {
var parts []string
tagsStr, _ := cmd.Flags().GetString("tags")
if tagsStr != "" {
parts = append(parts, fmt.Sprintf("tags=[%s]", tagsStr))
}
docType, _ := cmd.Flags().GetString("type")
if docType != "" {
parts = append(parts, fmt.Sprintf("type=%s", docType))
}
idsStr, _ := cmd.Flags().GetString("ids")
if idsStr != "" {
parts = append(parts, fmt.Sprintf("ids=[%s]", idsStr))
}
fromID, _ := cmd.Flags().GetInt("from-id")
if fromID > 0 {
parts = append(parts, fmt.Sprintf("from_id=%d", fromID))
}
toID, _ := cmd.Flags().GetInt("to-id")
if toID > 0 {
parts = append(parts, fmt.Sprintf("to_id=%d", toID))
}
return strings.Join(parts, " ")
}
func printBulkResult(action string, result map[string]interface{}) {
matched := int(result["matched"].(float64))
succeeded := int(result["succeeded"].(float64))
failed := int(result["failed"].(float64))
fmt.Printf("%s %d of %d documents", action, succeeded, matched)
if failed > 0 {
fmt.Printf(" (%d failed)", failed)
}
fmt.Println()
}
func parseIntList(s string) ([]int, error) {
var ids []int
for _, part := range strings.Split(s, ",") {
part = strings.TrimSpace(part)
if part == "" {
continue
}
id, err := strconv.Atoi(part)
if err != nil {
return nil, fmt.Errorf("invalid ID %q: %w", part, err)
}
ids = append(ids, id)
}
return ids, nil
}
+73
View File
@@ -0,0 +1,73 @@
package cmd
import (
"bufio"
"fmt"
"os"
"strings"
"github.com/kb-search/kb/internal/api"
"github.com/kb-search/kb/internal/output"
"github.com/spf13/cobra"
)
var bulkSetTagsCmd = &cobra.Command{
Use: "bulk-set-tags",
Short: "Replace all tags on multiple documents matching a filter",
RunE: runBulkSetTags,
}
func init() {
addBulkFilterFlags(bulkSetTagsCmd)
bulkSetTagsCmd.Flags().String("set", "", "replacement tags (comma-separated)")
rootCmd.AddCommand(bulkSetTagsCmd)
}
func runBulkSetTags(cmd *cobra.Command, args []string) error {
body, err := buildBulkBody(cmd)
if err != nil {
return err
}
setStr, _ := cmd.Flags().GetString("set")
if setStr == "" {
return fmt.Errorf("--set is required (comma-separated list of replacement tags)")
}
body["new_tags"] = splitTags(setStr)
yes, _ := cmd.Flags().GetBool("yes")
if !yes {
desc := describeBulkFilter(cmd)
fmt.Printf("This will replace all tags with [%s] on documents matching: %s\nProceed? [y/N] ", setStr, desc)
reader := bufio.NewReader(os.Stdin)
answer, _ := reader.ReadString('\n')
answer = strings.TrimSpace(strings.ToLower(answer))
if answer != "y" && answer != "yes" {
fmt.Println("Cancelled.")
return nil
}
}
client := api.NewClient()
resp, err := client.Post("/api/v1/bulk/set-tags", body)
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if err := api.CheckError(resp); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
var result map[string]interface{}
if err := api.DecodeJSON(resp, &result); err != nil {
return fmt.Errorf("failed to decode response: %w", err)
}
if output.IsJSON() {
output.PrintJSON(result)
} else {
printBulkResult("Set tags on", result)
}
return nil
}
+92
View File
@@ -0,0 +1,92 @@
package cmd
import (
"bufio"
"fmt"
"os"
"strings"
"github.com/kb-search/kb/internal/api"
"github.com/kb-search/kb/internal/output"
"github.com/spf13/cobra"
)
var bulkTagCmd = &cobra.Command{
Use: "bulk-tag",
Short: "Add or remove tags on multiple documents matching a filter",
RunE: runBulkTag,
}
func init() {
addBulkFilterFlags(bulkTagCmd)
bulkTagCmd.Flags().String("add", "", "tags to add (comma-separated)")
bulkTagCmd.Flags().String("remove", "", "tags to remove (comma-separated)")
rootCmd.AddCommand(bulkTagCmd)
}
func runBulkTag(cmd *cobra.Command, args []string) error {
body, err := buildBulkBody(cmd)
if err != nil {
return err
}
addStr, _ := cmd.Flags().GetString("add")
removeStr, _ := cmd.Flags().GetString("remove")
if addStr == "" && removeStr == "" {
return fmt.Errorf("specify --add and/or --remove")
}
if addStr != "" {
body["add"] = splitTags(addStr)
}
if removeStr != "" {
body["remove"] = splitTags(removeStr)
}
yes, _ := cmd.Flags().GetBool("yes")
if !yes {
desc := describeBulkFilter(cmd)
action := ""
if addStr != "" {
action += fmt.Sprintf("add=[%s]", addStr)
}
if removeStr != "" {
if action != "" {
action += " "
}
action += fmt.Sprintf("remove=[%s]", removeStr)
}
fmt.Printf("This will update tags (%s) on documents matching: %s\nProceed? [y/N] ", action, desc)
reader := bufio.NewReader(os.Stdin)
answer, _ := reader.ReadString('\n')
answer = strings.TrimSpace(strings.ToLower(answer))
if answer != "y" && answer != "yes" {
fmt.Println("Cancelled.")
return nil
}
}
client := api.NewClient()
resp, err := client.Post("/api/v1/bulk/tags", body)
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if err := api.CheckError(resp); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
var result map[string]interface{}
if err := api.DecodeJSON(resp, &result); err != nil {
return fmt.Errorf("failed to decode response: %w", err)
}
if output.IsJSON() {
output.PrintJSON(result)
} else {
printBulkResult("Tagged", result)
}
return nil
}
+40
View File
@@ -0,0 +1,40 @@
package cmd
import (
"fmt"
"github.com/spf13/cobra"
)
var examplesCmd = &cobra.Command{
Use: "examples",
Short: "Show common usage examples",
Args: cobra.NoArgs,
Run: func(cmd *cobra.Command, args []string) {
fmt.Print(`Add notes:
kb addnote "Remember to update DNS records"
kb addnote "Server room is building 3" --tags ops
Add files:
kb addfile report.pdf
kb addfile ~/docs/ --recursive --tags reference
Search:
kb search "how to restart nginx"
kb search "deploy" --tags ops --top 5
Update notes:
kb updatenote 42 "revised note content"
Manage documents:
kb list --type pdf
kb info 3
kb tag 3 --add important,ops
kb remove 3 --yes
`)
},
}
func init() {
rootCmd.AddCommand(examplesCmd)
}
+74
View File
@@ -0,0 +1,74 @@
package cmd
import (
"fmt"
"io"
"mime"
"os"
"path/filepath"
"github.com/kb-search/kb/internal/api"
"github.com/spf13/cobra"
)
var exportCmd = &cobra.Command{
Use: "export <id>",
Short: "Download original document file",
Args: cobra.ExactArgs(1),
RunE: runExport,
}
func init() {
exportCmd.Flags().StringP("output", "o", "", "output file path (default: original filename to current directory)")
rootCmd.AddCommand(exportCmd)
}
func runExport(cmd *cobra.Command, args []string) error {
client := api.NewClient()
resp, err := client.Get("/api/v1/documents/" + args[0] + "/file")
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if err := api.CheckError(resp); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
defer resp.Body.Close()
outPath, _ := cmd.Flags().GetString("output")
if outPath == "" {
// Try to get filename from Content-Disposition header
cd := resp.Header.Get("Content-Disposition")
if cd != "" {
_, params, err := mime.ParseMediaType(cd)
if err == nil && params["filename"] != "" {
outPath = params["filename"]
}
}
if outPath == "" {
outPath = "document-" + args[0]
}
}
if outPath == "-" {
_, err := io.Copy(os.Stdout, resp.Body)
return err
}
outPath = filepath.Clean(outPath)
f, err := os.Create(outPath)
if err != nil {
return fmt.Errorf("failed to create output file: %w", err)
}
defer f.Close()
n, err := io.Copy(f, resp.Body)
if err != nil {
return fmt.Errorf("failed to write file: %w", err)
}
fmt.Fprintf(os.Stderr, "Saved %s (%d bytes)\n", outPath, n)
return nil
}
+83
View File
@@ -0,0 +1,83 @@
package cmd
import (
"bufio"
"fmt"
"os"
"strings"
"github.com/kb-search/kb/internal/api"
"github.com/kb-search/kb/internal/output"
"github.com/spf13/cobra"
)
var reindexCmd = &cobra.Command{
Use: "reindex",
Short: "Re-embed all chunks with the current engine model",
Args: cobra.NoArgs,
RunE: runReindex,
}
func init() {
reindexCmd.Flags().BoolP("yes", "y", false, "skip confirmation prompt")
rootCmd.AddCommand(reindexCmd)
}
func runReindex(cmd *cobra.Command, args []string) error {
yes, _ := cmd.Flags().GetBool("yes")
client := api.NewClient()
if !yes {
// Fetch model name from engine status
modelName := "current"
statusResp, err := client.Get("/api/v1/status")
if err == nil && api.CheckError(statusResp) == nil {
var status struct {
ModelName string `json:"model_name"`
}
if api.DecodeJSON(statusResp, &status) == nil && status.ModelName != "" {
modelName = status.ModelName
}
}
fmt.Printf("Reindex all chunks? This will re-embed everything with the %s model. [y/N] ", modelName)
reader := bufio.NewReader(os.Stdin)
answer, _ := reader.ReadString('\n')
answer = strings.TrimSpace(strings.ToLower(answer))
if answer != "y" && answer != "yes" {
fmt.Println("Cancelled.")
return nil
}
}
resp, err := client.Post("/api/v1/reindex", nil)
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if err := api.CheckError(resp); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
var result struct {
ChunksReindexed int `json:"chunks_reindexed"`
Model string `json:"model"`
}
if output.IsJSON() {
var raw interface{}
if err := api.DecodeJSON(resp, &raw); err != nil {
fmt.Fprintln(os.Stderr, "Failed to parse response:", err)
os.Exit(1)
}
output.PrintJSON(raw)
} else {
if err := api.DecodeJSON(resp, &result); err != nil {
fmt.Fprintln(os.Stderr, "Failed to parse response:", err)
os.Exit(1)
}
fmt.Printf("Reindexed %d chunks (model: %s)\n", result.ChunksReindexed, result.Model)
}
return nil
}
+7 -2
View File
@@ -4,6 +4,7 @@ import (
"fmt"
"os"
"github.com/kb-search/kb/internal/api"
"github.com/kb-search/kb/internal/config"
"github.com/spf13/cobra"
)
@@ -11,6 +12,9 @@ import (
// Version is set at build time via -ldflags.
var Version = "dev"
// MinEngineVersion is set at build time via -ldflags.
var MinEngineVersion = "dev"
var (
flagEngine string
flagFormat string
@@ -18,9 +22,9 @@ var (
)
var rootCmd = &cobra.Command{
Use: "kb",
Use: "kb [command]",
Short: "kb-search CLI client",
Long: "A CLI client for the kb-search v2 engine API.",
Long: "A CLI client for the kb-search v2 engine API.\nRun 'kb examples' for common usage patterns.",
PersistentPreRunE: func(cmd *cobra.Command, args []string) error {
if err := config.Load(); err != nil {
return err
@@ -31,6 +35,7 @@ var rootCmd = &cobra.Command{
}
func init() {
api.SetVersionInfo(Version, MinEngineVersion)
rootCmd.Version = Version
rootCmd.PersistentFlags().StringVar(&flagEngine, "engine", "", "engine API URL")
rootCmd.PersistentFlags().StringVar(&flagFormat, "format", "", "output format (human|json)")
+69
View File
@@ -0,0 +1,69 @@
package cmd
import (
"bytes"
"strings"
"testing"
)
func TestRootCmd_NoArgs_ShowsHelp(t *testing.T) {
rootCmd.SetArgs([]string{})
var stdout bytes.Buffer
rootCmd.SetOut(&stdout)
err := rootCmd.Execute()
if err != nil {
t.Fatalf("expected no error for zero args, got: %v", err)
}
output := stdout.String()
if !strings.Contains(output, "Available Commands") {
t.Errorf("expected help output, got: %s", output)
}
}
func TestRootCmd_UnknownCommand_ReturnsError(t *testing.T) {
rootCmd.SetArgs([]string{"notacommand"})
var stderr bytes.Buffer
rootCmd.SetErr(&stderr)
err := rootCmd.Execute()
if err == nil {
t.Fatal("expected error for unknown command, got nil")
}
errMsg := err.Error()
if !strings.Contains(errMsg, "unknown command") {
t.Errorf("expected 'unknown command' error, got: %s", errMsg)
}
}
func TestAddnoteCmd_NoArgs_ReturnsError(t *testing.T) {
rootCmd.SetArgs([]string{"addnote"})
err := rootCmd.Execute()
if err == nil {
t.Fatal("expected error for addnote with no args, got nil")
}
errMsg := err.Error()
if !strings.Contains(errMsg, "requires a note text argument") {
t.Errorf("expected 'requires a note text argument' error, got: %s", errMsg)
}
}
func TestAddnoteCmd_TooManyArgs_ReturnsError(t *testing.T) {
rootCmd.SetArgs([]string{"addnote", "hello", "world"})
err := rootCmd.Execute()
if err == nil {
t.Fatal("expected error for addnote with too many args, got nil")
}
errMsg := err.Error()
if !strings.Contains(errMsg, "quote your note text") {
t.Errorf("expected 'accepts 1 arg' error, got: %s", errMsg)
}
}
+19 -20
View File
@@ -67,15 +67,12 @@ func runSearch(cmd *cobra.Command, args []string) error {
var result struct {
Results []struct {
Score float64 `json:"score"`
Document struct {
Title string `json:"title"`
Type string `json:"doc_type"`
Tags []string `json:"tags"`
} `json:"document"`
Page interface{} `json:"page"`
Section string `json:"section"`
Text string `json:"text"`
Score float64 `json:"score"`
Title string `json:"title"`
DocType string `json:"doc_type"`
Tags []string `json:"tags"`
ChunkMetadata map[string]interface{} `json:"chunk_metadata"`
Text string `json:"text"`
} `json:"results"`
}
@@ -103,26 +100,28 @@ func runSearch(cmd *cobra.Command, args []string) error {
snippet = snippet[:200] + "..."
}
fmt.Printf("\n%d. [%.4f] %s\n", i+1, r.Score, r.Document.Title)
fmt.Printf("\n%d. [%.4f] %s\n", i+1, r.Score, r.Title)
location := ""
if r.Page != nil {
location = fmt.Sprintf("Page %v", r.Page)
if page, ok := r.ChunkMetadata["page"]; ok && page != nil {
location = fmt.Sprintf("Page %v", page)
}
if r.Section != "" {
if location != "" {
location += " / "
if section, ok := r.ChunkMetadata["section_header"]; ok && section != nil {
if s, ok := section.(string); ok && s != "" {
if location != "" {
location += " / "
}
location += s
}
location += r.Section
}
if location != "" {
fmt.Printf(" Location: %s\n", location)
}
if r.Document.Type != "" {
fmt.Printf(" Type: %s\n", r.Document.Type)
if r.DocType != "" {
fmt.Printf(" Type: %s\n", r.DocType)
}
if len(r.Document.Tags) > 0 {
fmt.Printf(" Tags: %s\n", joinStrings(r.Document.Tags))
if len(r.Tags) > 0 {
fmt.Printf(" Tags: %s\n", joinStrings(r.Tags))
}
fmt.Printf(" %s\n", snippet)
}
+61
View File
@@ -0,0 +1,61 @@
package cmd
import (
"fmt"
"os"
"strconv"
"github.com/kb-search/kb/internal/api"
"github.com/kb-search/kb/internal/output"
"github.com/spf13/cobra"
)
var updatenoteCmd = &cobra.Command{
Use: "updatenote <id> <text>",
Short: "Update an existing note's content",
Args: func(cmd *cobra.Command, args []string) error {
if len(args) < 2 {
return fmt.Errorf("requires document ID and text arguments\n\n Usage: kb updatenote 42 \"updated note text\"")
}
if _, err := strconv.Atoi(args[0]); err != nil {
return fmt.Errorf("document ID must be an integer, got %q", args[0])
}
return nil
},
RunE: runUpdatenote,
}
func init() {
rootCmd.AddCommand(updatenoteCmd)
}
func runUpdatenote(cmd *cobra.Command, args []string) error {
docID := args[0]
text := args[1]
client := api.NewClient()
body := map[string]string{"text": text}
resp, err := client.Patch(fmt.Sprintf("/api/v1/notes/%s", docID), body)
if err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
if err := api.CheckError(resp); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
var result interface{}
if err := api.DecodeJSON(resp, &result); err != nil {
return fmt.Errorf("failed to decode response: %w", err)
}
if output.IsJSON() {
output.PrintJSON(result)
} else {
fmt.Printf("Updated note %s\n", docID)
}
return nil
}
+104 -3
View File
@@ -7,6 +7,9 @@ import (
"io"
"mime/multipart"
"net/http"
"os"
"strconv"
"strings"
"github.com/kb-search/kb/internal/config"
)
@@ -18,11 +21,25 @@ type FileUpload struct {
Reader io.Reader
}
// Package-level version info, set once by cmd.init via SetVersionInfo.
var (
clientVersion string
minEngineVersion string
)
// SetVersionInfo configures the client and minimum engine version for compatibility checking.
// Called once from cmd package initialization.
func SetVersionInfo(cv, minEV string) {
clientVersion = cv
minEngineVersion = minEV
}
// Client is an HTTP client for the kb-search engine API.
type Client struct {
baseURL string
apiKey string
httpClient *http.Client
baseURL string
apiKey string
httpClient *http.Client
versionChecked bool
}
// NewClient creates a Client from the current configuration.
@@ -48,6 +65,7 @@ func (c *Client) newRequest(method, path string, body io.Reader) (*http.Request,
}
func (c *Client) do(req *http.Request) (*http.Response, error) {
c.checkEngineVersion()
resp, err := c.httpClient.Do(req)
if err != nil {
return nil, fmt.Errorf("Cannot reach engine at %s: %v", c.baseURL, err)
@@ -55,6 +73,75 @@ func (c *Client) do(req *http.Request) (*http.Response, error) {
return resp, nil
}
func (c *Client) checkEngineVersion() {
if c.versionChecked {
return
}
c.versionChecked = true
minVer := minEngineVersion
if minVer == "" || minVer == "dev" {
return
}
statusReq, err := c.newRequest(http.MethodGet, "/api/v1/status", nil)
if err != nil {
return
}
resp, err := c.httpClient.Do(statusReq)
if err != nil {
return // unreachable — let the actual request surface the error
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
return // auth error or other issue — let the actual request surface it
}
var status struct {
Version string `json:"version"`
}
if err := json.NewDecoder(resp.Body).Decode(&status); err != nil {
return
}
if !semverAtLeast(status.Version, minVer) {
fmt.Fprintf(os.Stderr, "Error: kb client v%s requires engine v%s+ (connected engine is v%s)\nUpdate your engine image to engine-v%s or later.\n",
clientVersion, minVer, status.Version, minVer)
os.Exit(1)
}
}
// semverAtLeast returns true if version >= minimum, comparing major.minor.patch.
func semverAtLeast(version, minimum string) bool {
parse := func(s string) (int, int, int) {
s = strings.TrimPrefix(s, "v")
parts := strings.SplitN(s, ".", 3)
var major, minor, patch int
if len(parts) >= 1 {
major, _ = strconv.Atoi(parts[0])
}
if len(parts) >= 2 {
minor, _ = strconv.Atoi(parts[1])
}
if len(parts) >= 3 {
patch, _ = strconv.Atoi(parts[2])
}
return major, minor, patch
}
vMaj, vMin, vPat := parse(version)
mMaj, mMin, mPat := parse(minimum)
if vMaj != mMaj {
return vMaj > mMaj
}
if vMin != mMin {
return vMin > mMin
}
return vPat >= mPat
}
// Get performs a GET request to the given path.
func (c *Client) Get(path string) (*http.Response, error) {
req, err := c.newRequest(http.MethodGet, path, nil)
@@ -134,6 +221,20 @@ func (c *Client) Put(path string, body interface{}) (*http.Response, error) {
return c.do(req)
}
// Patch performs a PATCH request with a JSON body.
func (c *Client) Patch(path string, body interface{}) (*http.Response, error) {
data, err := json.Marshal(body)
if err != nil {
return nil, fmt.Errorf("failed to marshal request body: %w", err)
}
req, err := c.newRequest(http.MethodPatch, path, bytes.NewReader(data))
if err != nil {
return nil, err
}
req.Header.Set("Content-Type", "application/json")
return c.do(req)
}
// DecodeJSON reads the response body and decodes it into target.
func DecodeJSON(resp *http.Response, target interface{}) error {
defer resp.Body.Close()
+136
View File
@@ -0,0 +1,136 @@
package api
import (
"encoding/json"
"net/http"
"net/http/httptest"
"testing"
)
func TestSemverAtLeast(t *testing.T) {
tests := []struct {
version string
minimum string
expected bool
}{
{"2.1.0", "2.0.0", true},
{"2.0.0", "2.0.0", true},
{"2.0.5", "2.0.0", true},
{"2.1.5", "2.1.0", true},
{"2.0.9", "2.1.0", false},
{"1.9.9", "2.0.0", false},
{"3.0.0", "2.9.9", true},
{"2.0.0", "2.0.1", false},
}
for _, tt := range tests {
t.Run(tt.version+">="+tt.minimum, func(t *testing.T) {
got := semverAtLeast(tt.version, tt.minimum)
if got != tt.expected {
t.Errorf("semverAtLeast(%q, %q) = %v, want %v", tt.version, tt.minimum, got, tt.expected)
}
})
}
}
func TestCheckEngineVersion_Compatible(t *testing.T) {
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
json.NewEncoder(w).Encode(map[string]string{"version": "2.1.0"})
}))
defer srv.Close()
clientVersion = "2.2.0"
minEngineVersion = "2.1.0"
defer func() { clientVersion = ""; minEngineVersion = "" }()
c := &Client{
baseURL: srv.URL,
httpClient: &http.Client{},
}
// Should not panic or exit
c.checkEngineVersion()
if !c.versionChecked {
t.Error("versionChecked should be true after check")
}
}
func TestCheckEngineVersion_SkipsWhenDev(t *testing.T) {
clientVersion = "dev"
minEngineVersion = "dev"
defer func() { clientVersion = ""; minEngineVersion = "" }()
c := &Client{
baseURL: "http://localhost:99999",
httpClient: &http.Client{},
}
// Should not attempt connection
c.checkEngineVersion()
if !c.versionChecked {
t.Error("versionChecked should be true after skipping")
}
}
func TestCheckEngineVersion_SkipsWhenEmpty(t *testing.T) {
clientVersion = "1.0.0"
minEngineVersion = ""
defer func() { clientVersion = ""; minEngineVersion = "" }()
c := &Client{
baseURL: "http://localhost:99999",
httpClient: &http.Client{},
}
c.checkEngineVersion()
if !c.versionChecked {
t.Error("versionChecked should be true after skipping")
}
}
func TestCheckEngineVersion_SkipsWhenUnreachable(t *testing.T) {
clientVersion = "2.0.0"
minEngineVersion = "2.0.0"
defer func() { clientVersion = ""; minEngineVersion = "" }()
c := &Client{
baseURL: "http://localhost:99999",
httpClient: &http.Client{},
}
// Should not panic — just skip
c.checkEngineVersion()
if !c.versionChecked {
t.Error("versionChecked should be true even when unreachable")
}
}
func TestCheckEngineVersion_CachedAfterFirstCall(t *testing.T) {
callCount := 0
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
callCount++
json.NewEncoder(w).Encode(map[string]string{"version": "2.1.0"})
}))
defer srv.Close()
clientVersion = "2.1.0"
minEngineVersion = "2.0.0"
defer func() { clientVersion = ""; minEngineVersion = "" }()
c := &Client{
baseURL: srv.URL,
httpClient: &http.Client{},
}
c.checkEngineVersion()
c.checkEngineVersion()
c.checkEngineVersion()
if callCount != 1 {
t.Errorf("expected 1 status call, got %d", callCount)
}
}
+36
View File
@@ -0,0 +1,36 @@
FROM ubuntu:24.04
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && apt-get install -y --no-install-recommends \
python3.12 python3.12-venv python3.12-dev python3-pip \
libpoppler-cpp-dev poppler-utils \
libgl1 libglib2.0-0 \
build-essential curl \
&& rm -rf /var/lib/apt/lists/*
COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
WORKDIR /app
COPY pyproject.toml ./
COPY kb/ kb/
COPY main.py ./
COPY VERSION ./
RUN uv venv .venv && \
. .venv/bin/activate && \
uv pip install -e . && \
uv pip install "sentence-transformers[onnx]" && \
uv pip install --reinstall torch torchvision --index-url https://download.pytorch.org/whl/cpu
ENV PATH="/app/.venv/bin:$PATH"
ENV VIRTUAL_ENV="/app/.venv"
ENV KB_DEVICE=cpu
ENV KB_INGEST_DEVICE=cpu
ENV KB_DATA_DIR=/data
EXPOSE 8000
VOLUME ["/data"]
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
+2 -2
View File
@@ -20,8 +20,8 @@ COPY VERSION ./
RUN uv venv .venv && \
. .venv/bin/activate && \
uv pip install -e . && \
uv pip install --no-deps onnxruntime-gpu
UV_HTTP_TIMEOUT=600 uv pip install torch torchvision --index-url https://download.pytorch.org/whl/cu130 && \
uv pip install -e .
