History

Yiorgis Gozadinos 8e93b639bc Migrate existing databases to the full index set Adds the 0.75.0 upgrade, which brings a pre-existing database up to the index set `_init_tables` now creates. It rewrites no table data, so unlike the earlier data migrations its cost is the index builds alone, each of which reads the column it indexes. `ensure_indexes` ensures an index of the declared type covers each declared column, rather than checking that the column is indexed at all. The distinction is what makes it safe to run against a database of unknown provenance: - A wrong-typed index no longer satisfies the check. A BTree on `label` covers the column while losing the low-cardinality equality lookup the Bitmap is for. - Nothing is dropped or converted away from. Two index types over one column can be deliberate, serving different query shapes, so an index this function did not declare survives even on a column it does. The one thing it overwrites is an index at LanceDB's default name, `{column}_idx`, which is the name it creates itself. - A column already carrying the declared type is skipped, so a database with the full set migrates instantly rather than re-sorting every indexed column. - Undeclared columns are untouched, so a vector index on `chunks` survives. It returns the columns it acted on, because a change is not always visible from outside: adding a Bitmap beside an existing BTree leaves the column indexed before and after. The version bump to 0.75.0 is required, not incidental: `_set_initial_version` stamps a new database with the installed package version, so a migration numbered above it would be pending the moment the database was created. `test_client_update_document_replaces_rows_with_bounded_versions` turns auto_vacuum off. Indexing `documents` means a background vacuum now has an index to maintain on that table, so `optimize()` writes a version where it previously had nothing to do, and it landed inside the window the test measures. The document update itself is still one version, so the bound stays exact.		2026-08-17 16:34:58 +03:00
..
backend	Migrate existing databases to the full index set	2026-08-17 16:34:58 +03:00
frontend	Refuse to compact evidence the host kept no record of	2026-08-13 15:46:23 +03:00
.env.example	Update docs for app	2026-01-13 12:18:13 +02:00
docker-compose.dev.yml	Bind app example backend to loopback and document its lack of auth	2026-07-08 11:37:03 +03:00
docker-compose.yml	Bind app example backend to loopback and document its lack of auth	2026-07-08 11:37:03 +03:00
haiku.rag.yaml.example	replace fixed-radius expansion with section-bounded algorithm	2026-04-16 12:11:53 +03:00
README.md	Bind app example backend to loopback and document its lack of auth	2026-07-08 11:37:03 +03:00

README.md

haiku.rag Chat App

A conversational RAG interface built with CopilotKit and pydantic-ai's AG-UI protocol.

Note: An illustrative example meant as a starting point, with no authentication. The compose files bind the backend to 127.0.0.1; don't expose it to an untrusted network.

Prerequisites

Docker and Docker Compose
A haiku.rag database (created via the haiku-rag CLI)
An LLM API key (Anthropic, OpenAI, or local Ollama)

Quick Start

Set up environment variables:

cp .env.example .env
# Edit .env with your API keys and database path

Configure the LLM and embedding models:

cp haiku.rag.yaml.example haiku.rag.yaml
# Edit haiku.rag.yaml to configure your models

Start the app:
```
docker compose up -d
```
Open the chat interface: http://localhost:3000

Configuration

Environment Variables

Variable	Description	Required
`DB_PATH`	Path to your haiku.rag LanceDB database	Yes
`ANTHROPIC_API_KEY`	Anthropic API key	One LLM key required
`OPENAI_API_KEY`	OpenAI API key	One LLM key required
`OLLAMA_BASE_URL`	Ollama server URL (default: `http://host.docker.internal:11434`)	For local models
`LOGFIRE_TOKEN`	Pydantic Logfire token for debugging	No

haiku.rag.yaml

Configure the LLM, embeddings, and search settings:

qa:
  model:
    provider: anthropic  # or openai, ollama
    name: claude-sonnet-4-20250514

embeddings:
  model:
    provider: ollama
    name: nomic-embed-text

search:
  limit: 10

See haiku.rag.yaml.example for all options.

Development

For local development with hot reloading:

docker compose -f docker-compose.dev.yml up -d --build

Backend code changes reload automatically
Frontend available at http://localhost:3000
Backend API at http://localhost:8001

Architecture

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│    Frontend     │────▶│     Backend     │────▶│   haiku.rag     │
│  (CopilotKit)   │     │  (pydantic-ai)  │     │   (LanceDB)     │
│  localhost:3000 │     │  localhost:8001 │     │                 │
└─────────────────┘     └─────────────────┘     └─────────────────┘

Backend Endpoints

Endpoint	Method	Description
`/v1/chat/stream`	POST	AG-UI chat streaming
`/api/documents`	GET	List documents in database
`/api/info`	GET	Database statistics
`/api/visualize/{chunk_id}`	GET	Visual grounding for chunks
`/health`	GET	Health check

Chat Capabilities

The chat can:

Search your documents with hybrid vector + full-text search
Answer questions with citations from your knowledge base
Filter by document when you ask about specific files
Show visual grounding for PDF/image sources