diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 00000000..86b3638d --- /dev/null +++ b/.dockerignore @@ -0,0 +1,13 @@ +.venv +node_modules +dist +.git +.github +*.md +!README.md +__pycache__ +*.pyc +.env +.env.* +e2e +tests diff --git a/.env.example b/.env.example index 94b8210c..c37f9772 100644 --- a/.env.example +++ b/.env.example @@ -42,29 +42,61 @@ FALKORDB_URL=redis://localhost:6379/0 # REQUIRED - change to your FalkorDB URL # FALKORDB_PORT=6379 # ----------------------------- -# Optional API / secret tokens +# API / secret tokens # ----------------------------- -# API token for internal API access (optional) -# SECRET_TOKEN=your_secret_token +# Optional: static bearer token for internal / programmatic API access. +# When set, this token is accepted as a "master" API key. +# When unset, only user-generated tokens are accepted. # SECRET_TOKEN_ERP=your_erp_token # ----------------------------- # AI / LLM configuration (optional) # ----------------------------- -# The default is to use Azure OpenAI if all three variables are set. -# If the OPENAI_API_KEY is set, it will use OpenAI directly. +# QueryWeaver supports multiple AI providers. Set ONE of the following API keys. +# Provider selection precedence (first match wins): +# OLLAMA_MODEL > OPENAI_API_KEY > GEMINI_API_KEY > ANTHROPIC_API_KEY > COHERE_API_KEY > Azure (fallback) +# +# Optional: Override the default models (both must be from the SAME provider): +# COMPLETION_MODEL=provider/model-name +# EMBEDDING_MODEL=provider/model-name +# +# IMPORTANT: The provider must match your API key. If you set gemini/* models, +# you must have GEMINI_API_KEY set. Mismatched overrides may cause runtime errors. +# +# Examples (using Gemini - requires GEMINI_API_KEY): +# COMPLETION_MODEL=gemini/gemini-3-pro-preview +# EMBEDDING_MODEL=gemini/gemini-embedding-001 -# Azure OpenAI (example) -# AZURE_API_KEY=your_azure_api_key -# AZURE_API_BASE=https://your-resource.openai.azure.com/ -# AZURE_API_VERSION=2023-05-15 +# Examples (using OpenAI - requires OPENAI_API_KEY): +# COMPLETION_MODEL=openai/gpt-4.1 +# EMBEDDING_MODEL=openai/text-embedding-ada-002 -# OpenAI (example) +# OpenAI - uses openai/gpt-4.1 and openai/text-embedding-ada-002 # OPENAI_API_KEY=your_openai_api_key -# Optional: override default model names from api/config.py -# COMPLETION_MODEL=azure/gpt-4.1 -# EMBEDDING_MODEL=azure/text-embedding-ada-002 +# Google Gemini - uses gemini/gemini-3-pro-preview and gemini/gemini-embedding-001 +# GEMINI_API_KEY=your_gemini_api_key + +# Anthropic - uses anthropic/claude-sonnet-4-5-20250929 +# Note: Anthropic has no native embeddings. You MUST also set one of: +# VOYAGE_API_KEY or EMBEDDING_MODEL for embeddings (startup fails otherwise). +# ANTHROPIC_API_KEY=your_anthropic_api_key +# VOYAGE_API_KEY=your_voyage_api_key # Optional: for Voyage AI embeddings with Anthropic + +# Cohere - uses cohere/command-a-03-2025 and cohere/embed-v4.0 +# COHERE_API_KEY=your_cohere_api_key +# COHERE_MODEL=command-a-03-2025 +# COHERE_EMBEDDING_MODEL=embed-v4.0 + +# Local open-source model via Ollama (through LiteLLM) +# OLLAMA_MODEL=llama3.1 +# OLLAMA_EMBEDDING_MODEL=nomic-embed-text +# OLLAMA_API_BASE=http://localhost:11434 + +# Azure OpenAI (default fallback) - uses azure/gpt-4.1 and azure/text-embedding-ada-002 +# AZURE_API_KEY=your_azure_api_key +# AZURE_API_BASE=https://your-resource.openai.azure.com/ +# AZURE_API_VERSION=2023-05-15 # ----------------------------- # OAuth configuration (optional — uncomment to enable login flows) diff --git a/.github/copilot-instructions.md b/.github/copilot-instructions.md index 32367ffb..7f74723f 100644 --- a/.github/copilot-instructions.md +++ b/.github/copilot-instructions.md @@ -10,7 +10,7 @@ QueryWeaver is an open-source Text2SQL tool that transforms natural language int - **Backend**: Python 3.12+, FastAPI 0.115.0+, FalkorDB (Redis-based graph database) - **AI/ML**: LiteLLM with Azure OpenAI/OpenAI integration for text-to-SQL generation - **Testing**: pytest for unit tests, Playwright for E2E testing -- **Dependencies**: pipenv for package management +- **Dependencies**: uv for package management - **Authentication**: authlib with Google/GitHub OAuth - **Deployment**: Docker support, Vercel configuration @@ -22,8 +22,9 @@ Follow this order for a reliable local setup; if you customize the steps, ensure ### 1. Initial Setup (recommended for new contributors) ```bash -# Install pipenv if not available -pip install pipenv +# Install uv if not available +pip install uv +# or visit https://docs.astral.sh/uv/getting-started/installation/ # Install dependencies (backend + frontend) and prepare dev tools # Recommended: use the Make helper which installs Python deps and frontend deps @@ -34,9 +35,9 @@ make install make setup-dev # OR manual steps if you prefer more granular control: -# pipenv sync --dev -# pipenv run playwright install chromium -# pipenv run playwright install-deps +# uv sync +# uv run playwright install chromium +# uv run playwright install-deps # Set up environment file cp .env.example .env @@ -51,9 +52,9 @@ Note: This project includes a TypeScript frontend in `app/` that must be built b make setup-dev # OR manual steps: -pipenv sync --dev -pipenv run playwright install chromium -pipenv run playwright install-deps +uv sync +uv run playwright install chromium +uv run playwright install-deps ``` ### 3. Testing Commands @@ -82,7 +83,7 @@ make docker-stop ```bash # Run pylint (can be run without FalkorDB) make lint -# OR manually: pipenv run pylint $(git ls-files '*.py') +# OR manually: uv run pylint $(git ls-files '*.py') ``` ### 5. Running the Application @@ -90,11 +91,11 @@ make lint ```bash # Development server with debug mode make run-dev -# OR manually: pipenv run uvicorn api.index:app --host "localhost" --port "5000" --reload +# OR manually: uv run uvicorn api.index:app --host "localhost" --port "5000" --reload # Production mode make run-prod -# OR manually: pipenv run uvicorn api.index:app --host "localhost" --port "5000" +# OR manually: uv run uvicorn api.index:app --host "localhost" --port "5000" ``` Important: If you're preparing a production deployment or have changed frontend code, run `make build-prod` (or `make build-dev` for a development build) first to produce the static bundle used by the app. @@ -183,8 +184,8 @@ make docker-falkordb **Error**: E2E tests fail with browser not found **Solution**: ```bash -pipenv run playwright install chromium -pipenv run playwright install-deps +uv run playwright install chromium +uv run playwright install-deps ``` ### 3. Missing Environment File @@ -197,10 +198,10 @@ cp .env.example .env ### 4. Import Errors During Testing **Error**: Module import failures in tests -**Solution**: Ensure you're using pipenv and dependencies are installed: +**Solution**: Ensure you're using uv and dependencies are installed: ```bash -pipenv sync --dev -pipenv run pytest tests/ -k "not e2e" +uv sync +uv run python -m pytest tests/ -k "not e2e" ``` ### 5. Port Conflicts @@ -242,7 +243,7 @@ tests/ ``` ### Configuration Files -- `Pipfile` & `Pipfile.lock`: Python dependencies +- `pyproject.toml` & `uv.lock`: Python dependencies - `pytest.ini`: Test configuration with custom markers - `Makefile`: Build and development commands - `.env.example`: Environment variable template @@ -268,7 +269,7 @@ The repository has comprehensive CI/CD in `.github/workflows/`: 2. **pylint.yml**: Code quality checks - Runs on every push - - Uses same Python/pipenv setup + - Uses same Python/uv setup 3. **e2e-tests.yml**: Dedicated E2E testing - Separate workflow for E2E tests @@ -281,8 +282,8 @@ The repository has comprehensive CI/CD in `.github/workflows/`: All workflows follow this pattern: ```yaml - Python 3.12 setup -- pipenv installation -- pipenv sync --dev +- uv installation +- uv sync - .env file creation with test values (use FALKORDB_URL in CI) - FalkorDB service startup (for tests requiring DB) - Playwright browser installation (for E2E tests) diff --git a/.github/dependabot.yml b/.github/dependabot.yml index bcb81510..8fa39381 100644 --- a/.github/dependabot.yml +++ b/.github/dependabot.yml @@ -10,7 +10,7 @@ updates: target-branch: "staging" schedule: interval: "weekly" - - package-ecosystem: "pip" + - package-ecosystem: "uv" directory: "/" target-branch: "staging" schedule: diff --git a/.github/wordlist.txt b/.github/wordlist.txt index 0bbe3fe9..5eacb0df 100644 --- a/.github/wordlist.txt +++ b/.github/wordlist.txt @@ -1,6 +1,8 @@ QueryWeaver FalkorDB OAuth +DDL +DML AGPL Affero nullability @@ -8,6 +10,7 @@ schemas psycopg html PostgreSQLLoader +PostgresLoader api postgres postgresql @@ -30,8 +33,8 @@ Nullability endcapture CVSS falkordb -pipenv -Pipenv +uv +pyproject README md UI @@ -71,9 +74,13 @@ namespace namespaced CSRF +Anthropic +Cohere LLM +Ollama OpenAI OpenAI's +DockerHub Dockerhub FDE github @@ -95,4 +102,22 @@ Sanitization JOINs subqueries subquery -TTL \ No newline at end of file +TTL + +config +docstring +dotenv +ESLint +GraphNotFoundError +HSTS +init +InternalError +InvalidArgumentError +Middleware +monorepo +PRs +pylint +pytest +Radix +Zod +Dependabot diff --git a/.github/workflows/dependency-review.yml b/.github/workflows/dependency-review.yml index 4e43cdf8..e0c3be3e 100644 --- a/.github/workflows/dependency-review.yml +++ b/.github/workflows/dependency-review.yml @@ -29,12 +29,9 @@ jobs: runs-on: ubuntu-latest steps: - name: 'Checkout repository' - uses: actions/checkout@v6 + uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6 - name: 'Dependency Review' - uses: actions/dependency-review-action@v4 + uses: actions/dependency-review-action@2031cfc080254a8a887f58cffee85186f0e49e48 # v4 # Commonly enabled options, see https://github.com/actions/dependency-review-action#configuration-options for all available options. with: comment-summary-in-pr: always - # fail-on-severity: moderate - # deny-licenses: GPL-1.0-or-later, LGPL-2.0-or-later - # retry-on-snapshot-warnings: true diff --git a/.github/workflows/playwright.yml b/.github/workflows/playwright.yml index 94891b53..c0d9d871 100644 --- a/.github/workflows/playwright.yml +++ b/.github/workflows/playwright.yml @@ -19,36 +19,41 @@ env: jobs: test: + # Skip for Dependabot PRs — the LLM-dependent E2E tests require Azure OpenAI + # secrets that are not available in Dependabot PR runs. Full E2E coverage runs + # on the merge-to-staging/main push event where secrets are accessible. + if: github.event_name != 'pull_request' || github.event.pull_request.user.login != 'dependabot[bot]' timeout-minutes: 60 runs-on: ubuntu-latest steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6 # Setup Python - name: Set up Python - uses: actions/setup-python@v6 + uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6 with: python-version: ${{ env.PYTHON_VERSION }} - cache: 'pip' - cache-dependency-path: Pipfile.lock - + + # Install uv + - name: Install uv + uses: astral-sh/setup-uv@cec208311dfd045dd5311c1add060b2062131d57 # v8.0.0 + with: + version: "0.7.12" + # Setup Node.js - - uses: actions/setup-node@v6 + - uses: actions/setup-node@53b83947a5a98c8d113130e565377fae1a50d02f # v6 with: node-version: ${{ env.NODE_VERSION }} cache: 'npm' cache-dependency-path: | package-lock.json app/package-lock.json - - # Install pipenv - - name: Install pipenv - run: pip install pipenv - + + # Install Python dependencies - name: Install Python dependencies - run: pipenv sync --dev + run: uv sync --locked # Install Node dependencies (root - for Playwright) - name: Install root dependencies @@ -57,7 +62,7 @@ jobs: # Cache Playwright browsers - name: Cache Playwright browsers id: playwright-cache - uses: actions/cache@v4 + uses: actions/cache@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5 with: path: ~/.cache/ms-playwright key: playwright-browsers-${{ runner.os }}-${{ hashFiles('package-lock.json') }} @@ -107,12 +112,25 @@ jobs: echo "Testing FalkorDB connectivity from host..." docker ps -a + # Create CI .env so load_dotenv() finds the required variables + - name: Create CI .env + run: | + cat > .env < /tmp/uvicorn.log 2>&1 & + # Start server in background with uv + uv run uvicorn api.index:app --host localhost --port 5000 > /tmp/uvicorn.log 2>&1 & UVICORN_PID=$! + echo "pid=$UVICORN_PID" >> "$GITHUB_OUTPUT" echo "Started server with PID: $UVICORN_PID" # Wait for app to start echo "Waiting for application to start..." @@ -162,7 +180,7 @@ jobs: CI: true # Upload test results on failure - - uses: actions/upload-artifact@v7 + - uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7 if: failure() with: name: playwright-report @@ -170,17 +188,18 @@ jobs: retention-days: 30 # Upload test screenshots on failure - - uses: actions/upload-artifact@v7 + - uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7 if: failure() with: name: test-results path: test-results/ retention-days: 30 - # Cleanup - Stop all containers - - name: Cleanup Docker containers + # Cleanup - Stop all containers and background processes + - name: Cleanup if: always() run: | + kill ${{ steps.start-server.outputs.pid }} || true docker compose -f e2e/docker-compose.test.yml down -v || true docker stop falkordb-test || true docker rm falkordb-test || true diff --git a/.github/workflows/publish-docker.yml b/.github/workflows/publish-docker.yml index 8eb2753b..265bd456 100644 --- a/.github/workflows/publish-docker.yml +++ b/.github/workflows/publish-docker.yml @@ -12,22 +12,22 @@ jobs: runs-on: ubuntu-latest steps: - name: Check out the repo - uses: actions/checkout@v6 + uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6 - name: Log in to Docker Hub - uses: docker/login-action@v3 + uses: docker/login-action@b45d80f862d83dbcd57f89517bcf500b2ab88fb2 # v4 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - name: Extract metadata (tags, labels) for Docker id: meta - uses: docker/metadata-action@v5 + uses: docker/metadata-action@030e881283bb7a6894de51c315a6bfe6a94e05cf # v6 with: images: falkordb/queryweaver - name: Build and push