ENV PATH="/app/.venv/bin:$PATH"
ENV VIRTUAL_ENV="/app/.venv"
-68
View File
@@ -1,68 +0,0 @@
# Stage 1: Build — install Python deps with dev tools available
FROM rocm/dev-ubuntu-24.04:6.4-complete AS builder
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && apt-get install -y --no-install-recommends \
python3.12 python3.12-venv python3.12-dev python3-pip \
libpoppler-cpp-dev poppler-utils \
build-essential curl \
&& rm -rf /var/lib/apt/lists/*
COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
WORKDIR /app
COPY pyproject.toml ./
COPY kb/ kb/
COPY main.py ./
COPY VERSION ./
RUN uv venv .venv && \
. .venv/bin/activate && \
uv pip install -e . && \
uv pip install --no-deps onnxruntime-rocm
# Stage 2: Runtime — minimal ROCm runtime libs only
FROM ubuntu:24.04
ENV DEBIAN_FRONTEND=noninteractive
# Add ROCm apt repository
RUN apt-get update && apt-get install -y --no-install-recommends \
ca-certificates curl gnupg \
&& mkdir -p /etc/apt/keyrings \
&& curl -fsSL https://repo.radeon.com/rocm/rocm.gpg.key \
| gpg --dearmor -o /etc/apt/keyrings/rocm.gpg \
&& echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/6.4.1 noble main" \
> /etc/apt/sources.list.d/rocm.list \
&& printf 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600\n' \
> /etc/apt/preferences.d/rocm-pin-600 \
&& apt-get update && apt-get install -y --no-install-recommends \
python3.12 python3.12-venv \
libpoppler-cpp0t64 poppler-utils \
libgl1 libglib2.0-0 \
rocm-hip-runtime \
rocm-hip-libraries \
miopen-hip \
&& rm -rf /var/lib/apt/lists/*
WORKDIR /app
# Copy built venv and application from builder
COPY --from=builder /app/.venv .venv
COPY --from=builder /app/kb kb
COPY --from=builder /app/main.py .
COPY --from=builder /app/pyproject.toml .
COPY --from=builder /app/VERSION .
ENV PATH="/app/.venv/bin:$PATH"
ENV VIRTUAL_ENV="/app/.venv"
ENV KB_DEVICE=auto
ENV KB_INGEST_DEVICE=auto
ENV KB_DATA_DIR=/data
EXPOSE 8000
VOLUME ["/data"]
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
+1 -1
View File
@@ -1 +1 @@
2.0.4
3.2.2
+33
View File
@@ -0,0 +1,33 @@
services:
kb-engine:
build:
context: .
dockerfile: Dockerfile.cpu
ports:
- "${KB_PORT:-8000}:8000"
volumes:
- ${KB_DATA_PATH:-./data}:/data
environment:
- KB_MODEL=${KB_MODEL:-all-MiniLM-L6-v2}
- KB_DEVICE=cpu
- KB_INGEST_DEVICE=cpu
- KB_API_KEY=${KB_API_KEY:-}
- KB_SEARCH_THRESHOLD=${KB_SEARCH_THRESHOLD:-0.01}
- HF_HUB_OFFLINE=${HF_HUB_OFFLINE:-}
restart: unless-stopped
kb-mcp:
build:
context: ../mcp
dockerfile: Dockerfile
ports:
- "${KB_MCP_PORT:-3000}:3000"
environment:
- KB_ENGINE_URL=http://kb-engine:8000
- KB_API_KEY=${KB_API_KEY:-}
- KB_MCP_API_KEY=${KB_MCP_API_KEY:-}
# Comma-separated IPs/FQDNs allowed to connect remotely (e.g. 192.168.1.50,kb.example.com)
- KB_MCP_ALLOWED_HOSTS=${KB_MCP_ALLOWED_HOSTS:-}
depends_on:
- kb-engine
restart: unless-stopped
+17
View File
@@ -21,4 +21,21 @@ services:
- KB_INGEST_DEVICE=${KB_INGEST_DEVICE:-auto}
- KB_API_KEY=${KB_API_KEY:-}
- KB_SEARCH_THRESHOLD=${KB_SEARCH_THRESHOLD:-0.01}
- HF_HUB_OFFLINE=${HF_HUB_OFFLINE:-}
restart: unless-stopped
kb-mcp:
build:
context: ../mcp
dockerfile: Dockerfile
ports:
- "${KB_MCP_PORT:-3000}:3000"
environment:
- KB_ENGINE_URL=http://kb-engine:8000
- KB_API_KEY=${KB_API_KEY:-}
- KB_MCP_API_KEY=${KB_MCP_API_KEY:-}
# Comma-separated IPs/FQDNs allowed to connect remotely (e.g. 192.168.1.50,kb.example.com)
- KB_MCP_ALLOWED_HOSTS=${KB_MCP_ALLOWED_HOSTS:-}
depends_on:
- kb-engine
restart: unless-stopped
-21
View File
@@ -1,21 +0,0 @@
services:
kb-engine:
build:
context: .
dockerfile: Dockerfile.rocm
devices:
- "/dev/kfd"
- "/dev/dri"
group_add:
- "video"
ports:
- "${KB_PORT:-8000}:8000"
volumes:
- ${KB_DATA_PATH:-./data}:/data
environment:
- KB_MODEL=${KB_MODEL:-all-MiniLM-L6-v2}
- KB_DEVICE=${KB_DEVICE:-auto}
- KB_INGEST_DEVICE=${KB_INGEST_DEVICE:-auto}
- KB_API_KEY=${KB_API_KEY:-}
- KB_SEARCH_THRESHOLD=${KB_SEARCH_THRESHOLD:-0.01}
restart: unless-stopped
Executable
+4
View File
@@ -0,0 +1,4 @@
#!/bin/bash
docker stop engine-kb-engine-1
KB_MODEL=BAAI/bge-base-en-v1.5 KB_DATA_PATH=~/kb-data docker compose -f compose.nvidia.yaml up -d --build
+6
View File
@@ -20,6 +20,7 @@ class Config:
self.ingest_device = os.environ.get("KB_INGEST_DEVICE", "auto")
self.api_key = os.environ.get("KB_API_KEY") or None
self.search_threshold = float(os.environ.get("KB_SEARCH_THRESHOLD", "0.01"))
self.bulk_safety_percent = int(os.environ.get("KB_BULK_SAFETY_PERCENT", "70"))
self.host = os.environ.get("KB_HOST", "0.0.0.0")
self.port = int(os.environ.get("KB_PORT", "8000"))
@@ -35,10 +36,15 @@ class Config:
def staging_dir(self) -> Path:
return self.data_dir / "staging"
@property
def documents_dir(self) -> Path:
return self.data_dir / "documents"
def ensure_dirs(self):
self.data_dir.mkdir(parents=True, exist_ok=True)
self.hf_cache.mkdir(exist_ok=True)
self.staging_dir.mkdir(exist_ok=True)
self.documents_dir.mkdir(exist_ok=True)
cfg = Config()
+206 -9
View File
@@ -10,6 +10,60 @@ import struct
from typing import Any, Optional
def build_enriched_text(title: str, chunk_text: str, metadata: dict | None = None) -> str:
"""Build enriched text by prepending document title and optional section header.
Format: "{title} > {section_header}\\n\\n{chunk_text}" or "{title}\\n\\n{chunk_text}".
"""
section_header = (metadata or {}).get("section_header")
if section_header:
return f"{title} > {section_header}\n\n{chunk_text}"
return f"{title}\n\n{chunk_text}"
def _backfill_enriched_text(conn: sqlite3.Connection) -> None:
"""Backfill enriched_text for all existing chunks."""
rows = conn.execute(
"SELECT c.id, c.text, c.metadata, d.title "
"FROM chunks c JOIN documents d ON c.document_id = d.id"
).fetchall()
for row in rows:
metadata = json.loads(row["metadata"]) if row["metadata"] else None
enriched = build_enriched_text(row["title"], row["text"], metadata)
conn.execute("UPDATE chunks SET enriched_text = ? WHERE id = ?", (enriched, row["id"]))
def _rebuild_fts(conn: sqlite3.Connection) -> None:
"""Drop and recreate chunks_fts to index enriched_text, with updated triggers."""
conn.executescript("""
DROP TRIGGER IF EXISTS chunks_ai;
DROP TRIGGER IF EXISTS chunks_ad;
DROP TRIGGER IF EXISTS chunks_au;
DROP TABLE IF EXISTS chunks_fts;
CREATE VIRTUAL TABLE chunks_fts USING fts5(
text,
content=chunks,
content_rowid=id
);
CREATE TRIGGER chunks_ai AFTER INSERT ON chunks BEGIN
INSERT INTO chunks_fts(rowid, text) VALUES (new.id, new.enriched_text);
END;
CREATE TRIGGER chunks_ad AFTER DELETE ON chunks BEGIN
INSERT INTO chunks_fts(chunks_fts, rowid, text) VALUES ('delete', old.id, old.enriched_text);
END;
CREATE TRIGGER chunks_au AFTER UPDATE ON chunks BEGIN
INSERT INTO chunks_fts(chunks_fts, rowid, text) VALUES ('delete', old.id, old.enriched_text);
INSERT INTO chunks_fts(rowid, text) VALUES (new.id, new.enriched_text);
END;
""")
# Repopulate FTS from existing enriched_text
conn.execute("INSERT INTO chunks_fts(rowid, text) SELECT id, enriched_text FROM chunks")
def get_connection(db_path: str) -> sqlite3.Connection:
"""Return a sqlite3 connection with WAL mode, Row factory, and foreign keys enabled."""
import sqlite_vec
@@ -20,6 +74,7 @@ def get_connection(db_path: str) -> sqlite3.Connection:
conn.enable_load_extension(False)
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA journal_mode=WAL")
conn.execute("PRAGMA busy_timeout=5000")
conn.execute("PRAGMA foreign_keys=ON")
return conn
@@ -34,6 +89,8 @@ def init_schema(conn: sqlite3.Connection, embedding_dim: int) -> None:
content_hash TEXT UNIQUE,
doc_type TEXT,
language TEXT,
stored_path TEXT,
original_filename TEXT,
created_at TEXT DEFAULT current_timestamp
);
@@ -42,6 +99,7 @@ def init_schema(conn: sqlite3.Connection, embedding_dim: int) -> None:
document_id INTEGER REFERENCES documents(id) ON DELETE CASCADE,
chunk_index INTEGER,
text TEXT,
enriched_text TEXT,
token_count INTEGER,
metadata TEXT DEFAULT '{{}}',
UNIQUE(document_id, chunk_index)
@@ -53,18 +111,18 @@ def init_schema(conn: sqlite3.Connection, embedding_dim: int) -> None:
content_rowid=id
);
-- Triggers to keep FTS index in sync with chunks table
-- Triggers to keep FTS index in sync with chunks table (using enriched_text)
CREATE TRIGGER IF NOT EXISTS chunks_ai AFTER INSERT ON chunks BEGIN
INSERT INTO chunks_fts(rowid, text) VALUES (new.id, new.text);
INSERT INTO chunks_fts(rowid, text) VALUES (new.id, new.enriched_text);
END;
CREATE TRIGGER IF NOT EXISTS chunks_ad AFTER DELETE ON chunks BEGIN
INSERT INTO chunks_fts(chunks_fts, rowid, text) VALUES ('delete', old.id, old.text);
INSERT INTO chunks_fts(chunks_fts, rowid, text) VALUES ('delete', old.id, old.enriched_text);
END;
CREATE TRIGGER IF NOT EXISTS chunks_au AFTER UPDATE ON chunks BEGIN
INSERT INTO chunks_fts(chunks_fts, rowid, text) VALUES ('delete', old.id, old.text);
INSERT INTO chunks_fts(rowid, text) VALUES (new.id, new.text);
INSERT INTO chunks_fts(chunks_fts, rowid, text) VALUES ('delete', old.id, old.enriched_text);
INSERT INTO chunks_fts(rowid, text) VALUES (new.id, new.enriched_text);
END;
CREATE TABLE IF NOT EXISTS tags (
@@ -94,6 +152,7 @@ def init_schema(conn: sqlite3.Connection, embedding_dim: int) -> None:
document_id INTEGER,
chunk_count INTEGER DEFAULT 0,
staging_path TEXT,
content_hash TEXT,
created_at TEXT DEFAULT current_timestamp,
completed_at TEXT
);
@@ -108,6 +167,34 @@ def init_schema(conn: sqlite3.Connection, embedding_dim: int) -> None:
f"CREATE VIRTUAL TABLE chunks_vec USING vec0(embedding float[{embedding_dim}], chunk_id integer)"
)
# Migrate: add content_hash to jobs if missing (added in v2.0.5)
cols = {row[1] for row in conn.execute("PRAGMA table_info(jobs)").fetchall()}
if "content_hash" not in cols:
conn.execute("ALTER TABLE jobs ADD COLUMN content_hash TEXT")
# Migrate: add stored_path and original_filename to documents if missing
doc_cols = {row[1] for row in conn.execute("PRAGMA table_info(documents)").fetchall()}
if "stored_path" not in doc_cols:
conn.execute("ALTER TABLE documents ADD COLUMN stored_path TEXT")
if "original_filename" not in doc_cols:
conn.execute("ALTER TABLE documents ADD COLUMN original_filename TEXT")
# Migrate: add enriched_text to chunks and rebuild FTS to index it
chunk_cols = {row[1] for row in conn.execute("PRAGMA table_info(chunks)").fetchall()}
if "enriched_text" not in chunk_cols:
conn.execute("ALTER TABLE chunks ADD COLUMN enriched_text TEXT")
_backfill_enriched_text(conn)
_rebuild_fts(conn)
# Migrate: add updated_at to documents if missing (v3.0.0)
if "updated_at" not in doc_cols:
conn.execute("ALTER TABLE documents ADD COLUMN updated_at TEXT")
# Migrate: add job_type to jobs if missing (bulk operations)
job_cols = {row[1] for row in conn.execute("PRAGMA table_info(jobs)").fetchall()}
if "job_type" not in job_cols:
conn.execute("ALTER TABLE jobs ADD COLUMN job_type TEXT DEFAULT 'ingest'")
conn.commit()
@@ -142,6 +229,28 @@ def hash_exists(conn: sqlite3.Connection, content_hash: str) -> bool:
return row is not None
def get_document_by_hash(conn: sqlite3.Connection, content_hash: str) -> dict | None:
"""Return duplicate info for a given hash, or None.
Checks both the documents table (already ingested) and the jobs table
(queued/processing). Returns a dict with either ``document_id`` or
``job_id`` so callers can distinguish the two cases.
"""
row = conn.execute(
"SELECT id, title FROM documents WHERE content_hash = ?", (content_hash,)
).fetchone()
if row is not None:
return {"document_id": row["id"], "title": row["title"]}
# Also check pending/processing jobs that haven't been committed to documents yet
row = conn.execute(
"SELECT id, filename FROM jobs WHERE content_hash = ? AND status IN ('queued', 'processing')",
(content_hash,),
).fetchone()
if row is not None:
return {"job_id": row["id"], "title": row["filename"]}
return None
def insert_document(
conn: sqlite3.Connection,
title: str,
@@ -168,6 +277,7 @@ def insert_chunk(
document_id: int,
chunk_index: int,
text: str,
enriched_text: str | None = None,
token_count: Optional[int] = None,
metadata: Any = None,
) -> int:
@@ -180,8 +290,8 @@ def insert_chunk(
metadata_str = str(metadata)
cur = conn.execute(
"INSERT INTO chunks(document_id, chunk_index, text, token_count, metadata) VALUES (?, ?, ?, ?, ?)",
(document_id, chunk_index, text, token_count, metadata_str),
"INSERT INTO chunks(document_id, chunk_index, text, enriched_text, token_count, metadata) VALUES (?, ?, ?, ?, ?, ?)",
(document_id, chunk_index, text, enriched_text or text, token_count, metadata_str),
)
conn.commit()
return cur.lastrowid
@@ -225,6 +335,92 @@ def untag_document(conn: sqlite3.Connection, document_id: int, tag_names: list[s
conn.commit()
# ---------------------------------------------------------------------------
# Bulk operation helpers
# ---------------------------------------------------------------------------
def resolve_bulk_selection(
conn: sqlite3.Connection,
document_ids: list[int] | None = None,
tags: list[str] | None = None,
doc_type: str | None = None,
from_id: int | None = None,
to_id: int | None = None,
) -> list[int]:
"""Return document IDs matching the bulk selection filter.
Filters combine with AND logic. At least one filter must be provided.
"""
sql = "SELECT DISTINCT d.id FROM documents d"
joins: list[str] = []
where: list[str] = []
params: list = []
if tags:
for i, tag in enumerate(tags):
joins.append(f"JOIN document_tags dt{i} ON d.id = dt{i}.document_id")
joins.append(f"JOIN tags t{i} ON dt{i}.tag_id = t{i}.id")
where.append(f"t{i}.name = ?")
params.append(tag)
if doc_type:
where.append("d.doc_type = ?")
params.append(doc_type)
if document_ids:
placeholders = ",".join("?" for _ in document_ids)
where.append(f"d.id IN ({placeholders})")
params.extend(document_ids)
if from_id is not None:
where.append("d.id >= ?")
params.append(from_id)
if to_id is not None:
where.append("d.id <= ?")
params.append(to_id)
if joins:
sql += " " + " ".join(joins)
if where:
sql += " WHERE " + " AND ".join(where)
rows = conn.execute(sql, params).fetchall()
return [row["id"] for row in rows]
def create_bulk_job(
conn: sqlite3.Connection,
job_type: str,
filters_json: str,
matched: int,
succeeded: int,
failed: int,
errors_json: str = "[]",
) -> int:
"""Create an audit log entry for a bulk operation and return its id."""
cur = conn.execute(
"""INSERT INTO jobs(filename, status, job_type, document_id, chunk_count, error, completed_at)
VALUES (?, ?, ?, ?, ?, ?, current_timestamp)""",
(
filters_json,
"done" if failed == 0 else "partial_failure",
job_type,
matched,
succeeded,
errors_json if failed > 0 else None,
),
)
conn.commit()
return cur.lastrowid
def count_documents(conn: sqlite3.Connection) -> int:
"""Return total number of documents in the database."""
row = conn.execute("SELECT COUNT(*) AS cnt FROM documents").fetchone()
return row["cnt"]
# ---------------------------------------------------------------------------
# Vec table management
# ---------------------------------------------------------------------------
@@ -252,11 +448,12 @@ def create_job(
doc_type: Optional[str] = None,
tags_json: str = "[]",
title: Optional[str] = None,
content_hash: Optional[str] = None,
) -> int:
"""Create a new ingest job and return its id."""
cur = conn.execute(
"INSERT INTO jobs(filename, staging_path, doc_type, tags_json, title) VALUES (?, ?, ?, ?, ?)",
(filename, staging_path, doc_type, tags_json, title),
"INSERT INTO jobs(filename, staging_path, doc_type, tags_json, title, content_hash) VALUES (?, ?, ?, ?, ?, ?)",
(filename, staging_path, doc_type, tags_json, title, content_hash),
)
conn.commit()
return cur.lastrowid
+1 -1
View File
@@ -1 +1 @@
from kb.routes import health, search, jobs, documents, tags, status, reindex, auth
from kb.routes import health, search, jobs, documents, tags, status, reindex, auth, notes
+281
View File
@@ -0,0 +1,281 @@
"""Bulk operation endpoints — delete, tag, and set-tags on multiple documents."""
import json
import logging
from pathlib import Path
from typing import Optional
from fastapi import HTTPException
from pydantic import BaseModel, model_validator
from main import app
from kb.config import cfg
from kb.database import (
get_connection,
resolve_bulk_selection,
count_documents,
create_bulk_job,
tag_document,
untag_document,
)
logger = logging.getLogger("kb.routes.bulk")
# ---------------------------------------------------------------------------
# Request models
# ---------------------------------------------------------------------------
class BulkSelectionRequest(BaseModel):
document_ids: Optional[list[int]] = None
tags: Optional[list[str]] = None
doc_type: Optional[str] = None
from_id: Optional[int] = None
to_id: Optional[int] = None
force: bool = False
@model_validator(mode="after")
def require_at_least_one_filter(self):
if not any([self.document_ids, self.tags, self.doc_type,
self.from_id is not None, self.to_id is not None]):
raise ValueError("At least one selection filter is required")
return self
class BulkDeleteRequest(BulkSelectionRequest):
pass
class BulkTagsRequest(BulkSelectionRequest):
add: Optional[list[str]] = None
remove: Optional[list[str]] = None
@model_validator(mode="after")
def require_add_or_remove(self):
if not self.add and not self.remove:
raise ValueError("At least one of 'add' or 'remove' is required")
return self
class BulkSetTagsRequest(BulkSelectionRequest):
new_tags: list[str]
# ---------------------------------------------------------------------------
# Shared helpers
# ---------------------------------------------------------------------------
def _check_safety_threshold(matched: int, total: int, force: bool) -> None:
"""Raise 409 if the operation would affect too many documents."""
threshold = cfg.bulk_safety_percent
if threshold <= 0 or force or total == 0:
return
percent = (matched / total) * 100
if percent > threshold:
raise HTTPException(
status_code=409,
detail={
"error": "safety_threshold_exceeded",
"message": (
f"Operation would affect {matched} of {total} documents "
f"({percent:.1f}%). Exceeds safety threshold of {threshold}%. "
f"Use force: true to proceed."
