diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..d7b8e39 --- /dev/null +++ b/.env.example @@ -0,0 +1,21 @@ +GOOGLE_API_KEY="your-google-api-key-here" + +# API Security +# Generate a secure API key for your application +API_KEY="your-secure-api-key-here" + +# Database Configuration +DB_USER="marketting" +DB_PASSWORD="password" # Add password for production +DB_HOST="localhost" # Use "db" for Docker Compose +DB_PORT=5432 +DB_NAME="docuquery_db" + +# Redis Configuration (for Celery) +REDIS_HOST="localhost" # Use "redis" for Docker Compose +REDIS_PORT=6379 + +# Note: When using Docker Compose, the following environment variables +# are automatically overridden in docker-compose.yml: +# - DB_HOST=db (for containers to connect to PostgreSQL service) +# - REDIS_HOST=redis (for containers to connect to Redis service) \ No newline at end of file diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..cd4821d --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,162 @@ +name: CI Pipeline + +on: + push: + branches: + - '**' + pull_request: + branches: + - '**' + workflow_dispatch: + +jobs: + test: + runs-on: ubuntu-latest + + services: + postgres: + image: pgvector/pgvector:pg16 + env: + POSTGRES_USER: postgres + POSTGRES_PASSWORD: postgres + POSTGRES_DB: docuquery_db + options: >- + --health-cmd pg_isready + --health-interval 10s + --health-timeout 5s + --health-retries 5 + ports: + - 5432:5432 + + redis: + image: redis:7-alpine + options: >- + --health-cmd "redis-cli ping" + --health-interval 10s + --health-timeout 5s + --health-retries 5 + ports: + - 6379:6379 + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Python 3.12 + uses: actions/setup-python@v5 + with: + python-version: '3.12' + + - name: Install uv + run: | + pip install --upgrade pip + pip install uv + + - name: Cache uv dependencies + uses: actions/cache@v4 + with: + path: ~/.cache/uv + key: ${{ runner.os }}-uv-${{ hashFiles('pyproject.toml') }} + restore-keys: | + ${{ runner.os }}-uv- + + - name: Cache model files + uses: actions/cache@v4 + with: + path: | + ~/.cache/huggingface + ./model_cache + key: ${{ runner.os }}-models-${{ hashFiles('pyproject.toml') }} + restore-keys: | + ${{ runner.os }}-models- + + - name: Install dependencies + run: | + uv pip install --system ".[test]" + + - name: Set up environment variables + run: | + cat > .env < api.log 2>&1 & + echo $! > api.pid + sleep 5 # Wait for server to start + + - name: Start Celery worker in background + run: | + nohup celery -A app.worker.celery worker --loglevel=info > worker.log 2>&1 & + echo $! > worker.pid + sleep 5 # Wait for worker to start + + - name: Check API health + run: | + for i in {1..30}; do + if curl -f http://localhost:8000/docs > /dev/null 2>&1; then + echo "API is ready" + break + fi + echo "Waiting for API..." + sleep 1 + done + curl -f http://localhost:8000/docs || (echo "API failed to start" && cat api.log && exit 1) + + - name: Run tests + run: | + python -m pytest -v --tb=short + + - name: Upload API logs on failure + if: failure() + uses: actions/upload-artifact@v4 + with: + name: api-logs + path: api.log + + - name: Upload worker logs on failure + if: failure() + uses: actions/upload-artifact@v4 + with: + name: worker-logs + path: worker.log + + - name: Stop services + if: always() + run: | + if [ -f api.pid ]; then + kill $(cat api.pid) || true + fi + if [ -f worker.pid ]; then + kill $(cat worker.pid) || true + fi \ No newline at end of file diff --git a/.gitignore b/.gitignore index b7faf40..612649c 100644 --- a/.gitignore +++ b/.gitignore @@ -205,3 +205,12 @@ cython_debug/ marimo/_static/ marimo/_lsp/ __marimo__/ + +design_docs/ + +# Model cache directory +model_cache/ + +models/ + +*.lock diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..f5dc62f --- /dev/null +++ b/Dockerfile @@ -0,0 +1,15 @@ +FROM python:3.12-slim + +WORKDIR /app + +ENV PYTHONUNBUFFERED=1 + +RUN pip install --no-cache-dir uv + +COPY . . + +RUN uv pip install --system ".[test]" + +EXPOSE 8000 + +CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"] \ No newline at end of file diff --git a/README.md b/README.md index 9f37515..bac1a58 100644 --- a/README.md +++ b/README.md @@ -1 +1,648 @@ -# DocuQuery-API \ No newline at end of file +# DocuQuery API + +A powerful document intelligence system that enables natural language querying of uploaded documents using advanced vector search and retrieval-augmented generation (RAG) technology. + +[![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/) +[![FastAPI](https://img.shields.io/badge/FastAPI-0.120+-green.svg)](https://fastapi.tiangolo.com) +[![PostgreSQL](https://img.shields.io/badge/PostgreSQL-16+-blue.svg)](https://www.postgresql.org) +[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) + +DocuQuery API transforms static documents into an intelligent knowledge base, allowing users to ask questions in natural language and receive precise, contextual answers extracted from their document collections. + +## Quick Start + +Get DocuQuery running in under 5 minutes: + +```bash +# Clone the repository +git clone https://github.com/Igboke/DocuQuery-API.git +cd DocuQuery-API + +# Copy environment configuration +cp .env.example .env +# Edit .env with your Google API key and other settings + +# Start all services +docker-compose up -d + +# Run database migrations +docker-compose exec api alembic upgrade head + +# Verify installation +curl http://localhost:8000/docs +``` + +Visit http://localhost:8000/docs to explore the interactive API documentation. + +## What is DocuQuery API? + +### For Beginners +DocuQuery API is like having a smart assistant that reads through all your documents and can instantly answer questions about their content. Upload ZIP files containing documents, ask questions in plain English, and get accurate answers with source citations. + +### For Developers +DocuQuery API is a production-ready document intelligence platform built on modern technologies: + +- **Vector Database**: Uses PostgreSQL with pgvector extension for semantic search +- **Embedding Models**: Leverages sentence transformers for document vectorization +- **Language Models**: Integrates with Google's Generative AI for answer generation +- **Asynchronous Processing**: Celery-based background task queue for document ingestion +- **Semantic Caching**: Intelligent caching system for improved response times +- **Rate Limiting**: Built-in API protection and usage controls + +### Key Features + +- **Natural Language Queries**: Ask questions in conversational language +- **Document Upload**: Support for ZIP archives containing multiple document types +- **Semantic Search**: Vector-based similarity search for relevant content retrieval +- **Source Attribution**: Every answer includes references to source documents +- **Background Processing**: Asynchronous document ingestion and indexing +- **Intelligent Caching**: Semantic similarity-based response caching +- **RESTful API**: Clean, well-documented API endpoints +- **Production Ready**: Comprehensive logging, monitoring, and error handling + +### Use Cases + +- **Knowledge Management**: Create searchable repositories from document collections +- **Research Assistance**: Quickly find relevant information across large document sets +- **Customer Support**: Build intelligent FAQ systems from documentation +- **Legal Document Review**: Efficiently search through contracts and legal documents +- **Academic Research**: Query research papers and academic literature +- **Business Intelligence**: Extract insights from reports and business documents + +## Architecture Overview + +``` +┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ +│ Client App │ │ DocuQuery │ │ External │ +│ │ │ API │ │ Services │ +│ Web/Mobile/CLI │◄───┤ (FastAPI) │◄───┤ Google AI │ +└─────────────────┘ └─────────────────┘ └─────────────────┘ + │ + ▼ + ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ + │ Redis │ │ PostgreSQL │ │ Celery │ + │ (Task Queue) │◄───┤ (Vector Store) │◄───┤ Workers │ + └─────────────────┘ └─────────────────┘ └─────────────────┘ +``` + +### Component Breakdown + +- **FastAPI Application**: Handles HTTP requests, authentication, and API routing +- **PostgreSQL + pgvector**: Stores documents, chunks, and vector embeddings +- **Redis**: Message broker for background task queue +- **Celery Workers**: Process document ingestion and embedding generation +- **Google Generative AI**: Provides language model capabilities for answer generation +- **Embedding Models**: Transform text into vector representations for semantic search + +### Data Flow + +1. **Document Upload**: User uploads ZIP file via API endpoint +2. **Background Processing**: Celery worker extracts and chunks documents +3. **Embedding Generation**: Text chunks are converted to vector embeddings +4. **Storage**: Chunks and embeddings stored in PostgreSQL with vector indexes +5. **Query Processing**: User questions are embedded and matched against document vectors +6. **Answer Generation**: Retrieved contexts are sent to language model for answer synthesis +7. **Response**: User receives answer with source document references + +## Installation & Setup + +### Prerequisites + +- **Docker & Docker Compose**: For the easiest setup experience +- **Python 3.12+**: Required for local development +- **PostgreSQL 16+**: With pgvector extension (handled automatically in Docker) +- **Redis**: For task queue management (included in Docker setup) +- **Google API Key**: Required for generative AI features + +### Option A: Docker Compose (Recommended) + +The Docker setup provides a complete environment with all dependencies pre-configured: + +```bash +# 1. Clone the repository +git clone https://github.com/Igboke/DocuQuery-API.git +cd DocuQuery-API + +# 2. Set up environment variables +cp .env.example .env +# Edit .env file with your configuration (see Environment Configuration below) + +# 3. Start all services +docker-compose up -d + +# 4. Run database migrations +docker-compose exec api alembic upgrade head + +# 5. Verify services are running +docker-compose ps +``` + +### Option B: Local Development Setup + +For development or custom deployments: + +```bash +# 1. Install Python dependencies +pip install uv +uv pip install ".