Docker image - uses: docker/build-push-action@v6 + uses: docker/build-push-action@d08e5c354a6adb9ed34480a06d141179aa583294 # v7 with: context: . push: true diff --git a/.github/workflows/pylint.yml b/.github/workflows/pylint.yml index 08930af1..57da534b 100644 --- a/.github/workflows/pylint.yml +++ b/.github/workflows/pylint.yml @@ -9,22 +9,22 @@ jobs: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6 - name: Set up Python - uses: actions/setup-python@v6 + uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6 with: python-version: '3.12' - - name: Install pipenv - run: | - python -m pip install --upgrade pip - pip install pipenv + - name: Install uv + uses: astral-sh/setup-uv@cec208311dfd045dd5311c1add060b2062131d57 # v8.0.0 + with: + version: "latest" - name: Install dependencies run: | - pipenv sync --dev + uv sync - name: Run pylint run: | - pipenv run pylint $(git ls-files '*.py') \ No newline at end of file + uv run python -m pylint $(git ls-files '*.py') \ No newline at end of file diff --git a/.github/workflows/spellcheck.yml b/.github/workflows/spellcheck.yml index 7fce97f2..ffcc1d88 100644 --- a/.github/workflows/spellcheck.yml +++ b/.github/workflows/spellcheck.yml @@ -10,9 +10,9 @@ jobs: spellcheck: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6 - name: Spellcheck - uses: rojopolis/spellcheck-github-actions@0.58.0 + uses: rojopolis/spellcheck-github-actions@e3cd8e9aec4587ec73bc0e60745aafd45c37aa2e # 0.60.0 with: config_path: .github/spellcheck-settings.yml task_name: Markdown \ No newline at end of file diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index bba98e22..f393b892 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -29,21 +29,21 @@ jobs: --health-retries 5 steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6 - name: Set up Python - uses: actions/setup-python@v6 + uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6 with: python-version: '3.12' - - name: Install pipenv - run: | - python -m pip install --upgrade pip - pip install pipenv + - name: Install uv + uses: astral-sh/setup-uv@cec208311dfd045dd5311c1add060b2062131d57 # v8.0.0 + with: + version: "0.7.12" - name: Install dependencies run: | - pipenv sync --dev + uv sync --locked - name: Install frontend dependencies run: | @@ -63,7 +63,7 @@ jobs: - name: Run unit tests run: | - pipenv run pytest tests/ -k "not e2e" --verbose + uv run python -m pytest tests/ -k "not e2e" --verbose - name: Run lint run: | diff --git a/.gitignore b/.gitignore index a9e199cd..3bf6a813 100644 --- a/.gitignore +++ b/.gitignore @@ -31,4 +31,7 @@ demo_tokens.py /blob-report/ /playwright/.cache/ /playwright/.auth/ -e2e/.auth/ \ No newline at end of file +e2e/.auth/ +# Build artifacts +clients/python/queryweaver_client.egg-info/ +clients/ts/dist/ diff --git a/AGENTS.md b/AGENTS.md new file mode 100644 index 00000000..e99aae12 --- /dev/null +++ b/AGENTS.md @@ -0,0 +1,147 @@ +# AGENTS.md — QueryWeaver (Text2SQL) + +## Project Overview + +QueryWeaver is an open-source Text2SQL tool that converts natural-language questions into SQL using graph-powered schema understanding backed by FalkorDB. It is a full-stack monorepo with a Python/FastAPI backend (`api/`) and a React/TypeScript frontend (`app/`). + +Repository: `FalkorDB/QueryWeaver` + +## Tech Stack + +| Layer | Technology | +|-------|-----------| +| Backend | Python 3.12+, FastAPI, Uvicorn | +| Frontend | React 18, TypeScript 5.8, Vite 7, Tailwind CSS | +| Graph DB | FalkorDB | +| LLM | LiteLLM (multi-provider: OpenAI, Gemini, Anthropic, Cohere, Azure, Ollama) | +| Auth | OAuth 2.0 (Google, GitHub) via authlib | +| Package mgmt | uv (Python), npm (Node) | +| Testing | pytest (unit), Playwright (E2E) | +| Linting | pylint (Python), ESLint (TypeScript) | +| CI/CD | GitHub Actions | + +## Directory Structure + +``` +api/ Python backend (FastAPI) + agents/ AI agents (analysis, healing, relevancy, follow-up) + analyzers/ Code/syntax analyzers + auth/ OAuth handlers, user management + core/ Core text2sql logic, schema loading, errors + entities/ Data models / DTOs + loaders/ Database loaders (PostgreSQL, MySQL) + memory/ Conversation memory management + routes/ API endpoints (auth, graphs, database, tokens, settings) + sql_utils/ SQL sanitization + config.py LLM provider detection, configuration + app_factory.py FastAPI app init, middleware + index.py Application entry point +app/ React + Vite frontend + src/components/ React components + src/contexts/ React contexts (Auth, Chat, Database, Settings) + src/services/ API service layer + src/types/ TypeScript type definitions +tests/ Unit tests (pytest) +e2e/ End-to-end tests (Playwright) +docs/ Documentation +.github/workflows/ CI/CD pipelines +``` + +## Quick Reference + +### Install & Setup + +```bash +make install # uv sync + npm ci +make setup-dev # install + Playwright browsers +cp .env.example .env # configure environment +``` + +### Run + +```bash +make run-dev # dev server with hot reload (localhost:5000) +make run-prod # production server +make docker-falkordb # start FalkorDB in Docker +``` + +### Test + +```bash +make test-unit # pytest unit tests +make test-e2e # Playwright E2E (headless) +make test-e2e-headed # Playwright E2E (visible browser) +make test # build + unit + E2E +``` + +### Lint + +```bash +make lint # pylint + ESLint +make lint-frontend # ESLint only +``` + +### Build + +```bash +make build-dev # Vite dev build +make build-prod # Vite production build +``` + +## Code Conventions + +### Python (backend) + +- PEP 8 with **120-char line limit** +- Type hints throughout +- pylint for linting (docstring checks disabled) +- FastAPI routers split by domain under `api/routes/` +- Custom exceptions in `api/core/errors.py` (GraphNotFoundError, InternalError, InvalidArgumentError) +- Middleware: CSRF (double-submit cookies), HSTS headers +- Environment config via dotenv; see `api/config.py` for defaults and provider detection +- Run backend: `uv run uvicorn api.index:app` + +### TypeScript / React (frontend) + +- Strict TypeScript +- ESLint with `@typescript-eslint`; unused vars prefixed with `_` are allowed +- State management via React Context API +- API calls through service layer (`app/src/services/`) +- Styling with Tailwind CSS + Radix UI primitives +- Routing with React Router v7 +- Forms with React Hook Form + Zod validation +- Build tool: Vite (dev proxy to backend on port 5000) + +### Testing + +- **Unit tests** (`tests/`): pytest with markers `e2e`, `slow`, `auth`, `integration`, `unit` +- **E2E tests** (`e2e/`): Playwright with Page Object Model pattern; auth setup runs first +- E2E infra lives in `e2e/infra/`, page objects in `e2e/logic/pom/` +- Test data (SQL init scripts) in `e2e/test-data/` + +## Environment Variables + +Required: +- `FASTAPI_SECRET_KEY` — session secret +- `FALKORDB_URL` — FalkorDB connection string (e.g. `redis://localhost:6379/0`) + +LLM provider (set one): `OPENAI_API_KEY`, `GEMINI_API_KEY`, `ANTHROPIC_API_KEY`, `COHERE_API_KEY`, `AZURE_API_KEY`, or `OLLAMA_MODEL` + +Optional overrides: `COMPLETION_MODEL`, `EMBEDDING_MODEL` (must match provider) + +See `.env.example` for the full list. + +## CI/CD + +GitHub Actions workflows (`.github/workflows/`): +- **tests.yml** — unit tests + lint on push/PR to main/staging +- **playwright.yml** — dedicated Playwright E2E suite (skipped for Dependabot PRs; secrets unavailable) +- **pylint.yml** — Python linting +- **spellcheck.yml** — docs spellcheck +- **publish-docker.yml** — build & push Docker image to DockerHub +- **dependency-review.yml** — dependency security review + +## Branching + +- `main` — production branch, target for PRs +- `staging` — integration branch diff --git a/CLAUDE.md b/CLAUDE.md new file mode 120000 index 00000000..47dc3e3d --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1 @@ +AGENTS.md \ No newline at end of file diff --git a/Dockerfile b/Dockerfile index a9517927..972e9c86 100644 --- a/Dockerfile +++ b/Dockerfile @@ -28,14 +28,20 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ WORKDIR /app -# Install pipenv -RUN python3 -m pip install --no-cache-dir --break-system-packages pipenv +# Install uv +COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv -# Copy Pipfile and Pipfile.lock -COPY Pipfile Pipfile.lock ./ +# Copy pyproject.toml, uv.lock, and README.md (needed by hatchling during install) +COPY pyproject.toml uv.lock* README.md ./ -# Install Python dependencies from Pipfile -RUN PIP_BREAK_SYSTEM_PACKAGES=1 pipenv sync --system +# Install packages into system Python (no virtualenv in container) +ENV UV_SYSTEM_PYTHON=1 + +# Ensure venv binaries are on PATH (uv sync always creates .venv) +ENV PATH="/app/.venv/bin:$PATH" + +# Install Python dependencies only (project itself installed after COPY) +RUN uv sync --frozen --no-dev --no-install-project # Install Node.js (Node 22) so we can build the frontend inside the image. # Use NodeSource setup script to get a recent Node version on Debian-based images. @@ -69,6 +75,9 @@ RUN npm --prefix ./app run build # Copy application code COPY . . +# Install the project package now that source code is available +RUN uv sync --frozen --no-dev + # Copy and make start.sh executable COPY start.sh /start.sh RUN chmod +x /start.sh diff --git a/Makefile b/Makefile index 4ebeda8b..54b5ac9a 100644 --- a/Makefile +++ b/Makefile @@ -7,13 +7,13 @@ help: ## Show this help message @awk 'BEGIN {FS = ":.*?## "} /^[a-zA-Z_-]+:.*?## / {printf " %-15s %s\n", $$1, $$2}' $(MAKEFILE_LIST) install: ## Install dependencies - pipenv sync --dev - npm install --prefix ./app + uv sync + npm ci --prefix ./app setup-dev: install ## Set up development environment - pipenv run playwright install chromium - pipenv run playwright install-deps + uv run playwright install chromium + uv run playwright install-deps @echo "Development environment setup complete!" @echo "Don't forget to copy .env.example to .env and configure your settings" @@ -26,23 +26,23 @@ build-prod: test: build-dev test-unit test-e2e ## Run all tests test-unit: ## Run unit tests only - pipenv run python -m pytest tests/ -k "not e2e" --verbose + uv run python -m pytest tests/ -k "not e2e" --verbose test-e2e: build-dev ## Run E2E tests headless - pipenv run python -m pytest tests/e2e/ --browser chromium --video=on --screenshot=on + uv run python -m pytest tests/e2e/ --browser chromium --video=on --screenshot=on test-e2e-headed: build-dev ## Run E2E tests with browser visible - pipenv run python -m pytest tests/e2e/ --browser chromium --headed + uv run python -m pytest tests/e2e/ --browser chromium --headed test-e2e-debug: build-dev ## Run E2E tests with debugging enabled - pipenv run python -m pytest tests/e2e/ --browser chromium --slowmo=1000 + uv run python -m pytest tests/e2e/ --browser chromium --slowmo=1000 lint: ## Run linting (backend + frontend) @echo "Running backend lint (pylint)" - pipenv run pylint $(shell git ls-files '*.py') || true + uv run python -m pylint $(shell git ls-files '*.py') @echo "Running frontend lint (eslint)" make lint-frontend @@ -61,10 +61,10 @@ clean: ## Clean up test artifacts find . -name "*.pyo" -delete run-dev: build-dev ## Run development server - pipenv run uvicorn api.index:app --host $${HOST:-127.0.0.1} --port $${PORT:-5000} --reload + uv run uvicorn api.index:app --host $${HOST:-127.0.0.1} --port $${PORT:-5000} --reload run-prod: build-prod ## Run production server - pipenv run uvicorn api.index:app --host $${HOST:-0.0.0.0} --port $${PORT:-5000} + uv run uvicorn api.index:app --host $${HOST:-0.0.0.0} --port $${PORT:-5000} docker-falkordb: ## Start FalkorDB in Docker for testing docker run -d --name falkordb-test -p 6379:6379 falkordb/falkordb:latest diff --git a/Pipfile b/Pipfile deleted file mode 100644 index c1c7fa77..00000000 --- a/Pipfile +++ /dev/null @@ -1,30 +0,0 @@ -[[source]] -url = "https://pypi.org/simple" -verify_ssl = true -name = "pypi" - -[packages] -fastapi = "~=0.135.0" -uvicorn = "~=0.41.0" -litellm = "~=1.82.0" -falkordb = "~=1.6.0" -psycopg2-binary = "~=2.9.11" -pymysql = "~=1.1.0" -authlib = "~=1.6.4" -itsdangerous = "~=2.2.0" 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You can use `OPENAI_API_KEY`, `GEMINI_API_KEY`, `ANTHROPIC_API_KEY`, or `AZURE_API_KEY`. See the [AI/LLM configuration](#aillm-configuration) section for details. > For a full list of configuration options, consult `.env.example`. @@ -231,6 +231,7 @@ with requests.post(url, headers=headers, json={"chat": ["Count orders last week" continue obj = json.loads(part) print('STREAM:', obj) +``` Notes & tips - Graph IDs are namespaced per-user. When calling the API directly use the plain graph id (the server will namespace by the authenticated user). For uploaded files the `database` field determines the saved graph id. @@ -245,7 +246,7 @@ Follow these steps to run and develop QueryWeaver from source. ### Prerequisites - Python 3.12+ -- pipenv +- uv (Python package manager) - A FalkorDB instance (local or remote) - Node.js and npm (for the React frontend) @@ -263,11 +264,11 @@ make install make run-dev ``` -If you prefer to set up manually or need a custom environment, use Pipenv: +If you prefer to set up manually or need a custom environment, use uv: ```bash # Install Python (backend) and frontend dependencies -pipenv sync --dev +uv sync # Create a local environment file cp .env.example .env @@ -277,7 +278,7 @@ cp .env.example .env ### Run the app locally ```bash -pipenv run uvicorn api.index:app --host 0.0.0.0 --port 5000 --reload +uv run uvicorn api.index:app --host 0.0.0.0 --port 5000 --reload ``` The server will be available at http://localhost:5000 @@ -326,49 +327,63 @@ APP_ENV=development ### AI/LLM configuration -QueryWeaver uses AI models for Text2SQL conversion and supports both Azure OpenAI and OpenAI directly. +QueryWeaver supports multiple AI providers. Set one API key and QueryWeaver auto-detects which provider to use. + +**Priority order:** Ollama > OpenAI > Gemini > Anthropic > Cohere > Azure (default) -#### Default: Azure OpenAI +| Provider | API Key | Default Models | +|----------|---------|----------------| +| Ollama | `OLLAMA_MODEL` | `ollama/`, `ollama/nomic-embed-text` | +| OpenAI | `OPENAI_API_KEY` | `openai/gpt-4.1`, `openai/text-embedding-ada-002` | +| Google Gemini | `GEMINI_API_KEY` | `gemini/gemini-3-pro-preview`, `gemini/gemini-embedding-001` | +| Anthropic | `ANTHROPIC_API_KEY` | `anthropic/claude-sonnet-4-5-20250929`, `voyage/voyage-3`* | +| Cohere | `COHERE_API_KEY` | `cohere/command-a-03-2025`, `cohere/embed-v4.0` | +| Azure OpenAI | `AZURE_API_KEY` | `azure/gpt-4.1`, `azure/text-embedding-ada-002` | -By default, QueryWeaver is configured to use Azure OpenAI. You need to set all three Azure credentials: +\* Anthropic has no native embeddings. You must set `VOYAGE_API_KEY` or `EMBEDDING_MODEL` for embeddings, otherwise startup will fail with an error. + +**Optional: Override default models** ```bash -AZURE_API_KEY=your_azure_api_key -AZURE_API_BASE=https://your-resource.openai.azure.com/ -AZURE_API_VERSION=2024-12-01-preview +COMPLETION_MODEL=gemini/gemini-3-pro-preview +EMBEDDING_MODEL=gemini/gemini-embedding-001 ``` -#### Alternative: OpenAI directly +Both must match your API key's provider. -To use OpenAI directly instead of Azure, simply set the `OPENAI_API_KEY` environment variable: +#### Docker examples with AI configuration +Using OpenAI: ```bash -OPENAI_API_KEY=your_openai_api_key +docker run -p 5000:5000 -it \ + -e FASTAPI_SECRET_KEY=your_secret_key \ + -e OPENAI_API_KEY=your_openai_api_key \ + falkordb/queryweaver ``` -When `OPENAI_API_KEY` is provided, QueryWeaver automatically switches to use OpenAI's models: -- Embedding model: `openai/text-embedding-ada-002` -- Completion model: `openai/gpt-4.1` - -This configuration is handled automatically in `api/config.py` - you only need to provide the appropriate API key. - -#### Docker examples with AI configuration +Using Google Gemini: +```bash +docker run -p 5000:5000 -it \ + -e FASTAPI_SECRET_KEY=your_secret_key \ + -e GEMINI_API_KEY=your_gemini_api_key \ + falkordb/queryweaver +``` -Using Azure OpenAI: +Using Anthropic: ```bash docker run -p 5000:5000 -it \ -e FASTAPI_SECRET_KEY=your_secret_key \ - -e AZURE_API_KEY=your_azure_api_key \ - -e AZURE_API_BASE=https://your-resource.openai.azure.com/ \ - -e AZURE_API_VERSION=2024-12-01-preview \ + -e ANTHROPIC_API_KEY=your_anthropic_api_key \ falkordb/queryweaver ``` -Using OpenAI directly: +Using Azure OpenAI: ```bash docker run -p 5000:5000 -it \ -e FASTAPI_SECRET_KEY=your_secret_key \ - -e OPENAI_API_KEY=your_openai_api_key \ + -e AZURE_API_KEY=your_azure_api_key \ + -e AZURE_API_BASE=https://your-resource.openai.azure.com/ \ + -e AZURE_API_VERSION=2024-12-01-preview \ falkordb/queryweaver ``` @@ -378,9 +393,9 @@ docker run -p 5000:5000 -it \ ### Prerequisites -- Install dev dependencies: `pipenv sync --dev` +- Install dev dependencies: `uv sync` - Start FalkorDB (see `make docker-falkordb`) -- Install Playwright browsers: `pipenv run playwright install` +- Install Playwright browsers: `uv run playwright install` ### Quick commands @@ -412,7 +427,7 @@ make test-e2e-headed ### Test types -- Unit tests: focus on individual modules and utilities. Run with `make test-unit` or `pipenv run pytest tests/ -k "not e2e"`. +- Unit tests: focus on individual modules and utilities. Run with `make test-unit` or `uv run python -m pytest tests/ -k "not e2e"`. - End-to-end (E2E) tests: run via Playwright and exercise UI flows, OAuth, file uploads, schema processing, chat queries, and API endpoints. Use `make test-e2e`. See `tests/e2e/README.md` for full E2E test instructions. @@ -424,7 +439,7 @@ GitHub Actions run unit and E2E tests on pushes and pull requests. Failures capt ## Troubleshooting - FalkorDB connection issues: start the DB helper `make docker-falkordb` or check network/host settings. -- Playwright/browser failures: install browsers with `pipenv run playwright install` and ensure system deps are present. +- Playwright/browser failures: install browsers with `uv run playwright install` and ensure system deps are present. - Missing environment variables: copy `.env.example` and fill required values. - **OAuth "mismatching_state: CSRF Warning!" errors**: Set `APP_ENV=production` (or `staging`) in your environment for HTTPS deployments, or `APP_ENV=development` for HTTP development environments. This ensures session cookies are configured correctly for your deployment type. diff --git a/api/agents/analysis_agent.py b/api/agents/analysis_agent.py index 2eeff49a..050f42c1 100644 --- a/api/agents/analysis_agent.py +++ b/api/agents/analysis_agent.py @@ -1,9 +1,7 @@ """Analysis agent for analyzing user queries and generating database analysis.""" from typing import List -from litellm import completion -from api.config import Config -from .utils import BaseAgent, parse_response +from .utils import BaseAgent, parse_response, run_completion class AnalysisAgent(BaseAgent): @@ -38,13 +36,10 @@ def get_analysis( # pylint: disable=too-many-arguments, too-many-positional-arg instructions, memory_context, database_type, user_rules_spec ) self.messages.append({"role": "user", "content": prompt}) - completion_result = completion( - model=Config.COMPLETION_MODEL, - messages=self.messages, - temperature=0, - ) - response = completion_result.choices[0].message.content + response = run_completion( + self.messages, self.custom_model, self.custom_api_key, temperature=0 + ) analysis = parse_response(response) if isinstance(analysis["ambiguities"], list): analysis["ambiguities"] = [ diff --git a/api/agents/follow_up_agent.py b/api/agents/follow_up_agent.py index 3798f3b5..b39661ec 100644 --- a/api/agents/follow_up_agent.py +++ b/api/agents/follow_up_agent.py @@ -1,8 +1,6 @@ """Follow-up agent for generating helpful questions when queries fail or are off-topic.""" -from litellm import completion -from api.config import Config -from .utils import BaseAgent +from .utils import BaseAgent, run_completion FOLLOW_UP_GENERATION_PROMPT = """ @@ -70,14 +68,11 @@ def generate_follow_up_question( ) try: - completion_result = completion( - model=Config.COMPLETION_MODEL, - messages=[{"role": "user", "content": prompt}], - temperature=0.9 + response = run_completion( + [{"role": "user", "content": prompt}], + self.custom_model, self.custom_api_key, temperature=0.9 ) - - response = completion_result.choices[0].message.content.strip() - return response + return response.strip() except Exception: # pylint: disable=broad-exception-caught # Fallback response if LLM call fails diff --git a/api/agents/relevancy_agent.py b/api/agents/relevancy_agent.py index 9317ec60..7db4f987 100644 --- a/api/agents/relevancy_agent.py +++ b/api/agents/relevancy_agent.py @@ -1,9 +1,7 @@ """Relevancy agent for determining relevancy of queries to database schema.""" import json -from litellm import completion -from api.config import Config -from .utils import BaseAgent, parse_response +from .utils import BaseAgent, parse_response, run_completion RELEVANCY_PROMPT = """ @@ -82,12 +80,9 @@ async def get_answer(self, user_question: str, database_desc: dict) -> dict: ), } ) - completion_result = completion( - model=Config.COMPLETION_MODEL, - messages=self.messages, - temperature=0, - ) - answer = completion_result.choices[0].message.content + answer = run_completion( + self.messages, self.custom_model, self.custom_api_key, temperature=0 + ) self.messages.append({"role": "assistant", "content": answer}) return parse_response(answer) diff --git a/api/agents/response_formatter_agent.py b/api/agents/response_formatter_agent.py index 198450b0..9e9dfe87 100644 --- a/api/agents/response_formatter_agent.py +++ b/api/agents/response_formatter_agent.py @@ -1,8 +1,7 @@ """Response formatter agent for generating user-readable responses from SQL query results.""" from typing import List, Dict -from litellm import completion -from api.config import Config +from .utils import run_completion RESPONSE_FORMATTER_PROMPT = """ @@ -43,8 +42,20 @@ class ResponseFormatterAgent: # pylint: disable=too-few-public-methods """Agent for generating user-readable responses from SQL query results.""" - def __init__(self): - """Initialize the response formatter agent.""" + def __init__(self, queries_history: List[str] = None, result_history: List[str] = None, + custom_api_key: str = None, custom_model: str = None): + """Initialize the response formatter agent. + + Args: + queries_history: List of previous user queries (for context) + result_history: List of previous results (for context) + custom_api_key: Optional custom API key for LLM calls + custom_model: Optional custom model name for LLM calls + """ + self.queries_history = queries_history or [] + self.result_history = result_history or [] + self.custom_api_key = custom_api_key + self.custom_model = custom_model def format_response(self, user_query: str, sql_query: str, query_results: List[Dict], db_description: str = "") -> str: @@ -64,14 +75,10 @@ def format_response(self, user_query: str, sql_query: str, messages = [{"role": "user", "content": prompt}] - completion_result = completion( - model=Config.COMPLETION_MODEL, - messages=messages, - temperature=0.3, # Slightly higher temperature for more natural responses - top_p=1, + response = run_completion( + messages, self.custom_model, self.custom_api_key, + temperature=0.3 # Slightly higher temperature for more natural responses ) - - response = completion_result.choices[0].message.content return response.strip() def _build_response_prompt(self, user_query: str, sql_query: str, diff --git a/api/agents/utils.py b/api/agents/utils.py index ceafff23..bc28c99f 100644 --- a/api/agents/utils.py +++ b/api/agents/utils.py @@ -1,13 +1,37 @@ """Utility functions for agents.""" import json -from typing import Any, Dict +from typing import Any, Dict, List + +from litellm import completion +from api.config import Config + + +def run_completion(messages: List[Dict[str, str]], custom_model: str = None, + custom_api_key: str = None, **kwargs) -> str: + """Run an LLM completion with optional custom model/key overrides. + + Returns the content string from the first choice. + """ + completion_args = { + "model": custom_model if custom_model else Config.COMPLETION_MODEL, + "messages": messages, + "top_p": 1, + **kwargs, + } + + if custom_api_key: + completion_args["api_key"] = custom_api_key + + result = completion(**completion_args) + return result.choices[0].message.content class BaseAgent: # pylint: disable=too-few-public-methods """Base class for agents.""" - def __init__(self, queries_history: list, result_history: list): + def __init__(self, queries_history: list, result_history: list, + custom_api_key: str = None, custom_model: str = None): """Initialize the agent with query and result history.""" if result_history is None: self.messages = [] @@ -17,6 +41,9 @@ def __init__(self, queries_history: list, result_history: list): self.messages.append({"role": "user", "content": query}) self.messages.append({"role": "assistant", "content": result}) + self.custom_api_key = custom_api_key + self.custom_model = custom_model + def parse_response(response: str) -> Dict[str, Any]: """ diff --git a/api/app_factory.py b/api/app_factory.py index 7c93cce9..3b95b5bf 100644 --- a/api/app_factory.py +++ b/api/app_factory.py @@ -5,7 +5,6 @@ import os import secrets -from dotenv import load_dotenv from fastapi import FastAPI, Request, HTTPException from fastapi.responses import RedirectResponse, JSONResponse, FileResponse from fastapi.staticfiles import StaticFiles @@ -22,9 +21,8 @@ from api.routes.graphs import graphs_router from api.routes.database import database_router from api.routes.tokens import tokens_router +from api.routes.settings import settings_router -# Load environment variables from .env file -load_dotenv() logging.basicConfig( level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s" ) @@ -60,14 +58,17 @@ def _is_secure_request(request: Request) -> bool: """Determine if the request is over HTTPS.""" forwarded_proto = request.headers.get("x-forwarded-proto") if forwarded_proto: - return forwarded_proto == "https" + # Normalize: proxies may send comma-separated or mixed-case values + first_proto = forwarded_proto.split(",")[0].strip().lower() + return first_proto == "https" return request.url.scheme == "https" class CSRFMiddleware(BaseHTTPMiddleware): # pylint: disable=too-few-public-methods """Double Submit Cookie CSRF protection. - Sets a csrf_token cookie (readable by JS) on every response. + Ensures a csrf_token cookie (readable by JS) exists, setting it + on the response if the incoming request does not already carry one. State-changing requests must echo the cookie value back via the X-CSRF-Token header. Bearer-token authenticated requests and auth/login endpoints are exempt. @@ -129,10 +130,10 @@ def _ensure_csrf_cookie(self, request: Request, response): ) -def create_app(): +def create_app(): # pylint: disable=too-many-statements """Create and configure the FastAPI application.""" - # Create the FastAPI app instance just to set the o routes + # Create the FastAPI app instance with original routes # Will be merged with MCP app later if MCP is enabled app = FastAPI( title="QueryWeaver" @@ -143,6 +144,7 @@ def create_app(): app.include_router(graphs_router, prefix="/graphs") app.include_router(database_router) app.include_router(tokens_router, prefix="/tokens") + app.include_router(settings_router, prefix="/settings") diff --git a/api/auth/user_management.py b/api/auth/user_management.py index c7a82196..3b5cd00f 100644 --- a/api/auth/user_management.py +++ b/api/auth/user_management.py @@ -235,11 +235,13 @@ async def validate_user(request: Request) -> Tuple[Optional[Dict[str, Any]], boo try: api_token = get_token(request) - if api_token: - db_info = await _get_user_info(api_token) + if not api_token: + return None, False - if db_info: - return db_info, True + db_info = await _get_user_info(api_token) + + if db_info: + return