),
"matched": matched,
"total": total,
"percent": round(percent, 1),
"threshold": threshold,
},
)
def _filters_dict(req: BulkSelectionRequest) -> str:
"""Build a JSON string of the selection filter for audit logging."""
d = {}
if req.document_ids:
d["document_ids"] = req.document_ids
if req.tags:
d["tags"] = req.tags
if req.doc_type:
d["doc_type"] = req.doc_type
if req.from_id is not None:
d["from_id"] = req.from_id
if req.to_id is not None:
d["to_id"] = req.to_id
return json.dumps(d)
# ---------------------------------------------------------------------------
# Endpoints
# ---------------------------------------------------------------------------
@app.post("/api/v1/bulk/delete")
async def bulk_delete(req: BulkDeleteRequest):
conn = get_connection(cfg.db_path)
try:
doc_ids = resolve_bulk_selection(
conn, req.document_ids, req.tags, req.doc_type, req.from_id, req.to_id,
)
total = count_documents(conn)
_check_safety_threshold(len(doc_ids), total, req.force)
succeeded = 0
failed = 0
errors = []
stored_files: list[str] = []
for doc_id in doc_ids:
try:
doc = conn.execute(
"SELECT id, stored_path FROM documents WHERE id = ?", (doc_id,)
).fetchone()
if not doc:
failed += 1
errors.append({"document_id": doc_id, "error": "not found"})
continue
if doc["stored_path"]:
stored_files.append(doc["stored_path"])
# Delete embeddings
chunk_ids = conn.execute(
"SELECT id FROM chunks WHERE document_id = ?", (doc_id,)
).fetchall()
for row in chunk_ids:
conn.execute("DELETE FROM chunks_vec WHERE chunk_id = ?", (row["id"],))
# Delete document (cascades to chunks, document_tags)
conn.execute("DELETE FROM documents WHERE id = ?", (doc_id,))
succeeded += 1
except Exception as exc:
failed += 1
errors.append({"document_id": doc_id, "error": str(exc)})
conn.commit()
# Best-effort file cleanup after commit
for path in stored_files:
try:
f = Path(path)
if f.exists():
f.unlink()
except OSError as exc:
logger.warning("Failed to delete stored file %s: %s", path, exc)
errors_json = json.dumps(errors) if errors else "[]"
job_id = create_bulk_job(
conn, "bulk_delete", _filters_dict(req),
len(doc_ids), succeeded, failed, errors_json,
)
return {
"job_id": job_id,
"status": "done" if failed == 0 else "partial_failure",
"matched": len(doc_ids),
"succeeded": succeeded,
"failed": failed,
"errors": errors,
}
finally:
conn.close()
@app.post("/api/v1/bulk/tags")
async def bulk_tags(req: BulkTagsRequest):
conn = get_connection(cfg.db_path)
try:
doc_ids = resolve_bulk_selection(
conn, req.document_ids, req.tags, req.doc_type, req.from_id, req.to_id,
)
total = count_documents(conn)
_check_safety_threshold(len(doc_ids), total, req.force)
succeeded = 0
failed = 0
errors = []
for doc_id in doc_ids:
try:
if req.add:
tag_document(conn, doc_id, req.add)
if req.remove:
untag_document(conn, doc_id, req.remove)
conn.execute(
"UPDATE documents SET updated_at = current_timestamp WHERE id = ?",
(doc_id,),
)
succeeded += 1
except Exception as exc:
failed += 1
errors.append({"document_id": doc_id, "error": str(exc)})
conn.commit()
errors_json = json.dumps(errors) if errors else "[]"
job_id = create_bulk_job(
conn, "bulk_tags", _filters_dict(req),
len(doc_ids), succeeded, failed, errors_json,
)
return {
"job_id": job_id,
"status": "done" if failed == 0 else "partial_failure",
"matched": len(doc_ids),
"succeeded": succeeded,
"failed": failed,
"errors": errors,
}
finally:
conn.close()
@app.post("/api/v1/bulk/set-tags")
async def bulk_set_tags(req: BulkSetTagsRequest):
conn = get_connection(cfg.db_path)
try:
doc_ids = resolve_bulk_selection(
conn, req.document_ids, req.tags, req.doc_type, req.from_id, req.to_id,
)
total = count_documents(conn)
_check_safety_threshold(len(doc_ids), total, req.force)
succeeded = 0
failed = 0
errors = []
for doc_id in doc_ids:
try:
# Remove all existing tags
conn.execute(
"DELETE FROM document_tags WHERE document_id = ?", (doc_id,)
)
# Apply new tag set
if req.new_tags:
tag_document(conn, doc_id, req.new_tags)
conn.execute(
"UPDATE documents SET updated_at = current_timestamp WHERE id = ?",
(doc_id,),
)
succeeded += 1
except Exception as exc:
failed += 1
errors.append({"document_id": doc_id, "error": str(exc)})
conn.commit()
errors_json = json.dumps(errors) if errors else "[]"
job_id = create_bulk_job(
conn, "bulk_set_tags", _filters_dict(req),
len(doc_ids), succeeded, failed, errors_json,
)
return {
"job_id": job_id,
"status": "done" if failed == 0 else "partial_failure",
"matched": len(doc_ids),
"succeeded": succeeded,
"failed": failed,
"errors": errors,
}
finally:
conn.close()
+68 -3
View File
@@ -1,14 +1,20 @@
"""Document management endpoints — list, view, and delete documents."""
import json
import logging
import mimetypes
from pathlib import Path
from typing import Optional
from fastapi import HTTPException, Query
from fastapi.responses import FileResponse
from main import app
from kb.config import cfg
from kb.database import get_connection
logger = logging.getLogger("kb.routes.documents")
@app.get("/api/v1/documents")
async def list_documents(
@@ -20,7 +26,7 @@ async def list_documents(
sql = """
SELECT d.id, d.title, d.doc_type,
(SELECT COUNT(*) FROM chunks c WHERE c.document_id = d.id) AS chunk_count,
d.created_at
d.created_at, d.updated_at
FROM documents d
"""
joins: list[str] = []
@@ -44,7 +50,7 @@ async def list_documents(
if where:
sql += " WHERE " + " AND ".join(where)
sql += " ORDER BY d.created_at DESC"
sql += " ORDER BY COALESCE(d.updated_at, d.created_at) DESC"
rows = conn.execute(sql, params).fetchall()
@@ -68,6 +74,7 @@ async def list_documents(
"tags": [t["name"] for t in tag_rows],
"chunk_count": row["chunk_count"],
"created_at": row["created_at"],
"updated_at": row["updated_at"],
})
return results
@@ -100,8 +107,12 @@ async def get_document(doc_id: int):
(doc_id,),
).fetchall()
stored_path = doc["stored_path"]
has_file = bool(stored_path and Path(stored_path).exists())
return {
**dict(doc),
"has_file": has_file,
"tags": [t["name"] for t in tag_rows],
"chunks": [dict(c) for c in chunks],
}
@@ -109,12 +120,53 @@ async def get_document(doc_id: int):
conn.close()
@app.get("/api/v1/documents/{doc_id}/file")
async def download_document_file(doc_id: int):
conn = get_connection(cfg.db_path)
try:
doc = conn.execute(
"SELECT id, title, stored_path, original_filename FROM documents WHERE id = ?",
(doc_id,),
).fetchone()
if not doc:
raise HTTPException(status_code=404, detail="Document not found.")
stored_path = doc["stored_path"]
if not stored_path:
raise HTTPException(
status_code=404,
detail="Original file not available - ingested before document storage was enabled.",
)
file_path = Path(stored_path)
if not file_path.exists():
raise HTTPException(
status_code=404,
detail="Stored file not found on disk.",
)
original_filename = doc["original_filename"]
if not original_filename:
ext = file_path.suffix
original_filename = (doc["title"] or "document") + ext
media_type = mimetypes.guess_type(original_filename)[0] or "application/octet-stream"
return FileResponse(
path=str(file_path),
media_type=media_type,
filename=original_filename,
)
finally:
conn.close()
@app.delete("/api/v1/documents/{doc_id}")
async def delete_document(doc_id: int):
conn = get_connection(cfg.db_path)
try:
doc = conn.execute(
"SELECT id, title FROM documents WHERE id = ?", (doc_id,)
"SELECT id, title, stored_path FROM documents WHERE id = ?", (doc_id,)
).fetchone()
if not doc:
raise HTTPException(status_code=404, detail="Document not found.")
@@ -134,6 +186,19 @@ async def delete_document(doc_id: int):
conn.execute("DELETE FROM documents WHERE id = ?", (doc_id,))
conn.commit()
# Delete stored file from disk
stored_path = doc["stored_path"]
if stored_path:
try:
file_path = Path(stored_path)
if file_path.exists():
file_path.unlink()
logger.info("Deleted stored file: %s", stored_path)
else:
logger.warning("Stored file already missing: %s", stored_path)
except OSError as exc:
logger.warning("Failed to delete stored file %s: %s", stored_path, exc)
return {
"status": "deleted",
"document_id": doc_id,
+24 -8
View File
@@ -1,13 +1,15 @@
"""Job management endpoints — submit files/notes for ingestion and track progress."""
import hashlib
import json
from typing import Optional
from fastapi import HTTPException, UploadFile, File, Form, Query
from fastapi.responses import JSONResponse
from main import app
from kb.config import cfg
from kb.database import get_connection, create_job, get_job, list_jobs
from kb.database import get_connection, create_job, get_job, list_jobs, get_document_by_hash
from kb.staging import stage_file, stage_note
@@ -27,18 +29,32 @@ async def submit_job(
if file:
content = await file.read()
staging_path = stage_file(cfg.staging_dir, file.filename, content)
content_hash = hashlib.sha256(content).hexdigest()
filename = file.filename
else:
staging_path = stage_note(cfg.staging_dir, title or "note", note)
filename = staging_path.name
tags_list = [t.strip() for t in tags.split(",") if t.strip()] if tags else []
tags_json = json.dumps(tags_list)
content = note.encode("utf-8")
content_hash = hashlib.sha256(content).hexdigest()
filename = None
conn = get_connection(cfg.db_path)
try:
job_id = create_job(conn, filename, str(staging_path), doc_type, tags_json, title)
existing = get_document_by_hash(conn, content_hash)
if existing:
return JSONResponse(
status_code=409,
content={"error": "duplicate", **existing},
)
if file:
staging_path = stage_file(cfg.staging_dir, file.filename, content)
else:
staging_path = stage_note(cfg.staging_dir, title or "note", note)
filename = staging_path.name
tags_list = [t.strip() for t in tags.split(",") if t.strip()] if tags else []
tags_json = json.dumps(tags_list)
job_id = create_job(conn, filename, str(staging_path), doc_type, tags_json, title, content_hash)
return {"job_id": job_id, "status": "queued", "filename": filename}
finally:
conn.close()
+120
View File
@@ -0,0 +1,120 @@
"""Note mutation endpoint — update existing notes in place."""
import hashlib
import logging
from fastapi import HTTPException
from pydantic import BaseModel
from main import app
from kb.config import cfg
from kb.database import (
get_connection,
build_enriched_text,
insert_chunk,
insert_embedding,
)
from kb.embeddings import embed_texts
from kb.ingest.note import chunk_note
logger = logging.getLogger("kb.routes.notes")
class NoteUpdateRequest(BaseModel):
text: str
@app.patch("/api/v1/notes/{doc_id}")
async def update_note(doc_id: int, req: NoteUpdateRequest):
conn = get_connection(cfg.db_path)
try:
doc = conn.execute(
"SELECT id, title, doc_type FROM documents WHERE id = ?", (doc_id,)
).fetchone()
if not doc:
raise HTTPException(status_code=404, detail="Document not found.")
if doc["doc_type"] != "note":
raise HTTPException(
status_code=422,
detail="Only notes can be updated via this endpoint.",
)
title = doc["title"]
# Delete existing chunks and their embeddings
chunk_ids = conn.execute(
"SELECT id FROM chunks WHERE document_id = ?", (doc_id,)
).fetchall()
for row in chunk_ids:
conn.execute("DELETE FROM chunks_vec WHERE chunk_id = ?", (row["id"],))
conn.execute("DELETE FROM chunks WHERE document_id = ?", (doc_id,))
# Run note chunking pipeline on new text
chunks = chunk_note(req.text)
chunk_texts = [c["text"] for c in chunks]
chunk_metas = [
{k: v for k, v in c.items() if k != "text"} or None for c in chunks
]
enriched_texts = [
build_enriched_text(title, ct, cm)
for ct, cm in zip(chunk_texts, chunk_metas)
]
# Embed — if this fails, the transaction rolls back
vectors = embed_texts(enriched_texts)
for idx, (chunk_text, enriched, vector) in enumerate(
zip(chunk_texts, enriched_texts, vectors)
):
chunk_id = insert_chunk(
conn,
document_id=doc_id,
chunk_index=idx,
text=chunk_text,
enriched_text=enriched,
metadata=chunk_metas[idx],
)
insert_embedding(conn, chunk_id, vector)
# Update content_hash and updated_at
content_hash = hashlib.sha256(req.text.encode("utf-8")).hexdigest()
conn.execute(
"UPDATE documents SET content_hash = ?, updated_at = current_timestamp WHERE id = ?",
(content_hash, doc_id),
)
conn.commit()
# Return updated document
updated_doc = conn.execute(
"SELECT * FROM documents WHERE id = ?", (doc_id,)
).fetchone()
new_chunks = conn.execute(
"SELECT * FROM chunks WHERE document_id = ? ORDER BY chunk_index",
(doc_id,),
).fetchall()
tag_rows = conn.execute(
"""
SELECT t.name FROM tags t
JOIN document_tags dt ON t.id = dt.tag_id
WHERE dt.document_id = ?
ORDER BY t.name
""",
(doc_id,),
).fetchall()
return {
**dict(updated_doc),
"tags": [t["name"] for t in tag_rows],
"chunks": [dict(c) for c in new_chunks],
}
except HTTPException:
raise
except Exception:
conn.rollback()
logger.exception("Failed to update note %d", doc_id)
raise HTTPException(status_code=500, detail="Failed to update note.")
finally:
conn.close()
+3 -3
View File
@@ -19,10 +19,10 @@ async def reindex():
conn = get_connection(cfg.db_path)
try:
# Fetch all chunks
rows = conn.execute("SELECT id, text FROM chunks ORDER BY id").fetchall()
# Fetch all chunks — use enriched_text for embedding (includes title context)
rows = conn.execute("SELECT id, enriched_text FROM chunks ORDER BY id").fetchall()
chunk_ids = [row["id"] for row in rows]
chunk_texts = [row["text"] for row in rows]
chunk_texts = [row["enriched_text"] or "" for row in rows]
logger.info("Reindexing %d chunks with model '%s'", len(chunk_ids), cfg.model)
+7
View File
@@ -48,6 +48,13 @@ async def update_document_tags(doc_id: int, req: TagUpdateRequest):
if req.remove:
untag_document(conn, doc_id, req.remove)
if req.add or req.remove:
conn.execute(
"UPDATE documents SET updated_at = current_timestamp WHERE id = ?",
(doc_id,),
)
conn.commit()
tag_rows = conn.execute(
"""
SELECT t.name FROM tags t
+28 -2
View File
@@ -1,9 +1,12 @@
"""Hybrid search — FTS5 + sqlite-vec with Reciprocal Rank Fusion."""
import json
import logging
import struct
import sqlite3
logger = logging.getLogger("kb.search")
def hybrid_search(
conn: sqlite3.Connection,
@@ -74,6 +77,21 @@ def hybrid_search(
# Internal helpers
# ---------------------------------------------------------------------------
def _sanitize_fts_query(query: str) -> str:
"""Escape a raw user query for safe use with FTS5 MATCH.
Splits on whitespace, strips double quotes from each token, wraps each
token in double quotes (making FTS5 treat all content as literals), and
joins with spaces. Returns empty string if no valid tokens remain.
"""
tokens = []
for token in query.split():
token = token.replace('"', '')
if token:
tokens.append(f'"{token}"')
return " ".join(tokens)
def _fts_search(
conn: sqlite3.Connection,
query: str,
@@ -86,10 +104,14 @@ def _fts_search(
Returns:
{chunk_id: bm25_score} where scores are positive (higher = better).
"""
safe_query = _sanitize_fts_query(query)
if not safe_query:
return {}
sql = "SELECT f.rowid AS chunk_id, bm25(chunks_fts) AS rank FROM chunks_fts f"
joins: list[str] = []
where: list[str] = ["chunks_fts MATCH ?"]
params: list = [query]
params: list = [safe_query]
if tags or doc_type:
joins.append("JOIN chunks c ON f.rowid = c.id")
@@ -111,7 +133,11 @@ def _fts_search(
sql += " ORDER BY rank LIMIT ?"
params.append(limit)
rows = conn.execute(sql, params).fetchall()
try:
rows = conn.execute(sql, params).fetchall()
except sqlite3.OperationalError:
logger.warning("FTS5 query failed for input: %r", query)
return {}
# BM25 returns negative values (lower = better match); negate so
# higher = better.
+4 -2
View File
@@ -16,7 +16,8 @@ def stage_file(staging_dir: Path, filename: str, content: bytes) -> Path:
The path to the newly created staged file.
"""
staging_dir.mkdir(parents=True, exist_ok=True)
dest = staging_dir / f"{uuid.uuid4()}_{filename}"
safe_filename = filename.replace("/", "_").replace("\\", "_")
dest = staging_dir / f"{uuid.uuid4()}_{safe_filename}"
dest.write_bytes(content)
logger.debug("Staged file: %s (%d bytes)", dest, len(content))
return dest
@@ -31,7 +32,8 @@ def stage_note(staging_dir: Path, title: str, text: str) -> Path:
The path to the newly created staged note file.
"""
staging_dir.mkdir(parents=True, exist_ok=True)
dest = staging_dir / f"{uuid.uuid4()}_{title}.note"
safe_title = title.replace("/", "_").replace("\\", "_")
dest = staging_dir / f"{uuid.uuid4()}_{safe_title}.note"
dest.write_text(text, encoding="utf-8")
logger.debug("Staged note: %s (%d chars)", dest, len(text))
return dest
+44 -9
View File
@@ -4,9 +4,11 @@ import asyncio
import hashlib
import json
import logging
import shutil
from pathlib import Path
from kb import config, database, embeddings, staging
from kb.database import build_enriched_text
from kb.ingest import detector
logger = logging.getLogger("kb.worker")
@@ -145,20 +147,30 @@ def _process_job(job_row) -> tuple[str, int | None, int]:
)
chunk_texts = [c if isinstance(c, str) else c["text"] for c in chunks]
vectors = embeddings.embed_texts(chunk_texts)
chunk_metas = []
for idx, c in enumerate(chunks):
if isinstance(c, str):
chunk_metas.append(None)
else:
meta = {k: v for k, v in c.items() if k != "text"} or None
chunk_metas.append(meta)
for idx, (chunk_text, vector) in enumerate(zip(chunk_texts, vectors)):
metadata = None
if not isinstance(chunks[idx], str):
metadata = {
k: v for k, v in chunks[idx].items() if k != "text"
} or None
enriched_texts = [
build_enriched_text(title, ct, cm)
for ct, cm in zip(chunk_texts, chunk_metas)
]
vectors = embeddings.embed_texts(enriched_texts)
for idx, (chunk_text, enriched, vector) in enumerate(
zip(chunk_texts, enriched_texts, vectors)
):
chunk_id = database.insert_chunk(
conn,
document_id=doc_id,
chunk_index=idx,
text=chunk_text,
metadata=metadata,
enriched_text=enriched,
metadata=chunk_metas[idx],
)
database.insert_embedding(conn, chunk_id, vector)
@@ -168,8 +180,31 @@ def _process_job(job_row) -> tuple[str, int | None, int]:
database.tag_document(conn, doc_id, tags)
conn.commit()
# --- Move original file to persistent storage ---------------------
ext = Path(filename).suffix or staged_path.suffix
dest = cfg.documents_dir / f"{content_hash}{ext}"
try:
cfg.documents_dir.mkdir(parents=True, exist_ok=True)
shutil.move(str(staged_path), str(dest))
conn_update = database.get_connection(cfg.db_path)
try:
conn_update.execute(
"UPDATE documents SET stored_path = ?, original_filename = ? WHERE id = ?",
(str(dest), filename, doc_id),
)
conn_update.commit()
finally:
conn_update.close()
logger.info("Stored original file: %s", dest)
except Exception as exc:
logger.warning("Failed to store original file: %s", exc)
staging.cleanup(staged_path)
return ("done", doc_id, len(chunk_texts))
finally:
conn.close()
staging.cleanup(staged_path)
# Only clean up staging if the file is still there (not moved)
if staged_path.exists():
staging.cleanup(staged_path)
+1 -1
View File
@@ -62,7 +62,7 @@ async def lifespan(app: FastAPI):
app = FastAPI(title="kb-engine", version=__version__, lifespan=lifespan)
# Import routes after app is created
from kb.routes import health, search, jobs, documents, tags, status, reindex, auth # noqa: E402, F401
from kb.routes import health, search, jobs, documents, tags, status, reindex, auth, notes, bulk # noqa: E402, F401
if __name__ == "__main__":
import uvicorn
View File
+223
View File
@@ -0,0 +1,223 @@
"""Tests for original document storage feature."""
import hashlib
import shutil
import sqlite3
from pathlib import Path
from unittest.mock import patch
import pytest
from fastapi.testclient import TestClient
@pytest.fixture
def data_dir(tmp_path):
"""Create a temporary data directory with required subdirectories."""
staging = tmp_path / "staging"
staging.mkdir()
documents = tmp_path / "documents"
documents.mkdir()
return tmp_path
@pytest.fixture
def db_conn(data_dir):
"""Create an in-memory-style SQLite DB with the full schema."""
db_path = data_dir / "kb.db"
conn = sqlite3.connect(str(db_path))
conn.row_factory = sqlite3.Row
conn.execute("PRAGMA foreign_keys=ON")
conn.executescript("""
CREATE TABLE IF NOT EXISTS documents (
id INTEGER PRIMARY KEY,
title TEXT,
source_path TEXT,
content_hash TEXT UNIQUE,
doc_type TEXT,
language TEXT,
stored_path TEXT,
original_filename TEXT,
created_at TEXT DEFAULT current_timestamp
);
CREATE TABLE IF NOT EXISTS chunks (
id INTEGER PRIMARY KEY,
document_id INTEGER REFERENCES documents(id) ON DELETE CASCADE,
chunk_index INTEGER,
text TEXT,
token_count INTEGER,
metadata TEXT DEFAULT '{}',
UNIQUE(document_id, chunk_index)
);
CREATE TABLE IF NOT EXISTS tags (
id INTEGER PRIMARY KEY,
name TEXT UNIQUE COLLATE NOCASE
);
CREATE TABLE IF NOT EXISTS document_tags (
document_id INTEGER REFERENCES documents(id) ON DELETE CASCADE,
tag_id INTEGER REFERENCES tags(id) ON DELETE CASCADE,
UNIQUE(document_id, tag_id)
);
CREATE TABLE IF NOT EXISTS jobs (
id INTEGER PRIMARY KEY,
filename TEXT,
status TEXT DEFAULT 'queued',
doc_type TEXT,
tags_json TEXT DEFAULT '[]',
title TEXT,
error TEXT,
document_id INTEGER,
chunk_count INTEGER DEFAULT 0,
staging_path TEXT,
content_hash TEXT,
created_at TEXT DEFAULT current_timestamp,
completed_at TEXT
);
""")
conn.commit()
yield conn
conn.close()
@pytest.fixture
def sample_pdf(data_dir):
"""Create a fake PDF file in staging."""
content = b"%PDF-1.4 fake pdf content for testing"
staging = data_dir / "staging"
path = staging / "test_upload.pdf"
path.write_bytes(content)
return path, content
class TestWorkerFileStorage:
"""Tests for worker moving files to persistent storage."""
