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README.md

@@ -6,15 +6,21 @@ and answers queries using retrieval + LLM generation. Commits are tied to
 
 ## Quick start
 
-1. Configure environment variables:
+1. (Optional) Run Postgres and the app via Docker (clone the repo first):
+   - `git clone git@git.lesha.spb.ru:alex/RagAgent.git && cd RagAgent`
+   - `docker compose up -d` — starts Postgres and the RAG app in one network `rag_net`; app connects to DB at host `postgres`.
+   - On first start (empty DB), scripts in `docker/postgres-init/` run automatically (extension + tables). To disable, comment out the init volume in `docker-compose.yml`.
+   - Default DSN inside the app: `postgresql://rag:rag_secret@postgres:5432/rag`. Override with `POSTGRES_*` and `RAG_REPO_PATH` (path to your knowledge-base repo, mounted into the app container).
+   - Run commands: `docker compose run --rm app index --story my-branch`, `docker compose run --rm app ask "Question?"`.
+2. Configure environment variables:
    - `RAG_REPO_PATH` — path to git repo with text files
-   - `RAG_DB_DSN` — Postgres DSN (e.g. `postgresql://user:pass@localhost:5432/rag`)
+   - `RAG_DB_DSN` — Postgres DSN (e.g. `postgresql://rag:rag_secret@localhost:5432/rag`)
    - `RAG_EMBEDDINGS_DIM` — embedding vector dimension (e.g. `1536`)
-2. Create DB schema:
+3. Create DB schema (only if not using Docker, or if init was disabled):
    - `python scripts/create_db.py` (or `psql "$RAG_DB_DSN" -f scripts/schema.sql`)
-3. Index files for a story (e.g. branch name as story slug):
+4. Index files for a story (e.g. branch name as story slug):
    - `rag-agent index --story my-branch --changed --base-ref HEAD~1 --head-ref HEAD`
-4. Ask a question (optionally scoped to a story):
+5. Ask a question (optionally scoped to a story):
    - `rag-agent ask "What is covered?"`
    - `rag-agent ask "What is covered?" --story my-branch`
 
@@ -36,8 +42,11 @@ Story for the commit is taken from (in order): env `RAG_STORY`, file `.rag-story
 
 Scripts: `scripts/create_db.py` (Python, uses `ensure_schema` and `RAG_*` env), `scripts/schema.sql` (raw SQL).
 
+## Embeddings (GigaChat)
+
+If `GIGACHAT_CREDENTIALS` is set (e.g. in `.env` for local runs), embeddings use GigaChat API; otherwise the stub client is used. Optional env: `GIGACHAT_EMBEDDINGS_MODEL` (default `Embeddings`), `GIGACHAT_VERIFY_SSL` (`true`/`false`). Ensure `RAG_EMBEDDINGS_DIM` matches the model output (see GigaChat docs).
+
 ## Notes
 
-- The default embedding/LLM clients are stubs. Replace them in
-  `src/rag_agent/index/embeddings.py` and `src/rag_agent/agent/pipeline.py`.
+- LLM client is still a stub; replace it in `src/rag_agent/agent/pipeline.py` for real answers.
 - This project requires Postgres with the `pgvector` extension.