[test]" + +# 2. Set up PostgreSQL with pgvector +# Install PostgreSQL 16+ and the pgvector extension +createdb docuquery_db +psql docuquery_db -c "CREATE EXTENSION vector;" + +# 3. Set up Redis +# Install and start Redis server on default port 6379 + +# 4. Configure environment +cp .env.example .env +# Edit .env with your local database and Redis settings + +# 5. Run database migrations +alembic upgrade head + +# 6. Start the application +uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload + +# 7. Start Celery worker (in a separate terminal) +celery -A app.worker.celery worker --loglevel=info +``` + +### Environment Configuration + +Edit your `.env` file with the following required settings: + +```bash +# Google API Configuration (Required) +GOOGLE_API_KEY="your-google-api-key-here" + +# API Security (Required) +# Generate a secure random string for API authentication +API_KEY="your-secure-api-key-here" + +# Database Configuration +DB_USER="marketting" +DB_PASSWORD="password" +DB_HOST="localhost" # Use "db" for Docker Compose +DB_PORT=5432 +DB_NAME="docuquery_db" + +# Redis Configuration +REDIS_HOST="localhost" # Use "redis" for Docker Compose +REDIS_PORT=6379 +``` + +### Database Setup & Migrations + +The application uses Alembic for database migrations: + +```bash +# Apply all migrations (creates tables and indexes) +alembic upgrade head + +# Check migration status +alembic current + +# Create new migration (for developers) +alembic revision --autogenerate -m "Description of changes" +``` + +## API Documentation + +### Authentication + +All API endpoints require authentication via API key header: + +```bash +# Include this header in all requests +X-API-KEY: your-api-key-here +``` + +### Core Endpoints + +#### Document Upload + +Upload ZIP files containing documents for processing. + +**Endpoint**: `POST /api/v1/documents/upload` + +**Request**: +```bash +curl -X POST http://localhost:8000/api/v1/documents/upload \ + -H "X-API-KEY: your-api-key" \ + -F "file=@documents.zip" +``` + +**Response**: +```json +{ + "job_id": "550e8400-e29b-41d4-a716-446655440000", + "filename": "documents.zip", + "status": "PENDING", +} +``` + +**Supported File Types**: ZIP archives containing text documents (MD), (PDF, DOCX, TXT, etc. to come) + +#### Query Documents + +Ask natural language questions about uploaded documents. + +**Endpoint**: `POST /api/v1/query` + +**Request**: +```bash +curl -X POST http://localhost:8000/api/v1/query \ + -H "X-API-KEY: your-api-key" \ + -H "Content-Type: application/json" \ + -d '{"question": "What is the main topic of the uploaded documents?"}' +``` + +**Response**: +```json +{ + "answer": "The uploaded documents primarily focus on API development best practices, covering topics such as RESTful design patterns, authentication mechanisms, and error handling strategies.", + "sources": [ + { + "document_filename": "api-guide.pdf", + "chunk_text": "API development requires careful consideration of...", + } + ] +} +``` + +#### Health Check + +Verify API status and dependencies. + +**Endpoint**: `GET /health/ping` + +**Endpoint**: `GET /health/db` + +### Error Handling + +The API uses standard HTTP status codes and provides detailed error messages: + +```json +{ + "detail": "Invalid file type. Only ZIP archives are supported.", + "error_code": "INVALID_FILE_TYPE", + "timestamp": "2024-11-11T10:30:00Z" +} +``` + +Common status codes: +- `200`: Success +- `202`: Accepted (background processing started) +- `400`: Bad Request (invalid input) +- `401`: Unauthorized (missing or invalid API key) +- `422`: Validation Error (malformed request data) +- `429`: Rate Limit Exceeded +- `500`: Internal Server Error + +## Usage Examples + +### Basic Document Upload + +```python +import requests + +with open('documents.zip', 'rb') as f: + response = requests.post( + 'http://localhost:8000/api/v1/documents/upload', + headers={'X-API-KEY': 'your-api-key'}, + files={'file': f} + ) + +job_data = response.json() +print(f"Upload job ID: {job_data['job_id']}") +``` + +### Querying Documents + +```python +import requests + +response = requests.post( + 'http://localhost:8000/api/v1/query', + headers={ + 'X-API-KEY': 'your-api-key', + 'Content-Type': 'application/json' + }, + json={'question': 'What are the key findings in the research?'} +) + +result = response.json() +print(f"Answer: {result['answer']}") +print(f"Sources: {len(result['sources'])} documents") +``` + +### JavaScript Integration + +```javascript + +const formData = new FormData(); +formData.append('file', fileInput.files[0]); + +fetch('http://localhost:8000/api/v1/documents/upload', { + method: 'POST', + headers: { + 'X-API-KEY': 'your-api-key' + }, + body: formData +}) +.then(response => response.json()) +.then(data => console.log('Upload successful:', data)); + +fetch('http://localhost:8000/api/v1/query', { + method: 'POST', + headers: { + 'X-API-KEY': 'your-api-key', + 'Content-Type': 'application/json' + }, + body: JSON.stringify({ + question: 'What is the main conclusion?' + }) +}) +.then(response => response.json()) +.then(data => console.log('Answer:', data.answer)); +``` + +### Rate Limiting + +The API includes built-in rate limiting: + +- **Query Endpoint**: 5 requests per minute +- **Upload Endpoint**: 3 uploads per minute +- **Rate limit headers** included in responses + +```bash + +curl -I http://localhost:8000/api/v1/query \ + -H "X-API-KEY: your-api-key" + +``` + +## Development + +### Project Structure + +``` +DocuQuery-API/ +├── app/ +│ ├── api/ # API route definitions +│ │ └── v1/ # Version 1 endpoints +│ ├── core/ # Core functionality +│ │ ├── config.py # Configuration management +│ │ ├── database.py # Database connections +│ │ └── security.py # Authentication logic +│ ├── models/ # Database models +│ ├── repositories/ # Data access layer +│ ├── schemas/ # Pydantic schemas +│ ├── services/ # Business logic +│ ├── tests/ # Test suite +│ ├── main.py # Application entry point +│ └── worker.py # Celery worker tasks +├── alembic/ # Database migrations +├── .github/ +│ └── workflows/ # CI/CD pipeline +├── docker-compose.yml # Service orchestration +├── Dockerfile # Container definition +└── pyproject.toml # Python dependencies +``` + +### Running Tests + +```bash +python -m pytest -v + +python -m pytest --cov=app --cov-report=html + +python -m pytest app/tests/api/v1/test_query.py -v + +docker-compose exec api python -m pytest -v +``` + +### Code Quality Tools + +The project uses several tools to maintain code quality: + +```bash +mypy app/ + +black app/ +ruff format app/ + +ruff check app/ + +bandit -r app/ +``` + +### Contributing Guidelines + +1. **Fork the repository** and create a feature branch +2. **Write tests** for new functionality +3. **Ensure all tests pass** and maintain coverage above 80% +4. **Follow code style** guidelines (Black + Ruff) +5. **Update documentation** for user-facing changes +6. **Submit a pull request** with clear description + +## Deployment + +### Docker Production Setup + +For production deployment, use the multi-stage Dockerfile: + +```dockerfile +FROM python:3.12-slim as production + +RUN adduser --disabled-password --gecos '' appuser + +COPY requirements.txt . +RUN pip install -r requirements.txt + +COPY --chown=appuser:appuser app/ /app/ +USER appuser + +CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"] +``` + +### Environment Variables Reference + +```bash +GOOGLE_API_KEY=your-google-api-key +API_KEY=your-secure-api-key + +DB_HOST=db-server.example.com +DB_PORT=5432 +DB_NAME=docuquery_production +DB_USER=docuquery +DB_PASSWORD=secure-password + +REDIS_HOST=redis-server.example.com +REDIS_PORT=6379 + +``` + +### Scaling Considerations + +- **Horizontal Scaling**: Multiple API instances behind a load balancer +- **Worker Scaling**: Scale Celery workers based on queue length +- **Database**: Use read replicas for query-heavy workloads +- **Caching**: Redis cluster for high-availability caching +- **File Storage**: Object storage (S3, GCS) for uploaded documents + +### Monitoring & Logging + +Built-in monitoring endpoints: + +```bash +GET /metrics + +GET /health + +docker-compose logs api +``` + +## Advanced Features + +### Semantic Caching + +DocuQuery includes intelligent caching that recognizes semantically similar questions: + +```python +# These questions would share the same cached response +"What is machine learning?" +"Can you explain machine learning?" +"What does ML mean?" +``` + +Cache configuration: +- **Similarity Threshold**: 0.3 (configurable) + +### Vector Search Configuration + +Fine-tune search behavior: + +```python +VECTOR_SIMILARITY_THRESHOLD = 0.2 # Lower = more permissive +TOP_K_RESULTS = 5 # Number of chunks to retrieve +EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2" +``` + +### Background Task Processing + +Monitor and manage background tasks: + +```bash +# View active workers +celery -A app.worker.celery inspect active + +# Monitor task queue +celery -A app.worker.celery inspect reserved + +# View task statistics +celery -A app.worker.celery inspect stats +``` + +### Performance Tuning + +- **Database Indexes**: Optimize vector search with HNSW indexes +- **Chunk Size**: Balance context quality vs. search precision +- **Embedding Batch Size**: Optimize memory usage during ingestion +- **Connection Pooling**: Configure database connection limits + +## Troubleshooting + +### Common Issues & Solutions + +**Issue: "ModuleNotFoundError: No module named 'app.core'"** +```bash +# Solution: Use module execution for tests +python -m pytest instead of pytest +``` + +**Issue: "Invalid or missing API Key"** +```bash +# Solution: Check X-API-KEY header in requests +curl -H "X-API-KEY: your-key" http://localhost:8000/health +``` + +**Issue: "Connection refused to PostgreSQL"** +```bash +# Solution: Verify services are running +docker-compose ps +docker-compose logs db +``` + +**Issue: "Celery worker not processing tasks"** +```bash +# Solution: Check worker status and logs +docker-compose logs worker +celery -A app.worker.celery inspect active +``` + +### Debugging Tips + +1. **Check Service Health**: Use `/health` endpoint for diagnostics +2. **Monitor Resource Usage**: Watch CPU/memory during document processing +3. **Validate Environment**: Ensure all required environment variables are set + +### Log Analysis + +Key log patterns to monitor: + +```bash +# Successful document processing +grep "Document processing completed" app.log + +# API errors +grep "ERROR" app.log | grep "api" + +# Database connection issues +grep "database" app.log | grep -i "error" + +# Rate limiting events +grep "Rate limit exceeded" app.log +``` + +### FAQ + +**Q: How large can uploaded ZIP files be?** +A: There is currently no max size + +**Q: What document formats are supported?** +A: MD formats within ZIP archives. + +**Q: How do I backup the vector database?** +A: Use PostgreSQL backup tools: `pg_dump docuquery_db > backup.sql` + +**Q: Can I use a different embedding model?** +A: Yes, set `MODEL_NAME` in configuration to any sentence-transformers model. + +**Q: How do I monitor API performance?