def test_successful_ingestion_stores_file(self, data_dir, db_conn, sample_pdf):
"""7.1 - Test successful ingestion stores file at expected path."""
staged_path, content = sample_pdf
content_hash = hashlib.sha256(content).hexdigest()
documents_dir = data_dir / "documents"
expected_dest = documents_dir / f"{content_hash}.pdf"
# Simulate what the worker does: move file to documents dir
shutil.move(str(staged_path), str(expected_dest))
assert expected_dest.exists()
assert expected_dest.read_bytes() == content
assert not staged_path.exists()
# Simulate DB update
db_conn.execute(
"INSERT INTO documents(title, source_path, content_hash, doc_type, stored_path, original_filename) "
"VALUES (?, ?, ?, ?, ?, ?)",
("Test PDF", str(staged_path), content_hash, "pdf", str(expected_dest), "test_upload.pdf"),
)
db_conn.commit()
row = db_conn.execute("SELECT stored_path, original_filename FROM documents WHERE content_hash = ?", (content_hash,)).fetchone()
assert row["stored_path"] == str(expected_dest)
assert row["original_filename"] == "test_upload.pdf"
def test_failed_ingestion_no_file_in_documents(self, data_dir, sample_pdf):
"""7.2 - Test failed ingestion does not leave file in documents dir."""
staged_path, _ = sample_pdf
documents_dir = data_dir / "documents"
# Simulate failure: staging file gets cleaned up, nothing in documents dir
staged_path.unlink()
assert len(list(documents_dir.iterdir())) == 0
def test_document_deletion_removes_stored_file(self, data_dir, db_conn, sample_pdf):
"""7.4 - Test document deletion removes stored file."""
staged_path, content = sample_pdf
content_hash = hashlib.sha256(content).hexdigest()
documents_dir = data_dir / "documents"
dest = documents_dir / f"{content_hash}.pdf"
shutil.move(str(staged_path), str(dest))
db_conn.execute(
"INSERT INTO documents(title, source_path, content_hash, doc_type, stored_path, original_filename) "
"VALUES (?, ?, ?, ?, ?, ?)",
("Test PDF", str(staged_path), content_hash, "pdf", str(dest), "test_upload.pdf"),
)
db_conn.commit()
# Simulate delete: remove from DB and disk
doc = db_conn.execute("SELECT id, stored_path FROM documents WHERE content_hash = ?", (content_hash,)).fetchone()
stored = Path(doc["stored_path"])
db_conn.execute("DELETE FROM documents WHERE id = ?", (doc["id"],))
db_conn.commit()
if stored.exists():
stored.unlink()
assert not stored.exists()
assert db_conn.execute("SELECT COUNT(*) FROM documents", ()).fetchone()[0] == 0
def test_download_404_for_document_without_stored_file(self, db_conn):
"""7.5 - Test download returns 404 for documents without stored files."""
db_conn.execute(
"INSERT INTO documents(title, source_path, content_hash, doc_type) "
"VALUES (?, ?, ?, ?)",
("Old Doc", "/tmp/gone", "abc123", "pdf"),
)
db_conn.commit()
row = db_conn.execute("SELECT stored_path FROM documents WHERE content_hash = 'abc123'").fetchone()
assert row["stored_path"] is None
class TestFileDownloadEndpoint:
"""Tests for the /api/v1/documents/{id}/file endpoint logic."""
def test_file_response_uses_original_filename(self, data_dir, db_conn, sample_pdf):
"""7.3 - Test file download uses correct original filename."""
staged_path, content = sample_pdf
content_hash = hashlib.sha256(content).hexdigest()
documents_dir = data_dir / "documents"
dest = documents_dir / f"{content_hash}.pdf"
shutil.move(str(staged_path), str(dest))
db_conn.execute(
"INSERT INTO documents(title, source_path, content_hash, doc_type, stored_path, original_filename) "
"VALUES (?, ?, ?, ?, ?, ?)",
("My Report", str(staged_path), content_hash, "pdf", str(dest), "quarterly_report.pdf"),
)
db_conn.commit()
doc = db_conn.execute("SELECT stored_path, original_filename, title FROM documents WHERE content_hash = ?", (content_hash,)).fetchone()
# Verify the original filename is preserved and different from title
assert doc["original_filename"] == "quarterly_report.pdf"
assert doc["title"] == "My Report"
assert Path(doc["stored_path"]).exists()
def test_fallback_to_title_when_no_original_filename(self, data_dir, db_conn):
"""Test that title+ext is used when original_filename is NULL."""
documents_dir = data_dir / "documents"
fake_file = documents_dir / "somehash.pdf"
fake_file.write_bytes(b"fake")
db_conn.execute(
"INSERT INTO documents(title, source_path, content_hash, doc_type, stored_path) "
"VALUES (?, ?, ?, ?, ?)",
("Engine Manual", "/tmp/old", "hash456", "pdf", str(fake_file)),
)
db_conn.commit()
doc = db_conn.execute("SELECT original_filename, title, stored_path FROM documents WHERE content_hash = 'hash456'").fetchone()
# When original_filename is NULL, the endpoint should fall back to title + ext
original_filename = doc["original_filename"]
if not original_filename:
ext = Path(doc["stored_path"]).suffix
original_filename = (doc["title"] or "document") + ext
assert original_filename == "Engine Manual.pdf"
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FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt
COPY *.py ./
ENV KB_ENGINE_URL=http://engine:8000
ENV KB_API_KEY=
ENV KB_MCP_API_KEY=
ENV KB_MCP_PORT=3000
EXPOSE 3000
CMD ["python", "server.py"]
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"""Configuration from environment variables."""
import os
KB_ENGINE_URL = os.environ.get("KB_ENGINE_URL", "http://localhost:8000")
KB_API_KEY = os.environ.get("KB_API_KEY", "")
KB_MCP_API_KEY = os.environ.get("KB_MCP_API_KEY", "")
KB_MCP_PORT = int(os.environ.get("KB_MCP_PORT", "3000"))
KB_MCP_ALLOWED_HOSTS = os.environ.get("KB_MCP_ALLOWED_HOSTS", "")
def parse_allowed_hosts() -> list[str]:
"""Parse KB_MCP_ALLOWED_HOSTS into a list of host strings."""
if not KB_MCP_ALLOWED_HOSTS:
return []
return [h.strip() for h in KB_MCP_ALLOWED_HOSTS.split(",") if h.strip()]
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"""HTTP client for the kb engine API."""
import httpx
from config import KB_ENGINE_URL, KB_API_KEY
def _auth_headers() -> dict[str, str]:
h: dict[str, str] = {}
if KB_API_KEY:
h["Authorization"] = f"Bearer {KB_API_KEY}"
return h
def _client() -> httpx.Client:
return httpx.Client(base_url=KB_ENGINE_URL, headers=_auth_headers(), timeout=60.0)
def search(query: str, top: int = 10, tags: list[str] | None = None,
doc_type: str | None = None, fts_only: bool = False,
vec_only: bool = False, threshold: float | None = None) -> dict:
body: dict = {"query": query, "top": top}
if tags:
body["tags"] = tags
if doc_type:
body["doc_type"] = doc_type
if fts_only:
body["fts_only"] = True
if vec_only:
body["vec_only"] = True
if threshold is not None:
body["threshold"] = threshold
with _client() as c:
r = c.post("/api/v1/search", json=body)
r.raise_for_status()
return r.json()
def add_note(text: str, tags: list[str] | None = None,
title: str | None = None) -> dict:
fields = {"note": text}
if tags:
fields["tags"] = ",".join(tags)
if title:
fields["title"] = title
with _client() as c:
r = c.post("/api/v1/jobs", data=fields)
r.raise_for_status()
return r.json()
def update_note(doc_id: int, text: str) -> dict:
with _client() as c:
r = c.patch(f"/api/v1/notes/{doc_id}", json={"text": text})
r.raise_for_status()
return r.json()
def get_document(doc_id: int) -> dict:
with _client() as c:
r = c.get(f"/api/v1/documents/{doc_id}")
r.raise_for_status()
return r.json()
def list_documents(doc_type: str | None = None,
tags: str | None = None) -> list[dict]:
params: dict = {}
if doc_type:
params["type"] = doc_type
if tags:
params["tags"] = tags
with _client() as c:
r = c.get("/api/v1/documents", params=params)
r.raise_for_status()
return r.json()
def get_status() -> dict:
with _client() as c:
r = c.get("/api/v1/status")
r.raise_for_status()
return r.json()
def list_jobs(status: str | None = None) -> list[dict]:
params: dict = {}
if status:
params["status"] = status
with _client() as c:
r = c.get("/api/v1/jobs", params=params)
r.raise_for_status()
return r.json()
def update_tags(doc_id: int, add: list[str] | None = None,
remove: list[str] | None = None) -> dict:
body: dict = {}
if add:
body["add"] = add
if remove:
body["remove"] = remove
with _client() as c:
r = c.put(f"/api/v1/documents/{doc_id}/tags", json=body)
r.raise_for_status()
return r.json()
def delete_document(doc_id: int) -> dict:
with _client() as c:
r = c.delete(f"/api/v1/documents/{doc_id}")
r.raise_for_status()
return r.json()
def _bulk_body(
document_ids: list[int] | None = None,
tags: list[str] | None = None,
doc_type: str | None = None,
from_id: int | None = None,
to_id: int | None = None,
force: bool = False,
**extra,
) -> dict:
body: dict = {}
if document_ids:
body["document_ids"] = document_ids
if tags:
body["tags"] = tags
if doc_type:
body["doc_type"] = doc_type
if from_id is not None:
body["from_id"] = from_id
if to_id is not None:
body["to_id"] = to_id
if force:
body["force"] = True
body.update(extra)
return body
def bulk_delete(
document_ids: list[int] | None = None,
tags: list[str] | None = None,
doc_type: str | None = None,
from_id: int | None = None,
to_id: int | None = None,
force: bool = False,
) -> dict:
body = _bulk_body(document_ids, tags, doc_type, from_id, to_id, force)
with _client() as c:
r = c.post("/api/v1/bulk/delete", json=body)
r.raise_for_status()
return r.json()
def bulk_tags(
document_ids: list[int] | None = None,
tags: list[str] | None = None,
doc_type: str | None = None,
from_id: int | None = None,
to_id: int | None = None,
add: list[str] | None = None,
remove: list[str] | None = None,
force: bool = False,
) -> dict:
extra = {}
if add:
extra["add"] = add
if remove:
extra["remove"] = remove
body = _bulk_body(document_ids, tags, doc_type, from_id, to_id, force, **extra)
with _client() as c:
r = c.post("/api/v1/bulk/tags", json=body)
r.raise_for_status()
return r.json()
def bulk_set_tags(
document_ids: list[int] | None = None,
tags: list[str] | None = None,
doc_type: str | None = None,
from_id: int | None = None,
to_id: int | None = None,
new_tags: list[str] | None = None,
force: bool = False,
) -> dict:
extra = {"new_tags": new_tags or []}
body = _bulk_body(document_ids, tags, doc_type, from_id, to_id, force, **extra)
with _client() as c:
r = c.post("/api/v1/bulk/set-tags", json=body)
r.raise_for_status()
return r.json()
def upload_file(filename: str, file_bytes: bytes,
tags: list[str] | None = None) -> dict:
fields: dict = {}
if tags:
fields["tags"] = ",".join(tags)
with _client() as c:
r = c.post(
"/api/v1/jobs",
data=fields,
files={"file": (filename, file_bytes)},
)
r.raise_for_status()
return r.json()
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mcp>=1.9.0
httpx>=0.27
uvicorn>=0.30
starlette>=0.38
+446
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"""kb MCP server — exposes knowledge base operations as MCP tools."""
import asyncio
import json
import logging
from mcp.server.fastmcp import FastMCP
from mcp.server.transport_security import TransportSecuritySettings
from starlette.applications import Starlette
from starlette.middleware import Middleware
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.requests import Request
from starlette.responses import JSONResponse
from starlette.routing import Mount
import config
import engine
import uploads
logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")
logger = logging.getLogger("kb.mcp")
# ---------------------------------------------------------------------------
# Transport security — DNS rebinding protection with configurable allowed hosts
# ---------------------------------------------------------------------------
_LOCALHOST_HOSTS = ["127.0.0.1:*", "localhost:*", "[::1]:*"]
_LOCALHOST_ORIGINS = ["http://127.0.0.1:*", "http://localhost:*", "http://[::1]:*"]
_extra_hosts = config.parse_allowed_hosts()
_allowed_hosts = _LOCALHOST_HOSTS + [f"{h}:*" for h in _extra_hosts]
_allowed_origins = _LOCALHOST_ORIGINS + [f"http://{h}:*" for h in _extra_hosts]
_transport_security = TransportSecuritySettings(
enable_dns_rebinding_protection=True,
allowed_hosts=_allowed_hosts,
allowed_origins=_allowed_origins,
)
# ---------------------------------------------------------------------------
# FastMCP server
# ---------------------------------------------------------------------------
mcp = FastMCP(
"kb",
instructions=(
"Knowledge base MCP server. Provides tools for searching, adding, and "
"managing documents and notes. Use tags to organise and filter documents "
"(e.g. tag notes with 'agent:mybot' and filter searches by that tag). "
"This server requires Bearer token authentication — all requests are "
"authenticated via the Authorization header at the HTTP transport layer."
),
transport_security=_transport_security,
)
@mcp.tool()
async def kb_search(
query: str,
top: int = 10,
tags: list[str] | None = None,
doc_type: str | None = None,
fts_only: bool = False,
) -> str:
"""Search the knowledge base for relevant documents and notes.
Returns ranked chunks matching the query, with text content, relevance scores,
and document metadata.
Args:
query: The search query. Can be a natural language question or keywords.
top: Maximum number of results to return (default 10).
tags: Filter results to documents with ALL of these tags.
doc_type: Filter by document type (e.g. "note", "pdf", "markdown", "code").
fts_only: If true, use only full-text search (no vector similarity).
Tips for complex queries:
- Consider expanding into 2-3 variant phrasings and calling this tool multiple
times, then deduplicating results by chunk_id. For example, search for both
"pension revaluation rules" and "how are pensions revalued" to cast a wider net.
- For precision, rerank the returned results using your own judgement based on
relevance to the original question.
"""
result = engine.search(
query=query,
top=top,
tags=tags or None,
doc_type=doc_type,
fts_only=fts_only,
)
results_list = result if isinstance(result, list) else result.get("results", [])
return json.dumps(results_list, indent=2)
@mcp.tool()
async def kb_addnote(
text: str,
tags: list[str] | None = None,
title: str | None = None,
) -> str:
"""Add a text note to the knowledge base for indexing and search.
The note is queued for ingestion — it will be chunked, embedded, and made
searchable. Use kb_jobs to check ingestion status.
Args:
text: The note text content.
tags: Tags to apply to the note.
title: Optional title (auto-derived from first line if omitted).
"""
result = engine.add_note(text=text, tags=tags or None, title=title)
return json.dumps(result, indent=2)
@mcp.tool()
async def kb_update_note(
document_id: int,
text: str,
) -> str:
"""Update an existing note's content in place.
Replaces the note text, re-chunks, and re-embeds while preserving the
document ID, creation timestamp, and tags. Only works on documents with
doc_type "note".
Args:
document_id: The ID of the note document to update.
text: The new text content for the note.
"""
result = engine.update_note(document_id, text)
return json.dumps(result, indent=2)
@mcp.tool()
async def kb_get(
document_id: int | None = None,
source_path: str | None = None,
) -> str:
"""Retrieve document details from the knowledge base.
Look up a document by its ID or source path. Returns full document metadata,
tags, and chunk contents.
Args:
document_id: The numeric document ID.
source_path: The document's source path (alternative to document_id).
"""
if document_id is not None:
result = engine.get_document(document_id)
return json.dumps(result, indent=2)
elif source_path is not None:
docs = engine.list_documents()
matches = [d for d in docs if d.get("source_path") == source_path]
if not matches:
return json.dumps({"error": "No document found with that source_path"})
doc = engine.get_document(matches[0]["id"])
return json.dumps(doc, indent=2)
else:
return json.dumps({"error": "Provide either document_id or source_path"})
@mcp.tool()
async def kb_status() -> str:
"""Get knowledge base engine status.
Returns engine version, embedding model info, device info, document counts,
database size, and ingestion queue state.
"""
result = engine.get_status()
result["authenticated"] = bool(config.KB_MCP_API_KEY)
return json.dumps(result, indent=2)
@mcp.tool()
async def kb_jobs(
status: str | None = None,
) -> str:
"""List ingestion jobs and their status.
Returns recent jobs showing what has been queued, is processing, completed,
or failed.
Args:
status: Filter by job status ("queued", "processing", "done", "failed", "skipped").
"""
result = engine.list_jobs(status=status)
return json.dumps(result, indent=2)
@mcp.tool()
async def kb_delete(
document_id: int,
) -> str:
"""Permanently delete a document from the knowledge base.
Removes the document and all associated data (chunks, embeddings, tags,
stored files). This action cannot be undone.
Args:
document_id: The ID of the document to delete.
"""
result = engine.delete_document(document_id)
return json.dumps(result, indent=2)
@mcp.tool()
async def kb_upload_start(
filename: str,
total_size: int,
tags: list[str] | None = None,
) -> str:
"""Start a chunked file upload to the knowledge base.
Use this for uploading files from a remote agent. The upload process is:
1. Call kb_upload_start to get an upload_id
2. Call kb_upload_chunk repeatedly with base64-encoded file chunks (recommended ~1MB each)
3. Call kb_upload_finish to submit the file for ingestion
Example for a 3MB file:
upload = kb_upload_start(filename="report.pdf", total_size=3145728, tags=["project:x"])
kb_upload_chunk(upload_id=upload["upload_id"], data="<base64 chunk 0>", chunk_index=0)
kb_upload_chunk(upload_id=upload["upload_id"], data="<base64 chunk 1>", chunk_index=1)
kb_upload_chunk(upload_id=upload["upload_id"], data="<base64 chunk 2>", chunk_index=2)
result = kb_upload_finish(upload_id=upload["upload_id"])
Args:
filename: Original filename (used for type detection).
total_size: Total file size in bytes.
tags: Tags to apply to the uploaded document.
"""
upload_id = uploads.start_upload(filename, total_size, tags or [])
return json.dumps({"upload_id": upload_id})
@mcp.tool()
async def kb_upload_chunk(
upload_id: str,
data: str,
chunk_index: int,
) -> str:
"""Upload a base64-encoded chunk of a file.
Part of the chunked upload flow started by kb_upload_start.
Args:
upload_id: The upload ID from kb_upload_start.
data: Base64-encoded file data for this chunk.
chunk_index: Zero-based index of this chunk.
"""
try:
uploads.add_chunk(upload_id, data, chunk_index)
return json.dumps({"status": "ok", "chunk_index": chunk_index})
except KeyError as e:
return json.dumps({"error": str(e)})
@mcp.tool()
async def kb_upload_finish(
upload_id: str,
) -> str:
"""Finish a chunked upload and submit the file for ingestion.
Reassembles all uploaded chunks and forwards the complete file to the
engine for processing. Returns the ingestion job ID.
Args:
upload_id: The upload ID from kb_upload_start.
"""
try:
filename, file_bytes, tags = uploads.finish_upload(upload_id)
result = engine.upload_file(filename, file_bytes, tags)
return json.dumps(result, indent=2)
except KeyError as e:
return json.dumps({"error": str(e)})
# ---------------------------------------------------------------------------
# Bulk operation tools
# ---------------------------------------------------------------------------
@mcp.tool()
async def kb_bulk_delete(
document_ids: list[int] | None = None,
tags: list[str] | None = None,
doc_type: str | None = None,
from_id: int | None = None,
to_id: int | None = None,
force: bool = False,
) -> str:
"""Permanently delete multiple documents matching a filter.
Removes matched documents and all associated data (chunks, embeddings, tags,
stored files). This action cannot be undone.
Selection filters combine with AND logic — at least one is required.
A safety threshold applies: if the operation would affect more than 70% of
all documents, it is rejected unless force=true.
Args:
document_ids: Delete documents with these specific IDs.
tags: Delete documents that have ALL of these tags (selection filter).
doc_type: Delete documents of this type (e.g. "note", "pdf").
from_id: Delete documents with id >= this value.
to_id: Delete documents with id <= this value.
force: Override the safety threshold if it would block the operation.
"""
result = engine.bulk_delete(
document_ids=document_ids, tags=tags, doc_type=doc_type,
from_id=from_id, to_id=to_id, force=force,
)
return json.dumps(result, indent=2)
@mcp.tool()
async def kb_bulk_tags(
document_ids: list[int] | None = None,
tags: list[str] | None = None,
doc_type: str | None = None,
from_id: int | None = None,
to_id: int | None = None,
add: list[str] | None = None,
remove: list[str] | None = None,
force: bool = False,
) -> str:
"""Add and/or remove tags on multiple documents matching a filter.
Selection filters combine with AND logic — at least one is required.
Note: the 'tags' parameter is a SELECTION FILTER (which documents to target),
while 'add' and 'remove' specify the TAG CHANGES to apply to those documents.
Args:
document_ids: Target documents with these specific IDs.
tags: Target documents that have ALL of these tags (selection filter).
doc_type: Target documents of this type.
from_id: Target documents with id >= this value.
to_id: Target documents with id <= this value.
add: Tags to add to matched documents.
remove: Tags to remove from matched documents.
force: Override the safety threshold if it would block the operation.
"""
result = engine.bulk_tags(
document_ids=document_ids, tags=tags, doc_type=doc_type,
from_id=from_id, to_id=to_id, add=add, remove=remove, force=force,
)
return json.dumps(result, indent=2)
@mcp.tool()
async def kb_bulk_set_tags(
document_ids: list[int] | None = None,
tags: list[str] | None = None,
doc_type: str | None = None,
from_id: int | None = None,
to_id: int | None = None,
new_tags: list[str] | None = None,
force: bool = False,
) -> str:
"""Replace all tags on multiple documents with a new set.
Removes ALL existing tags from matched documents, then applies the new tag set.
Selection filters combine with AND logic — at least one is required.
Note: the 'tags' parameter is a SELECTION FILTER (which documents to target),
while 'new_tags' is the REPLACEMENT tag set to apply.
Args:
document_ids: Target documents with these specific IDs.
tags: Target documents that have ALL of these tags (selection filter).
doc_type: Target documents of this type.
from_id: Target documents with id >= this value.
to_id: Target documents with id <= this value.
new_tags: The replacement tag set to apply to all matched documents.
force: Override the safety threshold if it would block the operation.