db_info, True return None, False diff --git a/api/config.py b/api/config.py index 7063f067..b029970c 100644 --- a/api/config.py +++ b/api/config.py @@ -7,8 +7,13 @@ import logging import dataclasses from typing import Union + +from dotenv import load_dotenv from litellm import embedding +# Ensure .env is loaded before Config reads os.getenv() at class definition time +load_dotenv() + # Configure litellm logging to prevent sensitive data leakage def configure_litellm_logging(): """Configure litellm to suppress completion logs.""" @@ -58,19 +63,70 @@ def get_vector_size(self) -> int: return size +def _with_prefix(model: str, provider: str) -> str: + """Ensure a model string has exactly one provider prefix.""" + prefix = f"{provider}/" + return prefix + model.removeprefix(prefix) + + +SUPPORTED_VENDORS = ("openai", "anthropic", "gemini", "azure", "ollama", "cohere") + + @dataclasses.dataclass class Config: """ Configuration class for the text2sql module. """ - AZURE_FLAG = True - if not os.getenv("OPENAI_API_KEY"): - EMBEDDING_MODEL_NAME = "azure/text-embedding-ada-002" - COMPLETION_MODEL = "azure/gpt-4.1" - else: + + # User-provided overrides via env vars + _user_completion = os.getenv("COMPLETION_MODEL", "") + _user_embedding = os.getenv("EMBEDDING_MODEL", "") + + # Determine the provider and models based on available API keys + # Priority: Ollama > OpenAI > Gemini > Anthropic > Cohere > Azure (default) + if os.getenv("OLLAMA_MODEL"): + LLM_PROVIDER = "ollama" + AZURE_FLAG = False + COMPLETION_MODEL = _user_completion or _with_prefix( + os.getenv("OLLAMA_MODEL"), "ollama") + EMBEDDING_MODEL_NAME = _user_embedding or _with_prefix( + os.getenv("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text"), "ollama") + elif os.getenv("OPENAI_API_KEY"): + LLM_PROVIDER = "openai" + AZURE_FLAG = False + COMPLETION_MODEL = _user_completion or "openai/gpt-4.1" + EMBEDDING_MODEL_NAME = _user_embedding or "openai/text-embedding-ada-002" + elif os.getenv("GEMINI_API_KEY"): + LLM_PROVIDER = "gemini" AZURE_FLAG = False - EMBEDDING_MODEL_NAME = "openai/text-embedding-ada-002" - COMPLETION_MODEL = "openai/gpt-4.1" + COMPLETION_MODEL = _user_completion or "gemini/gemini-3-pro-preview" + EMBEDDING_MODEL_NAME = _user_embedding or "gemini/gemini-embedding-001" + elif os.getenv("ANTHROPIC_API_KEY"): + LLM_PROVIDER = "anthropic" + AZURE_FLAG = False + COMPLETION_MODEL = _user_completion or "anthropic/claude-sonnet-4-5-20250929" + if _user_embedding: + EMBEDDING_MODEL_NAME = _user_embedding + elif os.getenv("VOYAGE_API_KEY"): + EMBEDDING_MODEL_NAME = "voyage/voyage-3" + else: + raise ValueError( + "ANTHROPIC_API_KEY is set, but Anthropic has no native embeddings. " + "Set EMBEDDING_MODEL or VOYAGE_API_KEY for embeddings." + ) + elif os.getenv("COHERE_API_KEY"): + LLM_PROVIDER = "cohere" + AZURE_FLAG = False + COMPLETION_MODEL = _user_completion or _with_prefix( + os.getenv("COHERE_MODEL", "command-a-03-2025"), "cohere") + EMBEDDING_MODEL_NAME = _user_embedding or _with_prefix( + os.getenv("COHERE_EMBEDDING_MODEL", "embed-v4.0"), "cohere") + else: + # Default to Azure + LLM_PROVIDER = "azure" + AZURE_FLAG = True + COMPLETION_MODEL = _user_completion or "azure/gpt-4.1" + EMBEDDING_MODEL_NAME = _user_embedding or "azure/text-embedding-ada-002" DB_MAX_DISTINCT: int = 100 # pylint: disable=invalid-name DB_UNIQUENESS_THRESHOLD: float = 0.5 # pylint: disable=invalid-name diff --git a/api/core/schema_loader.py b/api/core/schema_loader.py index bb4dcedb..b1568514 100644 --- a/api/core/schema_loader.py +++ b/api/core/schema_loader.py @@ -13,6 +13,7 @@ from api.loaders.base_loader import BaseLoader from api.loaders.postgres_loader import PostgresLoader from api.loaders.mysql_loader import MySQLLoader +from api.loaders.snowflake_loader import SnowflakeLoader # Use the same delimiter as in the JavaScript frontend for streaming chunks MESSAGE_DELIMITER = "|||FALKORDB_MESSAGE_BOUNDARY|||" @@ -44,6 +45,9 @@ def _step_detect_db_type(steps_counter: int, url: str) -> tuple[type[BaseLoader] elif url.startswith("mysql://"): db_type = "mysql" loader = MySQLLoader + elif url.startswith("snowflake://"): + db_type = "snowflake" + loader = SnowflakeLoader else: raise InvalidArgumentError("Invalid database URL format") diff --git a/api/core/text2sql.py b/api/core/text2sql.py index efdca397..65bc0b4f 100644 --- a/api/core/text2sql.py +++ b/api/core/text2sql.py @@ -15,10 +15,12 @@ from api.agents import AnalysisAgent, RelevancyAgent, ResponseFormatterAgent, FollowUpAgent from api.agents.healer_agent import HealerAgent from api.config import Config +from api.config import SUPPORTED_VENDORS from api.extensions import db from api.graph import find, get_db_description, get_user_rules from api.loaders.postgres_loader import PostgresLoader from api.loaders.mysql_loader import MySQLLoader +from api.loaders.snowflake_loader import SnowflakeLoader from api.memory.graphiti_tool import MemoryTool from api.sql_utils import SQLIdentifierQuoter, DatabaseSpecificQuoter @@ -45,6 +47,8 @@ class ChatRequest(BaseModel): chat: list[str] result: list[str] | None = None instructions: str | None = None + custom_api_key: str | None = None + custom_model: str | None = None use_user_rules: bool = True # If True, fetch rules from database; if False, don't use rules use_memory: bool = True @@ -58,6 +62,8 @@ class ConfirmRequest(BaseModel): sql_query: str confirmation: str = "" chat: list = [] + custom_api_key: str | None = None + custom_model: str | None = None def get_database_type_and_loader(db_url: str): @@ -79,6 +85,8 @@ def get_database_type_and_loader(db_url: str): return 'postgresql', PostgresLoader if db_url_lower.startswith('mysql://'): return 'mysql', MySQLLoader + if db_url_lower.startswith('snowflake://'): + return 'snowflake', SnowflakeLoader # Default to PostgresLoader for backward compatibility return 'postgresql', PostgresLoader @@ -248,9 +256,25 @@ async def generate(): # pylint: disable=too-many-locals,too-many-branches,too-m logging.info("Starting query processing pipeline for query: %s", sanitize_query(queries_history[-1])) # nosemgrep - agent_rel = RelevancyAgent(queries_history, result_history) - agent_an = AnalysisAgent(queries_history, result_history) - follow_up_agent = FollowUpAgent(queries_history, result_history) + # Extract custom API key and model from chat_data + custom_api_key = chat_data.custom_api_key + custom_model = chat_data.custom_model + + # Validate custom model format (vendor/model) + if custom_model: + parts = custom_model.split("/", 1) + if len(parts) != 2 or not parts[0] or not parts[1]: + raise InvalidArgumentError( + "Invalid model format. Expected 'vendor/model' (e.g. 'openai/gpt-4.1')" + ) + if parts[0] not in SUPPORTED_VENDORS: + raise InvalidArgumentError( + f"Unsupported vendor '{parts[0]}'. Supported: {', '.join(SUPPORTED_VENDORS)}" + ) + + agent_rel = RelevancyAgent(queries_history, result_history, custom_api_key, custom_model) + agent_an = AnalysisAgent(queries_history, result_history, custom_api_key, custom_model) + follow_up_agent = FollowUpAgent(queries_history, result_history, custom_api_key, custom_model) step = {"type": "reasoning_step", "final_response": False, @@ -576,7 +600,9 @@ def execute_sql(sql: str): "message": f"Step {step_num}: Generating user-friendly response"} yield json.dumps(step) + MESSAGE_DELIMITER - response_agent = ResponseFormatterAgent() + response_agent = ResponseFormatterAgent( + queries_history, result_history, custom_api_key, custom_model + ) user_readable_response = response_agent.format_response( user_query=queries_history[-1], sql_query=answer_an["sql_query"], @@ -715,6 +741,8 @@ async def execute_destructive_operation( # pylint: disable=too-many-statements sql_query = confirm_data.sql_query if hasattr(confirm_data, 'sql_query') else "" queries_history = confirm_data.chat if hasattr(confirm_data, 'chat') else [] + custom_api_key = confirm_data.custom_api_key + custom_model = confirm_data.custom_model if not sql_query: raise InvalidArgumentError("No SQL query provided") @@ -723,6 +751,7 @@ async def execute_destructive_operation( # pylint: disable=too-many-statements async def generate_confirmation(): # pylint: disable=too-many-locals,too-many-statements # Create memory tool for saving query results memory_tool = await MemoryTool.create(user_id, graph_id) + result_history = [] # Initialize result_history for this context if confirmation == "CONFIRM": try: @@ -823,7 +852,9 @@ async def generate_confirmation(): # pylint: disable=too-many-locals,too-many-s "message": f"Step {step_num}: Generating user-friendly response"} yield json.dumps(step) + MESSAGE_DELIMITER - response_agent = ResponseFormatterAgent() + response_agent = ResponseFormatterAgent( + queries_history, result_history, custom_api_key, custom_model + ) user_readable_response = response_agent.format_response( user_query=queries_history[-1] if queries_history else "Destructive operation", sql_query=sql_query, diff --git a/api/index.py b/api/index.py index 829e3e0a..1bb7d061 100644 --- a/api/index.py +++ b/api/index.py @@ -1,6 +1,10 @@ """Main entry point for the text2sql API.""" -from api.app_factory import create_app +# Load .env before any app imports that read os.getenv at module level +from dotenv import load_dotenv +load_dotenv() + +from api.app_factory import create_app # pylint: disable=wrong-import-position app = create_app() diff --git a/api/loaders/postgres_loader.py b/api/loaders/postgres_loader.py index be0be497..9d58f4e2 100644 --- a/api/loaders/postgres_loader.py +++ b/api/loaders/postgres_loader.py @@ -5,6 +5,7 @@ import decimal import logging from typing import AsyncGenerator, Dict, Any, List, Tuple +from urllib.parse import urlparse, parse_qs, unquote import psycopg2 from psycopg2 import sql @@ -52,7 +53,7 @@ class PostgresLoader(BaseLoader): @staticmethod def _execute_sample_query( - cursor, table_name: str, col_name: str, sample_size: int = 3 + cursor: Any, table_name: str, col_name: str, sample_size: int = 3 ) -> List[Any]: """ Execute query to get random sample values for a column. @@ -96,6 +97,48 @@ def _serialize_value(value): return None return value + @staticmethod + def parse_schema_from_url(connection_url: str) -> str: + """ + Parse the search_path from the connection URL's options parameter. + + The options parameter follows PostgreSQL's libpq format: + postgresql://user:pass@host:port/db?options=-csearch_path%3Dschema_name + + Args: + connection_url: PostgreSQL connection URL + + Returns: + The first schema from search_path, or 'public' if not specified + """ + try: + parsed = urlparse(connection_url) + query_params = parse_qs(parsed.query) + + options = query_params.get('options', []) + if not options: + return 'public' + + options_str = unquote(options[0]) + + # Parse -c search_path=value from options + # Format can be: -csearch_path=schema or -c search_path=schema + # Match comma-separated schema tokens (supports spaces after commas). + match = re.search(r'-c\s*search_path\s*=\s*([^\s,]+(?:\s*,\s*[^\s,]+)*)', options_str, re.IGNORECASE) + if match: + search_path = match.group(1) + schemas = search_path.split(',') + for s in schemas: + s = s.strip().strip('"\'') + if s and s != '$user': + return s + return 'public' + + return 'public' + + except Exception: # pylint: disable=broad-exception-caught + return 'public' + @staticmethod async def load(prefix: str, connection_url: str) -> AsyncGenerator[tuple[bool, str], None]: """ @@ -103,16 +146,29 @@ async def load(prefix: str, connection_url: str) -> AsyncGenerator[tuple[bool, s Args: connection_url: PostgreSQL connection URL in format: - postgresql://username:password@host:port/database + postgresql://username:password@host:port/database + Optionally with schema via options parameter: + postgresql://...?options=-csearch_path%3Dschema_name Returns: Tuple[bool, str]: Success status and message """ + conn = None + cursor = None try: + # Parse schema from connection URL (defaults to 'public') + schema = PostgresLoader.parse_schema_from_url(connection_url) + # Connect to PostgreSQL database conn = psycopg2.connect(connection_url) cursor = conn.cursor() + # Set the session search_path to the parsed schema so unqualified + # table references (e.g. in sample queries) resolve correctly. + cursor.execute( + sql.SQL("SET search_path TO {}").format(sql.Identifier(schema)) + ) + # Extract database name from connection URL db_name = connection_url.split('/')[-1] if '?' in db_name: @@ -120,15 +176,17 @@ async def load(prefix: str, connection_url: str) -> AsyncGenerator[tuple[bool, s # Get all table information yield True, "Extracting table information..." - entities = PostgresLoader.extract_tables_info(cursor) + entities = PostgresLoader.extract_tables_info(cursor, schema) yield True, "Extracting relationship information..." # Get all relationship information - relationships = PostgresLoader.extract_relationships(cursor) + relationships = PostgresLoader.extract_relationships(cursor, schema) - # Close database connection + # Close database connection before graph loading cursor.close() + cursor = None conn.close() + conn = None yield True, "Loading data into graph..." # Load data into graph @@ -144,21 +202,27 @@ async def load(prefix: str, connection_url: str) -> AsyncGenerator[tuple[bool, s except Exception as e: # pylint: disable=broad-exception-caught logging.error("Error loading PostgreSQL schema: %s", e) yield False, "Failed to load PostgreSQL database schema" + finally: + if cursor is not None: + cursor.close() + if conn is not None: + conn.close() @staticmethod - def extract_tables_info(cursor) -> Dict[str, Any]: + def extract_tables_info(cursor: Any, schema: str = 'public') -> Dict[str, Any]: """ Extract table and column information from PostgreSQL database. Args: cursor: Database cursor + schema: Database schema to extract tables from (default: 'public') Returns: Dict containing table information """ entities = {} - # Get all tables in public schema + # Get all tables in the specified schema