** +A: Use the `/metrics` endpoint with Prometheus for comprehensive monitoring. + +## License + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. + +## Contributing + +We welcome contributions! + +### Reporting Issues + +Please use the [GitHub issue tracker](https://github.com/Igboke/DocuQuery-API/issues) to report bugs or request features. + +## Support & Community + +- **Documentation**: Comprehensive API docs available at `/docs` endpoint +- **Issues**: [GitHub Issues](https://github.com/Igboke/DocuQuery-API/issues) +- **Email**: For security issues, contact [danieligboke669@gmail.com] + +--- + +**Built with**: FastAPI, PostgreSQL, Redis, Celery, OpenAI, Docker + +**Maintained by**: [Igboke](https://github.com/Igboke) \ No newline at end of file diff --git a/alembic.ini b/alembic.ini new file mode 100644 index 0000000..aa73379 --- /dev/null +++ b/alembic.ini @@ -0,0 +1,147 @@ +# A generic, single database configuration. + +[alembic] +# path to migration scripts. +# this is typically a path given in POSIX (e.g. forward slashes) +# format, relative to the token %(here)s which refers to the location of this +# ini file +script_location = %(here)s/alembic + +# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s +# Uncomment the line below if you want the files to be prepended with date and time +# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file +# for all available tokens +# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s + +# sys.path path, will be prepended to sys.path if present. +# defaults to the current working directory. for multiple paths, the path separator +# is defined by "path_separator" below. +prepend_sys_path = . + +# timezone to use when rendering the date within the migration file +# as well as the filename. +# If specified, requires the python>=3.9 or backports.zoneinfo library and tzdata library. +# Any required deps can installed by adding `alembic[tz]` to the pip requirements +# string value is passed to ZoneInfo() +# leave blank for localtime +# timezone = + +# max length of characters to apply to the "slug" field +# truncate_slug_length = 40 + +# set to 'true' to run the environment during +# the 'revision' command, regardless of autogenerate +# revision_environment = false + +# set to 'true' to allow .pyc and .pyo files without +# a source .py file to be detected as revisions in the +# versions/ directory +# sourceless = false + +# version location specification; This defaults +# to /versions. When using multiple version +# directories, initial revisions must be specified with --version-path. +# The path separator used here should be the separator specified by "path_separator" +# below. +# version_locations = %(here)s/bar:%(here)s/bat:%(here)s/alembic/versions + +# path_separator; This indicates what character is used to split lists of file +# paths, including version_locations and prepend_sys_path within configparser +# files such as alembic.ini. +# The default rendered in new alembic.ini files is "os", which uses os.pathsep +# to provide os-dependent path splitting. +# +# Note that in order to support legacy alembic.ini files, this default does NOT +# take place if path_separator is not present in alembic.ini. If this +# option is omitted entirely, fallback logic is as follows: +# +# 1. Parsing of the version_locations option falls back to using the legacy +# "version_path_separator" key, which if absent then falls back to the legacy +# behavior of splitting on spaces and/or commas. +# 2. Parsing of the prepend_sys_path option falls back to the legacy +# behavior of splitting on spaces, commas, or colons. +# +# Valid values for path_separator are: +# +# path_separator = : +# path_separator = ; +# path_separator = space +# path_separator = newline +# +# Use os.pathsep. Default configuration used for new projects. +path_separator = os + + +# set to 'true' to search source files recursively +# in each "version_locations" directory +# new in Alembic version 1.10 +# recursive_version_locations = false + +# the output encoding used when revision files +# are written from script.py.mako +# output_encoding = utf-8 + +# database URL. This is consumed by the user-maintained env.py script only. +# other means of configuring database URLs may be customized within the env.py +# file. +sqlalchemy.url = %(DB_URL)s + + +[post_write_hooks] +# post_write_hooks defines scripts or Python functions that are run +# on newly generated revision scripts. See the documentation for further +# detail and examples + +# format using "black" - use the console_scripts runner, against the "black" entrypoint +# hooks = black +# black.type = console_scripts +# black.entrypoint = black +# black.options = -l 79 REVISION_SCRIPT_FILENAME + +# lint with attempts to fix using "ruff" - use the module runner, against the "ruff" module +# hooks = ruff +# ruff.type = module +# ruff.module = ruff +# ruff.options = check --fix REVISION_SCRIPT_FILENAME + +# Alternatively, use the exec runner to execute a binary found on your PATH +# hooks = ruff +# ruff.type = exec +# ruff.executable = ruff +# ruff.options = check --fix REVISION_SCRIPT_FILENAME + +# Logging configuration. This is also consumed by the user-maintained +# env.py script only. +[loggers] +keys = root,sqlalchemy,alembic + +[handlers] +keys = console + +[formatters] +keys = generic + +[logger_root] +level = WARNING +handlers = console +qualname = + +[logger_sqlalchemy] +level = WARNING +handlers = +qualname = sqlalchemy.engine + +[logger_alembic] +level = INFO +handlers = +qualname = alembic + +[handler_console] +class = StreamHandler +args = (sys.stderr,) +level = NOTSET +formatter = generic + +[formatter_generic] +format = %(levelname)-5.5s [%(name)s] %(message)s +datefmt = %H:%M:%S diff --git a/alembic/README b/alembic/README new file mode 100644 index 0000000..e0d0858 --- /dev/null +++ b/alembic/README @@ -0,0 +1 @@ +Generic single-database configuration with an async dbapi. \ No newline at end of file diff --git a/alembic/env.py b/alembic/env.py new file mode 100644 index 0000000..270469f --- /dev/null +++ b/alembic/env.py @@ -0,0 +1,94 @@ +import asyncio +from logging.config import fileConfig + +from sqlalchemy import pool +from sqlalchemy.engine import Connection +from sqlalchemy.ext.asyncio import async_engine_from_config + +from app.core.config import settings +from app.models.base import Base + +from alembic import context + +# this is the Alembic Config object, which provides +# access to the values within the .ini file in use. +config = context.config + +config.set_main_option("DB_URL", settings.DATABASE_URL) + +# Interpret the config file for Python logging. +# This line sets up loggers basically. +if config.config_file_name is not None: + fileConfig(config.config_file_name) + +# add your model's MetaData object here +# for 'autogenerate' support +# from myapp import mymodel +# target_metadata = mymodel.Base.metadata +target_metadata = Base.metadata + +# other values from the config, defined by the needs of env.py, +# can be acquired: +# my_important_option = config.get_main_option("my_important_option") +# ... etc. + + +def run_migrations_offline() -> None: + """Run migrations in 'offline' mode. + + This configures the context with just a URL + and not an Engine, though an Engine is acceptable + here as well. By skipping the Engine creation + we don't even need a DBAPI to be available. + + Calls to context.execute() here emit the given string to the + script output. + + """ + url = config.get_main_option("sqlalchemy.url") + context.configure( + url=url, + target_metadata=target_metadata, + literal_binds=True, + dialect_opts={"paramstyle": "named"}, + ) + + with context.begin_transaction(): + context.run_migrations() + + +def do_run_migrations(connection: Connection) -> None: + context.configure(connection=connection, target_metadata=target_metadata) + + with context.begin_transaction(): + context.run_migrations() + + +async def run_async_migrations() -> None: + """In this scenario we need to create an Engine + and associate a connection with the context. + + """ + + connectable = async_engine_from_config( + config.get_section(config.config_ini_section, {}), + prefix="sqlalchemy.", + poolclass=pool.NullPool, + ) + + async with connectable.connect() as connection: + await connection.run_sync(do_run_migrations) + + await connectable.dispose() + + +def run_migrations_online() -> None: + """Run migrations in 'online' mode.""" + + asyncio.run(run_async_migrations()) + + +if context.is_offline_mode(): + run_migrations_offline() +else: + run_migrations_online() diff --git a/alembic/script.py.mako b/alembic/script.py.mako new file mode 100644 index 0000000..1101630 --- /dev/null +++ b/alembic/script.py.mako @@ -0,0 +1,28 @@ +"""${message} + +Revision ID: ${up_revision} +Revises: ${down_revision | comma,n} +Create Date: ${create_date} + +""" +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa +${imports if imports else ""} + +# revision identifiers, used by Alembic. +revision: str = ${repr(up_revision)} +down_revision: Union[str, Sequence[str], None] = ${repr(down_revision)} +branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)} +depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)} + + +def upgrade() -> None: + """Upgrade schema.""" + ${upgrades if upgrades else "pass"} + + +def downgrade() -> None: + """Downgrade schema.""" + ${downgrades if downgrades else "pass"} diff --git a/alembic/versions/4413860a671e_create_initial_tables_for_documents_and_.py b/alembic/versions/4413860a671e_create_initial_tables_for_documents_and_.py new file mode 100644 index 0000000..327fa5c --- /dev/null +++ b/alembic/versions/4413860a671e_create_initial_tables_for_documents_and_.py @@ -0,0 +1,71 @@ +"""Create initial tables for documents and chunks + +Revision ID: 4413860a671e +Revises: +Create Date: 2025-11-01 14:13:01.472834 + +""" +from typing import Sequence, Union + +from alembic import op +import pgvector +import sqlalchemy as sa +from sqlalchemy.dialects import postgresql + +# revision identifiers, used by Alembic. +revision: str = '4413860a671e' +down_revision: Union[str, Sequence[str], None] = None +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + """Upgrade schema.""" + # Enable pgvector extension + op.execute('CREATE EXTENSION IF NOT EXISTS vector') + + # ### commands auto generated by Alembic - please adjust! ### + op.create_table('documents', + sa.Column('id', sa.UUID(), nullable=False), + sa.Column('filename', sa.String(), nullable=False), + sa.Column('status', postgresql.ENUM('PENDING', 'PROCESSING', 'COMPLETED', 