"""
result = engine.bulk_set_tags(
document_ids=document_ids, tags=tags, doc_type=doc_type,
from_id=from_id, to_id=to_id, new_tags=new_tags, force=force,
)
return json.dumps(result, indent=2)
# ---------------------------------------------------------------------------
# Auth middleware
# ---------------------------------------------------------------------------
class BearerAuthMiddleware(BaseHTTPMiddleware):
async def dispatch(self, request: Request, call_next):
if not config.KB_MCP_API_KEY:
return await call_next(request)
auth_header = request.headers.get("authorization", "")
if auth_header.startswith("Bearer ") and auth_header[7:] == config.KB_MCP_API_KEY:
return await call_next(request)
return JSONResponse(
status_code=401,
content={"error": "Unauthorized"},
)
# ---------------------------------------------------------------------------
# ASGI app assembly
# ---------------------------------------------------------------------------
def create_app():
"""Create the ASGI app with auth middleware wrapping the MCP server."""
from contextlib import asynccontextmanager
mcp_app = mcp.streamable_http_app()
@asynccontextmanager
async def lifespan(app):
uploads.start_cleanup_task()
logger.info("Upload cleanup task started")
# Delegate to the MCP app's lifespan if it has one
if hasattr(mcp_app, 'router') and hasattr(mcp_app.router, 'lifespan_context'):
async with mcp_app.router.lifespan_context(app):
yield
else:
yield
app = Starlette(
routes=[Mount("/", app=mcp_app)],
middleware=[Middleware(BearerAuthMiddleware)],
lifespan=lifespan,
)
return app
# ---------------------------------------------------------------------------
# Entry point
# ---------------------------------------------------------------------------
if __name__ == "__main__":
import uvicorn
logger.info(
"Starting kb MCP server on port %d, engine=%s",
config.KB_MCP_PORT,
config.KB_ENGINE_URL,
)
app = create_app()
uvicorn.run(app, host="0.0.0.0", port=config.KB_MCP_PORT)
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"""Chunked upload staging management."""
import asyncio
import base64
import logging
import shutil
import tempfile
import time
import uuid
from dataclasses import dataclass, field
from pathlib import Path
logger = logging.getLogger("kb.mcp.uploads")
UPLOAD_TIMEOUT_SECONDS = 600 # 10 minutes
@dataclass
class StagedUpload:
upload_id: str
filename: str
total_size: int
tags: list[str]
staging_dir: Path
created_at: float = field(default_factory=time.time)
chunks: dict[int, Path] = field(default_factory=dict)
_uploads: dict[str, StagedUpload] = {}
_cleanup_task: asyncio.Task | None = None
def start_upload(filename: str, total_size: int, tags: list[str]) -> str:
upload_id = str(uuid.uuid4())
staging_dir = Path(tempfile.mkdtemp(prefix=f"kb_upload_{upload_id[:8]}_"))
_uploads[upload_id] = StagedUpload(
upload_id=upload_id,
filename=filename,
total_size=total_size,
tags=tags,
staging_dir=staging_dir,
)
logger.info("Started upload %s for %s (%d bytes)", upload_id, filename, total_size)
return upload_id
def add_chunk(upload_id: str, data_b64: str, chunk_index: int) -> None:
upload = _uploads.get(upload_id)
if upload is None:
raise KeyError(f"Upload ID not found: {upload_id}")
chunk_bytes = base64.b64decode(data_b64)
chunk_path = upload.staging_dir / f"chunk_{chunk_index:06d}"
chunk_path.write_bytes(chunk_bytes)
upload.chunks[chunk_index] = chunk_path
logger.info("Added chunk %d to upload %s (%d bytes)", chunk_index, upload_id, len(chunk_bytes))
def finish_upload(upload_id: str) -> tuple[str, bytes, list[str]]:
"""Reassemble chunks and return (filename, file_bytes, tags)."""
upload = _uploads.get(upload_id)
if upload is None:
raise KeyError(f"Upload ID not found: {upload_id}")
try:
parts = []
for idx in sorted(upload.chunks.keys()):
parts.append(upload.chunks[idx].read_bytes())
file_bytes = b"".join(parts)
return upload.filename, file_bytes, upload.tags
finally:
_cleanup_upload(upload_id)
def _cleanup_upload(upload_id: str) -> None:
upload = _uploads.pop(upload_id, None)
if upload and upload.staging_dir.exists():
shutil.rmtree(upload.staging_dir, ignore_errors=True)
async def cleanup_abandoned_uploads() -> None:
"""Background task that removes uploads older than the timeout."""
while True:
await asyncio.sleep(60)
now = time.time()
expired = [
uid for uid, u in _uploads.items()
if now - u.created_at > UPLOAD_TIMEOUT_SECONDS
]
for uid in expired:
logger.warning("Cleaning up abandoned upload %s", uid)
_cleanup_upload(uid)
def start_cleanup_task() -> None:
global _cleanup_task
if _cleanup_task is None or _cleanup_task.done():
_cleanup_task = asyncio.create_task(cleanup_abandoned_uploads())
@@ -0,0 +1,2 @@
schema: spec-driven
created: 2026-03-26
@@ -0,0 +1,40 @@
## Context
FTS5 has its own query syntax. Characters like `?`, `*`, `"`, `(`, `)`, `+`, `-`, `^` and keywords like `AND`, `OR`, `NOT`, `NEAR` have special meaning. The current code passes the raw user query to `chunks_fts MATCH ?` — parameterized (safe from SQL injection) but not safe from FTS5 syntax errors.
The fix point is `_fts_search()` in `engine/kb/search.py:92` where `params: list = [query]`.
## Goals / Non-Goals
**Goals:**
- Any user input to the search endpoint produces either valid results or an empty result set — never a 500 error
- Preserve the user's search intent as much as possible (don't over-strip)
**Non-Goals:**
- Exposing FTS5 advanced syntax to users (they can't use AND/OR/NEAR operators intentionally)
- Changing vector search (it already handles arbitrary strings via the embedding model)
## Decisions
### 1. Quote each token individually
Split the query on whitespace, wrap each token in double quotes (`"token"`), and join with spaces. FTS5 interprets double-quoted strings as literal phrases, disabling all operator parsing within them. Any embedded double quotes in a token are stripped.
Example: `what color is grass?` becomes `"what" "color" "is" "grass?"` — FTS5 treats `?` as a literal character inside quotes.
**Alternative considered**: Strip all non-alphanumeric characters. Rejected because it would break searches for terms containing hyphens, dots, or other meaningful punctuation (e.g., searching for "v2.0" or "self-hosted").
**Alternative considered**: Use a try/except to catch FTS5 errors and fall back. Rejected as a primary strategy because it silently degrades — but we'll add it as a safety net.
### 2. Handle empty/whitespace-only queries
If after sanitization no tokens remain, skip FTS search entirely and return empty results. This prevents sending an empty string to MATCH which would also error.
### 3. Try/except safety net
Wrap the FTS5 execute call in a try/except for `sqlite3.OperationalError`. If an edge case still slips through, return empty FTS results and log a warning rather than crashing with a 500.
## Risks / Trade-offs
- **[Reduced FTS expressiveness]** Users cannot use FTS5 operators like `AND`, `OR`, phrase matching. → Acceptable trade-off for a personal knowledge base tool where natural language queries are the norm. The hybrid search (vector + FTS) compensates.
- **[Edge cases]** Some Unicode or control characters might still cause issues. → The try/except safety net handles these.
@@ -0,0 +1,24 @@
## Why
Searching with natural language queries containing characters like `?`, `"`, `*`, `(`, `)`, `-`, or FTS5 keywords (`AND`, `OR`, `NOT`, `NEAR`) causes a 500 error because the raw query string is passed directly to `chunks_fts MATCH ?` without escaping. Users should be able to type anything into a search query without triggering syntax errors.
## What Changes
- **Sanitize FTS5 query input**: Escape or strip FTS5 special characters from the user's query before passing it to the MATCH operator
- **Graceful fallback**: If the sanitized query produces no valid FTS5 terms, return empty results from FTS instead of erroring
## Capabilities
### New Capabilities
_(none)_
### Modified Capabilities
- `engine-api`: The "Hybrid search" requirement changes — the engine must sanitize user queries to prevent FTS5 syntax errors for any input
## Impact
- **Engine search** (`engine/kb/search.py`): `_fts_search()` needs query sanitization before the MATCH parameter
- **No client changes**: The client already displays results or errors correctly
- **No schema changes**: No database modifications needed
@@ -0,0 +1,21 @@
## MODIFIED Requirements
### Requirement: Hybrid search
The engine SHALL provide hybrid search combining BM25 full-text search (via FTS5) and vector similarity search (via sqlite-vec), merged using Reciprocal Rank Fusion. Search SHALL complete in under 100ms when the model is warm. The engine SHALL sanitize user query strings to prevent FTS5 syntax errors for any input.
#### Scenario: Search with special characters
- **WHEN** a client sends `POST /api/v1/search` with body `{"query": "what color is grass?"}`
- **THEN** the engine SHALL sanitize the query for FTS5, execute the search successfully, and return results (not a 500 error)
#### Scenario: Search with FTS5 operators in query
- **WHEN** a client sends `POST /api/v1/search` with body `{"query": "NOT something OR (other)"}`
- **THEN** the engine SHALL treat the input as literal search terms, not FTS5 operators, and return matching results
#### Scenario: Search with only special characters
- **WHEN** a client sends `POST /api/v1/search` with body `{"query": "??!@#"}`
- **THEN** the engine SHALL return HTTP 200 with an empty result set (not a 500 error)
#### Scenario: Search with quotes in query
- **WHEN** a client sends `POST /api/v1/search` with body `{"query": "the \"quick\" fox"}`
- **THEN** the engine SHALL sanitize embedded quotes and return results normally
@@ -0,0 +1,15 @@
## 1. Query Sanitization
- [x] 1.1 Add `_sanitize_fts_query(query)` function to `engine/kb/search.py` that splits on whitespace, strips double quotes from each token, wraps each token in double quotes, and joins with spaces
- [x] 1.2 Handle edge case: if no valid tokens remain after sanitization, return empty dict from `_fts_search` without executing the query
## 2. Integration
- [x] 2.1 Call `_sanitize_fts_query()` in `_fts_search()` before adding the query to params (line 92)
- [x] 2.2 Add try/except `sqlite3.OperationalError` around the FTS5 execute call — log a warning and return empty results on error
## 3. Testing
- [x] 3.1 Test: `kb search "what color is grass?"` returns results, not a 500 error
- [x] 3.2 Test: `kb search "NOT something OR (other)"` returns results, treating input as literal terms
- [x] 3.3 Test: query with only special characters returns empty results, not an error
@@ -0,0 +1,2 @@
schema: spec-driven
created: 2026-03-26
@@ -0,0 +1,58 @@
## Context
The engine currently accepts all uploads with HTTP 202, stages the file, creates a job record, and relies on the background worker to detect duplicates via SHA256 content hash. When a duplicate is found, the worker marks the job as `skipped` — but the user has already received a success response and must poll job status to discover the duplicate. This creates unnecessary I/O (staging), pollutes the job list, and provides poor UX.
The `documents` table already has a `content_hash TEXT UNIQUE` column, and `database.hash_exists()` already exists. The infrastructure for dedup is in place — it just runs too late in the pipeline.
## Goals / Non-Goals
**Goals:**
- Reject duplicate uploads at the API boundary with HTTP 409 and useful context (existing document ID/title)
- Avoid staging files or creating job records for duplicates
- Apply to both file uploads and note submissions
- Keep the worker-side hash check as a race condition safety net
- Update the Go client to handle 409 and display a clear message
**Non-Goals:**
- Fuzzy/near-duplicate detection (e.g., same PDF with different metadata) — byte-identical only
- Changing the hash algorithm (SHA256 is fine)
- Adding a "force re-import" override flag (can be added later if needed)
- Dedup across different file formats with identical content (e.g., .md and .pdf of same text)
## Decisions
### 1. Hash in the upload endpoint, before staging
Compute SHA256 from the uploaded bytes in `submit_job()` before calling `stage_file()`. This avoids writing to disk or creating a DB job record for duplicates.
**Alternative considered**: Hash after staging but before job creation. Rejected because it still wastes disk I/O for the staging write.
### 2. Return HTTP 409 Conflict with context-dependent metadata
The 409 response includes `{"error": "duplicate", ...}` with a distinct shape depending on where the duplicate was found:
- **Already-ingested document**: `{"error": "duplicate", "document_id": <id>, "title": "<title>"}`
- **In-flight job (queued/processing)**: `{"error": "duplicate", "job_id": <id>, "title": "<filename>"}`
This allows clients to distinguish between "this document already exists" and "this document is already being processed" and display appropriate messages.
**Alternative considered**: Return 200 with a `"status": "duplicate"` field. Rejected because 409 is the semantically correct status code and allows clients to distinguish duplicates from successful uploads without parsing the body.
### 3. New database helper: `get_document_by_hash()`
Returns a dict with duplicate info for a given hash, or `None`. Checks both the `documents` table (already ingested) and the `jobs` table (queued/processing), returning `document_id` or `job_id` accordingly. The `content_hash` column on the `jobs` table is populated at upload time to support this check. The boolean `hash_exists()` is retained for the worker safety net.
**Alternative considered**: Modify `hash_exists()` to return the document row. Rejected to avoid changing the worker's existing interface — keep changes minimal.
### 4. Retain worker-side dedup as safety net
The worker's `hash_exists()` check stays. In theory, two identical uploads could arrive in the same instant — both pass the API hash check before either commits. The jobs-table check closes most of this window (the hash is written at job creation), but a narrow race remains between the API check and the job insert. The UNIQUE constraint on `documents.content_hash` is the final backstop.
### 5. Note dedup: hash the text content
For notes submitted via the `note` field, SHA256-hash the UTF-8 encoded text. This catches identical note resubmissions.
## Risks / Trade-offs
- **[Race condition window]** Two identical files uploaded in the same millisecond could both pass the API hash check. → Mitigated by the worker-side `hash_exists()` check and the UNIQUE constraint. The second job would be `skipped`, not a crash.
- **[Blocking I/O in async endpoint]** SHA256 hashing is CPU-bound but fast (~5ms for 10MB). → Acceptable for the upload endpoint which already reads the full file into memory. No need for `run_in_executor`.
- **[Client compatibility]** Older clients not expecting 409 will see an error. → This is correct behavior — they'll see an HTTP error rather than silently accepting a duplicate. The Go client will be updated to handle it gracefully.
@@ -0,0 +1,31 @@
## Why
Duplicate document detection currently happens in the background worker — the upload endpoint always returns HTTP 202, and the user only discovers a duplicate later when the job status is `skipped`. This wastes staging I/O, creates noise in the job list, and gives poor user feedback. Moving the SHA256 content hash check to the upload endpoint allows immediate rejection with a clear error, preventing unnecessary work and giving the user instant feedback.
## What Changes
- **Compute content hash at upload time**: The `POST /api/v1/jobs` endpoint will SHA256-hash the uploaded file bytes before staging and check against `documents.content_hash`
- **Reject duplicates immediately**: Return HTTP 409 Conflict with the existing document ID when a duplicate is detected, instead of accepting and later skipping
- **No job created for duplicates**: Duplicate uploads will not create a job record or stage a file
- **Remove worker-side dedup**: The background worker's `hash_exists()` check becomes redundant for the normal flow but should be retained as a safety net (race condition guard)
- **Update Go client**: Surface the 409 response with a clear message (e.g., "Already imported: <title> (doc ID: <id>)")
- **Note dedup**: Apply the same check to notes — hash the note text content
## Capabilities
### New Capabilities
_(none — this modifies existing capabilities)_
### Modified Capabilities
- `engine-api`: The "Async ingestion via job queue" requirement changes — duplicate content is now rejected at upload time (HTTP 409) instead of accepted and later skipped by the worker. The "Duplicate content detection" scenario moves from background to synchronous.
- `go-client`: The "Add command" requirement changes — the client must handle HTTP 409 responses and display the duplicate document info to the user.
## Impact
- **Engine API** (`engine/kb/routes/jobs.py`): `submit_job()` gains hash computation and DB lookup before staging/job creation
- **Engine database** (`engine/kb/database.py`): Need a query to return the existing document ID/title for a given hash (not just boolean exists check)
- **Engine worker** (`engine/kb/worker.py`): Dedup check retained as safety net but no longer the primary guard
- **Go client** (`client/cmd/add.go`): Handle 409 response, display duplicate info
- **API contract**: New HTTP 409 response on `POST /api/v1/jobs` — this is additive, not breaking, since no consumer expects 409 today
@@ -0,0 +1,41 @@
## MODIFIED Requirements
### Requirement: Async ingestion via job queue
The engine SHALL accept file uploads and text notes for ingestion asynchronously. Uploaded content SHALL be written to a staging area and a job record created in the database. The engine SHALL return HTTP 202 immediately. A background worker SHALL process queued jobs sequentially. Before staging, the engine SHALL compute a SHA256 hash of the uploaded content and reject duplicates immediately.
#### Scenario: Upload a PDF file
- **WHEN** a client sends `POST /api/v1/jobs` with a multipart form containing a PDF file and optional fields (tags, doc_type)
- **THEN** the engine SHALL compute the SHA256 hash of the file bytes, verify no existing document has the same hash, write the file to the staging directory, create a job record with status `queued`, and return HTTP 202 with `{"job_id": "<id>", "status": "queued", "filename": "report.pdf"}`
#### Scenario: Upload a text note
- **WHEN** a client sends `POST /api/v1/jobs` with a multipart form containing a `note` text field and optional `title` field
- **THEN** the engine SHALL compute the SHA256 hash of the note text (UTF-8 encoded), verify no existing document has the same hash, write the note content to a staging file, create a job record with status `queued`, and return HTTP 202 with the job ID
#### Scenario: Upload multiple files in sequence
- **WHEN** a client sends multiple `POST /api/v1/jobs` requests in quick succession
- **THEN** the engine SHALL queue each job independently and the background worker SHALL process them in FIFO order
#### Scenario: Duplicate file detected at upload time (already ingested)
- **WHEN** a client uploads a file whose SHA256 content hash matches an already-ingested document
- **THEN** the engine SHALL NOT stage the file or create a job record, and SHALL return HTTP 409 with `{"error": "duplicate", "document_id": <id>, "title": "<title>"}`
#### Scenario: Duplicate file detected at upload time (in-flight job)
- **WHEN** a client uploads a file whose SHA256 content hash matches a queued or processing job
- **THEN** the engine SHALL NOT stage the file or create a job record, and SHALL return HTTP 409 with `{"error": "duplicate", "job_id": <id>, "title": "<filename>"}`
#### Scenario: Duplicate note detected at upload time (already ingested)
- **WHEN** a client submits a note whose SHA256 content hash matches an already-ingested document
- **THEN** the engine SHALL NOT stage the note or create a job record, and SHALL return HTTP 409 with `{"error": "duplicate", "document_id": <id>, "title": "<title>"}`
#### Scenario: Duplicate note detected at upload time (in-flight job)
- **WHEN** a client submits a note whose SHA256 content hash matches a queued or processing job
- **THEN** the engine SHALL NOT stage the note or create a job record, and SHALL return HTTP 409 with `{"error": "duplicate", "job_id": <id>, "title": "<filename>"}`
#### Scenario: Duplicate uploaded during concurrent request handling
- **WHEN** two identical files are uploaded in the same instant, both passing the API hash check before either job is committed
- **THEN** both jobs SHALL be queued, and the background worker SHALL process the first normally and mark the second as `skipped` (worker-side safety net via `hash_exists()` and UNIQUE constraint)
#### Scenario: Upload failure due to unsupported file type
- **WHEN** a client uploads a file with an unsupported extension
- **THEN** the engine SHALL return HTTP 422 with an error message listing supported types
@@ -0,0 +1,49 @@
## MODIFIED Requirements
### Requirement: Add command (file and note ingestion)
The client SHALL provide a `kb add` command that uploads files or notes to the engine for async ingestion. The client SHALL exit immediately after a successful upload. The client SHALL handle duplicate rejection (HTTP 409) and display the existing document information.
#### Scenario: Add a single file
- **WHEN** the user runs `kb add report.pdf`
- **THEN** the client SHALL upload the file via `POST /api/v1/jobs` (multipart), print "Queued: report.pdf", and exit
#### Scenario: Add a file with tags
- **WHEN** the user runs `kb add manual.pdf --tags car,maintenance`
- **THEN** the client SHALL include the tags in the multipart upload metadata
#### Scenario: Add a directory recursively
- **WHEN** the user runs `kb add ~/documents/ --recursive`
- **THEN** the client SHALL discover all supported files in the directory tree, upload each one sequentially, and print "Queued: N files"
#### Scenario: Add a text note
- **WHEN** the user runs `kb add --note "The server room is in building 3, floor 2"`
- **THEN** the client SHALL submit the note text via `POST /api/v1/jobs` (multipart with note field), print "Queued: note", and exit
#### Scenario: Duplicate file rejected (already ingested)
- **WHEN** the user runs `kb add report.pdf` and the engine returns HTTP 409 with `{"error": "duplicate", "document_id": 42, "title": "report.pdf"}`
- **THEN** the client SHALL print "Already imported: report.pdf (doc ID: 42)" and exit with code 0
#### Scenario: Duplicate file rejected (in-flight job)
- **WHEN** the user runs `kb add report.pdf` and the engine returns HTTP 409 with `{"error": "duplicate", "job_id": 7, "title": "report.pdf"}`
- **THEN** the client SHALL print "Already queued: report.pdf (job ID: 7)" and exit with code 0
#### Scenario: Duplicate file in recursive add
- **WHEN** the user runs `kb add ~/documents/ --recursive` and some files are rejected as duplicates
- **THEN** the client SHALL print the duplicate message for each rejected file (distinguishing "Already imported" from "Already queued"), continue uploading remaining files, and include a summary (e.g., "Queued: 5 files, 2 duplicates skipped")
#### Scenario: Duplicate with JSON output
- **WHEN** the user runs `kb add report.pdf --format json` and the engine returns HTTP 409
- **THEN** the client SHALL output the raw JSON response from the engine including the document_id and title
#### Scenario: Add with JSON output
- **WHEN** the user runs `kb add report.pdf --format json`
- **THEN** the client SHALL output the JSON response from the engine including the job_id
#### Scenario: File not found
- **WHEN** the user runs `kb add nonexistent.pdf`
- **THEN** the client SHALL print an error and exit with a non-zero code without making any API call
#### Scenario: Upload failure
- **WHEN** the upload fails (network error, engine returns 4xx/5xx other than 409)
- **THEN** the client SHALL print the error and exit with a non-zero code
@@ -0,0 +1,22 @@
## 1. Database Layer
- [x] 1.1 Add `get_document_by_hash(conn, content_hash)` function to `engine/kb/database.py` that returns `(document_id, title)` or `None`
## 2. Upload Endpoint
- [x] 2.1 Update `submit_job()` in `engine/kb/routes/jobs.py` to compute SHA256 hash of uploaded file bytes before staging
- [x] 2.2 Add duplicate check: call `get_document_by_hash()` and return HTTP 409 with `{"error": "duplicate", "document_id": <id>, "title": "<title>"}` if match found
- [x] 2.3 Apply same hash check for note submissions (hash the UTF-8 encoded note text)
## 3. Go Client
- [x] 3.1 Update `uploadFile()` in `client/cmd/add.go` to handle HTTP 409 responses — parse the JSON body and print "Already imported: <title> (doc ID: <id>)"
- [x] 3.2 Update recursive directory upload to continue on 409, track duplicate count, and include in summary output
- [x] 3.3 Handle 409 in JSON output mode — pass through the raw engine response
## 4. Testing
- [x] 4.1 Test: upload a file, then upload the same file again — verify 409 with correct document_id and title
- [x] 4.2 Test: upload a note, then upload the same note text — verify 409
- [x] 4.3 Test: upload a file, then upload a different file — verify 202 as normal
- [x] 4.4 Test: verify the worker-side `hash_exists()` safety net still works (direct job insertion bypassing API)
@@ -0,0 +1,2 @@
schema: spec-driven
created: 2026-03-27
@@ -0,0 +1,84 @@
## Context
Currently, uploaded files pass through a staging directory and are deleted after the worker extracts chunks and embeddings. The `documents.source_path` column stores the (now-stale) staging path. Users who want the original file must re-source it externally. The data directory structure today is:
```
/data/
kb.db
hf_cache/
staging/ # temporary, cleaned after processing
```
## Goals / Non-Goals
**Goals:**
- Persist every successfully-ingested original file for the lifetime of the document
- Serve the original file via API (`GET /api/v1/documents/{id}/file`)
- Clean up stored files when a document is deleted
- Work transparently with the existing Docker volume mount (`/data`)
**Non-Goals:**
- Serving transformed/converted versions of documents (e.g. PDF→HTML)
- De-duplicating file storage (same content hash = same row, so 1:1 is fine)
- Compression or archival of stored files
- Retroactive storage of files ingested before this change (they're already gone)
## Decisions
### 1. Storage layout: content-hash-based flat directory
Store files at `{data_dir}/documents/{content_hash}{ext}` (e.g. `documents/a1b2c3...d4.pdf`).