cursor.execute(""" SELECT table_name, table_comment FROM information_schema.tables t @@ -166,13 +230,14 @@ def extract_tables_info(cursor) -> Dict[str, Any]: SELECT schemaname, tablename, description as table_comment FROM pg_tables pt JOIN pg_class pc ON pc.relname = pt.tablename + JOIN pg_namespace pn ON pn.oid = pc.relnamespace AND pn.nspname = pt.schemaname JOIN pg_description pd ON pd.objoid = pc.oid AND pd.objsubid = 0 - WHERE pt.schemaname = 'public' + WHERE pt.schemaname = %s ) tc ON tc.tablename = t.table_name - WHERE t.table_schema = 'public' + WHERE t.table_schema = %s AND t.table_type = 'BASE TABLE' ORDER BY t.table_name; - """) + """, (schema, schema)) tables = cursor.fetchall() @@ -180,10 +245,10 @@ def extract_tables_info(cursor) -> Dict[str, Any]: table_name = table_name.strip() # Get column information for this table - columns_info = PostgresLoader.extract_columns_info(cursor, table_name) + columns_info = PostgresLoader.extract_columns_info(cursor, table_name, schema) # Get foreign keys for this table - foreign_keys = PostgresLoader.extract_foreign_keys(cursor, table_name) + foreign_keys = PostgresLoader.extract_foreign_keys(cursor, table_name, schema) # Generate table description table_description = table_comment if table_comment else f"Table: {table_name}" @@ -201,13 +266,14 @@ def extract_tables_info(cursor) -> Dict[str, Any]: return entities @staticmethod - def extract_columns_info(cursor, table_name: str) -> Dict[str, Any]: + def extract_columns_info(cursor: Any, table_name: str, schema: str = 'public') -> Dict[str, Any]: """ Extract column information for a specific table. Args: cursor: Database cursor table_name: Name of the table + schema: Database schema (default: 'public') Returns: Dict containing column information @@ -230,7 +296,9 @@ def extract_columns_info(cursor, table_name: str) -> Dict[str, Any]: FROM information_schema.table_constraints tc JOIN information_schema.key_column_usage ku ON tc.constraint_name = ku.constraint_name + AND tc.constraint_schema = ku.constraint_schema WHERE tc.table_name = %s + AND tc.table_schema = %s AND tc.constraint_type = 'PRIMARY KEY' ) pk ON pk.column_name = c.column_name LEFT JOIN ( @@ -238,16 +306,19 @@ def extract_columns_info(cursor, table_name: str) -> Dict[str, Any]: FROM information_schema.table_constraints tc JOIN information_schema.key_column_usage ku ON tc.constraint_name = ku.constraint_name + AND tc.constraint_schema = ku.constraint_schema WHERE tc.table_name = %s + AND tc.table_schema = %s AND tc.constraint_type = 'FOREIGN KEY' ) fk ON fk.column_name = c.column_name - LEFT JOIN pg_class pc ON pc.relname = c.table_name + LEFT JOIN pg_namespace pn ON pn.nspname = c.table_schema + LEFT JOIN pg_class pc ON pc.relname = c.table_name AND pc.relnamespace = pn.oid LEFT JOIN pg_attribute pa ON pa.attrelid = pc.oid AND pa.attname = c.column_name LEFT JOIN pg_description pgd ON pgd.objoid = pc.oid AND pgd.objsubid = pa.attnum WHERE c.table_name = %s - AND c.table_schema = 'public' + AND c.table_schema = %s ORDER BY c.ordinal_position; - """, (table_name, table_name, table_name)) + """, (table_name, schema, table_name, schema, table_name, schema)) columns = cursor.fetchall() columns_info = {} @@ -289,13 +360,14 @@ def extract_columns_info(cursor, table_name: str) -> Dict[str, Any]: return columns_info @staticmethod - def extract_foreign_keys(cursor, table_name: str) -> List[Dict[str, str]]: + def extract_foreign_keys(cursor: Any, table_name: str, schema: str = 'public') -> List[Dict[str, str]]: """ Extract foreign key information for a specific table. Args: cursor: Database cursor table_name: Name of the table + schema: Database schema (default: 'public') Returns: List of foreign key dictionaries @@ -315,8 +387,8 @@ def extract_foreign_keys(cursor, table_name: str) -> List[Dict[str, str]]: AND ccu.table_schema = tc.table_schema WHERE tc.constraint_type = 'FOREIGN KEY' AND tc.table_name = %s - AND tc.table_schema = 'public'; - """, (table_name,)) + AND tc.table_schema = %s; + """, (table_name, schema)) foreign_keys = [] for constraint_name, column_name, foreign_table, foreign_column in cursor.fetchall(): @@ -330,12 +402,13 @@ def extract_foreign_keys(cursor, table_name: str) -> List[Dict[str, str]]: return foreign_keys @staticmethod - def extract_relationships(cursor) -> Dict[str, List[Dict[str, str]]]: + def extract_relationships(cursor: Any, schema: str = 'public') -> Dict[str, List[Dict[str, str]]]: """ Extract all relationship information from the database. Args: cursor: Database cursor + schema: Database schema (default: 'public') Returns: Dict containing relationship information @@ -355,9 +428,9 @@ def extract_relationships(cursor) -> Dict[str, List[Dict[str, str]]]: ON ccu.constraint_name = tc.constraint_name AND ccu.table_schema = tc.table_schema WHERE tc.constraint_type = 'FOREIGN KEY' - AND tc.table_schema = 'public' + AND tc.table_schema = %s ORDER BY tc.table_name, tc.constraint_name; - """) + """, (schema,)) relationships = {} for (table_name, constraint_name, column_name, diff --git a/api/loaders/snowflake_loader.py b/api/loaders/snowflake_loader.py new file mode 100644 index 00000000..7685daa9 --- /dev/null +++ b/api/loaders/snowflake_loader.py @@ -0,0 +1,711 @@ +"""Snowflake loader for loading database schemas into FalkorDB graphs.""" + +import base64 +import datetime +import decimal +import logging +import re +from typing import AsyncGenerator, Dict, Any, List, Tuple +from urllib.parse import urlparse, parse_qs + +from cryptography.hazmat.backends import default_backend +from cryptography.hazmat.primitives import serialization + +import tqdm +import snowflake.connector +from snowflake.connector import DictCursor + +from api.loaders.base_loader import BaseLoader +from api.loaders.graph_loader import load_to_graph + + +class SnowflakeQueryError(Exception): + """Exception raised for Snowflake query execution errors.""" + + +class SnowflakeConnectionError(Exception): + """Exception raised for Snowflake connection errors.""" + + +logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") + + +class SnowflakeLoader(BaseLoader): + """ + Loader for Snowflake databases that connects and extracts schema information. + """ + + # DDL operations that modify database schema # pylint: disable=duplicate-code + SCHEMA_MODIFYING_OPERATIONS = { + 'CREATE', 'ALTER', 'DROP', 'RENAME', 'TRUNCATE' + } + + # More specific patterns for schema-affecting operations + SCHEMA_PATTERNS = [ # pylint: disable=duplicate-code + r'^\s*CREATE\s+TABLE', + r'^\s*CREATE\s+INDEX', + r'^\s*CREATE\s+UNIQUE\s+INDEX', + r'^\s*ALTER\s+TABLE', + r'^\s*DROP\s+TABLE', + r'^\s*DROP\s+INDEX', + r'^\s*RENAME\s+TABLE', + r'^\s*TRUNCATE\s+TABLE', + r'^\s*CREATE\s+VIEW', + r'^\s*DROP\s+VIEW', + r'^\s*CREATE\s+DATABASE', + r'^\s*DROP\s+DATABASE', + r'^\s*CREATE\s+SCHEMA', + r'^\s*DROP\s+SCHEMA', + ] + + @staticmethod + def _validate_identifier(identifier: str, identifier_type: str = "identifier") -> None: + """ + Validate that an identifier (table, column, database, schema name) is safe. + + Args: + identifier: The identifier to validate + identifier_type: Type of identifier for error messages + + Raises: + ValueError: If identifier contains invalid characters + """ + # Allow alphanumeric, underscore, dollar sign, and limit to reasonable length + # Snowflake identifiers can contain these characters when quoted + if not re.match(r'^[A-Za-z0-9_$]+$', identifier): + raise ValueError( + f"Invalid {identifier_type}: {identifier!r}. " + "Only alphanumeric characters, underscore, and dollar sign are allowed." + ) + if len(identifier) > 255: + raise ValueError(f"Invalid {identifier_type}: exceeds maximum length of 255") + + @staticmethod + def _quote_identifier(identifier: str) -> str: + """ + Safely quote a Snowflake identifier by escaping double quotes. + + Args: + identifier: The identifier to quote + + Returns: + Quoted identifier safe for SQL interpolation + """ + # Escape any existing double quotes by doubling them + escaped = identifier.replace('"', '""') + return f'"{escaped}"' + + @staticmethod + def _execute_sample_query( + cursor, table_name: str, col_name: str, sample_size: int = 3 + ) -> List[Any]: + """ + Execute query to get random sample values for a column. + Snowflake implementation using SAMPLE for random sampling. + """ + # Validate identifiers to prevent SQL injection + SnowflakeLoader._validate_identifier(table_name, "table name") + SnowflakeLoader._validate_identifier(col_name, "column name") + + # Validate sample_size is a positive integer + if not isinstance(sample_size, int) or sample_size <= 0: + raise ValueError(f"sample_size must be a positive integer, got {sample_size!r}") + + # Quote identifiers safely + quoted_table = SnowflakeLoader._quote_identifier(table_name) + quoted_col = SnowflakeLoader._quote_identifier(col_name) + + # Oversample by 10x to increase the chance of getting sample_size + # distinct non-null values after filtering (Snowflake's SAMPLE clause + # returns approximate row counts, and rows may contain NULLs or duplicates) + sample_rows = sample_size * 10 + + query = f""" + SELECT DISTINCT {quoted_col} + FROM {quoted_table} SAMPLE ({sample_rows} ROWS) + WHERE {quoted_col} IS NOT NULL + LIMIT %s; + """ + cursor.execute(query, (sample_size,)) + + sample_results = cursor.fetchall() + # DictCursor returns dicts; extract the column value by name + return [row[col_name] for row in sample_results if row[col_name] is not None] + + @staticmethod + def _serialize_value(value): + """ + Convert non-JSON serializable values to JSON serializable format. + + Args: + value: The value to serialize + + Returns: + JSON serializable version of the value + """ + if isinstance(value, (datetime.date, datetime.datetime)): + return value.isoformat() + if isinstance(value, datetime.time): + return value.isoformat() + if isinstance(value, decimal.Decimal): + return float(value) + if value is None: + return None + return value + + @staticmethod + def _parse_snowflake_url(connection_url: str) -> Dict[str, Any]: # pylint: disable=too-many-locals + """ + Parse Snowflake connection URL into components. + + Supports two authentication modes: + - Password: snowflake://user:pass@account/db/schema?warehouse=WH + - Key-pair: snowflake://user@account/db/schema?warehouse=WH&private_key=BASE64_PEM + (optionally with &private_key_passphrase=PASSPHRASE) + + Args: + connection_url: Snowflake connection URL + + Returns: + Dict with connection parameters for snowflake.connector.connect() + """ + if not connection_url.startswith('snowflake://'): + raise ValueError( + "Invalid Snowflake URL format. Expected " + "snowflake://username:password@account/database/schema?warehouse=warehouse_name" + ) + + parsed = urlparse(connection_url) + + if not parsed.username: + raise ValueError("Snowflake URL must include username") + + username = parsed.username + password = parsed.password or "" + + if not parsed.hostname: + raise ValueError("Snowflake URL must include account") + account = parsed.hostname + + path_parts = [p for p in parsed.path.split('/') if p] + if len(path_parts) < 1: + raise ValueError("Snowflake URL must include database name") + + database = path_parts[0] + schema = path_parts[1] if len(path_parts) > 1 else "PUBLIC" + + query_params = parse_qs(parsed.query) + warehouse = query_params.get('warehouse', ['COMPUTE_WH'])[0] + + # Validate all identifiers + SnowflakeLoader._validate_identifier(database, "database") + SnowflakeLoader._validate_identifier(schema, "schema") + SnowflakeLoader._validate_identifier(warehouse, "warehouse") + + conn_params: Dict[str, Any] = { + 'user': username, + 'account': account, + 'database': database, + 'schema': schema, + 'warehouse': warehouse, + 'login_timeout': 30, + 'network_timeout': 60, + } + + # Check for key-pair authentication + private_key_b64 = query_params.get('private_key', [None])[0] + if private_key_b64: + passphrase = query_params.get('private_key_passphrase', [None])[0] + passphrase_bytes = passphrase.encode() if passphrase else None + + try: + # Handle both standard and URL-safe base64 (browsers may + # convert '+' to spaces when URL-encoding query params) + cleaned_b64 = private_key_b64.replace(' ', '+') + pem_bytes = base64.b64decode(cleaned_b64) + private_key = serialization.load_pem_private_key( + pem_bytes, + password=passphrase_bytes, + backend=default_backend(), + ) + conn_params['private_key'] = private_key.private_bytes( + encoding=serialization.Encoding.DER, + format=serialization.PrivateFormat.PKCS8, + encryption_algorithm=serialization.NoEncryption(), + ) + except Exception as e: + raise ValueError(f"Failed to load private key: {e}") from e + else: + conn_params['password'] = password + + return conn_params + + @staticmethod + async def load(prefix: str, connection_url: str) -> AsyncGenerator[ + tuple[bool, str], None + ]: + """ + Load the graph data from a Snowflake database into the graph database. + + Args: + connection_url: Snowflake connection URL in format: + snowflake://username:password@account/database/schema?warehouse=warehouse_name + + Returns: + Tuple[bool, str]: Success status and message + """ + try: + # Parse connection URL + conn_params = SnowflakeLoader._parse_snowflake_url(connection_url) + + # Connect to Snowflake database + conn = snowflake.connector.connect(**conn_params) + cursor = conn.cursor(DictCursor) + + # Get database and schema name + db_name = conn_params['database'] + # Snowflake stores unquoted identifiers in UPPERCASE; + # INFORMATION_SCHEMA lookups require the canonical form. + schema_name = conn_params['schema'].upper() + + # Get all table information + yield True, "Extracting table information..." + entities = SnowflakeLoader.extract_tables_info(cursor, db_name, schema_name) + + # Get all relationship information + yield True, "Extracting relationship information..." + relationships = SnowflakeLoader.extract_relationships(cursor, db_name, schema_name) + + # Close database connection + cursor.close() + conn.close() + + # Load