'FAILED', name='ingestion_status', create_type=True), nullable=False), + sa.Column('error_message', sa.String(), nullable=True), + sa.Column('created_at', sa.TIMESTAMP(timezone=True), server_default=sa.text('now()'), nullable=False), + sa.Column('updated_at', sa.TIMESTAMP(timezone=True), server_default=sa.text('now()'), nullable=False), + sa.PrimaryKeyConstraint('id'), + sa.UniqueConstraint('filename') + ) + op.create_table('chunks', + sa.Column('id', sa.UUID(), nullable=False), + sa.Column('document_id', sa.UUID(), nullable=False), + sa.Column('chunk_text', sa.String(), nullable=False), + sa.Column('chunk_metadata', postgresql.JSONB(astext_type=sa.Text()), nullable=True), + sa.Column('embedding', pgvector.sqlalchemy.vector.VECTOR(dim=384), nullable=False), + sa.ForeignKeyConstraint(['document_id'], ['documents.id'], ondelete='CASCADE'), + sa.PrimaryKeyConstraint('id') + ) + + op.create_index( + 'ix_chunks_embedding', + 'chunks', + ['embedding'], + unique=False, + postgresql_using='hnsw', + postgresql_with={ + 'm': 16, + 'ef_construction': 64 + }, + postgresql_ops={ + 'embedding': 'vector_cosine_ops' + } + ) + # ### end Alembic commands ### + + +def downgrade() -> None: + """Downgrade schema.""" + # ### commands auto generated by Alembic - please adjust! ### + op.drop_table('chunks') + op.drop_table('documents') + postgresql.ENUM(name='ingestion_status').drop(op.get_bind(), checkfirst=True) + # ### end Alembic commands ### diff --git a/alembic/versions/a0f7ab8486ce_add_cached_queries_table_for_semantic_.py b/alembic/versions/a0f7ab8486ce_add_cached_queries_table_for_semantic_.py new file mode 100644 index 0000000..e5a6856 --- /dev/null +++ b/alembic/versions/a0f7ab8486ce_add_cached_queries_table_for_semantic_.py @@ -0,0 +1,40 @@ +"""Add cached_queries table for semantic caching new + +Revision ID: a0f7ab8486ce +Revises: e40291de16a1 +Create Date: 2025-11-10 12:33:50.351956 + +""" +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa +from sqlalchemy.dialects import postgresql + +# revision identifiers, used by Alembic. +revision: str = 'a0f7ab8486ce' +down_revision: Union[str, Sequence[str], None] = 'e40291de16a1' +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + """Upgrade schema.""" + # ### commands auto generated by Alembic - please adjust! ### + op.create_table('cached_query_chunks_link', + sa.Column('cached_query_id', sa.UUID(), nullable=False), + sa.Column('chunk_id', sa.UUID(), nullable=False), + sa.ForeignKeyConstraint(['cached_query_id'], ['cached_queries.id'], ondelete='CASCADE'), + sa.ForeignKeyConstraint(['chunk_id'], ['chunks.id'], ondelete='CASCADE'), + sa.PrimaryKeyConstraint('cached_query_id', 'chunk_id') + ) + op.drop_column('cached_queries', 'response_sources') + # ### end Alembic commands ### + + +def downgrade() -> None: + """Downgrade schema.""" + # ### commands auto generated by Alembic - please adjust! ### + op.add_column('cached_queries', sa.Column('response_sources', postgresql.JSONB(astext_type=sa.Text()), autoincrement=False, nullable=False)) + op.drop_table('cached_query_chunks_link') + # ### end Alembic commands ### diff --git a/alembic/versions/e40291de16a1_add_cached_queries_table_for_semantic_.py b/alembic/versions/e40291de16a1_add_cached_queries_table_for_semantic_.py new file mode 100644 index 0000000..7cca569 --- /dev/null +++ b/alembic/versions/e40291de16a1_add_cached_queries_table_for_semantic_.py @@ -0,0 +1,48 @@ +"""Add cached_queries table for semantic caching + +Revision ID: e40291de16a1 +Revises: 4413860a671e +Create Date: 2025-11-10 11:43:37.650436 + +""" +from typing import Sequence, Union + +from alembic import op +import pgvector +import sqlalchemy as sa +from sqlalchemy.dialects import postgresql + +# revision identifiers, used by Alembic. +revision: str = 'e40291de16a1' +down_revision: Union[str, Sequence[str], None] = '4413860a671e' +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + """Upgrade schema.""" + # ### commands auto generated by Alembic - please adjust! ### + op.create_table('cached_queries', + sa.Column('id', sa.UUID(), nullable=False), + sa.Column('question_text', sa.String(), nullable=False), + sa.Column('question_embedding', pgvector.sqlalchemy.vector.VECTOR(dim=384), nullable=False), + sa.Column('response_answer', sa.String(), nullable=False), + sa.Column('response_sources', postgresql.JSONB(astext_type=sa.Text()), nullable=False), + sa.Column('created_at', sa.DateTime(timezone=True), nullable=False), + sa.PrimaryKeyConstraint('id') + ) + op.create_index( + 'ix_cached_queries_embedding', + 'cached_queries', + ['question_embedding'], + unique=False, + postgresql_using='hnsw', + postgresql_ops={'question_embedding': 'vector_cosine_ops'} + ) + + +def downgrade() -> None: + """Downgrade schema.""" + # ### commands auto generated by Alembic - please adjust! ### + op.drop_table('cached_queries') + # ### end Alembic commands ### diff --git a/app/__init__.py b/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/api/health_check.py b/app/api/health_check.py new file mode 100644 index 0000000..3e0467d --- /dev/null +++ b/app/api/health_check.py @@ -0,0 +1,29 @@ +from fastapi import APIRouter, Depends, HTTPException +from sqlalchemy.exc import OperationalError +from app.services.health_service import HealthService +from app.dependencies import get_health_service + +router = APIRouter() + +@router.get("/ping",summary="Check Network Connection") +async def ping(): + return {"status":"ok"} + +@router.get("/db",summary="Check the database connection") +async def check_db_connection( + service: HealthService = Depends(get_health_service) +): + try: + return await service.check_db_connection() + except OperationalError as e: + raise HTTPException( + status_code=503, + detail=f"Could not connect to the database: {e}", + ) from e + except Exception as e: + raise HTTPException( + status_code=500, + detail=f"An unexpected error occurred during DB check: {e}" + ) from e + + diff --git a/app/api/v1/documents.py b/app/api/v1/documents.py new file mode 100644 index 0000000..4d0ec79 --- /dev/null +++ b/app/api/v1/documents.py @@ -0,0 +1,68 @@ +import uuid +from fastapi import APIRouter, Depends, Request, UploadFile, File, HTTPException, status +from app.dependencies import limiter +import logging +from app.core.config import settings +from app.core.security import get_api_key +from app.services.document_service import DocumentService +from app.schemas.document import DocumentJob +from app.dependencies import get_document_service + +logger = logging.getLogger(__name__) +router = APIRouter() + +@router.post("/documents/upload", + response_model=DocumentJob, + status_code=status.HTTP_202_ACCEPTED, + summary="Upload a knowledge base", + dependencies=[Depends(get_api_key)] +) +@limiter.limit("20/minute") +async def upload_documents( + request: Request, + file: UploadFile = File(..., description="A file for the knowledge base."), + service: DocumentService = Depends(get_document_service) +): + """ + Accepts a file for asynchronous processing. + """ + if file.content_type not in settings.ALLOWED_MIME_TYPES: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail=f"Invalid file type. Allowed MIME types are: {', '.join(settings.ALLOWED_MIME_TYPES)}" + ) + + try: + document = await service.process_upload(file) + + except Exception as e: + logger.exception("Error at upload document",exc_info=True) + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail=f"An error occurred while processing the file: {e}" + ) from e + + return DocumentJob(job_id=document.id, filename=document.filename, status=document.status) + +@router.get( + "/documents/{job_id}/status", + response_model=DocumentJob, + summary="Get ingestion job status" +) +async def get_job_status( + job_id: uuid.UUID, + service: DocumentService = Depends(get_document_service) +): + """ + Retrieves the current status of a document processing job. + """ + + document = await service.get_document_by_id(job_id) + + if not document: + raise HTTPException( + status_code=status.HTTP_404_NOT_FOUND, + detail="Job not found." + ) + + return DocumentJob(job_id=document.id, filename=document.filename, status=document.status) \ No newline at end of file diff --git a/app/api/v1/query.py b/app/api/v1/query.py new file mode 100644 index 0000000..c347d59 --- /dev/null +++ b/app/api/v1/query.py @@ -0,0 +1,28 @@ +from fastapi import APIRouter, Depends, status, Request +from app.dependencies import limiter + +from app.core.security import get_api_key +from app.schemas.query import QueryRequest, QueryResponse +from app.services.query_service import QueryService +from app.dependencies import get_query_service + +router = APIRouter() + +@router.post( + "/query", + response_model=QueryResponse, + status_code=status.HTTP_200_OK, + summary="Ask a question", + dependencies=[Depends(get_api_key)] +) +@limiter.limit("5/minute") +def query_knowledgebase( + request: Request, + query_request: QueryRequest, + service: QueryService = Depends(get_query_service) +): + """ + Submits a natural language query and gets a synthesized answer + based on the ingested knowledge base. + """ + return service.answer_question(query_request) \ No newline at end of file diff --git a/app/core/__init__.py b/app/core/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/app/core/config.py b/app/core/config.py new file mode 100644 index 0000000..240faed --- /dev/null +++ b/app/core/config.py @@ -0,0 +1,90 @@ +import os +from fastembed import TextEmbedding +import google.generativeai as genai +from prometheus_client import Histogram +from pydantic_settings import BaseSettings, SettingsConfigDict + +os.environ['HF_HUB_OFFLINE'] = '1' + + +class Settings(BaseSettings): + """ + Application setting are read from here, it gets them from the environment variables + """ + model_config = SettingsConfigDict(env_file=".env", env_file_encoding='utf-8') + + DB_USER: str = os.getenv("DB_USER", "") + DB_PASSWORD: str = os.getenv("DB_PASSWORD", "") + DB_HOST: str = os.getenv("DB_HOST", "localhost") + DB_PORT: int = 5432 + DB_NAME: str = os.getenv("DB_NAME", "name") + + REDIS_HOST: str = os.getenv("REDIS_HOST", "localhost") + REDIS_PORT: int = int(os.getenv("REDIS_PORT", "6379")) + + ALLOWED_FILE_EXTENSIONS: list[str] = ["zip"] + + ALLOWED_MIME_TYPES: set[str] = { + "application/zip", + "application/x-zip-compressed", + } + + UPLOAD_DIRECTORY: str = "./uploads" + + MODEL_CACHE_DIR: str = "./model_cache" + + MODEL_NAME: str = "sentence-transformers/all-MiniLM-L6-v2" + + os.makedirs(UPLOAD_DIRECTORY, exist_ok=True) + os.makedirs(MODEL_CACHE_DIR, exist_ok=True) + + @property + def DATABASE_URL(self) -> str: + return f"postgresql+asyncpg://{self.DB_USER}:{self.DB_PASSWORD}@{self.DB_HOST}:{self.DB_PORT}/{self.DB_NAME}" + + @property + def CELERY_BROKER_URL(self) -> str: + return f"redis://{self.REDIS_HOST}:{self.REDIS_PORT}/0" + + @property + def CELERY_RESULT_BACKEND(self) -> str: + return f"redis://{self.REDIS_HOST}:{self.REDIS_PORT}/0" + + GOOGLE_API_KEY: str = os.getenv("GOOGLE_API_KEY", "default_key") + + API_KEY: str = os.getenv("API_KEY", "default_key") + + +settings = Settings() + +genai.configure(api_key=settings.GOOGLE_API_KEY) + +_embedding_model = None +_generative_model = None + +def get_embedding_model(): + """ + Lazy initialization of the embedding model. + This ensures the model is loaded only once and only when needed. + """ + global _embedding_model + if _embedding_model is None: + _embedding_model = TextEmbedding( + model_name=settings.MODEL_NAME, + cache_dir=settings.MODEL_CACHE_DIR + ) + return _embedding_model + +def get_generative_model(): + """ + Lazy initialization of the Gemini generative model. + """ + global _generative_model + if _generative_model is None: + _generative_model = genai.GenerativeModel('gemini-2.5-flash') + return _generative_model + +LLM_QUERY_DURATION = Histogram( + "llm_query_duration_seconds", + "Histogram of the duration of LLM API calls in seconds." +) diff --git a/app/core/database.py b/app/core/database.py new file mode 100644 index 0000000..ed712a0 --- /dev/null +++ b/app/core/database.py @@ -0,0 +1,26 @@ +import os +from typing import AsyncGenerator +from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker, AsyncSession +from sqlalchemy.exc import SQLAlchemyError +from .config import settings + +engine = create_async_engine(settings.DATABASE_URL) + +AsyncSessionLocal = async_sessionmaker( + bind=engine, + autoflush=False, + expire_on_commit=False +) + +async def get_session() -> AsyncGenerator[AsyncSession, None]: + """ + Provides a database session with automatic transaction management. + Commits on success, rolls back on exception. + """ + async with AsyncSessionLocal() as session: + try: + yield session + await session.commit() + except Exception: + await session.rollback() + raise diff --git a/app/core/db_sync.py b/app/core/db_sync.py new file mode 100644 index 0000000..f262127 --- /dev/null +++ b/app/core/db_sync.py @@ -0,0 +1,39 @@ +from sqlalchemy import create_engine +from sqlalchemy.orm import sessionmaker +from contextlib import contextmanager +from app.core.config import settings + +SYNC_DATABASE_URL = settings.DATABASE_URL.replace("+asyncpg", "").replace("+aiosqlite", "") + +engine = create_engine(SYNC_DATABASE_URL) + +SessionLocalSync = sessionmaker(autocommit=False, autoflush=False, bind=engine) + + +@contextmanager +def get_sync_db(): + """ + Provides a synchronous database session for use in Celery tasks. + """ + db = SessionLocalSync() + try: + yield db + finally: + db.close() + + +def get_sync_db_session(): + """ + A FastAPI dependency that provides a synchronous database session. + It yields the session and ensures it's closed after the request. + Automatically commits on success and rolls back on exceptions. + """ + db = SessionLocalSync() + try: + yield db + db.commit() + except Exception: + db.rollback() + raise + finally: + db.close() diff --git a/app/core/logging_config.py b/app/core/logging_config.py new file mode 100644 index 0000000..358ff6d --- /dev/null +++ b/app/core/logging_config.py @@ -0,0 +1,46 @@ +import logging.config +import sys + +def setup_logging(): + """ + Configures the application's logging to output structured JSON logs. + """ + LOGGING_CONFIG = { + "version": 1, + "disable_existing_loggers": False, + "formatters": { + "json": { + "()": "pythonjsonlogger.jsonlogger.JsonFormatter", + "format": "%(asctime)s %(name)s %(levelname)s %(message)s %(pathname)s %(lineno)d", + }, + }, + "handlers": { + "console": { + "class": "logging.StreamHandler", + "formatter": "json", + "stream": sys.stdout, + }, + }, + "loggers": { + "app": { + "handlers": ["console"], + "level": "INFO", + "propagate": False + }, + "uvicorn": { + "handlers": ["console"], + "level": "INFO", + "propagate": False + }, + "alembic": { + "handlers": ["console"], + "level": "INFO", + "propagate": False + }, + "": { + "handlers": ["console"], + "level": "WARNING", + }, + }, + } + logging.config.dictConfig(LOGGING_CONFIG) \ No newline at end of file diff --git a/app/core/security.py b/app/core/security.py new file mode 100644 index 0000000..3de93bb --- /dev/null +++ b/app/core/security.py @@ -0,0 +1,18 @@ +from fastapi import Security, HTTPException, status +from fastapi.security import APIKeyHeader +from app.core.config import settings + +api_key_header = APIKeyHeader(name="X-API-KEY") + + +def get_api_key(api_key: str = Security(api_key_header)): + """ + Dependency that checks for a valid API key in the X-API-KEY header. + """ + if api_key == settings.API_KEY: + return api_key + else: + raise HTTPException( + status_code=status.HTTP_401_UNAUTHORIZED, + detail="Invalid or missing API Key", + ) \ No newline at end of file diff --git a/app/dependencies.py b/app/dependencies.py new file mode 100644 index 0000000..4884e91 --- /dev/null +++ b/app/dependencies.py @@ -0,0 +1,52 @@ +""" +Dependency injection configuration for FastAPI endpoints. +Provides properly wired services and repositories without exposing database sessions to handlers. +""" +from fastapi import Depends +from sqlalchemy.orm import Session as SyncSession +from sqlalchemy.ext.asyncio import AsyncSession +from slowapi import Limiter +from slowapi.util import get_remote_address + +from app.core.db_sync import get_sync_db_session +from app.core.database import get_session +from app.repositories.chunk_repository import ChunkRepository +from app.repositories.cached_query_repository import CachedQueryRepository +from app.repositories.document_repo import DocumentRepository +from app.services.query_service import QueryService +from app.services.document_service import DocumentService +from app.services.health_service import HealthService + +limiter = Limiter(key_func=get_remote_address) + + + +def get_query_service( + db: SyncSession = Depends(get_sync_db_session) +) -> QueryService: + """ + Provides a fully configured QueryService with all its dependencies. + Handlers depend on this instead of constructing services manually. + """ + chunk_repo = ChunkRepository(db) + cached_query_repo = CachedQueryRepository(db) + return QueryService(chunk_repo, cached_query_repo) + + +def get_document_service( + session: AsyncSession = Depends(get_session) +) -> DocumentService: + """ + Provides a fully configured DocumentService with all its dependencies. + """ + document_repo = DocumentRepository(session) + return DocumentService(document_repo) + + +def get_health_service( + session: AsyncSession = Depends(get_session) +) -> HealthService: + """ + Provides a fully configured HealthService. + """ + return HealthService(session) diff --git a/app/main.py b/app/main.py new file mode 100644 index 0000000..92c0f01 --- /dev/null +++ b/app/main.py @@ -0,0 +1,43 @@ +""" +Creation Factory file +""" + +from fastapi import APIRouter, FastAPI +from slowapi import _rate_limit_exceeded_handler +from slowapi.errors import RateLimitExceeded +from app.core.logging_config import setup_logging +from app.api import health_check +from app.api.v1 import documents as documents_v1 +from app.api.v1 import query as query_v1 +from starlette_prometheus import PrometheusMiddleware, metrics +from app.dependencies import limiter + +def create_app()->FastAPI: + """ + Create app flow + """ + setup_logging() + + app = FastAPI( + title="DocuQuery", + description="RAG", + version="1.0.0" + ) + + app.state.limiter = limiter + + app.add_middleware(PrometheusMiddleware) + + app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler) + + api_router_v1 = APIRouter(prefix="/api/v1") + api_router_v1.include_router(documents_v1.router, tags=["Documents"]) + api_router_v1.include_router(query_v1.router, tags=["Query"]) + + app.include_router(api_router_v1) + app.include_router(health_check.router,prefix="/health",tags=["Health"]) + app.add_route("/metrics", metrics) + + return app + +app = create_app() diff --git a/app/models/__init__.py b/app/models/__init__.py new file mode 100644 index 0000000..18f52c6 --- /dev/null +++ b/app/models/__init__.py @@ -0,0 +1,6 @@ +from .base import Base +from .document import Document, IngestionStatus +from .chunk import Chunk +from .cached_query import CachedQuery + +__all__ = ["Base", "Document", "IngestionStatus", "Chunk", "CachedQuery"] \ No newline at end of file diff --git a/app/models/base.py b/app/models/base.py new file mode 100644 index 0000000..95ebc0c --- /dev/null +++ b/app/models/base.py @@ -0,0 +1,3 @@ +from sqlalchemy.orm import declarative_base + +Base = declarative_base() \ No newline at end of file diff --git a/app/models/cached_query.py b/app/models/cached_query.py new file mode 100644 index 0000000..faa2a16 --- /dev/null +++ b/app/models/cached_query.py @@ -0,0 +1,34 @@ +import uuid +import datetime +from sqlalchemy import String, DateTime, Table, Column, ForeignKey +from sqlalchemy.orm import Mapped, mapped_column, relationship +from sqlalchemy.dialects.postgresql import UUID +from pgvector.sqlalchemy import Vector +from .base import Base + +cached_query_chunks_link = Table( + "cached_query_chunks_link", + Base.metadata, + Column("cached_query_id", ForeignKey("cached_queries.id", ondelete="CASCADE"), primary_key=True), + Column("chunk_id", ForeignKey("chunks.id", ondelete="CASCADE"), primary_key=True), +) + +class CachedQuery(Base): + __tablename__ = "cached_queries" + + id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4) + + question_text: Mapped[str] = mapped_column(String, nullable=False) + question_embedding: Mapped[list[float]] = mapped_column(Vector(384), nullable=False) + + response_answer: Mapped[str] = mapped_column(String, nullable=False) + + source_chunks: Mapped[list["Chunk"]] = relationship( + secondary=cached_query_chunks_link, + back_populates="cached_queries" + ) + + created_at: Mapped[datetime.datetime] = mapped_column( + DateTime(timezone=True), + default=lambda: datetime.datetime.now(datetime.timezone.utc) + ) \ No newline at end of file diff --git a/app/models/chunk.py b/app/models/chunk.py new file mode 100644 index 0000000..d4eea85 --- /dev/null +++ b/app/models/chunk.py @@ -0,0 +1,22 @@ +import uuid +from sqlalchemy import String, ForeignKey +from sqlalchemy.orm import Mapped, mapped_column, relationship +from sqlalchemy.dialects.postgresql import UUID, JSONB +from pgvector.sqlalchemy import Vector +from .base import Base +from .cached_query import cached_query_chunks_link + +class Chunk(Base): + __tablename__= "chunks" + + id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4) + document_id: Mapped[uuid.UUID] = mapped_column(ForeignKey("documents.id", ondelete="CASCADE")) + chunk_text: Mapped[str] = mapped_column(String, nullable=False) + chunk_metadata: Mapped[dict | None] = mapped_column(JSONB) + embedding: Mapped[list[float]] = mapped_column(Vector(384), nullable=False) + document = relationship("Document", back_populates="chunks") + + cached_queries: Mapped[list["CachedQuery"]] = relationship( + secondary=cached_query_chunks_link, + back_populates="source_chunks" + ) \ No newline at end of file diff --git a/app/models/document.py b/app/models/document.py new file mode 100644 index 0000000..1a1ed7d --- /dev/null +++ b/app/models/document.py @@ -0,0 +1,32 @@ +from datetime import datetime, timezone +import uuid +from enum import Enum as PyEnum +from sqlalchemy import DateTime, String, TIMESTAMP, Enum, text +from sqlalchemy.orm import Mapped, mapped_column, relationship +from sqlalchemy.dialects.postgresql import UUID +from .base import Base + +class IngestionStatus(PyEnum): + PENDING = "PENDING" + PROCESSING = "PROCESSING" + COMPLETED = "COMPLETED" + FAILED = "FAILED" + +class Document(Base): + __tablename__ = "documents" + + id: Mapped[uuid.UUID] = mapped_column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4) + filename: Mapped[str] = mapped_column(String, nullable=False, unique=True) + status: Mapped[IngestionStatus] = mapped_column( + Enum(IngestionStatus, name="ingestion_status"), + nullable=False, + default=IngestionStatus.PENDING + ) + error_message: Mapped[str | None] = mapped_column(String) + created_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), default=lambda: datetime.now(timezone.utc) + ) + updated_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), default=lambda: datetime.now(timezone.utc) + ) + chunks = relationship("Chunk", back_populates="document", cascade="all, delete-orphan") \ No newline at end of file diff --git a/app/repositories/cached_query_repository.py b/app/repositories/cached_query_repository.py new file mode 100644 index 0000000..6f3d525 --- /dev/null +++ b/app/repositories/cached_query_repository.py @@ -0,0 +1,42 @@ +from sqlalchemy.orm import Session as SyncSession +from sqlalchemy import select, text +from sqlalchemy.orm import selectinload +from app.models import CachedQuery +from app.models.chunk import Chunk +from typing import List + +SIMILARITY_THRESHOLD = 0.70 + + + +class CachedQueryRepository: + def __init__(self, session: SyncSession): + self.session = session + + def find_similar_query(self, query_embedding: List[float]) -> CachedQuery | None: + """ + Finds a cached query if its embedding is within the similarity threshold. + This is done in a single, efficient query using the ORM. + """ + + distance_threshold = 1 - SIMILARITY_THRESHOLD + + stmt = select(CachedQuery).options( + selectinload(CachedQuery.source_chunks) + ).where( + CachedQuery.question_embedding.cosine_distance(query_embedding) < distance_threshold + ).order_by( + CachedQuery.question_embedding.cosine_distance(query_embedding) + ).limit(1) + + return self.session.execute(stmt).scalar_one_or_none() + + def save_query(self, question_text: str, query_embedding: list[float], answer: str, source_chunks: list[Chunk]): + """Saves a new query and links it to its source chunks.""" + new_cached_query = CachedQuery( + question_text=question_text, + question_embedding=query_embedding, + response_answer=answer, + source_chunks=source_chunks + ) + self.session.add(new_cached_query) \ No newline at end of file diff --git a/app/repositories/chunk_repository.py b/app/repositories/chunk_repository.py new file mode 100644 index 0000000..6a0a6cc --- /dev/null +++ b/app/repositories/chunk_repository.py @@ -0,0 +1,27 @@ +from sqlalchemy.orm import Session as SyncSession +from sqlalchemy import delete, text, select +from app.models import Chunk, Document + +class ChunkRepository: + def __init__(self, session: SyncSession): + + self.session = session + + def delete_by_document_id_sync(self, document_id: str): + """ + Synchronously deletes all chunks associated with a given document ID. + """ + self.session.execute( + delete(Chunk).where(Chunk.document_id == document_id) + ) + + def find_relevant_chunks_sync(self, query_embedding: list[float], top_k: int = 5) -> list[Chunk]: + """ + Finds the most relevant chunks using vector similarity. + """ + stmt = select(Chunk).order_by( + Chunk.embedding.cosine_distance(query_embedding) + ).limit(top_k) + + return self.session.execute(stmt).scalars().all() + diff --git a/app/repositories/document_repo.py b/app/repositories/document_repo.py new file mode 100644 index 0000000..6143764 --- /dev/null +++ b/app/repositories/document_repo.py @@ -0,0 +1,67 @@ +from datetime import datetime, timezone +import uuid +from sqlalchemy import select +from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy.orm import Session as SyncSession +from app.models.document import Document, IngestionStatus + + +class DocumentRepository: + """ + Handles the database operations for the Document model. + """ + def __init__(self, session: AsyncSession | SyncSession): + self.session = session + + async def get_by_filename(self, filename: str | None) -> Document | None: + """ + Returns a document by filename if it exists + """ + + result = await self.session.execute(select(Document).where(Document.filename == filename)) + return result.scalars().first() + + async def get_by_id(self, document_id: uuid.UUID) -> Document | None: + """Asynchronously retrieves a document by its ID.""" + return await self.session.get(Document, document_id) + + async def create_document(self, filename: str | None) -> Document: + """ + Creates a new document record in the database with PENDING status. + + Args: + filename: The original name of the uploaded file. + + Returns: + The newly created Document object. + """ + + new_document = Document(filename=filename) + self.session.add(new_document) + await self.session.flush() + await self.session.refresh(new_document) + + return new_document + + async def update_for_reupload(self, document: Document) -> Document: + """ + update the document for reupload + """ + document.status = IngestionStatus.PENDING + document.error_message = None + await self.session.flush() + await self.session.refresh(document) + return document + + def get_by_id_sync(self, document_id: str) -> Document | None: + """Synchronously retrieves a document by its ID.""" + return self.session.get(Document, document_id) + + def update_status_sync(self, document: Document, status: IngestionStatus, error_message: str | None = None) -> Document: + """Synchronously updates a document's status and error message.""" + document.status = status + document.error_message = error_message + document.updated_at = datetime.now(timezone.utc) + self.session.commit() + self.session.refresh(document) + return document \ No newline at end of file diff --git a/app/schemas/document.py b/app/schemas/document.py new file mode 100644 index 0000000..673d517 --- /dev/null +++ b/app/schemas/document.py @@ -0,0 +1,13 @@ +import uuid +from pydantic import BaseModel, ConfigDict +from app.models.document import IngestionStatus + +class DocumentJob(BaseModel): + """ + The response model for a document upload job. + """ + job_id: uuid.UUID + filename: str + status: IngestionStatus + + model_config = ConfigDict(from_attributes=True) \ No newline at end of file diff --git a/app/schemas/query.py b/app/schemas/query.py new file mode 100644 index 0000000..3ce1295 --- /dev/null +++ b/app/schemas/query.py @@ -0,0 +1,31 @@ +from pydantic import BaseModel, Field +from typing import List + + +class QueryRequest(BaseModel): + """ + The request model for a user's query. + """ + question: str = Field( + ..., + min_length=3, + max_length=300, + description="The natural language question to ask the knowledge base." + ) + + +class Source(BaseModel): + """ + Represents a single source document chunk that contributed to the answer. + """ + filename: str = Field(..., description="The name of the source file.") + snippet: str = Field(..., description="The specific text snippet from the source file.") + + +class QueryResponse(BaseModel): + """ + The successful response model for a query. + """ + answer: str = Field(..., description="The synthesized natural language answer.") + sources: List[Source] = Field(..., description="A list of source snippets used to generate the answer.") + \ No newline at end of file diff --git a/app/services/document_service.py b/app/services/document_service.py new file mode 100644 index 0000000..b4c681f --- /dev/null +++ b/app/services/document_service.py @@ -0,0 +1,58 @@ +import aiofiles +import os +import logging +from fastapi import UploadFile +from app.repositories.document_repo import DocumentRepository +from app.models.document import Document +from app.core.config import settings +from app.worker import dispatch_processing_task + +logger = logging.getLogger(__name__) + +class DocumentService: + def __init__(self, repository: DocumentRepository): + self.repository = repository + + async def process_upload(self, file: UploadFile) -> Document: + """ + Handles the logic for a new file upload. + - Checks for an existing document with the same name. + - Creates or updates the database record. + - Saves the file to disk. + """ + + filename = file.filename + logger.info(f"Processing upload for file: {filename}") + + if not filename: + raise FileNotFoundError + + existing_document = await self.repository.get_by_filename(filename) + + if existing_document: + logger.info(f"File '{filename}' already exists. Updating record for re-processing.") + document = await self.repository.update_for_reupload(existing_document) + else: + logger.info(f"File '{filename}' is new. Creating new document record.") + document = await self.repository.create_document(filename=filename) + + file_path = os.path.join(settings.UPLOAD_DIRECTORY, str(document.id) + ".zip") + try: + async with aiofiles.open(file_path, 'wb') as out_file: + content = await file.read() + await out_file.write(content) + logger.info(f"Successfully saved file '{filename}' to '{file_path}'") + except Exception as e: + logger.error(f"Failed to save file '{filename}'. Error: {e}",exc_info=True) + raise + + logger.info(f"Handing off document ID {document.id} to the background worker.") + dispatch_processing_task.delay(str(document.id)) + + return document + + async def get_document_by_id(self, document_id) -> Document | None: + """ + Retrieves a document by its ID. + """ + return await self.repository.get_by_id(document_id) diff --git a/app/services/health_service.py b/app/services/health_service.py new file mode 100644 index 0000000..8a21758 --- /dev/null +++ b/app/services/health_service.py @@ -0,0 +1,24 @@ +from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy import text +from sqlalchemy.exc import OperationalError +import logging + +logger = logging.getLogger(__name__) + +class HealthService: + def __init__(self, session: AsyncSession): + self.session = session + + async def check_db_connection(self) -> dict: + """ + Checks the database connection by executing a simple query. + """ + try: + await self.session.execute(text("SELECT 1")) + return {"db_status": "ok"} + except OperationalError as e: + logger.error(f"Health check failed: Database operational error: {e}") + raise + except Exception as e: + logger.error(f"Health check failed: Unexpected error: {e}") + raise diff --git a/app/services/query_service.py b/app/services/query_service.py new file mode 100644 index 0000000..3c54cd6 --- /dev/null +++ b/app/services/query_service.py @@ -0,0 +1,118 @@ +from app.models.chunk import Chunk +from app.repositories.cached_query_repository import CachedQueryRepository +from app.schemas.query import QueryRequest, QueryResponse, Source +from app.repositories.chunk_repository import ChunkRepository +from sqlalchemy.exc import SQLAlchemyError +import logging +from app.core.config import get_embedding_model, get_generative_model, LLM_QUERY_DURATION + +logger = logging.getLogger(__name__) + + +class QueryService: + """ + Contains the business logic for the RAG (Retrieval-Augmented Generation) process. + """ + def __init__(self, chunk_repo: ChunkRepository, cached_query_repo: CachedQueryRepository): + self.chunk_repo = chunk_repo + self.cached_query_repo = cached_query_repo + + def answer_question(self, query: QueryRequest) -> QueryResponse: + """ + Orchestrates the RAG pipeline to answer a user's question. + """ + try: + + logger.info(f"Embedding question for cache lookup: '{query.question}'") + + embedding_model = get_embedding_model() + + question_embedding = next(embedding_model.embed(query.question)) + logger.debug(f"Generated embedding type: {type(question_embedding)}, shape: {getattr(question_embedding, 'shape', 'N/A')}") + + cached_result = self.cached_query_repo.find_similar_query(question_embedding.tolist()) + + if cached_result: + logger.info(f"Semantic cache HIT. Found similar question: '{cached_result.question_text}'") + return QueryResponse( + answer=cached_result.response_answer, + sources=[Source( + filename=chunk.chunk_metadata.get("source_filename", "Unknown"), + snippet=chunk.chunk_text + ) for chunk in cached_result.source_chunks] + ) + + logger.info("Semantic cache MISS. Proceeding with full RAG pipeline.") + + answer, source_chunks = self._perform_rag(query, question_embedding) + + logger.info("Populating semantic cache with new response.") + + self.cached_query_repo.save_query( + question_text=query.question, + query_embedding=question_embedding.tolist() if hasattr(question_embedding, 'tolist') else question_embedding, + answer=answer, + source_chunks=source_chunks + ) + + return QueryResponse( + answer=answer, + sources=[Source( + filename=chunk.chunk_metadata.get("source_filename", "Unknown"), + snippet=chunk.chunk_text + ) for chunk in source_chunks] + ) + + except SQLAlchemyError as e: + logger.exception(f"A database error occurred during the query process => {e}.") + return QueryResponse( + answer="I'm sorry, but I encountered a database error while trying to answer your question. Please try again later.", + sources=[] + ) + except Exception as e: + logger.exception("An unexpected error occurred in the query service.") + return QueryResponse( + answer=f"An unexpected error occurred: {e}", + sources=[] + ) + + def _perform_rag(self, query: QueryRequest, question_embedding: list[float]) -> tuple[str, list[Chunk]]: + """ + Performs the core RAG logic and returns the answer string AND the source chunk objects. + """ + logger.info("Finding relevant chunks in the database...") + relevant_chunks = self.chunk_repo.find_relevant_chunks_sync(question_embedding) + + if not relevant_chunks: + return "I could not find any relevant information in the knowledge base to answer your question.", [] + + logger.info(f"Found {len(relevant_chunks)} relevant chunks.") + context = "\n---\n".join([chunk.chunk_text for chunk in relevant_chunks]) + + prompt = f""" + You are a helpful AI assistant for developers. Your name is DocuQuery. + Answer the user's question based ONLY on the following context. + If the context does not contain the answer, say "I'm sorry, I cannot answer this question based on the provided documents." + + CONTEXT: + {context} + + QUESTION: + {query.question} + + ANSWER: + """ + + logger.info("Sending prompt to Gemini for generation...") + + try: + generative_model = get_generative_model() + with LLM_QUERY_DURATION.time(): + response = generative_model.generate_content(prompt) + answer = response.text + except Exception as e: + logger.exception("Error calling Gemini API.") + answer = f"An error occurred while generating the answer with the Gemini API: {e}" + + return answer, relevant_chunks + \ No newline at end of file diff --git a/app/tests/api/v1/test_documents.py b/app/tests/api/v1/test_documents.py new file mode 100644 index 0000000..55909cb --- /dev/null +++ b/app/tests/api/v1/test_documents.py @@ -0,0 +1,52 @@ +import io +from httpx import AsyncClient +from pytest_mock import MockerFixture + +async def test_upload_zip_file_success(test_client: AsyncClient): + """ + Tests the successful upload of a .zip file. + """ + zip_content = b"PK\x05\x06\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00" + files = {"file": ("mydocs.zip", io.BytesIO(zip_content), "application/zip")} + + response = await test_client.post("/api/v1/documents/upload", files=files) + + assert response.status_code == 202 + + data = response.json() + assert data["filename"] == "mydocs.zip" + assert data["status"] == "PENDING" + assert "job_id" in data + +async def test_upload_invalid_file_type(test_client: AsyncClient): + """ + Tests that uploading a non-zip file results in a 400 error. + """ + files = {"file": ("test.txt", io.BytesIO(b"some text"), "text/plain")} + + response = await test_client.post("/api/v1/documents/upload", files=files) + + assert response.status_code == 400 + data = response.json() + assert "Invalid file type" in data["detail"] + + +async def test_upload_enqueues_background_task( + test_client: AsyncClient, + mocker: MockerFixture +): + """ + Tests that a successful upload correctly calls the background dispatcher task. + """ + mock_dispatch = mocker.patch('app.services.document_service.dispatch_processing_task.delay') + + zip_content = b"PK\x05\x06\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00" + files = {"file": ("test_task.zip", io.BytesIO(zip_content), "application/zip")} + + response = await test_client.post("/api/v1/documents/upload", files=files) + + assert response.status_code == 202 + + job_id = response.json()["job_id"] + + mock_dispatch.assert_called_once_with(job_id) \ No newline at end of file diff --git a/app/tests/api/v1/test_query.py b/app/tests/api/v1/test_query.py new file mode 100644 index 0000000..0217a8d --- /dev/null +++ b/app/tests/api/v1/test_query.py @@ -0,0 +1,51 @@ +from typing import Any +from httpx import Client +import pytest + + +class TestQueryEndpoint: + """ + A test class to group all tests related to the /query endpoint. + """ + + def test_query_happy_path(self, test_client_sync: Client): + """ + Tests a successful query with a valid question. + Expects a 200 OK response with the correct structure. + """ + + request_data = {"question": "How does the retry logic work?"} + + response = test_client_sync.post("/api/v1/query", json=request_data) + + assert response.status_code == 200 + + data = response.json() + assert "answer" in data + assert "sources" in data + assert isinstance(data["sources"], list) + + @pytest.mark.parametrize( + "invalid_payload, expected_detail_part", + [ + ({}, "Field required"), + ({"question": None}, "Input should be a valid string"), + ({"question": ""}, "String should have at least 3 characters"), + ({"question": "hi"}, "String should have at least 3 characters"), + ({"question": 123}, "Input should be a valid string"), + ] + ) + def test_query_validation_errors( + self, test_client_sync: Client, invalid_payload: dict[Any, Any], expected_detail_part: str + ): + """ + Tests various invalid request payloads. + Expects a 422 Unprocessable Entity response with a helpful error message. + """ + response = test_client_sync.post("/api/v1/query", json=invalid_payload) + + assert response.status_code == 422 + + error_data = response.json() + assert "detail" in error_data + assert any(expected_detail_part in detail["msg"] for detail in error_data["detail"]) \ No newline at end of file diff --git a/app/tests/conftest.py b/app/tests/conftest.py new file mode 100644 index 0000000..2d44033 --- /dev/null +++ b/app/tests/conftest.py @@ -0,0 +1,136 @@ +import pytest +from typing import AsyncGenerator, Generator +from httpx import AsyncClient, Client +from httpx._transports.asgi import ASGITransport +from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker, AsyncSession + +from app.main import app +from app.core.database import get_session +from app.models.base import Base +from app.core.config import settings + + +@pytest.fixture(scope="function") +async def test_engine(): + """ + Creates a test database engine for each test. + """ + engine = create_async_engine(settings.DATABASE_URL, echo=False) + + async with engine.begin() as conn: + await conn.run_sync(Base.metadata.drop_all) + await conn.run_sync(Base.metadata.create_all) + + yield engine + + async with engine.begin() as conn: + await conn.run_sync(Base.metadata.drop_all) + + await engine.dispose() + + +@pytest.fixture(scope="function") +async def test_client(test_engine) -> AsyncGenerator[AsyncClient, None]: + """ + A fixture that sets up the test database and provides an HTTP client. + Each test gets its own client and database session. + """ + TestingSessionLocal = async_sessionmaker( + autoflush=False, + autocommit=False, + bind=test_engine, + expire_on_commit=False + ) + + async def override_get_session() -> AsyncGenerator[AsyncSession, None]: + """ + A dependency override that provides a session to the test database. + Each request gets a fresh session that will be rolled back after the test. + """ + async with TestingSessionLocal() as session: + try: + yield session + await session.commit() + except Exception: + await session.rollback() + raise + finally: + await session.close() + + app.dependency_overrides[get_session] = override_get_session + + headers = {"X-API-KEY": settings.API_KEY} + + transport = ASGITransport(app=app) + async with AsyncClient(transport=transport, base_url="http://test", headers=headers) as client: + yield client + + app.dependency_overrides.clear() + +@pytest.fixture(scope="function") +def zip_file_fixture(tmp_path): + """ + Creates a temporary zip file with sample markdown content for testing. + Returns the path to the created zip