**Why over document-ID naming:** Content hash is available at staging time before the DB row exists, avoids race conditions, and makes dedup trivially safe (same hash = same file, overwrite is harmless). The hash is already computed for dedup checks.
**Why flat over nested:** The KB is a personal tool — expected scale is hundreds to low-thousands of documents. A flat directory is simpler and sufficient. If needed later, a `ab/cd/` prefix scheme is easy to add.
**Alternatives considered:**
- *Store in SQLite as BLOBs*: Bloats the DB, complicates backups, and degrades WAL performance for large files. Rejected.
- *Keep the staging path as-is*: Staging uses UUID prefixes which are meaningless; content-hash naming is deterministic and self-deduplicating.
### 2. Move file from staging to documents dir (not copy)
Use `shutil.move()` from staging to documents dir after successful ingestion, before `staging.cleanup()`. This avoids doubling disk usage during processing.
**Why not copy-then-delete:** Move is atomic on the same filesystem (which `/data/staging` and `/data/documents` share). Faster, no temporary disk spike.
### 3. New columns `stored_path` and `original_filename` on `documents` table
Add two nullable columns:
- `stored_path TEXT` — permanent file location on disk
- `original_filename TEXT` — the exact filename from the upload (e.g. `report.pdf`)
Both are nullable because existing documents (ingested before this change) won't have values.
**Why `original_filename` separate from `title`:** The `title` field can be user-overridden (e.g. "Engine Manual" instead of `report.pdf`). When serving the file for download, the `Content-Disposition` header should use the original filename so the downloaded file has the correct name and extension. The `original_filename` is sourced from `jobs.filename` which is already captured at upload time.
Keep `source_path` as-is for backward compatibility (it records what the staging path was). `stored_path` is the permanent location.
**Migration:** Two `ALTER TABLE` statements — safe additive migrations, no data rewrite needed.
### 4. File download endpoint returns the file directly
`GET /api/v1/documents/{id}/file` uses FastAPI's `FileResponse` with:
- `media_type` derived from the file extension
- `Content-Disposition: attachment; filename="{original_filename}"` (falls back to `{title}{ext}` if `original_filename` is NULL)
- Returns 404 if `stored_path` is NULL or file is missing from disk
### 5. Delete cascades to file removal
When `DELETE /api/v1/documents/{id}` is called, delete the stored file from disk after the DB delete succeeds. If file removal fails (already gone, permissions), log a warning but don't fail the API call — the DB is the source of truth.
## Risks / Trade-offs
- **Disk usage increases** — every ingested file persists. For the personal-use scale this is expected and acceptable. Users manage this via document deletion.
→ Mitigation: Document the storage behavior; `GET /api/v1/status` already shows DB size, could add documents-dir size later.
- **Pre-existing documents have no stored file** — `stored_path` will be NULL for documents ingested before this change.
→ Mitigation: The download endpoint returns 404 with a clear message ("original file not available — ingested before document storage was enabled"). No attempt to backfill.
- **File-DB consistency** — crash between DB commit and file move could leave orphan staged files or missing stored files.
→ Mitigation: Move file first, then commit DB. If DB commit fails, the file in documents dir is harmless (orphan cleanup can be added later). If move fails, the job fails and staged file remains for retry.
## Open Questions
None — the scope is straightforward enough to proceed.
@@ -0,0 +1,30 @@
## Why
The knowledge base currently discards original files after chunking and embedding. Once a document is ingested, only the extracted text chunks and vectors remain — the original PDF, markdown, or code file is deleted from staging. Users cannot retrieve the source document from the KB, which limits its usefulness as a document store and prevents use cases like re-processing with a different model or serving the original file to downstream tools.
## What Changes
- Add a persistent document storage directory (`{data_dir}/documents/`) alongside the SQLite database
- After successful ingestion, copy the original file from staging to permanent storage instead of deleting it
- Store the permanent file path in the `documents` table (`stored_path` column) and the original upload filename (`original_filename` column) so downloads use the correct name
- Add an API endpoint to download the original file by document ID
- Add a CLI command to export/retrieve the original document
- **BREAKING**: Delete document now also removes the stored file from disk
- Notes (text-only) are stored as `.note` files in the same directory for consistency
## Capabilities
### New Capabilities
- `document-storage`: Persistent storage of original uploaded files on disk, lifecycle management (store on ingest, delete on document removal), and retrieval via API
### Modified Capabilities
- `engine-api`: New endpoint `GET /api/v1/documents/{id}/file` to download the original file; delete endpoint must also clean up stored files; ingestion worker stores files instead of discarding them
## Impact
- **Engine config**: New `documents_dir` property on Config, new directory created at startup via `ensure_dirs()`
- **Worker**: After successful chunking, move/copy file from staging to documents dir; update `source_path``stored_path` with permanent location
- **Database schema**: Add `stored_path` and `original_filename` columns to `documents` table (migration for existing DBs)
- **Routes**: New file-download endpoint; update delete handler to remove stored file
- **Go client**: New `export` / `get-file` subcommand to download original documents
- **Docker**: `documents/` directory lives inside the existing `/data` volume — no new mounts needed
@@ -0,0 +1,83 @@
## ADDED Requirements
### Requirement: Persistent original file storage
The engine SHALL persistently store the original uploaded file on disk after successful ingestion. Files SHALL be stored at `{data_dir}/documents/{content_hash}{extension}` where `content_hash` is the SHA-256 hex digest already computed for dedup and `extension` is preserved from the original filename. The `documents` table SHALL record the stored file path in a `stored_path` column and the original upload filename in an `original_filename` column.
#### Scenario: File stored after successful ingestion
- **WHEN** the background worker successfully processes an ingestion job for a PDF file
- **THEN** the worker SHALL move the staged file to `{data_dir}/documents/{content_hash}.pdf`, store the permanent path in `documents.stored_path`, store the original filename in `documents.original_filename`, and delete the staging entry
#### Scenario: Note stored after successful ingestion
- **WHEN** the background worker successfully processes an ingestion job for a text note
- **THEN** the worker SHALL move the staged `.note` file to `{data_dir}/documents/{content_hash}.note` and store the permanent path in `documents.stored_path`
#### Scenario: Markdown file stored after successful ingestion
- **WHEN** the background worker successfully processes an ingestion job for a markdown file
- **THEN** the worker SHALL move the staged file to `{data_dir}/documents/{content_hash}.md` and store the permanent path in `documents.stored_path`
#### Scenario: Code file stored after successful ingestion
- **WHEN** the background worker successfully processes an ingestion job for a code file (e.g. `.py`, `.go`)
- **THEN** the worker SHALL move the staged file to `{data_dir}/documents/{content_hash}{original_extension}` and store the permanent path in `documents.stored_path`
#### Scenario: Documents directory created at startup
- **WHEN** the engine starts up and calls `ensure_dirs()`
- **THEN** the `{data_dir}/documents/` directory SHALL be created if it does not exist
#### Scenario: Ingestion failure does not store file
- **WHEN** the background worker fails to process an ingestion job
- **THEN** the staged file SHALL be cleaned up as before and no file SHALL be written to the documents directory
---
### Requirement: File retrieval via API
The engine SHALL serve the original stored file for any document that has a stored file on disk.
#### Scenario: Download original file
- **WHEN** a client sends `GET /api/v1/documents/{id}/file` for a document with a stored file
- **THEN** the engine SHALL return the file with appropriate `Content-Type` based on file extension and `Content-Disposition: attachment; filename="{original_filename}"` header, falling back to `{title}{ext}` if `original_filename` is NULL
#### Scenario: Download file for pre-existing document
- **WHEN** a client sends `GET /api/v1/documents/{id}/file` for a document ingested before this feature was added (stored_path is NULL)
- **THEN** the engine SHALL return HTTP 404 with `{"error": "Original file not available - ingested before document storage was enabled"}`
#### Scenario: Download file when file missing from disk
- **WHEN** a client sends `GET /api/v1/documents/{id}/file` for a document whose `stored_path` is set but the file no longer exists on disk
- **THEN** the engine SHALL return HTTP 404 with `{"error": "Stored file not found on disk"}`
#### Scenario: Download file for non-existent document
- **WHEN** a client sends `GET /api/v1/documents/{id}/file` with a non-existent document ID
- **THEN** the engine SHALL return HTTP 404 with `{"error": "Document not found"}`
---
### Requirement: File cleanup on document deletion
The engine SHALL remove the stored original file from disk when a document is deleted.
#### Scenario: Delete document with stored file
- **WHEN** a client sends `DELETE /api/v1/documents/{id}` for a document with a stored file
- **THEN** the engine SHALL delete the document from the database (cascading to chunks, embeddings, tags) AND delete the stored file from disk
#### Scenario: Delete document when stored file already missing
- **WHEN** a client sends `DELETE /api/v1/documents/{id}` for a document whose stored file has been manually removed from disk
- **THEN** the engine SHALL delete the document from the database successfully and log a warning about the missing file
#### Scenario: Delete document without stored file (pre-existing)
- **WHEN** a client sends `DELETE /api/v1/documents/{id}` for a document with `stored_path` NULL
- **THEN** the engine SHALL delete the document from the database without attempting file removal
---
### Requirement: Database schema migration for stored_path and original_filename
The engine SHALL add `stored_path` and `original_filename` columns to the `documents` table for tracking permanent file locations and original upload filenames.
#### Scenario: Fresh database initialization
- **WHEN** the engine initializes a new database
- **THEN** the `documents` table SHALL include `stored_path TEXT` and `original_filename TEXT` columns in its schema
#### Scenario: Existing database migration
- **WHEN** the engine starts with a database created before this feature
- **THEN** the engine SHALL add `stored_path TEXT` and `original_filename TEXT` to the `documents` table via `ALTER TABLE` if the columns do not exist
@@ -0,0 +1,61 @@
## MODIFIED Requirements
### Requirement: Background ingestion worker
The engine SHALL run a background worker that processes queued jobs. The worker SHALL process one job at a time. For each job, it SHALL: detect document type, run the appropriate chunking pipeline (Docling for PDFs, header-based for Markdown, AST-based for code, whole-text for notes), generate embeddings using the resident model, insert chunks and vectors into the database, and move the original file to persistent storage.
#### Scenario: Successful PDF ingestion
- **WHEN** the background worker picks up a queued PDF job
- **THEN** it SHALL update the job status to `processing`, run Docling conversion and chunking, embed all chunks, insert document and chunks into the database, move the staged file to `{data_dir}/documents/{content_hash}.pdf`, update `documents.stored_path` with the permanent path, store the original filename in `documents.original_filename`, update the job status to `done` with the resulting document_id and chunk count, and clean up the staging entry
#### Scenario: Ingestion failure
- **WHEN** the background worker encounters an error during processing (e.g., corrupt PDF)
- **THEN** it SHALL update the job status to `failed` with the error message, delete the staged file, and continue processing the next queued job
#### Scenario: Search during active ingestion
- **WHEN** a search request arrives while the background worker is processing a job
- **THEN** the search SHALL execute without blocking (SQLite WAL mode) and return results from already-ingested documents
---
### Requirement: Document management
The engine SHALL provide endpoints to list, inspect, remove, and download original files for ingested documents.
#### Scenario: List documents
- **WHEN** a client sends `GET /api/v1/documents`
- **THEN** the engine SHALL return a JSON array of documents with id, title, doc_type, tags, chunk_count, and created_at
#### Scenario: List documents with filters
- **WHEN** a client sends `GET /api/v1/documents?type=pdf&tags=manual`
- **THEN** the engine SHALL return only documents matching all specified filters
#### Scenario: Get document details
- **WHEN** a client sends `GET /api/v1/documents/{id}`
- **THEN** the engine SHALL return the full document record including all chunks, their text content, and whether the original file is available (`has_file: true/false`)
#### Scenario: Download original file
- **WHEN** a client sends `GET /api/v1/documents/{id}/file`
- **THEN** the engine SHALL return the original file with appropriate Content-Type and `Content-Disposition: attachment; filename="{original_filename}"` headers, or HTTP 404 if the file is not available
#### Scenario: Remove a document
- **WHEN** a client sends `DELETE /api/v1/documents/{id}`
- **THEN** the engine SHALL delete the document, all its chunks, associated embeddings, tag associations, and the stored original file from disk, and return HTTP 200 with a confirmation
#### Scenario: Remove non-existent document
- **WHEN** a client sends `DELETE /api/v1/documents/{id}` with a non-existent ID
- **THEN** the engine SHALL return HTTP 404
---
### Requirement: Engine configuration via environment variables
The engine SHALL be configured via environment variables. No config file is read by the engine — all configuration comes from the environment (set via compose.yaml or Docker run).
#### Scenario: Default configuration
- **WHEN** the engine starts with no environment variables set
- **THEN** it SHALL use defaults: data directory `/data`, model `all-MiniLM-L6-v2`, device `auto`, no API key required. It SHALL create `staging/` and `documents/` subdirectories under the data directory.
#### Scenario: Custom model
- **WHEN** `KB_MODEL` is set to `BAAI/bge-small-en-v1.5`
- **THEN** the engine SHALL download and load that model instead of the default
@@ -0,0 +1,38 @@
## 1. Config and Schema
- [x] 1.1 Add `documents_dir` property to `Config` in `engine/kb/config.py` returning `{data_dir}/documents`
- [x] 1.2 Add `documents_dir.mkdir()` to `Config.ensure_dirs()`
- [x] 1.3 Add `stored_path TEXT` and `original_filename TEXT` columns to `documents` table in `init_schema()` (both CREATE TABLE and ALTER TABLE migration for existing DBs)
## 2. Worker — File Persistence
- [x] 2.1 In `worker._process_job()`, after successful DB commit, move staged file to `{documents_dir}/{content_hash}{ext}` using `shutil.move()`
- [x] 2.2 Update `documents.stored_path` and `documents.original_filename` (from `jobs.filename`) after moving the file
- [x] 2.3 Remove `staging.cleanup()` call for successful jobs (file is moved, not deleted); keep cleanup on failure path
## 3. API — File Download Endpoint
- [x] 3.1 Add `GET /api/v1/documents/{id}/file` route in `engine/kb/routes/documents.py` using FastAPI `FileResponse`
- [x] 3.2 Return appropriate `Content-Type` from file extension and `Content-Disposition: attachment; filename="{original_filename}"` (fall back to `{title}{ext}` if NULL)
- [x] 3.3 Handle 404 cases: document not found, `stored_path` is NULL, file missing from disk
## 4. API — Delete Cleanup
- [x] 4.1 Update `DELETE /api/v1/documents/{id}` in `engine/kb/routes/documents.py` to also delete the stored file from disk
- [x] 4.2 Handle missing file gracefully (log warning, don't fail the request)
## 5. Document Details Enhancement
- [x] 5.1 Add `has_file` boolean to `GET /api/v1/documents/{id}` response based on `stored_path` presence and file existence on disk
## 6. Go Client
- [x] 6.1 Add `kb export <doc_id>` subcommand to the Go client that calls `GET /api/v1/documents/{id}/file` and writes to stdout or a specified output path
## 7. Testing
- [x] 7.1 Test successful ingestion stores file at expected path
- [x] 7.2 Test failed ingestion does not leave file in documents dir
- [x] 7.3 Test file download endpoint returns correct content and headers
- [x] 7.4 Test document deletion removes stored file
- [x] 7.5 Test download returns 404 for documents without stored files
@@ -0,0 +1,2 @@
schema: spec-driven
created: 2026-03-29
@@ -0,0 +1,23 @@
## Context
The engine's `POST /api/v1/reindex` re-embeds all chunks synchronously and returns `{"chunks_reindexed": N, "model": "..."}`. The client has an established confirmation pattern in `remove.go` using `--yes`/`-y` flag.
## Goals / Non-Goals
**Goals:**
- Add `kb reindex` with confirmation prompt matching `kb remove` pattern
- Display human-readable and JSON output
**Non-Goals:**
- Progress reporting during reindex (engine returns synchronously)
- Model selection from the client (model is engine-side config)
## Decisions
### 1. Confirmation prompt before reindex
Reindex drops and rebuilds the vector table — destructive if interrupted. Use the same `[y/N]` prompt pattern as `kb remove`, skippable with `--yes`/`-y`.
### 2. Warn that it may take a while
The prompt should mention that reindex re-embeds all chunks, so the user knows it's not instant.
@@ -0,0 +1,22 @@
## Why
The engine exposes `POST /api/v1/reindex` but there's no client command for it. Users switching embedding models must use curl directly. Adding `kb reindex` with a confirmation prompt keeps it consistent with other destructive commands like `kb remove`.
## What Changes
- Add `kb reindex` command to the Go client with confirmation prompt (skip with `--yes`/`-y`)
- Display reindex results (chunks reindexed, model used)
## Capabilities
### New Capabilities
(none)
### Modified Capabilities
- `go-client`: Add reindex command requirement
## Impact
- New file: `client/cmd/reindex.go`
@@ -0,0 +1,25 @@
## ADDED Requirements
### Requirement: Reindex command
The client SHALL provide a `kb reindex` command that triggers re-embedding of all chunks on the engine. The command SHALL prompt for confirmation before proceeding.
#### Scenario: Reindex with confirmation
- **WHEN** the user runs `kb reindex`
- **THEN** the client SHALL display a warning that all chunks will be re-embedded and prompt `Reindex all chunks? This will re-embed everything. [y/N]`. If confirmed, it SHALL POST to `/api/v1/reindex` and display the result.
#### Scenario: Reindex with skip confirmation
- **WHEN** the user runs `kb reindex --yes`
- **THEN** the client SHALL skip the confirmation prompt and POST to `/api/v1/reindex` immediately
#### Scenario: Reindex cancelled
- **WHEN** the user runs `kb reindex` and responds with anything other than `y` or `yes`
- **THEN** the client SHALL print `Cancelled.` and exit with code 0
#### Scenario: Reindex human output
- **WHEN** the reindex completes successfully with default format
- **THEN** the client SHALL print `Reindexed N chunks (model: <model_name>)`
#### Scenario: Reindex JSON output
- **WHEN** the user runs `kb reindex --yes --format json`
- **THEN** the client SHALL output the raw JSON response from the engine
@@ -0,0 +1,5 @@
## 1. Implementation
- [x] 1.1 Create `client/cmd/reindex.go` with `kb reindex` command, `--yes`/`-y` flag, confirmation prompt matching `remove.go` pattern
- [x] 1.2 POST to `/api/v1/reindex`, handle human output (`Reindexed N chunks (model: ...)`) and JSON output
- [x] 1.3 Verify build compiles and command appears in `kb --help`
@@ -0,0 +1,2 @@
schema: spec-driven
created: 2026-03-29
@@ -0,0 +1,43 @@
## Context
The `add` command currently handles both file uploads and notes via a `--note` string flag. This creates confusing flag parsing and a muddled help screen. The engine already auto-detects file type from extension (`detector.py`) and rejects unsupported ones, so the client's `--type` flag is redundant.
## Goals / Non-Goals
**Goals:**
- `kb "my note"` as the sole note entry path (replaces `kb add --note`)
- `kb addfile <path>` as a file-only upload command (replaces `kb add`)
- Client-side extension validation before uploading
- Clean, unambiguous help text for both paths
**Non-Goals:**
- Engine changes — type detection stays server-side
- Backward compatibility shim for `kb add` — clean break
- Client-side MIME type detection — extension check is sufficient
## Decisions
### Rename add → addfile, strip note/type flags
Rename the cobra command from `add` to `addfile`. Remove `--note`, `--title`, and `--type` flags. Keep `--tags`, `--recursive`. The command becomes purely about file uploads.
**Why not keep `add` as an alias?** Clean break is simpler. The old form was confusing — better to force a quick migration than maintain two paths.
### Extension validation on single file uploads
The `supportedExts` map already gates recursive walks. Apply the same check to single file uploads — reject with a clear error listing supported extensions. This gives instant feedback instead of a round-trip to the engine.
### Root command RunE for note shorthand
Use cobra's `Args: cobra.ArbitraryArgs` and `RunE` on the root command. When args are present and no subcommand matched, join all args into a single note string and submit. `--tags` flag on root for tagging notes. No `--title` — keep it minimal.
**Why join all args?** `kb remember to update dns` (unquoted) should work the same as `kb "remember to update dns"`.
### Reuse note submission logic via shared helper
Extract `submitNote` from the current `runAdd` so both the root command and any future callers use the same POST + duplicate-handling + output logic.
## Risks / Trade-offs
- **Breaking change** → Anyone with `kb add` in scripts needs to update to `kb addfile`. Acceptable for a personal tool.
- **No `--type` override** → If a user ever needs to force a type, they'd have to go through the engine API directly. Low risk since the engine's auto-detection covers all supported formats.
@@ -0,0 +1,34 @@
## Why
Adding a note requires `kb add --note "my note"` — too much ceremony for what should be instant. The `--note` flag taking a string value also creates confusing flag parsing (e.g. `kb add --note --tags foo` parses `--tags` as the note value). Meanwhile, `kb add` tries to do two things (files and notes) which muddies its help text and UX.
Splitting these into distinct paths makes the CLI clearer:
- **Notes**: `kb "my note"` — zero-friction, no subcommand needed
- **Files**: `kb addfile report.pdf` — explicit, file-only command
## What Changes
- **Add `kb "text"` shorthand**: bare string arguments without a subcommand are treated as notes, submitted via `POST /api/v1/jobs`
- **Rename `add``addfile`**: the command becomes file-only, no more `--note`/`--title` flags
- **Drop `--type` flag**: the engine already auto-detects type from file extension (`detector.py`); the client doesn't need to override this
- **Add client-side extension validation**: reject unsupported file extensions with a clear error before uploading, using the same extension set as recursive directory walks
- **Update README**: document the new shorthand and renamed command
- **BREAKING**: `kb add` no longer exists; `kb add --note` no longer exists
## Capabilities
### New Capabilities
_(none)_
### Modified Capabilities
- `go-client`: Rename `add` to `addfile`, remove `--note`/`--title`/`--type` flags, add extension validation for single file uploads, add implicit note shorthand on root command
## Impact
- `client/cmd/add.go` → renamed/refactored to `addfile` command, stripped of note logic, added extension check
- `client/cmd/root.go` — bare args handling + `--tags` flag for note shorthand
- `README.md` — updated usage examples
- No engine changes — engine already detects type from extension and rejects unsupported files
- Breaking change for any scripts using `kb add` or `kb add --note`
@@ -0,0 +1,95 @@
## ADDED Requirements
### Requirement: Implicit note shorthand
The client SHALL treat bare string arguments (with no subcommand) as an implicit note. `kb "my note"` SHALL behave identically to submitting a note via `POST /api/v1/jobs`. All persistent flags (`--format`, `--engine`, `--api-key`) and the root `--tags` flag SHALL work with the shorthand form.