data into graph + yield True, "Loading data into graph..." + await load_to_graph(f"{prefix}_{db_name}", entities, relationships, + db_name=db_name, db_url=connection_url) + + yield True, (f"Snowflake schema loaded successfully. " + f"Found {len(entities)} tables.") + + except snowflake.connector.Error as e: + logging.error("Snowflake error: %s", e) + yield False, f"Snowflake error: {e}" + except Exception as e: # pylint: disable=broad-exception-caught + logging.error("Error loading Snowflake schema: %s", e) + yield False, f"Failed to load Snowflake database schema: {e}" + + @staticmethod + def extract_tables_info(cursor, db_name: str, schema_name: str) -> Dict[str, Any]: + """ + Extract table and column information from Snowflake database. + + Args: + cursor: Database cursor + db_name: Database name + schema_name: Schema name + + Returns: + Dict containing table information + """ + # Validate identifiers to prevent SQL injection + SnowflakeLoader._validate_identifier(db_name, "database name") + SnowflakeLoader._validate_identifier(schema_name, "schema name") + + entities = {} + + # Get all tables in the schema + # Use quoted identifiers for database name, parameterize schema_name + quoted_db = SnowflakeLoader._quote_identifier(db_name) + cursor.execute(f""" + SELECT TABLE_NAME, COMMENT + FROM {quoted_db}.INFORMATION_SCHEMA.TABLES + WHERE TABLE_SCHEMA = %s + AND TABLE_TYPE = 'BASE TABLE' + ORDER BY TABLE_NAME; + """, (schema_name,)) + + tables = cursor.fetchall() + + for table_info in tqdm.tqdm(tables, desc="Extracting table information"): + table_name = table_info['TABLE_NAME'] + table_comment = table_info['COMMENT'] + + # Get column information for this table + columns_info = SnowflakeLoader.extract_columns_info( + cursor, db_name, schema_name, table_name + ) + + # Get foreign keys for this table + foreign_keys = SnowflakeLoader.extract_foreign_keys( + cursor, db_name, schema_name, table_name + ) + + # Generate table description + table_description = table_comment if table_comment else f"Table: {table_name}" + + # Get column descriptions for batch embedding + col_descriptions = [col_info['description'] for col_info in columns_info.values()] + + entities[table_name] = { + 'description': table_description, + 'columns': columns_info, + 'foreign_keys': foreign_keys, + 'col_descriptions': col_descriptions + } + + return entities + + @staticmethod + def extract_columns_info( # pylint: disable=too-many-locals + cursor, db_name: str, schema_name: str, table_name: str + ) -> Dict[str, Any]: + """ + Extract column information for a specific table. + + Args: + cursor: Database cursor + db_name: Database name + schema_name: Schema name + table_name: Name of the table + + Returns: + Dict containing column information + """ + # Validate identifiers to prevent SQL injection + SnowflakeLoader._validate_identifier(db_name, "database name") + SnowflakeLoader._validate_identifier(schema_name, "schema name") + SnowflakeLoader._validate_identifier(table_name, "table name") + + quoted_db = SnowflakeLoader._quote_identifier(db_name) + + cursor.execute(f""" + SELECT + COLUMN_NAME, + DATA_TYPE, + IS_NULLABLE, + COLUMN_DEFAULT, + COMMENT + FROM {quoted_db}.INFORMATION_SCHEMA.COLUMNS + WHERE TABLE_SCHEMA = %s + AND TABLE_NAME = %s + ORDER BY ORDINAL_POSITION; + """, (schema_name, table_name)) + + columns = cursor.fetchall() + columns_info = {} + + # Get primary key information using Snowflake's SHOW command + quoted_table = SnowflakeLoader._quote_identifier(table_name) + quoted_schema = SnowflakeLoader._quote_identifier(schema_name) + cursor.execute(f"SHOW PRIMARY KEYS IN TABLE {quoted_db}.{quoted_schema}.{quoted_table}") + primary_keys = {row['column_name'] for row in cursor.fetchall()} + + # Get foreign key columns using Snowflake's SHOW IMPORTED KEYS + cursor.execute(f"SHOW IMPORTED KEYS IN TABLE {quoted_db}.{quoted_schema}.{quoted_table}") + foreign_keys_cols = {row['fk_column_name'] for row in cursor.fetchall()} + + for col_info in columns: + col_name = col_info['COLUMN_NAME'] + data_type = col_info['DATA_TYPE'] + is_nullable = col_info['IS_NULLABLE'] + column_default = col_info['COLUMN_DEFAULT'] + column_comment = col_info['COMMENT'] + + # Determine key type + if col_name in primary_keys: + key_type = 'PRIMARY KEY' + elif col_name in foreign_keys_cols: + key_type = 'FOREIGN KEY' + else: + key_type = 'NONE' + + # Generate column description + description_parts = [] + if column_comment: + description_parts.append(column_comment) + else: + description_parts.append(f"Column {col_name} of type {data_type}") + + if key_type != 'NONE': + description_parts.append(f"({key_type})") + + if is_nullable == 'NO': + description_parts.append("(NOT NULL)") + + if column_default is not None: + description_parts.append(f"(Default: {column_default})") + + # Extract sample values for the column (stored separately, not in description) + sample_values = SnowflakeLoader.extract_sample_values_for_column( + cursor, table_name, col_name + ) + + columns_info[col_name] = { + 'type': data_type, + 'null': is_nullable, + 'key': key_type, + 'description': ' '.join(description_parts), + 'default': column_default, + 'sample_values': sample_values + } + + return columns_info + + @staticmethod + def extract_foreign_keys( + cursor, db_name: str, schema_name: str, table_name: str + ) -> List[Dict[str, str]]: + """ + Extract foreign key information for a specific table. + + Args: + cursor: Database cursor + db_name: Database name + schema_name: Schema name + table_name: Name of the table + + Returns: + List of foreign key dictionaries + """ + # Validate identifiers to prevent SQL injection + SnowflakeLoader._validate_identifier(db_name, "database name") + SnowflakeLoader._validate_identifier(schema_name, "schema name") + SnowflakeLoader._validate_identifier(table_name, "table name") + + quoted_db = SnowflakeLoader._quote_identifier(db_name) + quoted_schema = SnowflakeLoader._quote_identifier(schema_name) + quoted_table = SnowflakeLoader._quote_identifier(table_name) + + # Use Snowflake's SHOW IMPORTED KEYS for foreign key information + cursor.execute(f"SHOW IMPORTED KEYS IN TABLE {quoted_db}.{quoted_schema}.{quoted_table}") + + foreign_keys = [] + for fk_info in cursor.fetchall(): + foreign_keys.append({ + 'constraint_name': fk_info['fk_name'], + 'column': fk_info['fk_column_name'], + 'referenced_table': fk_info['pk_table_name'], + 'referenced_column': fk_info['pk_column_name'] + }) + + return foreign_keys + + @staticmethod + def extract_relationships( + cursor, db_name: str, schema_name: str + ) -> Dict[str, List[Dict[str, str]]]: + """ + Extract all relationship information from the database. + + Args: + cursor: Database cursor + db_name: Database name + schema_name: Schema name + + Returns: + Dict containing relationship information + """ + # Validate identifiers to prevent SQL injection + SnowflakeLoader._validate_identifier(db_name, "database name") + SnowflakeLoader._validate_identifier(schema_name, "schema name") + + quoted_db = SnowflakeLoader._quote_identifier(db_name) + quoted_schema = SnowflakeLoader._quote_identifier(schema_name) + + # Use Snowflake's SHOW IMPORTED KEYS for each table to get relationships + cursor.execute(f""" + SELECT TABLE_NAME + FROM {quoted_db}.INFORMATION_SCHEMA.TABLES + WHERE TABLE_SCHEMA = %s + AND TABLE_TYPE = 'BASE TABLE' + ORDER BY TABLE_NAME; + """, (schema_name,)) + tables = [row['TABLE_NAME'] for row in cursor.fetchall()] + + relationships = {} + for tbl in tables: + SnowflakeLoader._validate_identifier(tbl, "table name") + quoted_table = SnowflakeLoader._quote_identifier(tbl) + cursor.execute( + f"SHOW IMPORTED KEYS IN TABLE {quoted_db}.{quoted_schema}.{quoted_table}" + ) + for rel_info in cursor.fetchall(): + constraint_name = rel_info['fk_name'] + + if constraint_name not in relationships: + relationships[constraint_name] = [] + + relationships[constraint_name].append({ + 'from': rel_info['fk_table_name'], + 'to': rel_info['pk_table_name'], + 'source_column': rel_info['fk_column_name'], + 'target_column': rel_info['pk_column_name'], + 'note': f'Foreign key constraint: {constraint_name}' + }) + + return relationships + + @staticmethod + def is_schema_modifying_query(sql_query: str) -> Tuple[bool, str]: + """ + Check if a SQL query modifies the database schema. + + Args: + sql_query: The SQL query to check + + Returns: + Tuple of (is_schema_modifying, operation_type) + """ + if not sql_query or not sql_query.strip(): + return False, "" + + # Clean and normalize the query + normalized_query = sql_query.strip().upper() + + # Check for basic DDL operations + first_word = normalized_query.split()[0] if normalized_query.split() else "" + if first_word in SnowflakeLoader.SCHEMA_MODIFYING_OPERATIONS: + # Additional pattern matching for more precise detection + for pattern in SnowflakeLoader.SCHEMA_PATTERNS: + if re.match(pattern, normalized_query, re.IGNORECASE): + return True, first_word + + # If it's a known DDL operation but doesn't match specific patterns, + # still consider it schema-modifying (better safe than sorry) + return True, first_word + + return False, "" + + @staticmethod + async def refresh_graph_schema(graph_id: str, db_url: str) -> Tuple[bool, str]: + """ + Refresh the graph schema by clearing existing data and reloading from the database. + + Args: + graph_id: The graph ID to refresh + db_url: Database connection URL + + Returns: + Tuple of (success, message) + """ + try: + logging.info("Schema modification detected. Refreshing graph schema.") + + # Import here to avoid circular imports + from api.extensions import db # pylint: disable=import-error,import-outside-toplevel + + # Clear existing graph data + # Drop current graph before reloading + graph = db.select_graph(graph_id) + await graph.delete() + + # Extract prefix from graph_id (remove database name part) + # graph_id format is typically "prefix_database_name" + parts = graph_id.split('_') + if len(parts) >= 2: + # Reconstruct prefix by joining all parts except the last one + prefix = '_'.join(parts[:-1]) + else: + prefix = graph_id + + # Reuse the existing load method to reload the schema + success = False + message = "" + async for progress_tuple in SnowflakeLoader.load(prefix, db_url): + success, message = progress_tuple + + if success: + logging.info("Graph schema refreshed successfully.") + return True, message + + logging.error("Schema refresh failed") + return False, "Failed to reload schema" + + except Exception as e: # pylint: disable=broad-exception-caught + # Log the error and return failure + logging.error("Error refreshing graph schema: %s", str(e)) + error_msg = "Error refreshing graph schema" + logging.error(error_msg) + return False, error_msg + + @staticmethod + def execute_sql_query(sql_query: str, db_url: str) -> List[Dict[str, Any]]: + """ + Execute a SQL query on the Snowflake database and return the results. + + Args: + sql_query: The SQL query to execute + db_url: Snowflake connection URL in format: + snowflake://username:password@account/database/schema?warehouse=warehouse_name + + Returns: + List of dictionaries containing the query results + """ + try: + # Parse connection URL + conn_params = SnowflakeLoader._parse_snowflake_url(db_url) + + # Connect to Snowflake database + conn = snowflake.connector.connect(**conn_params) + cursor = conn.cursor(DictCursor) + + # Execute the SQL query + cursor.execute(sql_query) + + # Check if the query returns results (SELECT queries) + if cursor.description is not None: + # This is a SELECT query or similar that returns rows + results = cursor.fetchall() + result_list = [] + for row in results: + # Serialize each value to ensure JSON compatibility + serialized_row = { + key: SnowflakeLoader._serialize_value(value) + for key, value in row.items() + } + result_list.append(serialized_row) + else: + # This is an INSERT, UPDATE, DELETE, or other non-SELECT query + # Return information about the operation + affected_rows = cursor.rowcount + sql_type = sql_query.strip().split()[0].upper() + + if sql_type in ['INSERT', 'UPDATE', 'DELETE']: + result_list = [{ + "operation": sql_type, + "affected_rows": affected_rows, + "status": "success" + }] + else: + # For other types of queries (CREATE, DROP, etc.) + result_list = [{ + "operation": sql_type, + "status": "success" + }] + + # Commit the transaction for write operations + conn.commit() + + # Close database connection + cursor.close() + conn.close() + + return result_list + + except snowflake.connector.Error as e: + # Rollback in case of error + if 'conn' in locals(): + conn.rollback() + cursor.close() + conn.close() + logging.error("Snowflake query execution error: %s", e) + raise SnowflakeQueryError(f"Snowflake query execution error: {str(e)}") from e + except Exception as e: + # Rollback in case of error + if 'conn' in locals(): + conn.rollback() + cursor.close() + conn.close() + logging.error("Error executing SQL query: %s", e) + raise SnowflakeQueryError(f"Error executing SQL query: {str(e)}") from e diff --git a/api/memory/graphiti_tool.py b/api/memory/graphiti_tool.py index 3c944545..00a1b3e6 100644 --- a/api/memory/graphiti_tool.py +++ b/api/memory/graphiti_tool.py @@ -65,6 +65,7 @@ def __init__(self, user_id: str, graph_id: str): # Create Graphiti client with Azure OpenAI configuration self.graphiti_client = create_graphiti_client(falkor_driver) + self.memory_enabled = self.graphiti_client is not None self.user_id = user_id self.graph_id = graph_id @@ -82,6 +83,9 @@ async def create(cls, user_id: str, graph_id: str, use_direct_entities: bool = T """Async factory to construct and initialize the tool.""" self = cls(user_id, graph_id) + if not self.memory_enabled: + return self + await self._ensure_entity_nodes_direct(user_id, graph_id) @@ -301,16 +305,18 @@ async def add_new_memory(self, conversation: Dict[str, Any], history: Tuple[List async def save_query_memory(self, query: str, sql_query: str, success: bool, error: Optional[str] = None) -> bool: """ Save individual query memory directly to the database node. - + Args: query: The user's natural language query sql_query: The generated SQL query success: Whether the query execution was successful error: Error message if the query failed - + Returns: bool: True if memory was saved successfully, False otherwise """ + if not self.memory_enabled: + return False try: database_name = self.graph_id database_node_name = f"Database {database_name}" @@ -396,6 +402,8 @@ async def retrieve_similar_queries(self, query: str, limit: int = 5) -> List[Dic Returns: A list of similar query metadata. """ + if not self.memory_enabled: + return [] try: database_name = self.graph_id @@ -457,10 +465,12 @@ async def search_user_summary(self, limit: int = 5) -> str: Args: query: Natural language query to search for limit: Maximum number of results to return - + Returns: List of user node summaries with metadata """ + if not self.memory_enabled: + return "" try: driver = self.graphiti_client.driver query = """ @@ -508,14 +518,16 @@ async def extract_episode_from_rel(self, rel_result): async def search_database_facts(self, query: str, limit: int = 5, episode_limit: int = 3) -> str: """ Search for database-specific facts and interaction history using database node as center. - + Args: query: Natural language query to search for database facts limit: Maximum number of results to return - + Returns: String containing all relevant database facts with time relevancy information """ + if not self.memory_enabled: + return "" try: driver = self.graphiti_client.driver query = """ @@ -568,15 +580,18 @@ async def search_memories(self, query: str, user_limit: int = 5, database_limit: """ Run both user summary and database facts searches concurrently for better performance. Also builds a comprehensive memory context string for the analysis agent. - + Args: query: Natural language query to search for database facts user_limit: Maximum number of results for user summary search database_limit: Maximum number of results for database facts search - + Returns: - Dict containing user_summary, database_facts, similar_queries, and memory_context + A formatted memory context string combining user summary, database facts, + and similar query history, or empty string if memory is disabled. """ + if not self.memory_enabled: + return "" try: # Run both searches concurrently using asyncio.gather user_summary_task = self.search_user_summary(limit=user_limit) @@ -819,10 +834,10 @@ def create_graphiti_client(falkor_driver: FalkorDriver) -> Graphiti: client=llm_client_azure, ), ) - else: # Fallback to default OpenAI config but use Config's embedding model - # Extract just the model name without provider prefix for Graphiti + elif Config.LLM_PROVIDER == "openai": + # OpenAI provider — use OpenAIEmbedder with configured model embedding_model_name = extract_embedding_model_name(Config.EMBEDDING_MODEL_NAME) - + graphiti_client = Graphiti( graph_driver=falkor_driver, embedder=OpenAIEmbedder( @@ -832,6 +847,16 @@ def create_graphiti_client(falkor_driver: FalkorDriver) -> Graphiti: ) ), ) + else: + # Non-OpenAI/Azure providers (Gemini, Anthropic, Ollama, Cohere): + # Graphiti memory requires OpenAI-compatible embeddings. + # Memory is not supported for these providers. + logging.warning( + "Memory is only supported with Azure or OpenAI providers. " + "Current provider: %s. Memory will be disabled.", + getattr(Config, 'LLM_PROVIDER', 'unknown') + ) + return None return graphiti_client diff --git a/api/routes/settings.py b/api/routes/settings.py new file mode 100644 index 00000000..554081d2 --- /dev/null +++ b/api/routes/settings.py @@ -0,0 +1,114 @@ +"""Settings and configuration routes for the text2sql API.""" + +import logging +from fastapi import APIRouter, Request +from fastapi.responses import JSONResponse +from pydantic import BaseModel +from litellm import completion + +from api.auth.user_management import token_required +from api.routes.tokens import UNAUTHORIZED_RESPONSE + +settings_router = APIRouter(tags=["Settings"]) + + +def _sanitize_for_log(value: str) -> str: + """Remove control characters that could enable log injection.""" + return str(value).replace("\r", "").replace("\n", "").replace("\t", " ") + + +class ValidateKeyRequest(BaseModel): + """Request model for API key validation.""" + api_key: str + vendor: str = "openai" + model: str = "gpt-3.5-turbo" + + +@settings_router.post("/validate-api-key", responses={401: UNAUTHORIZED_RESPONSE}) +@token_required +async def validate_api_key(request: Request, data: ValidateKeyRequest): # pylint: disable=too-many-return-statements,unused-argument + """ + Validate an AI provider API key by making a simple test request. + This endpoint does not store the key, it only validates it. + Supports: openai, google, anthropic + """ + api_key = data.api_key.strip() + vendor = data.vendor.lower() + model = data.model + + if not api_key: + return JSONResponse( + content={"valid": False, "error": "API key is required"}, + status_code=400 + ) + + # Validate vendor — only key-based vendors can be validated via API call + validatable_vendors = ("openai", "anthropic", "gemini", "cohere") + if vendor not in validatable_vendors: + allowed = ", ".join(validatable_vendors) + return JSONResponse( + content={"valid": False, "error": f"Unsupported vendor for key validation. Supported: {allowed}"}, + status_code=400 + ) + + # Validate model is not empty + if not model or not model.strip(): + return JSONResponse( + content={"valid": False, "error": "Model name is required"}, + status_code=400 + ) + + # Validate key format based on vendor + if vendor == "openai" and not api_key.startswith('sk-'): + return JSONResponse( + content={"valid": False, "error": "Invalid OpenAI API key format"}, + status_code=400 + ) + if vendor == "anthropic" and not api_key.startswith('sk-ant-'): + return JSONResponse( + content={"valid": False, "error": "Invalid Anthropic API key format"}, + status_code=400 + ) + + try: + # Construct model name for LiteLLM (vendor/model format) + full_model_name = f"{vendor}/{model}" + + test_response = completion( + model=full_model_name, + messages=[{"role": "user", "content": "test"}], + max_tokens=1, + api_key=api_key, + ) + + # If we get here without exception, the key is valid + if test_response and test_response.choices: + return JSONResponse( + content={"valid": True}, + status_code=200 + ) + return JSONResponse( + content={"valid": False, "error": "Invalid API key"}, + status_code=401 + ) + + except Exception as e: # pylint: disable=broad-except + error_lower = str(e).lower() + logging.warning("API key validation failed for vendor=%s", + _sanitize_for_log(vendor)) + + # Return generic messages — never expose exception details + if "invalid" in error_lower or "authentication" in error_lower: + return JSONResponse( + content={"valid": False, "error": "Invalid API key"}, + status_code=401 + ) + if "quota" in error_lower or "rate" in error_lower: + return JSONResponse( + content={"valid": False, "error": "API quota exceeded or rate limited"}, + status_code=429 + ) + return JSONResponse( + content={"valid": False, "error": "Failed to validate API key"}, + status_code=500 + ) diff --git a/api/utils.py b/api/utils.py index 845ca604..e6979876 100644 --- a/api/utils.py +++ b/api/utils.py @@ -98,7 +98,8 @@ def create_combined_description( # pylint: disable=too-many-locals if isinstance(batch_response, Exception): table_info[table_name]["description"] = table_name else: - content = batch_response.choices[0].message["content"].strip() + msg_content = batch_response.choices[0].message["content"] + content = msg_content.strip() if msg_content else table_name table_info[table_name]["description"] = content return table_info diff --git a/app/package-lock.json b/app/package-lock.json index 33c4e227..13db7eed 100644 --- a/app/package-lock.json +++ b/app/package-lock.json @@ -8,8 +8,8 @@ "name": "queryweaver-app", "version": "0.1.0", "dependencies": { - "@falkordb/canvas": "^0.0.41", - "@hookform/resolvers": "^3.10.0", + "@falkordb/canvas": "^0.0.45", + "@hookform/resolvers": "^5.2.2", "@radix-ui/react-accordion": "^1.2.11", "@radix-ui/react-alert-dialog": "^1.1.14", "@radix-ui/react-aspect-ratio": "^1.1.7", @@ -46,7 +46,7 @@ "date-fns": "^3.6.0", "embla-carousel-react": "^8.6.0", "input-otp": "^1.4.2", - "lucide-react": "^0.462.0", + "lucide-react": "^0.577.0", "next-themes": "^0.3.0", "preact": "^10.28.4", "react": "^18.3.1", @@ -54,7 +54,7 @@ "react-dom": "^18.3.1", "react-hook-form": "^7.71.2", "react-resizable-panels": "^2.1.9", - "react-router-dom": "^6.30.1", + "react-router-dom": "^7.13.2", "recharts": "^2.15.4", "sonner": "^1.7.4", "tailwind-merge": "^2.6.0", @@ -74,10 +74,10 @@ "eslint-plugin-react-hooks": "^5.2.0", "eslint-plugin-react-refresh": "^0.4.20", "globals": "^17.3.0", - "postcss": "^8.5.6", + "postcss": "^8.5.8", "tailwindcss": "^3.4.17", "typescript": "^5.8.3", - "typescript-eslint": "^8.38.0", + "typescript-eslint": "^8.57.0", "vite": "^7.3.0" } }, @@ -674,9 +674,9 @@ } }, "node_modules/@falkordb/canvas": { - "version": "0.0.41", - "resolved": "https://registry.npmjs.org/@falkordb/canvas/-/canvas-0.0.41.tgz", - "integrity": "sha512-r2DC2Mo9naASr3DDmVKCQVY/S50Hn2bGlmKaFxDRFcn5btiuuvPBqJ3krtC+uz5ZPmad8EoXRRlcQ6KwKJhUZw==", + "version": "0.0.45", + "resolved": "https://registry.npmjs.org/@falkordb/canvas/-/canvas-0.0.45.tgz", + "integrity": "sha512-BIb24rfnaLCxO2UH7L4cNYLikmOTXlVR4I/FIpEG/d9ZEp3F+9U/ugaLYOcYe1pmZzT72YnzWUuvdhNE3zK99A==", "license": "MIT", "dependencies": { "d3": "^7.9.0", @@ -724,10 +724,15 @@ "license": "MIT" }, "node_modules/@hookform/resolvers": { - "version": "3.10.0", + "version": "5.2.2", + "resolved": "https://registry.npmjs.org/@hookform/resolvers/-/resolvers-5.2.2.tgz", + "integrity": "sha512-A/IxlMLShx3KjV/HeTcTfaMxdwy690+L/ZADoeaTltLx+CVuzkeVIPuybK3jrRfw7YZnmdKsVVHAlEPIAEUNlA==", "license": "MIT", + "dependencies": { + "@standard-schema/utils": "^0.3.0" + }, "peerDependencies": { - "react-hook-form": "^7.0.0" + "react-hook-form": "^7.55.0" } }, "node_modules/@humanfs/core": { @@ -2333,13 +2338,6 @@ "version": "1.1.1", "license": "MIT" }, - "node_modules/@remix-run/router": { - "version": "1.23.2", - "license": "MIT", - "engines": { - "node": ">=14.0.0" - } - }, "node_modules/@rolldown/pluginutils": { "version": "1.0.0-beta.27", "dev": true, @@ -2695,6 +2693,12 @@ "win32" ] }, + "node_modules/@standard-schema/utils": { + "version": "0.3.0", + "resolved": "https://registry.npmjs.org/@standard-schema/utils/-/utils-0.3.0.tgz", + "integrity": "sha512-e7Mew686owMaPJVNNLs55PUvgz371nKgwsc4vxE49zsODpJEnxgxRo2y/OKrqueavXgZNMDVj3DdHFlaSAeU8g==", + "license": "MIT" + }, "node_modules/@swc/core": { "version": "1.15.8", "dev": true, @@ -3192,15 +3196,17 @@ } }, "node_modules/@typescript-eslint/eslint-plugin": { - 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"version": "2.3.1", + "version": "2.3.2", + "resolved": "https://registry.npmjs.org/picomatch/-/picomatch-2.3.2.tgz", + "integrity": "sha512-V7+vQEJ06Z+c5tSye8S+nHUfI51xoXIXjHQ99cQtKUkQqqO1kO/KCJUfZXuB47h/YBlDhah2H3hdUGXn8ie0oA==", "license": "MIT", "engines": { "node": ">=8.6" @@ -5251,7 +5326,9 @@ } }, "node_modules/postcss": { - "version": "8.5.6", + "version": "8.5.8", + "resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.8.tgz", + "integrity": "sha512-OW/rX8O/jXnm82Ey1k44pObPtdblfiuWnrd8X7GJ7emImCOstunGbXUpp7HdBrFQX6rJzn3sPT397Wp5aCwCHg==", "funding": [ { "type": "opencollective", @@ -5566,31 +5643,41 @@ } }, "node_modules/react-router": { - "version": "6.30.3", + "version": "7.13.2", + "resolved": "https://registry.npmjs.org/react-router/-/react-router-7.13.2.tgz", + "integrity": "sha512-tX1Aee+ArlKQP+NIUd7SE6Li+CiGKwQtbS+FfRxPX6Pe4vHOo6nr9d++u5cwg+Z8K/x8tP+7qLmujDtfrAoUJA==", "license": "MIT", "dependencies": { - "@remix-run/router": "1.23.2" + "cookie": "^1.0.1", + "set-cookie-parser": "^2.6.0" }, "engines": { - "node": ">=14.0.0" + "node": ">=20.0.0" }, "peerDependencies": { - "react": ">=16.8" + "react": ">=18", + "react-dom": ">=18" + }, + "peerDependenciesMeta": { + "react-dom": { + "optional": true + } } }, "node_modules/react-router-dom": { - "version": "6.30.3", + "version": "7.13.2", + "resolved": "https://registry.npmjs.org/react-router-dom/-/react-router-dom-7.13.2.tgz", + "integrity": "sha512-aR7SUORwTqAW0JDeiWF07e9SBE9qGpByR9I8kJT5h/FrBKxPMS6TiC7rmVO+gC0q52Bx7JnjWe8Z1sR9faN4YA==", "license": "MIT", "dependencies": { - "@remix-run/router": "1.23.2", - "react-router": "6.30.3" + "react-router": "7.13.2" }, "engines": { - "node": ">=14.0.0" + "node": ">=20.0.0" }, "peerDependencies": { - "react": ">=16.8", - "react-dom": ">=16.8" + "react": ">=18", + "react-dom": ">=18" } }, "node_modules/react-smooth": { @@ -5811,7 +5898,9 @@ } }, "node_modules/semver": { - "version": "7.7.3", + "version": "7.7.4", + "resolved": "https://registry.npmjs.org/semver/-/semver-7.7.4.tgz", + "integrity": "sha512-vFKC2IEtQnVhpT78h1Yp8wzwrf8CM+MzKMHGJZfBtzhZNycRFnXsHk6E5TxIkkMsgNS7mdX3AGB7x2QM2di4lA==", "dev": true, "license": "ISC", "bin": { @@ -5821,6 +5910,12 @@ "node": ">=10" } }, + "node_modules/set-cookie-parser": { + "version": "2.7.2", + "resolved": "https://registry.npmjs.org/set-cookie-parser/-/set-cookie-parser-2.7.2.tgz", + "integrity": "sha512-oeM1lpU/UvhTxw+g3cIfxXHyJRc/uidd3yK1P242gzHds0udQBYzs3y8j4gCCW+ZJ7ad0yctld8RYO+bdurlvw==", + "license": "MIT" + }, "node_modules/shebang-command": { "version": "2.0.0", "dev": true, @@ -6032,7 +6127,9 @@ } }, "node_modules/tinyglobby/node_modules/picomatch": { - "version": "4.0.3", + "version": "4.0.4", + "resolved": "https://registry.npmjs.org/picomatch/-/picomatch-4.0.4.tgz", + "integrity": "sha512-QP88BAKvMam/3NxH6vj2o21R6MjxZUAd6nlwAS/pnGvN9IVLocLHxGYIzFhg6fUQ+5th6P4dv4eW9jX3DSIj7A==", "license": "MIT", "engines": { "node": ">=12" @@ -6052,7 +6149,9 @@ } }, "node_modules/ts-api-utils": { - "version": "2.4.0", + "version": "2.5.0", + "resolved": "https://registry.npmjs.org/ts-api-utils/-/ts-api-utils-2.5.0.tgz", + "integrity": "sha512-OJ/ibxhPlqrMM0UiNHJ/0CKQkoKF243/AEmplt3qpRgkW8VG7IfOS41h7V8TjITqdByHzrjcS/2si+y4lIh8NA==", "dev": true, "license": "MIT", "engines": { @@ -6094,14 +6193,16 @@ } }, "node_modules/typescript-eslint": { - "version": "8.53.0", + "version": "8.57.2", + "resolved": "https://registry.npmjs.org/typescript-eslint/-/typescript-eslint-8.57.2.tgz", + "integrity": "sha512-VEPQ0iPgWO/sBaZOU1xo4nuNdODVOajPnTIbog2GKYr31nIlZ0fWPoCQgGfF3ETyBl1vn63F/p50Um9Z4J8O8A==", "dev": true, "license": "MIT", "dependencies": { - "@typescript-eslint/eslint-plugin": "8.53.0", - "@typescript-eslint/parser": "8.53.0", - "@typescript-eslint/typescript-estree": "8.53.0", - "@typescript-eslint/utils": "8.53.0" + "@typescript-eslint/eslint-plugin": "8.57.2", + "@typescript-eslint/parser": "8.57.2", + "@typescript-eslint/typescript-estree": "8.57.2", + "@typescript-eslint/utils": "8.57.2" }, "engines": { "node": "^18.18.0 || ^20.9.0 || >=21.1.0" @@ -6111,7 +6212,7 @@ "url": "https://opencollective.com/typescript-eslint" }, "peerDependencies": { - "eslint": "^8.57.0 || ^9.0.0", + "eslint": "^8.57.0 || ^9.0.0 || ^10.0.0", "typescript": ">=4.8.4 <6.0.0" } }, @@ -6328,7 +6429,9 @@ } }, "node_modules/vite/node_modules/picomatch": { - "version": "4.0.3", + "version": "4.0.4", + "resolved": "https://registry.npmjs.org/picomatch/-/picomatch-4.0.4.tgz", + "integrity": "sha512-QP88BAKvMam/3NxH6vj2o21R6MjxZUAd6nlwAS/pnGvN9IVLocLHxGYIzFhg6fUQ+5th6P4dv4eW9jX3DSIj7A==", "dev": true, "license": "MIT", "engines": { diff --git a/app/package.json b/app/package.json index 6322ceab..ddcdb637 100644 --- a/app/package.json +++ b/app/package.json @@ -11,8 +11,8 @@ "preview": "vite preview" }, "dependencies": { - "@falkordb/canvas": "^0.0.41", - "@hookform/resolvers": "^3.10.0", + "@falkordb/canvas": "^0.0.45", + "@hookform/resolvers": "^5.2.2", "@radix-ui/react-accordion": "^1.2.11", "@radix-ui/react-alert-dialog": "^1.1.14", "@radix-ui/react-aspect-ratio": "^1.1.7", @@ -49,7 +49,7 @@ "date-fns": "^3.6.0", "embla-carousel-react": "^8.6.0", "input-otp": "^1.4.2", - "lucide-react": "^0.462.0", + "lucide-react": "^0.577.0", "next-themes": "^0.3.0", "preact": "^10.28.4", "react": "^18.3.1", @@ -57,7 +57,7 @@ "react-dom": "^18.3.1", "react-hook-form": "^7.71.2", "react-resizable-panels": "^2.1.9", - "react-router-dom": "^6.30.1", + "react-router-dom": "^7.13.2", "recharts": "^2.15.4", "sonner": "^1.7.4", "tailwind-merge": "^2.6.0", @@ -77,10 +77,10 @@ "eslint-plugin-react-hooks": "^5.2.0", "eslint-plugin-react-refresh": "^0.4.20", "globals": "^17.3.0", - "postcss": "^8.5.6", + "postcss": "^8.5.8", "tailwindcss": "^3.4.17", "typescript": "^5.8.3", - "typescript-eslint": "^8.38.0", + "typescript-eslint": "^8.57.0", "vite": "^7.3.0" }, "overrides": { diff --git a/app/src/App.tsx b/app/src/App.tsx index 25699055..1746e1be 100644 --- a/app/src/App.tsx +++ b/app/src/App.tsx @@ -4,6 +4,7 @@ import { QueryClient, QueryClientProvider } from "@tanstack/react-query"; import { BrowserRouter, Routes, Route } from "react-router-dom"; import { AuthProvider } from "@/contexts/AuthContext"; import { DatabaseProvider } from "@/contexts/DatabaseContext"; +import { SettingsProvider } from "@/contexts/SettingsContext"; import { ChatProvider } from "@/contexts/ChatContext"; import Index from "./pages/Index"; import Settings from "./pages/Settings"; @@ -15,19 +16,21 @@ const App = () => ( - - - - - - } /> - } /> - {/* ADD ALL CUSTOM ROUTES ABOVE THE CATCH-ALL "*" ROUTE */} - } /> - - - - + + + + + + + } /> + } /> + {/* ADD ALL CUSTOM ROUTES ABOVE THE CATCH-ALL "*" ROUTE */} + } /> + + + + + diff --git a/app/src/components/chat/ChatInterface.tsx b/app/src/components/chat/ChatInterface.tsx index 75548563..6f43691a 100644 --- a/app/src/components/chat/ChatInterface.tsx +++ b/app/src/components/chat/ChatInterface.tsx @@ -3,6 +3,7 @@ import { cn } from "@/lib/utils"; import { useToast } from "@/components/ui/use-toast"; import { useDatabase } from "@/contexts/DatabaseContext"; import { useAuth } from "@/contexts/AuthContext"; +import { useSettings } from "@/contexts/SettingsContext"; import { useChat } from "@/contexts/ChatContext"; import LoadingSpinner from "@/components/ui/loading-spinner"; import { Skeleton } from "@/components/ui/skeleton"; @@ -10,6 +11,8 @@ import ChatMessage from "./ChatMessage"; import QueryInput from "./QueryInput"; import SuggestionCards from "../SuggestionCards"; import { ChatService } from "@/services/chat"; +import type { ConfirmRequest } from "@/types/api"; +import { getVendorPrefix } from "@/utils/vendorConfig"; interface ChatMessageData { id: string; @@ -53,6 +56,7 @@ const ChatInterface = ({ }: ChatInterfaceProps) => { const { toast } = useToast(); const { selectedGraph } = useDatabase(); + const { vendor, apiKey, modelName, isApiKeyValid } = useSettings(); const { messages, setMessages, conversationHistory, isProcessing, setIsProcessing } = useChat(); const messagesEndRef = useRef(null); const chatContainerRef = useRef(null); @@ -146,13 +150,15 @@ const ChatInterface = ({ explanation?: string; isValid?: boolean; } = {}; - // Stream the query for await (const message of ChatService.streamQuery({ query, database: selectedGraph.id, history: historySnapshot, - use_user_rules: useRulesFromDatabase, // Backend fetches from DB when true + customApiKey: isApiKeyValid ? apiKey : undefined, + customModel: isApiKeyValid ? modelName : undefined, + customVendor: isApiKeyValid ? vendor : undefined, + use_user_rules: useRulesFromDatabase, use_memory: useMemory, })) { @@ -323,15 +329,27 @@ const ChatInterface = ({ let finalContent = ""; let queryResults: any[] | null = null; + // Build confirm request with custom credentials if available + const confirmRequest: ConfirmRequest = { + sql_query: confirmMessage.confirmationData.sqlQuery, + confirmation: 'CONFIRM', + chat: confirmMessage.confirmationData.chatHistory, + use_user_rules: useRulesFromDatabase, + }; + if (isApiKeyValid && apiKey) { + confirmRequest.custom_api_key = apiKey; + if (modelName && vendor) { + const vendorPrefix = getVendorPrefix(vendor); + confirmRequest.custom_model = modelName.startsWith(`${vendorPrefix}/`) + ? modelName + : `${vendorPrefix}/${modelName}`; + } + } + // Stream the confirmation response for await (const message of ChatService.streamConfirmOperation( selectedGraph.id, - { - sql_query: confirmMessage.confirmationData.sqlQuery, - confirmation: 'CONFIRM', - chat: confirmMessage.confirmationData.chatHistory, - use_user_rules: useRulesFromDatabase, // Backend fetches from DB when true - } + confirmRequest )) { if (message.type === 'status' || message.type === 'reasoning' || message.type === 'reasoning_step') { // Add reasoning steps diff --git a/app/src/components/layout/Sidebar.tsx b/app/src/components/layout/Sidebar.tsx index bdabc0fc..56acef9e 100644 --- a/app/src/components/layout/Sidebar.tsx +++ b/app/src/components/layout/Sidebar.tsx @@ -6,7 +6,7 @@ import { BookOpen, LifeBuoy, Waypoints, - Settings, + Sliders, } from 'lucide-react'; import { Tooltip, @@ -141,7 +141,7 @@ const Sidebar = ({ className, onSchemaClick, isSchemaOpen, isCollapsed = false, diff --git a/app/src/components/modals/DatabaseModal.tsx b/app/src/components/modals/DatabaseModal.tsx index 35feae26..e3a7f47a 100644 --- a/app/src/components/modals/DatabaseModal.tsx +++ b/app/src/components/modals/DatabaseModal.tsx @@ -29,6 +29,15 @@ const DatabaseModal = ({ open, onOpenChange }: DatabaseModalProps) => { const [database, setDatabase] = useState(""); const [username, setUsername] = useState(""); const [password, setPassword] = useState(""); + const [schema, setSchema] = useState(""); + const [schemaError, setSchemaError] = useState(""); + // Snowflake-specific fields + const [account, setAccount] = useState(""); + const [snowflakeSchema, setSnowflakeSchema] = useState("PUBLIC"); + const [warehouse, setWarehouse] = useState("COMPUTE_WH"); + const [authMode, setAuthMode] = useState<'password' | 'keypair'>('password'); + const [privateKey, setPrivateKey] = useState(""); + const [privateKeyPassphrase, setPrivateKeyPassphrase] = useState(""); const [isConnecting, setIsConnecting] = useState(false); const [connectionSteps, setConnectionSteps] = useState([]); const { refreshGraphs } = useDatabase(); @@ -73,13 +82,32 @@ const DatabaseModal = ({ open, onOpenChange }: DatabaseModalProps) => { return; } } else { - if (!selectedDatabase || !host || !port || !database || !username) { - toast({ - title: "Missing Information", - description: "Please fill in all required fields", - variant: "destructive", - }); - return; + if (selectedDatabase === 'snowflake') { + if (!account || !database || !username) { + toast({ + title: "Missing Information", + description: "Please fill in all required fields (account, database, username)", + variant: "destructive", + }); + return; + } + if (authMode === 'keypair' && !privateKey) { + toast({ + title: "Missing Information", + description: "Please paste your private key in PEM format", + variant: "destructive", + }); + return; + } + } else { + if (!selectedDatabase || !host || !port || !database || !username) { + toast({ + title: "Missing Information", + description: "Please fill in all required fields", + variant: "destructive", + }); + return; + } } } @@ -90,11 +118,37 @@ const DatabaseModal = ({ open, onOpenChange }: DatabaseModalProps) => { // Build the connection URL let dbUrl = connectionUrl; if (connectionMode === 'manual') { - const protocol = selectedDatabase === 'mysql' ? 'mysql' : 'postgresql'; - const builtUrl = new URL(`${protocol}://${host}:${port}/${database}`); - builtUrl.username = username; - builtUrl.password = password; - dbUrl = builtUrl.toString(); + if (selectedDatabase === 'snowflake') { + // Build Snowflake URL: snowflake://user@account/database/schema?warehouse=WH + const builtUrl = new URL(`snowflake://${account}/${database}/${snowflakeSchema}`); + builtUrl.username = username; + if (authMode === 'keypair' && privateKey) { + // Base64-encode the PEM key for safe URL transport + builtUrl.searchParams.set('private_key', btoa(privateKey)); + if (privateKeyPassphrase) { + builtUrl.searchParams.set('private_key_passphrase', privateKeyPassphrase); + } + } else { + builtUrl.password = password; + } + builtUrl.searchParams.set('warehouse', warehouse); + dbUrl = builtUrl.toString(); + } else { + const protocol = selectedDatabase === 'mysql' ? 'mysql' : 'postgresql'; + const builtUrl = new URL(`${protocol}://${host}:${port}/${database}`); + builtUrl.username = username; + builtUrl.password = password; + + // Append schema option for PostgreSQL if provided + if (selectedDatabase === 'postgresql' && schema.trim()) { + if (/[^a-zA-Z0-9_]/.test(schema.trim())) { + throw new Error('Schema name can only contain letters, digits, and underscores'); + } + builtUrl.searchParams.set('options', `-csearch_path=${schema.trim()}`); + } + + dbUrl = builtUrl.toString(); + } } // Make streaming request @@ -177,6 +231,14 @@ const DatabaseModal = ({ open, onOpenChange }: DatabaseModalProps) => { setDatabase(""); setUsername(""); setPassword(""); + setSchema(""); + setSchemaError(""); + setAccount(""); + setSnowflakeSchema("PUBLIC"); + setWarehouse("COMPUTE_WH"); + setAuthMode('password'); + setPrivateKey(""); + setPrivateKeyPassphrase(""); setConnectionSteps([]); }, 1000); } else { @@ -239,7 +301,7 @@ const DatabaseModal = ({ open, onOpenChange }: DatabaseModalProps) => { Connect to Database - Connect to PostgreSQL or MySQL database using a connection URL or manual entry.{" "} + Connect to PostgreSQL, MySQL, or Snowflake database using a connection URL or manual entry.{" "} { MySQL + +
+
+ Snowflake +
+ @@ -315,75 +383,248 @@ const DatabaseModal = ({ open, onOpenChange }: DatabaseModalProps) => { placeholder={ selectedDatabase === 'postgresql' ? 'postgresql://username:password@host:5432/database' - : 'mysql://username:password@host:3306/database' + : selectedDatabase === 'mysql' + ? 'mysql://username:password@host:3306/database' + : 'snowflake://username:password@account/database/schema?warehouse=warehouse_name' } value={connectionUrl} onChange={(e) => setConnectionUrl(e.target.value)} className="bg-muted border-border font-mono text-sm focus-visible:ring-purple-500" />

- Enter your database connection string + {selectedDatabase === 'snowflake' + ? 'Enter your Snowflake connection string (schema defaults to PUBLIC, warehouse to COMPUTE_WH)' + : 'Enter your database connection string'}

)} {selectedDatabase && connectionMode === 'manual' && ( <> -
- - setHost(e.target.value)} - className="bg-muted border-border focus-visible:ring-purple-500" - /> -
+ {selectedDatabase === 'snowflake' ? ( + <> +
+ + setAccount(e.target.value)} + className="bg-muted border-border focus-visible:ring-purple-500" + /> +

+ Your Snowflake account identifier (e.g., myorg-account) +

+
-
- - setPort(e.target.value)} - className="bg-muted border-border focus-visible:ring-purple-500" - /> -
+
+ + setDatabase(e.target.value)} + className="bg-muted border-border focus-visible:ring-purple-500" + /> +
-
- - setDatabase(e.target.value)} - className="bg-muted border-border focus-visible:ring-purple-500" - /> -
+
+ + setSnowflakeSchema(e.target.value)} + className="bg-muted border-border focus-visible:ring-purple-500" + /> +

+ Defaults to PUBLIC if not specified +

+
-
- - setUsername(e.target.value)} - className="bg-muted border-border focus-visible:ring-purple-500" - /> -
+
+ + setWarehouse(e.target.value)} + className="bg-muted border-border focus-visible:ring-purple-500" + /> +

+ Defaults to COMPUTE_WH if not specified +

+
-
- - setPassword(e.target.value)} - className="bg-muted border-border focus-visible:ring-purple-500" - /> -
+
+ + setUsername(e.target.value)} + className="bg-muted border-border focus-visible:ring-purple-500" + /> +
+ + {/* Auth Mode Toggle */} +
+ +
+ + +
+
+ + {authMode === 'password' ? ( +
+ + setPassword(e.target.value)} + className="bg-muted border-border focus-visible:ring-purple-500" + /> +
+ ) : ( + <> +
+ +