#### Scenario: Quick note via bare argument
- **WHEN** the user runs `kb "remember to update DNS"`
- **THEN** the client SHALL submit the text as a note via `POST /api/v1/jobs` and print `Queued: note`
#### Scenario: Bare argument with tags
- **WHEN** the user runs `kb "server room is building 3" --tags ops`
- **THEN** the client SHALL submit the note with the specified tags
#### Scenario: Bare argument with JSON output
- **WHEN** the user runs `kb "my note" --format json`
- **THEN** the client SHALL output the raw JSON response from the engine
#### Scenario: Bare argument duplicate detection
- **WHEN** the user runs `kb "my note"` and the engine returns HTTP 409
- **THEN** the client SHALL handle the duplicate response identically to the previous `kb add --note` behaviour
#### Scenario: Multiple unquoted words
- **WHEN** the user runs `kb remember to update dns` (without quotes)
- **THEN** the client SHALL join all arguments into a single note string and submit it
#### Scenario: No interference with subcommands
- **WHEN** the user runs `kb search "query"` or any other existing subcommand
- **THEN** the client SHALL route to the subcommand as before — the implicit note shorthand SHALL NOT interfere
#### Scenario: No arguments
- **WHEN** the user runs `kb` with no arguments
- **THEN** the client SHALL display the help text
---
## MODIFIED Requirements
### Requirement: Add command (file and note ingestion)
The client SHALL provide a `kb addfile` command that uploads files to the engine for async ingestion. The command SHALL validate file extensions before uploading and reject unsupported types. The client SHALL handle duplicate rejection (HTTP 409) and display the existing document information. The command SHALL NOT handle notes — notes are submitted via the implicit note shorthand (`kb "text"`).
#### Scenario: Add a single file
- **WHEN** the user runs `kb addfile report.pdf`
- **THEN** the client SHALL validate the file extension, upload the file via `POST /api/v1/jobs` (multipart), print "Queued: report.pdf", and exit
#### Scenario: Add a file with tags
- **WHEN** the user runs `kb addfile manual.pdf --tags car,maintenance`
- **THEN** the client SHALL include the tags in the multipart upload metadata
#### Scenario: Add a directory recursively
- **WHEN** the user runs `kb addfile ~/documents/ --recursive`
- **THEN** the client SHALL discover all supported files in the directory tree, upload each one sequentially, and print "Queued: N files"
#### Scenario: Unsupported file extension
- **WHEN** the user runs `kb addfile photo.jpg`
- **THEN** the client SHALL print an error listing supported extensions and exit with a non-zero code without making any API call
#### Scenario: Duplicate file rejected (already ingested)
- **WHEN** the user runs `kb addfile report.pdf` and the engine returns HTTP 409 with `{"error": "duplicate", "document_id": 42, "title": "report.pdf"}`
- **THEN** the client SHALL print "Already imported: report.pdf (doc ID: 42)" and exit with code 0
#### Scenario: Duplicate file rejected (in-flight job)
- **WHEN** the user runs `kb addfile report.pdf` and the engine returns HTTP 409 with `{"error": "duplicate", "job_id": 7, "title": "report.pdf"}`
- **THEN** the client SHALL print "Already queued: report.pdf (job ID: 7)" and exit with code 0
#### Scenario: Duplicate file in recursive add
- **WHEN** the user runs `kb addfile ~/documents/ --recursive` and some files are rejected as duplicates
- **THEN** the client SHALL print the duplicate message for each rejected file, continue uploading remaining files, and include a summary (e.g., "Queued: 5 files, 2 duplicates skipped")
#### Scenario: Duplicate with JSON output
- **WHEN** the user runs `kb addfile report.pdf --format json` and the engine returns HTTP 409
- **THEN** the client SHALL output the raw JSON response from the engine including the document_id and title
#### Scenario: Add with JSON output
- **WHEN** the user runs `kb addfile report.pdf --format json`
- **THEN** the client SHALL output the JSON response from the engine including the job_id
#### Scenario: File not found
- **WHEN** the user runs `kb addfile nonexistent.pdf`
- **THEN** the client SHALL print an error and exit with a non-zero code without making any API call
#### Scenario: Upload failure
- **WHEN** the upload fails (network error, engine returns 4xx/5xx other than 409)
- **THEN** the client SHALL print the error and exit with a non-zero code
## REMOVED Requirements
### Requirement: Note ingestion via add command
**Reason**: Notes are now submitted via the implicit note shorthand (`kb "text"`). The `--note` and `--title` flags on the add command are removed.
**Migration**: Use `kb "my note"` or `kb "my note" --tags ops` instead of `kb add --note "my note" --tags ops`.
### Requirement: Document type override via add command
**Reason**: The engine auto-detects document type from file extension (`detector.py`). The client `--type` flag is redundant.
**Migration**: Remove `--type` from scripts. The engine handles type detection automatically.
@@ -0,0 +1,19 @@
## 1. Refactor note submission
- [x] 1.1 Extract note submission logic from `runAdd` into a shared `submitNote` helper (multipart POST, duplicate detection, output formatting)
## 2. Root command shorthand
- [x] 2.1 Add `Args: cobra.ArbitraryArgs` and `RunE` to the root command — join args into a note string, call `submitNote`; show help when no args
- [x] 2.2 Add `--tags` flag on the root command for note tagging
## 3. Rename add → addfile
- [x] 3.1 Rename command from `add` to `addfile` (`Use: "addfile <path>"`)
- [x] 3.2 Remove `--note`, `--title`, and `--type` flags from the command
- [x] 3.3 Add extension validation for single file uploads — reject unsupported extensions with a clear error listing supported types
## 4. Documentation and verification
- [x] 4.1 Update README.md usage section: show `kb "text"` shorthand, rename `add` references to `addfile`
- [x] 4.2 Verify build compiles, `kb --help` and `kb addfile --help` show expected output
@@ -0,0 +1,2 @@
schema: spec-driven
created: 2026-03-28
@@ -0,0 +1,93 @@
## Context
Currently the project uses a single version number shared between client and engine, managed by `release.sh`. Both `client/VERSION` and `engine/VERSION` are always bumped to the same value. A single git tag `vX.Y.Z` is created, and a single Gitea release bundles Go client binaries and Docker engine image references. This means any change to either component forces a full release of both.
The client is a Go binary distributed as platform-specific downloads. The engine is a Python FastAPI server distributed as Docker images. They communicate over HTTP via `/api/v1/` endpoints. The engine already exposes its version via `GET /api/v1/status``{"version": "X.Y.Z", ...}`.
## Goals / Non-Goals
**Goals:**
- Allow client and engine to have independent version numbers and release cadences
- Provide a runtime compatibility check so users get a clear error when their client is too new for their engine
- Split release tooling so each component can be released without touching the other
**Non-Goals:**
- API versioning beyond the existing `/api/v1/` path prefix
- Backward-compatible negotiation or feature detection (client either works or fails)
- Automatic upgrades or update notifications
- Version checking in the other direction (engine requiring minimum client)
## Decisions
### 1. Tag naming: `client-vX.Y.Z` and `engine-vX.Y.Z`
Prefix-style tags clearly identify which component a release belongs to and sort well in git tag listings.
**Why over path-style (`client/vX.Y.Z`):** Slashes in git tags can cause issues with some tooling and are less conventional. Prefix-style is simpler and widely used in monorepos.
**Why over separate repos:** The project is small and tightly coupled at the API level. A monorepo with prefixed tags keeps everything together while allowing independent releases.
### 2. Two release scripts: `release-client.sh` and `release-engine.sh`
Each script handles its own component end-to-end: version bump, build, tag, release, push.
**Why over a single script with flags:** Two simple scripts are easier to understand and maintain than one script with component-selection logic. Each script is ~100 lines instead of one ~200-line script with branching. The shared logic (version helpers, pre-flight checks) is minimal and acceptable to duplicate.
**Shared structure for both scripts:**
1. Pre-flight checks (on main branch, tag doesn't exist)
2. Version bump (reads/writes component's VERSION file only)
3. Build artifacts (Go binaries or Docker images)
4. Commit version bump, create prefixed tag, push
5. Create Gitea release with assets
6. (Engine only) Push Docker images
### 3. `MinEngineVersion` as a build-time constant in the Go client
The client embeds a `MinEngineVersion` string constant alongside the existing `Version` constant. It is set via `-ldflags` at build time, sourced from a `client/MIN_ENGINE_VERSION` file.
**Why a separate file over embedding in `VERSION`:** The two values have different lifecycles. `VERSION` changes every release; `MIN_ENGINE_VERSION` changes only when the client starts using a new engine feature. A separate file makes the intent clear.
**Why ldflags over hardcoding in Go source:** Consistent with how `Version` is already injected. The value lives in a plain text file that's easy to bump manually.
### 4. Compatibility check on every API call via the `Client` struct
The `api.Client` checks engine compatibility on its first HTTP call by hitting `GET /api/v1/status` and comparing the `version` field against `MinEngineVersion`. The result is cached on the `Client` instance — subsequent calls skip the check.
**Flow:**
1. First call to any `Client` method (Get/Post/Delete/Put)
2. Before the actual request, call `GET /api/v1/status`
3. Parse `version` from response
4. Compare against `MinEngineVersion` using semver major.minor.patch comparison
5. If engine version < min: print error to stderr, `os.Exit(1)`
6. If check passes: set `versionChecked = true`, proceed with original request
7. If status endpoint unreachable: proceed with original request (connectivity error will surface on the actual call)
**Why hard fail, no skip flag:** This is a personal tool. If the client needs a newer engine, the user needs to update. A skip flag adds complexity for a scenario where the outcome (broken behavior) is worse than the error.
**Why check on first API call, not at startup:** The `PersistentPreRunE` in cobra runs before every command, but some future commands might not need the engine (e.g. `kb version`, `kb help`). Checking in the `Client` ensures we only check when actually contacting the engine.
**Why proceed when status endpoint is unreachable:** If we can't reach `/status`, the actual API call will also fail with a connection error. No point in double-failing. The compatibility check is for version mismatch, not connectivity.
### 5. Compose files: use `build:` context, not pinned image tags
The compose files currently use `build:` directives, not pre-built image references. Users who build locally don't need pinned tags — they're building from source. Users pulling pre-built images will reference the image tag directly in their own compose file or `docker run` command.
**Decision:** Leave compose files as-is. Release notes for engine releases will include the exact `docker pull` command with the versioned tag.
### 6. Semver comparison: major.minor.patch, no pre-release
Compare versions as three integers. No support for pre-release suffixes (`-rc1`, `-beta`) — the project doesn't use them. If `MinEngineVersion` is `2.1.0` and engine reports `2.1.5`, the check passes. If engine reports `2.0.9`, it fails.
## Risks / Trade-offs
- **Extra HTTP round-trip on first command** — One additional `GET /api/v1/status` call per client invocation. Negligible for a local-network tool.
→ Mitigation: Cached after first check within the Client instance.
- **Developer must remember to bump `MIN_ENGINE_VERSION`** — When adding client code that depends on a new engine endpoint/field, the developer must manually update the file.
→ Mitigation: This is a conscious decision point. The file's existence serves as a reminder. Could add a CI check later if needed.
- **Breaking change to git tag format** — Existing `v2.0.x` tags won't match the new `client-v*` / `engine-v*` convention. Old tags remain in history.
→ Mitigation: No migration needed. Old tags stay as historical artifacts. New convention starts from the first independent release.
- **Two Gitea releases per coordinated release** — When both components change, two releases are created instead of one.
→ Mitigation: Acceptable trade-off. Each release is self-contained with its own assets and notes.
@@ -0,0 +1,32 @@
## Why
Client and engine are currently locked to the same version number and released together via a single script. This means a client-only bug fix (e.g. output formatting) forces a full engine Docker image rebuild and push, and vice versa. Decoupling versions allows each component to be released independently on its own cadence, while a compatibility check ensures users don't run a client that requires engine features not yet deployed.
## What Changes
- **Separate version files** — `client/VERSION` and `engine/VERSION` may diverge (they already exist as separate files, but are currently always set to the same value)
- **Split release script** — Replace single `release.sh` with `release-client.sh` (builds Go binaries, tags `client-vX.Y.Z`, creates release) and `release-engine.sh` (builds Docker images, tags `engine-vX.Y.Z`, creates release, pushes images)
- **Client compatibility check** — Client embeds a `MinEngineVersion` constant (set at build time or in code). On every command that contacts the engine, the client calls `GET /api/v1/status`, compares the engine's reported version against `MinEngineVersion`, and hard-fails with an actionable error if the engine is too old. No skip flag, no warning — just a clear error with upgrade instructions.
- **Tag naming convention** — `client-vX.Y.Z` and `engine-vX.Y.Z` replace the current `vX.Y.Z` tag format. **BREAKING** — existing tag format changes.
## Capabilities
### New Capabilities
(none)
### Modified Capabilities
- `go-client`: Add engine version compatibility check requirement (hard fail if engine version < MinEngineVersion)
- `engine-api`: Status endpoint already returns `version` — no change needed, but delta spec documents the contract that the version field is required for compatibility checking
- `docker-deployment`: Compose files pin engine image tag; release script changes affect image tagging
## Impact
- `release.sh` — replaced by `release-client.sh` + `release-engine.sh`
- `client/cmd/root.go` — new `MinEngineVersion` constant
- `client/internal/api/client.go` — version check on first API call
- `client/Makefile` — may inject `MinEngineVersion` via ldflags alongside `Version`
- Git tags — new naming convention (`client-v*`, `engine-v*`)
- Gitea releases — two separate releases per independent release cycle
- `engine/compose.nvidia.yaml`, `engine/compose.rocm.yaml` — add pinned image tag
@@ -0,0 +1,25 @@
## MODIFIED Requirements
### Requirement: Compose files for deployment
The project SHALL provide Docker Compose files for single-command deployment. Compose files SHALL use `build:` context for local development. Release notes SHALL document the versioned image tag for users pulling pre-built images.
#### Scenario: Start NVIDIA deployment
- **WHEN** an admin runs `docker compose -f compose.nvidia.yaml up -d`
- **THEN** the engine SHALL start with GPU access, bind-mount the data directory, and be reachable on the configured port
#### Scenario: Start ROCm deployment
- **WHEN** an admin runs `docker compose -f compose.rocm.yaml up -d`
- **THEN** the engine SHALL start with GPU access via ROCm device passthrough, bind-mount the data directory, and be reachable on the configured port
#### Scenario: Automatic restart
- **WHEN** the engine process crashes or the host reboots
- **THEN** Docker SHALL automatically restart the container (restart policy `unless-stopped`)
#### Scenario: Configure via environment
- **WHEN** an admin sets environment variables in the compose file (KB_MODEL, KB_API_KEY, KB_DEVICE, etc.)
- **THEN** the engine SHALL use those values
#### Scenario: Pre-built image deployment
- **WHEN** an admin wants to use a pre-built engine image without building from source
- **THEN** the engine release notes SHALL include the exact `docker pull` command with the versioned tag (e.g. `docker.dcglab.co.uk/dcg/kb/engine:engine-v2.1.0-nvidia`)
@@ -0,0 +1,13 @@
## MODIFIED Requirements
### Requirement: Engine status and reindex
The engine SHALL provide status information and support re-embedding all chunks. The `version` field in the status response SHALL always be present and SHALL reflect the engine's release version as read from the `VERSION` file. This field is the contract used by clients for compatibility checking.
#### Scenario: Get engine status
- **WHEN** a client sends `GET /api/v1/status`
- **THEN** the engine SHALL return JSON with `version` (string, from VERSION file), model_name, embedding_dim, GPU device info, database stats (document count by type, total chunks, DB size), and queue stats (queued/processing job count)
#### Scenario: Trigger reindex
- **WHEN** a client sends `POST /api/v1/reindex`
- **THEN** the engine SHALL re-embed all existing chunks using the currently loaded model and return progress information. This operation SHALL NOT block search queries.
@@ -0,0 +1,45 @@
## ADDED Requirements
### Requirement: Engine version compatibility check
The client SHALL verify that the connected engine meets a minimum version requirement before executing any API command. The minimum required engine version SHALL be embedded in the client binary at build time. If the engine version is below the minimum, the client SHALL print an error message and exit with a non-zero code. There SHALL be no flag to skip or suppress this check.
#### Scenario: Compatible engine version
- **WHEN** the client connects to an engine reporting version `2.1.5` and `MinEngineVersion` is `2.1.0`
- **THEN** the client SHALL proceed with the command normally
#### Scenario: Incompatible engine version
- **WHEN** the client connects to an engine reporting version `2.0.3` and `MinEngineVersion` is `2.1.0`
- **THEN** the client SHALL print to stderr: `Error: kb client vX.Y.Z requires engine v2.1.0+ (connected engine is v2.0.3)` followed by an upgrade hint, and exit with code 1
#### Scenario: Engine unreachable during version check
- **WHEN** the client cannot reach the engine's `/api/v1/status` endpoint
- **THEN** the client SHALL skip the version check and proceed with the original command (the actual API call will surface the connectivity error)
#### Scenario: Version check is cached per session
- **WHEN** the client has already verified engine compatibility during the current invocation
- **THEN** subsequent API calls within the same invocation SHALL NOT repeat the version check
#### Scenario: Client version command does not check engine
- **WHEN** the user runs `kb --version`
- **THEN** the client SHALL print the client version without contacting the engine
#### Scenario: MinEngineVersion not set
- **WHEN** the client binary has `MinEngineVersion` set to empty string or `dev`
- **THEN** the client SHALL skip the version check entirely (development builds)
---
## MODIFIED Requirements
### Requirement: Single static binary with zero runtime dependencies
The Go client SHALL compile to a single static binary with no runtime dependencies. It SHALL support cross-compilation for Linux (amd64, arm64), macOS (amd64, arm64), and Windows (amd64). The build SHALL inject both `Version` and `MinEngineVersion` via ldflags.
#### Scenario: Install on a clean machine
- **WHEN** a user downloads the `kb` binary for their platform
- **THEN** they SHALL be able to run it immediately with no additional installs (no Python, no Docker, no shared libraries)
#### Scenario: Version and compatibility info embedded at build time
- **WHEN** the client is built with `make all VERSION=2.1.0 MIN_ENGINE_VERSION=2.0.0`
- **THEN** `kb --version` SHALL report `2.1.0` and the compatibility check SHALL use `2.0.0` as the minimum engine version
@@ -0,0 +1,35 @@
## 1. Client Compatibility Check
- [x] 1.1 Create `client/MIN_ENGINE_VERSION` file with initial value `2.0.0`
- [x] 1.2 Add `MinEngineVersion` variable to `client/cmd/root.go` (set via ldflags, default `dev`)
- [x] 1.3 Update `client/Makefile` to read `MIN_ENGINE_VERSION` file and inject via `-ldflags "-X cmd.MinEngineVersion=..."` alongside existing `Version`
- [x] 1.4 Add `CheckEngineVersion(minVersion string)` method to `client/internal/api/client.go` that calls `GET /api/v1/status`, parses `version` field, and compares against `minVersion` using semver major.minor.patch
- [x] 1.5 Add `versionChecked bool` field to `Client` struct; guard `CheckEngineVersion` so it runs at most once per Client instance
- [x] 1.6 Call `CheckEngineVersion` at the start of `Client.do()` (before executing the actual request); skip if `MinEngineVersion` is empty or `dev`
- [x] 1.7 On version mismatch: print `Error: kb client vX.Y.Z requires engine vM.N.P+ (connected engine is vA.B.C)\nUpdate your engine image to engine-vM.N.P or later.` to stderr and `os.Exit(1)`
- [x] 1.8 On status endpoint unreachable: skip version check silently (let the actual request surface the error)
## 2. Release Script — Client
- [x] 2.1 Create `release-client.sh` extracting client-specific logic from `release.sh`: version bump of `client/VERSION`, Go binary build, git tag `client-vX.Y.Z`, Gitea release with binary assets
- [x] 2.2 Release notes template: include `MinEngineVersion` requirement (e.g. "Requires engine v2.0.0+")
- [x] 2.3 Pass `MIN_ENGINE_VERSION` to `make all` in the build step
## 3. Release Script — Engine
- [x] 3.1 Create `release-engine.sh` extracting engine-specific logic from `release.sh`: version bump of `engine/VERSION`, Docker image build (nvidia + rocm), git tag `engine-vX.Y.Z`, Gitea release, image push
- [x] 3.2 Release notes template: include Docker pull commands with `engine-vX.Y.Z` prefixed tags
## 4. Cleanup
- [x] 4.1 Remove old `release.sh` (replaced by the two new scripts)
- [x] 4.2 Update Docker image tag format in release scripts from `vX.Y.Z-nvidia` to `engine-vX.Y.Z-nvidia` (and same for rocm/latest)
## 5. Testing
- [x] 5.1 Test client version check passes when engine version >= MinEngineVersion
- [x] 5.2 Test client version check fails with correct error message when engine version < MinEngineVersion
- [x] 5.3 Test client skips version check when MinEngineVersion is empty or `dev`
- [x] 5.4 Test client skips version check when engine is unreachable
- [x] 5.5 Dry-run `release-client.sh --dry-run --gitea` and verify correct tag format and build
- [x] 5.6 Dry-run `release-engine.sh --dry-run --gitea` and verify correct tag format and image names
@@ -0,0 +1,2 @@
schema: spec-driven
created: 2026-03-29
@@ -0,0 +1,69 @@
## Context
When a document is ingested, the worker chunks its content and stores each chunk's text in the `chunks` table. FTS5 triggers index that text, and the embedding model embeds it. The document title is stored only in `documents.title` — it never participates in search. This means short documents (or documents whose content lacks the title keywords) are invisible to queries that match the title.
The reindex endpoint (`POST /api/v1/reindex`) currently reads `chunks.text` and re-embeds it. Any fix must apply consistently at both ingestion and reindex time.
## Goals / Non-Goals
**Goals:**
- Document titles are searchable via both FTS5 and vector search
- Section header breadcrumbs (when present in chunk metadata) are also searchable
- Search results continue to return the original chunk text (no title prefix in the `text` field returned to clients)
- Existing documents become searchable by title after a `kb reindex`
- No schema-breaking migration — additive column only
**Non-Goals:**
- Changing the chunking strategies themselves (note, markdown, code, docling)
- Adding a separate title-search endpoint or client-side title filtering
- Changing the search result JSON structure
## Decisions
### 1. Add an `enriched_text` column to the `chunks` table
Store the title-prefixed text in a new `chunks.enriched_text` column alongside the existing `chunks.text`. The `text` column remains the raw chunk content (used for display in search results). The `enriched_text` column holds `"{title}\n\n{section_header}\n\n{text}"` (with section_header omitted when absent).
**Why not just modify `chunks.text`?** The title would then appear in every search result's text field, which is redundant (title is already a separate field) and would confuse consumers that display results.
**Why not reconstruct enriched text on-the-fly at search time?** FTS5 uses an external content table and triggers — it needs a real column to index. Reconstructing via JOIN at FTS query time would defeat the purpose of the FTS index.
### 2. Point FTS5 at `enriched_text` instead of `text`
Update the FTS5 virtual table definition and its sync triggers to index `enriched_text` rather than `text`. This is the core change that makes titles searchable via keyword search.
Since FTS5 external content tables cannot be ALTERed, existing databases require a rebuild: drop and recreate `chunks_fts` and its triggers, then repopulate. This is handled as a schema migration in `init_schema`.
### 3. Embed `enriched_text` instead of `text`
At ingestion time, pass `enriched_text` values to `embed_texts()` instead of raw chunk text. At reindex time, read `enriched_text` from the database. This makes titles searchable via vector similarity too.
### 4. Build enriched text in the worker, not in the ingest modules
The enrichment format is: `"{title}\n\n{chunk_text}"` or `"{title} > {section_header}\n\n{chunk_text}"` when a section header exists in chunk metadata.
This happens in `worker._process_job()` after chunking and before embedding/insertion. The ingest modules remain unchanged — they continue to return raw chunk text and metadata.
### 5. Schema migration adds `enriched_text` and rebuilds FTS
The `init_schema` function will:
1. Add `enriched_text TEXT` column to `chunks` if missing
2. Backfill `enriched_text` from existing data (join with `documents.title` and chunk metadata)
3. Drop and recreate `chunks_fts` to index `enriched_text` instead of `text`
4. Recreate the FTS sync triggers
This is safe because the migration only runs when the column is missing (first startup after upgrade). The backfill uses a single UPDATE...FROM query.
## Risks / Trade-offs
**Slightly larger database** — Each chunk stores the title string twice (once in `enriched_text`, once via the document FK). For a typical KB with short titles this is negligible (< 1% size increase).
→ Acceptable for the search quality improvement.
**FTS rebuild on upgrade** — First startup after upgrade will rebuild the FTS index, which takes a few seconds for large KBs.
→ This is a one-time cost and happens automatically.
**Embedding drift** — Existing vector embeddings won't include title context until `kb reindex` is run. The FTS backfill happens automatically, but vectors require an explicit reindex.
→ Document this in release notes. The FTS improvement alone is a significant win even without reindexing vectors.
**Title changes not propagated** — If a document's title were ever updated, `enriched_text` would be stale. Currently the engine has no title-update endpoint, so this is not a concern.
→ No mitigation needed now. If title editing is added later, it should update enriched_text.
@@ -0,0 +1,28 @@
## Why
Short documents and notes are unsearchable when the user's query matches the document title but not the chunk content. For example, a document titled "Suitcase Locks" containing only "Steve = 1234 / Theresa = 4567" is invisible to both FTS and vector search for the query "suitcase locks". This is because chunk text — the only thing indexed and embedded — does not include the document title. This is a standard RAG deficiency that most pipelines solve by prepending title context to each chunk.
## What Changes
- **Prepend document title to chunk text at ingestion time**: Before embedding and FTS indexing, each chunk's text will be prefixed with the document title (e.g., `"Suitcase Locks\n\n Steve = 363..."`). This ensures the title participates in both full-text and semantic search.
- **Include section header context in chunk text**: For chunks that have a `section_header` in their metadata, prepend the header breadcrumb too (e.g., `"DCG Lab Hardware > GRIMDAWN > motherboard\n\nMSI X870 Tomahawk..."`). This improves search for queries that reference section names.
- **Store the raw chunk text separately from the enriched text**: The original chunk text (without title prefix) must remain accessible so that search results don't display the prepended title redundantly — the title is already returned as a separate field.
- **Reindex command must apply the same enrichment**: When `kb reindex` re-embeds all chunks, it must reconstruct the enriched text (title + section header + chunk text) from stored metadata.
## Capabilities
### New Capabilities
- `chunk-enrichment`: Prepending document title and section context to chunk text before indexing and embedding, while preserving the original text for display.
### Modified Capabilities
- `engine-api`: The search endpoint's returned `text` field must continue to show the original chunk text (without the prepended title), so no visible API change, but the internal indexing behaviour changes. The reindex endpoint must apply enrichment consistently.
## Impact
- **Engine ingestion pipeline** (`worker.py`): The `_process_job` function must build enriched text from title + section headers + chunk text before passing to `embed_texts()` and `insert_chunk()`.
- **Database schema** (`database.py`): Need to store both raw `text` (for display) and enriched `text` (for FTS/embedding), or reconstruct enriched text at index time. Simplest approach: store raw text in `chunks.text`, use enriched text only for FTS content and embedding vectors.
- **FTS triggers** (`database.py`): The FTS5 external content table currently mirrors `chunks.text`. If we add an `enriched_text` column, the FTS index should be built from that instead.
- **Reindex flow** (`worker.py` / `database.py`): Must reconstruct enriched text by joining chunk metadata with document title.
- **Search result enrichment** (`routes/search.py`): No change needed — results already return `chunks.text` (raw) and `documents.title` separately.
- **All four ingest modules** (`note.py`, `markdown.py`, `code.py`, `docling_pipeline.py`): No changes needed — enrichment happens after chunking, in the worker.
- **Existing documents**: Require a `reindex` to benefit from the new enrichment. No data migration needed since the original text is preserved.
@@ -0,0 +1,75 @@
## ADDED Requirements
### Requirement: Chunk text enrichment with document title
The engine SHALL prepend the document title to each chunk's text before FTS indexing and vector embedding. The enriched text SHALL be stored in a dedicated `enriched_text` column on the `chunks` table. The original chunk text SHALL remain in the `text` column for display purposes.
The enrichment format SHALL be:
- Without section header: `"{title}\n\n{chunk_text}"`
- With section header: `"{title} > {section_header}\n\n{chunk_text}"`
Where `section_header` is the value from the chunk's metadata `section_header` field, when present.
#### Scenario: Note ingestion with title enrichment
- **WHEN** a note titled "Suitcase Locks" with content "Steve = 363" is ingested
- **THEN** the `chunks.text` column SHALL contain "Steve = 363" and the `chunks.enriched_text` column SHALL contain "Suitcase Locks\n\nSteve = 363"
#### Scenario: Markdown chunk with section header enrichment
- **WHEN** a markdown document titled "DCG Lab Hardware" produces a chunk with section_header "GRIMDAWN > motherboard" and text "MSI X870 Tomahawk"
- **THEN** the `chunks.enriched_text` SHALL contain "DCG Lab Hardware > GRIMDAWN > motherboard\n\nMSI X870 Tomahawk"
#### Scenario: Chunk without section header
- **WHEN** a document titled "Docker Tips" produces a chunk with no section_header in metadata and text "dbash() { docker exec -it $1 bash; }"
- **THEN** the `chunks.enriched_text` SHALL contain "Docker Tips\n\ndbash() { docker exec -it $1 bash; }"
---
### Requirement: FTS5 indexes enriched text
The FTS5 virtual table `chunks_fts` SHALL index the `enriched_text` column instead of the `text` column. All FTS sync triggers (insert, update, delete) SHALL operate on `enriched_text`.
#### Scenario: FTS search matches document title
- **WHEN** a user searches for "suitcase locks" and a document titled "Suitcase Locks" exists with chunk text "Steve = 363"
- **THEN** the FTS5 search SHALL return that chunk as a match
#### Scenario: FTS search still matches chunk content
- **WHEN** a user searches for "MSI X870" and a chunk contains that text in its body
- **THEN** the FTS5 search SHALL return that chunk as a match (enrichment does not break content matching)
---
### Requirement: Vector embeddings use enriched text
The embedding model SHALL receive `enriched_text` (not raw `text`) when generating vectors during both initial ingestion and reindex operations.
#### Scenario: Vector search matches document title
- **WHEN** a user searches semantically for "luggage combination codes" and a document titled "Suitcase Locks" exists
- **THEN** the vector search SHALL return that chunk with higher similarity than it would without title enrichment
#### Scenario: Reindex uses enriched text
- **WHEN** `POST /api/v1/reindex` is called
- **THEN** the engine SHALL read `enriched_text` from the chunks table and embed that (not `text`)
---
### Requirement: Schema migration adds enriched_text column
On startup, `init_schema` SHALL add the `enriched_text` column to the `chunks` table if it does not exist. It SHALL then backfill `enriched_text` for all existing chunks by joining with `documents.title` and parsing chunk metadata for section headers. It SHALL rebuild the FTS5 table and triggers to index `enriched_text`.
#### Scenario: First startup after upgrade
- **WHEN** the engine starts and `chunks.enriched_text` column does not exist
- **THEN** the engine SHALL add the column, backfill all rows, drop and recreate `chunks_fts` to index `enriched_text`, and recreate the FTS sync triggers
#### Scenario: Subsequent startup
- **WHEN** the engine starts and `chunks.enriched_text` column already exists
- **THEN** the engine SHALL not perform any migration and start normally
---
### Requirement: Search results return raw text
Search results SHALL continue to return the original chunk text (from `chunks.text`) in the `text` field, not the enriched text. The document title is already returned as a separate `title` field.
#### Scenario: Search result text field
- **WHEN** a search returns a chunk from document "Suitcase Locks" with raw text "Steve = 363"
- **THEN** the result `text` field SHALL be "Steve = 363" (not "Suitcase Locks\n\nSteve = 363")
@@ -0,0 +1,31 @@
## MODIFIED Requirements
### Requirement: Background ingestion worker
The engine SHALL run a background worker that processes queued jobs. The worker SHALL process one job at a time. For each job, it SHALL: detect document type, run the appropriate chunking pipeline (Docling for PDFs, header-based for Markdown, AST-based for code, whole-text for notes), build enriched text by prepending the document title (and section header when present) to each chunk's text, generate embeddings using the enriched text and the resident model, insert chunks (with both raw text and enriched text) and vectors into the database, and move the original file to persistent storage.
#### Scenario: Successful PDF ingestion
- **WHEN** the background worker picks up a queued PDF job
- **THEN** it SHALL update the job status to `processing`, run Docling conversion and chunking, build enriched text for each chunk by prepending the document title, embed all chunks using enriched text, insert document and chunks into the database, move the staged file to `{data_dir}/documents/{content_hash}.pdf`, update `documents.stored_path` with the permanent path, store the original filename in `documents.original_filename`, update the job status to `done` with the resulting document_id and chunk count, and clean up the staging entry
#### Scenario: Ingestion failure
- **WHEN** the background worker encounters an error during processing (e.g., corrupt PDF)
- **THEN** it SHALL update the job status to `failed` with the error message, delete the staged file, and continue processing the next queued job
#### Scenario: Search during active ingestion
- **WHEN** a search request arrives while the background worker is processing a job
- **THEN** the search SHALL execute without blocking (SQLite WAL mode) and return results from already-ingested documents
---
### Requirement: Engine status and reindex
The engine SHALL provide status information and support re-embedding all chunks. The `version` field in the status response SHALL always be present and SHALL reflect the engine's release version as read from the `VERSION` file. This field is the contract used by clients for compatibility checking.
#### Scenario: Get engine status
- **WHEN** a client sends `GET /api/v1/status`
- **THEN** the engine SHALL return JSON with `version` (string, from VERSION file), model_name, embedding_dim, GPU device info, database stats (document count by type, total chunks, DB size), and queue stats (queued/processing job count)
#### Scenario: Trigger reindex
- **WHEN** a client sends `POST /api/v1/reindex`
- **THEN** the engine SHALL re-embed all existing chunks using the `enriched_text` column and the currently loaded model, and return progress information. This operation SHALL NOT block search queries.
@@ -0,0 +1,33 @@
## 1. Schema Migration
- [x] 1.1 Add `enriched_text TEXT` column to `chunks` table in `database.py:init_schema` (with migration check for existing DBs)
- [x] 1.2 Write backfill query: `UPDATE chunks SET enriched_text = ... FROM documents` joining title and parsing chunk metadata for section_header
- [x] 1.3 Drop and recreate `chunks_fts` virtual table to index `enriched_text` instead of `text`
- [x] 1.4 Update FTS sync triggers (`chunks_ai`, `chunks_ad`, `chunks_au`) to use `enriched_text`
## 2. Enrichment Helper
- [x] 2.1 Create `build_enriched_text(title: str, chunk_text: str, metadata: dict | None) -> str` helper function in `worker.py` (or a shared util) that formats `"{title} > {section_header}\n\n{chunk_text}"` or `"{title}\n\n{chunk_text}"`
## 3. Ingestion Pipeline
- [x] 3.1 Update `worker._process_job()` to build enriched text for each chunk after chunking
- [x] 3.2 Pass enriched text to `embed_texts()` instead of raw chunk text
- [x] 3.3 Pass enriched text to `database.insert_chunk()` as the new `enriched_text` parameter
- [x] 3.4 Update `database.insert_chunk()` to accept and store `enriched_text`
## 4. Reindex
- [x] 4.1 Update `routes/reindex.py` to read `enriched_text` from chunks table and embed that instead of `text`
## 5. Search Results
- [x] 5.1 Verify `search.py:_enrich()` returns `chunks.text` (raw) not `enriched_text` — no change expected, but confirm
## 6. Testing
- [x] 6.1 Test: ingest a short note with a descriptive title, search by title keywords, confirm it is found
- [x] 6.2 Test: ingest a markdown doc, search by section header, confirm chunks are found
- [x] 6.3 Test: verify search result `text` field does not contain the prepended title
- [x] 6.4 Test: run `reindex`, verify enriched text is used for new embeddings
- [x] 6.5 Test: verify schema migration backfills enriched_text for pre-existing chunks on startup
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schema: spec-driven
created: 2026-03-29
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## Context
The root cobra command in `client/cmd/root.go` uses `cobra.ArbitraryArgs` and its `RunE` handler to catch any arguments not matching a subcommand. Currently, any non-empty args are joined and submitted as a note. This means a single mistyped word (e.g., `kb infow` instead of `kb info`) silently creates a junk note in the knowledge base.
## Goals / Non-Goals
**Goals:**
- Prevent single bare words from being silently ingested as notes
- Provide a clear error message that helps the user correct their input
- Preserve the multi-word implicit note shorthand (`kb remember to update dns`)
**Non-Goals:**
- Detecting "close matches" to real commands (fuzzy matching / did-you-mean)
- Changing how quoted strings work at the shell level (we can't detect quotes after shell expansion)
## Decisions
### Guard on argument count in RunE
When `len(args) == 1`, reject with an error message instead of submitting as a note. When `len(args) > 1`, continue treating as implicit note shorthand.
**Rationale**: This is the simplest reliable heuristic. The shell strips quotes before cobra sees args, so we cannot distinguish `kb "singleword"` from `kb singleword`. However, single-word notes are rare in practice, and the error message tells the user how to work around it (use multiple words or the full note workflow). Multi-word input is almost certainly intentional note text, not a mistyped command.
**Alternative considered**: Checking against a list of known subcommand names — rejected because it wouldn't catch typos of commands we don't know about and adds maintenance burden.
## Risks / Trade-offs
- **Single-word notes no longer work via shorthand** → Users must use `kb add --note "singleword"` or include additional words. This is an acceptable trade-off since single-word notes are uncommon and the error message is clear.
- **Shell quote stripping means we can't be perfect** → `kb "my note"` with exactly one word after quote removal will be rejected. This is a known limitation but very rare in practice.
@@ -0,0 +1,24 @@
## Why
A single unquoted word passed to `kb` (e.g., `kb infow`) is silently treated as a note and ingested. This is almost always a mistyped command, not an intentional note. Users lose trust when typos pollute their knowledge base.
## What Changes
- The implicit note shorthand will require **more than one argument** to be treated as a note. A single bare word will be rejected with a helpful error suggesting the user check their command or quote a multi-word note.
- This is a **BREAKING** change to the implicit note shorthand: `kb singleword` no longer creates a note. Users must write `kb "singleword is important"` or use multiple words.
## Capabilities
### New Capabilities
_(none)_
### Modified Capabilities
- `go-client`: The "Implicit note shorthand" requirement changes to reject single-word bare arguments and print an error instead of submitting them as notes.
## Impact
- **Code**: `client/cmd/root.go``RunE` handler for the root command
- **Tests**: `client/cmd/root_test.go` or equivalent — add/update tests for single-word rejection
- **Users**: Anyone who intentionally used `kb singleword` as a note shorthand will need to use multiple words or quotes
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## MODIFIED Requirements
### Requirement: Implicit note shorthand
The client SHALL treat bare string arguments (with no subcommand) as an implicit note only when **more than one argument** is provided. `kb "my note"` SHALL behave identically to submitting a note via `POST /api/v1/jobs`. All persistent flags (`--format`, `--engine`, `--api-key`) and the root `--tags` flag SHALL work with the shorthand form. A single bare word SHALL be rejected with an error message.
#### Scenario: Quick note via bare argument
- **WHEN** the user runs `kb "remember to update DNS"`
- **THEN** the client SHALL submit the text as a note via `POST /api/v1/jobs` and print `Queued: note`
#### Scenario: Bare argument with tags
- **WHEN** the user runs `kb "server room is building 3" --tags ops`
- **THEN** the client SHALL submit the note with the specified tags
#### Scenario: Bare argument with JSON output
- **WHEN** the user runs `kb "my note" --format json`
- **THEN** the client SHALL output the raw JSON response from the engine
#### Scenario: Bare argument duplicate detection
- **WHEN** the user runs `kb "my note"` and the engine returns HTTP 409
- **THEN** the client SHALL handle the duplicate response identically to the previous `kb add --note` behaviour
#### Scenario: Multiple unquoted words
- **WHEN** the user runs `kb remember to update dns` (without quotes)
- **THEN** the client SHALL join all arguments into a single note string and submit it
#### Scenario: Single bare word rejected
- **WHEN** the user runs `kb infow` (a single unrecognized word)
- **THEN** the client SHALL print to stderr: `Unknown command "infow". Run 'kb --help' for available commands.` followed by a hint about note usage, and exit with a non-zero code
#### Scenario: No interference with subcommands
- **WHEN** the user runs `kb search "query"` or any other existing subcommand
- **THEN** the client SHALL route to the subcommand as before — the implicit note shorthand SHALL NOT interfere
#### Scenario: No arguments
- **WHEN** the user runs `kb` with no arguments
- **THEN** the client SHALL display the help text
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## 1. Core Implementation
- [x] 1.1 Update `RunE` in `client/cmd/root.go` to reject single-word bare arguments with an error message and non-zero exit
- [x] 1.2 Update usage template in `root.go` to reflect that note shorthand requires multiple words
## 2. Tests
- [x] 2.1 Add test: single bare word prints error to stderr and exits non-zero
- [x] 2.2 Add test: multiple bare words are submitted as a note (existing behavior preserved)
- [x] 2.3 Add test: zero arguments shows help (existing behavior preserved)
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schema: spec-driven
created: 2026-03-31
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## Context
README.md currently serves as a single documentation file for both users and developers. It contains ~290 lines mixing installation/usage instructions with build-from-source steps, release scripts, Docker image internals, and developer notes (e.g., ROCm migration plans). There is no DEVELOPER.md or CONTRIBUTING.md file.
## Goals / Non-Goals
**Goals:**
- Separate user-facing documentation (README.md) from developer-facing documentation (DEVELOPER.md)
- README.md should answer: "What is this? How do I install it? How do I use it?"
- DEVELOPER.md should answer: "How do I build from source? How do I release? How do I contribute?"
- Provide a clear cross-reference link between the two files
**Non-Goals:**
- Rewriting or improving documentation content itself (just moving it)
- Creating additional docs files (CONTRIBUTING.md, architecture docs, etc.)
- Changing any code, build scripts, or CI configuration
## Decisions
### 1. Single DEVELOPER.md file (not multiple docs files)
All developer content goes into one top-level DEVELOPER.md rather than a `docs/` directory or separate CONTRIBUTING.md / BUILDING.md files. The total developer content is small enough (~80 lines) that splitting further would be unnecessary overhead. A single file at the repo root is immediately discoverable.
**Alternative considered**: `docs/` directory with multiple files. Rejected because the content volume doesn't justify the structure, and root-level DEVELOPER.md is a well-known convention.
### 2. Content split boundary
Content stays in README.md if it's needed by someone who just wants to **run** kb. Content moves to DEVELOPER.md if it's only needed by someone who wants to **build, modify, or release** kb.
Specifically moving to DEVELOPER.md:
- "From source" subsections under both engine and client install
- Entire "Building and releasing" section (release scripts, version checking, Docker image tags, registry overrides)
- "Future: ROCm runtime migration" developer note
Staying in README.md:
- Architecture overview (helps users understand what they're running)
- Pre-built image / release install instructions
- Client configuration
- Usage examples
- Engine configuration table
- Data portability
- API reference
- Claude Code skill reference
### 3. Cross-reference approach
A short note in README.md's Quick Start section pointing to DEVELOPER.md for building from source. No back-link needed from DEVELOPER.md since developers will naturally find README.md first.
## Risks / Trade-offs
- **[Stale cross-references]** If DEVELOPER.md sections are renamed, the link from README.md could break. Mitigation: link to the file, not to a specific anchor.
- **[Discoverability]** Some users who want to build from source might miss DEVELOPER.md. Mitigation: explicit "See DEVELOPER.md" callout in the Quick Start section where "from source" instructions used to be.
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## Why
README.md currently mixes user-facing content (what kb does, how to install and use it) with developer-facing content (building from source, releasing, Docker image internals, architecture deep-dives). Users looking for quick-start instructions have to scroll past release scripts and build commands. Developers looking for contribution/build info have to hunt through user docs. Splitting these into README.md (users) and DEVELOPER.md (developers/contributors) follows standard open-source convention and makes both audiences' experience cleaner.
## What Changes
- **Trim README.md** to focus on user-facing content: what kb is, how to install (from pre-built images/releases), how to configure, how to use, engine configuration reference, data portability, and API reference.
- **Remove "from source" build instructions** from README.md (both engine and client sections).
- **Remove "Building and releasing" section** from README.md entirely.
- **Remove "Future: ROCm runtime migration"** developer note from README.md.
- **Create DEVELOPER.md** containing: building engine from source, building client from source, release process (client and engine), Docker image details, version checking, ROCm migration notes, and any other contributor-oriented content.
- **Add a link** from README.md to DEVELOPER.md for developers who want to build from source or contribute.
## Capabilities
### New Capabilities
- `developer-docs`: Developer-facing documentation covering building from source, releasing, and contributing.
### Modified Capabilities
(none - no spec-level behavior changes, this is a documentation restructuring)
## Impact
- **Files modified**: `README.md` (trimmed)
- **Files created**: `DEVELOPER.md` (new)
- **No code changes**: purely documentation restructuring
- **No API changes**: no functional impact
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## ADDED Requirements
### Requirement: DEVELOPER.md exists at repo root
The repository SHALL have a `DEVELOPER.md` file at the project root containing all developer-facing documentation.
#### Scenario: File exists
- **WHEN** a developer navigates to the repository root
- **THEN** a `DEVELOPER.md` file SHALL be present
### Requirement: DEVELOPER.md contains build-from-source instructions
DEVELOPER.md SHALL contain instructions for building both the engine and client from source.
#### Scenario: Engine build from source
- **WHEN** a developer reads DEVELOPER.md
- **THEN** it SHALL include instructions for starting the engine from source using compose files (both NVIDIA and ROCm)
#### Scenario: Client build from source
- **WHEN** a developer reads DEVELOPER.md
- **THEN** it SHALL include instructions for building the client binary from source using `make build` and `make all`
### Requirement: DEVELOPER.md contains release process
DEVELOPER.md SHALL document the release process for both client and engine, including release scripts, version bumping, and Docker image tagging.
#### Scenario: Client release documentation
- **WHEN** a developer reads DEVELOPER.md
- **THEN** it SHALL include `release-client.sh` usage with flag options (--gitea, --github, --minor, --no-increment, --dry-run)
#### Scenario: Engine release documentation
- **WHEN** a developer reads DEVELOPER.md
- **THEN** it SHALL include `release-engine.sh` usage with flag options and Docker image tag conventions
#### Scenario: Version checking
- **WHEN** a developer reads DEVELOPER.md
- **THEN** it SHALL include how to check client and engine versions
### Requirement: DEVELOPER.md contains developer notes
DEVELOPER.md SHALL include any forward-looking developer notes such as migration plans or technical debt items.
#### Scenario: ROCm migration note
- **WHEN** a developer reads DEVELOPER.md
- **THEN** it SHALL include the ROCm runtime migration note about onnxruntime and MIGraphX
### Requirement: README.md excludes developer-only content
README.md SHALL NOT contain build-from-source instructions, release processes, or developer-only notes.
#### Scenario: No from-source build steps in README
- **WHEN** a user reads README.md
- **THEN** there SHALL be no "From source" subsections under engine or client installation
#### Scenario: No release section in README
- **WHEN** a user reads README.md
- **THEN** there SHALL be no "Building and releasing" section
#### Scenario: No developer notes in README
- **WHEN** a user reads README.md
- **THEN** there SHALL be no "Future: ROCm runtime migration" section
### Requirement: README.md cross-references DEVELOPER.md
README.md SHALL include a link to DEVELOPER.md for users who want to build from source or contribute.
#### Scenario: Developer link in quick start
- **WHEN** a user reads the Quick Start section of README.md
- **THEN** there SHALL be a note pointing to DEVELOPER.md for building from source

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