file. + """ + import zipfile + import textwrap + + files_to_create = { + "auth_service.md": """ + # Authentication Service Documentation + ## Overview + The Authentication Service is responsible for user login, registration, and token management. + It uses JWT for secure token generation. + """, + "api_gateway.md": """ + # API Gateway + ## Routing + The gateway routes incoming traffic based on the request path. + - `/api/v1/query` is routed to the Query Service. + - `/api/v1/documents` is routed to the Ingestion Service. + """, + "database_schema.md": """ + # Database Schema + ## Tables + - **documents**: Tracks the status of ingested files. + - **chunks**: Stores the vector data and text snippets. + """ + } + + zip_path = tmp_path / "sample.zip" + + with zipfile.ZipFile(zip_path, 'w') as zipf: + for filename, content in files_to_create.items(): + file_path = tmp_path / filename + file_path.write_text(textwrap.dedent(content).strip(), encoding="utf-8") + zipf.write(file_path, arcname=filename) + + return zip_path + +@pytest.fixture(scope="function") +def test_client_sync(test_engine) -> Generator[Client, None, None]: + """ + A fixture that provides a SYNCHRONOUS test client for testing 'def' endpoints. + """ + + from sqlalchemy.orm import sessionmaker + TestingSessionLocalSync = sessionmaker(autocommit=False, autoflush=False, bind=test_engine) + + def override_get_sync_db(): + db = TestingSessionLocalSync() + try: + yield db + finally: + db.close() + + from app.core.db_sync import get_sync_db + app.dependency_overrides[get_sync_db] = override_get_sync_db + + headers = {"X-API-KEY": settings.API_KEY} + + from fastapi.testclient import TestClient + with TestClient(app, headers=headers) as client: + yield client + + app.dependency_overrides.clear() \ No newline at end of file diff --git a/app/worker.py b/app/worker.py new file mode 100644 index 0000000..a79030a --- /dev/null +++ b/app/worker.py @@ -0,0 +1,230 @@ +import logging +import os +import tempfile +import zipfile +from celery import Celery, chord +from app.core.config import settings, get_embedding_model +from app.core.db_sync import get_sync_db +from langchain_text_splitters import RecursiveCharacterTextSplitter +from app.models import Chunk +from app.models.document import IngestionStatus +from app.repositories.chunk_repository import ChunkRepository +from app.repositories.document_repo import DocumentRepository + +logger = logging.getLogger(__name__) + +os.environ['HF_HUB_OFFLINE'] = '1' + +celery = Celery(__name__) + +celery.config_from_object(settings, namespace='CELERY') + +TEXT_SPLITTER = RecursiveCharacterTextSplitter( +chunk_size=2000, +chunk_overlap=200, +length_function=len, +) + +@celery.task +def dispatch_processing_task(document_id: str): + """ + The main entry point task (The Dispatcher). + For now, it just logs that it received the job. + """ + logger.info(f"[DISPATCHER] Received job for document_id: {document_id}. Routing to appropriate worker...") + + with get_sync_db() as db: + repo = DocumentRepository(db) + + document = repo.get_by_id_sync(document_id) + + if not document: + logger.error(f"[DISPATCHER] Document with ID {document_id} not found. Aborting.") + return + + repo.update_status_sync(document, status=IngestionStatus.PROCESSING) + logger.info(f"[DISPATCHER] Document '{document.filename}' status set to PROCESSING.") + + if document.filename.endswith('.zip'): + logger.info(f"[DISPATCHER] Routing '{document.filename}' to the Unpacker worker.") + unpack_zip_task.delay(document_id) + + elif document.filename.endswith('.md'): + logger.info(f"[DISPATCHER] Routing '{document.filename}' directly to the Ingestor worker.") + file_path = f"./uploads/{document.id}.md" + ingest_file_from_path_task.delay(document_id, file_path, document.filename) + + else: + error_msg = f"Unsupported file type: {document.filename}" + logger.error(f"[DISPATCHER] {error_msg}") + repo.update_status_sync(document, status=IngestionStatus.FAILED, error_message=error_msg) + + +@celery.task +def unpack_zip_task(document_id: str): + """ + The specialist for unpacking zip files. + Extracts files to a persistent temporary location and passes file paths to ingest tasks + to avoid serializing large content in Celery messages. + """ + logger.info(f"[UNPACKER] Received job for document_id: {document_id}. Starting to unpack...") + + with get_sync_db() as db: + doc_repo = DocumentRepository(db) + chunk_repo = ChunkRepository(db) + + document = doc_repo.get_by_id_sync(document_id) + if not document: + logger.error(f"[UNPACKER] Document {document_id} not found.") + return + + logger.info(f"[UNPACKER] Deleting old chunks for document {document_id}.") + chunk_repo.delete_by_document_id_sync(document_id) + db.commit() + + file_path = f"./uploads/{document.id}.zip" + + + temp_extract_dir = f"./uploads/temp_{document_id}" + os.makedirs(temp_extract_dir, exist_ok=True) + + ingest_tasks = [] + try: + with zipfile.ZipFile(file_path, 'r') as zip_ref: + zip_ref.extractall(temp_extract_dir) + + logger.info(f"[UNPACKER] Fanning out tasks for files in {document.filename}") + for filename in os.listdir(temp_extract_dir): + if filename.endswith('.md'): + full_path = os.path.join(temp_extract_dir, filename) + + ingest_tasks.append(ingest_file_from_path_task.s(document_id, full_path, filename)) + + logger.info(f"[UNPACKER] Created {len(ingest_tasks)} ingest tasks for files in temp directory: {temp_extract_dir}") + + except Exception as e: + logger.exception("[UNPACKER] Failed to unpack or prepare tasks.") + doc_repo.update_status_sync(document, IngestionStatus.FAILED, str(e)) + + if os.path.exists(temp_extract_dir): + import shutil + shutil.rmtree(temp_extract_dir, ignore_errors=True) + return + + if not ingest_tasks: + logger.warning(f"[UNPACKER] No .md files found in {document.filename}. Marking as complete.") + doc_repo.update_status_sync(document, IngestionStatus.COMPLETED) + + if os.path.exists(temp_extract_dir): + import shutil + shutil.rmtree(temp_extract_dir, ignore_errors=True) + return + + callback = finalize_processing_task.s(document_id=document_id, temp_dir=temp_extract_dir) + chord(ingest_tasks)(callback) + + logger.info(f"[UNPACKER] Dispatched {len(ingest_tasks)} ingest jobs with a finalization callback.") + +@celery.task +def finalize_processing_task(results: list, document_id: str, temp_dir: str = None): + """ + The callback task that inspects the results of all ingest tasks + and sets the final status for the parent Document. + Also cleans up the temporary directory used for extracted files. + """ + logger.info(f"[FINALIZER] All ingest jobs finished for document {document_id}. Analyzing results...") + + failed_files = [] + for result in results: + if result and result.get("status") == IngestionStatus.FAILED: + failed_files.append(result) + + with get_sync_db() as db: + repo = DocumentRepository(db) + document = repo.get_by_id_sync(document_id) + if not document: + logger.error(f"[FINALIZER] Document {document_id} not found. Cannot set final status.") + return + + if failed_files: + error_messages = [f" - {f.get('filename')}: {f.get('error', 'Unknown error')}" for f in failed_files] + full_error_message = f"Ingestion failed for {len(failed_files)} file(s):\n" + "\n".join(error_messages) + + logger.error(f"[FINALIZER] Job for document {document_id} failed. Details:\n{full_error_message}") + repo.update_status_sync(document, IngestionStatus.FAILED, full_error_message) + else: + logger.info(f"[FINALIZER] All {len(results)} files ingested successfully for document {document_id}. Setting status to COMPLETED.") + repo.update_status_sync(document, IngestionStatus.COMPLETED) + + if temp_dir and os.path.exists(temp_dir): + try: + import shutil + shutil.rmtree(temp_dir, ignore_errors=True) + logger.info(f"[FINALIZER] Cleaned up temporary directory: {temp_dir}") + except Exception as e: + logger.warning(f"[FINALIZER] Failed to clean up temp directory {temp_dir}: {e}") + +@celery.task +def ingest_file_from_path_task(document_id: str, file_path: str, original_filename: str): + """ + The specialist for ingesting a single file from a file path. + Reads content from disk to avoid large message serialization. + Uses batched processing to prevent out-of-memory errors. + """ + logger.info(f"[INGESTOR] Ingesting file from '{file_path}' (original: '{original_filename}') for document {document_id}.") + + BATCH_SIZE = 500 + + try: + if not os.path.exists(file_path): + raise FileNotFoundError(f"File not found: {file_path}") + + with open(file_path, 'r', encoding='utf-8') as f: + text = f.read() + + chunks_text = TEXT_SPLITTER.split_text(text) + total_chunks = len(chunks_text) + logger.info(f"[INGESTOR] Split '{original_filename}' into {total_chunks} chunks. Processing in batches of {BATCH_SIZE}...") + + embedding_model = get_embedding_model() + total_saved = 0 + + for batch_start in range(0, total_chunks, BATCH_SIZE): + batch_end = min(batch_start + BATCH_SIZE, total_chunks) + batch_chunks = chunks_text[batch_start:batch_end] + + logger.info(f"[INGESTOR] Processing batch {batch_start}-{batch_end} of {total_chunks} chunks...") + + + batch_embeddings = list(embedding_model.embed(batch_chunks)) + + + chunks_to_create = [] + for i, text_chunk in enumerate(batch_chunks): + chunk = Chunk( + document_id=document_id, + chunk_text=text_chunk, + embedding=batch_embeddings[i].tolist(), + chunk_metadata={ + "source_filename": original_filename, + "chunk_index": batch_start + i + } + ) + chunks_to_create.append(chunk) + + + with get_sync_db() as db: + db.bulk_save_objects(chunks_to_create) + db.commit() + + total_saved += len(chunks_to_create) + logger.info(f"[INGESTOR] Saved batch to database. Progress: {total_saved}/{total_chunks} chunks ({total_saved*100//total_chunks}%)") + + logger.info(f"[INGESTOR] Successfully saved all {total_saved} chunks to the database.") + + return {"status": "SUCCESS", "filename": original_filename} + + except Exception as e: + logger.exception(f"[INGESTOR] Failed to ingest file '{original_filename}' from path '{file_path}'.", exc_info=True) + + return {"status": "FAILED", "filename": original_filename, "error": str(e)} diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 0000000..c549f7b --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,62 @@ +services: + db: + image: pgvector/pgvector:pg16 + container_name: docuquery_db + environment: + - POSTGRES_USER=${DB_USER} + - POSTGRES_PASSWORD=${DB_PASSWORD} + - POSTGRES_DB=${DB_NAME} + volumes: + - postgres_data:/var/lib/postgresql/data + ports: + - "${DB_PORT}:5432" + healthcheck: + test: ["CMD-SHELL", "pg_isready -U ${DB_USER} -d ${DB_NAME}"] + interval: 5s + timeout: 5s + retries: 5 + + redis: + image: redis:7-alpine + container_name: docuquery_redis + ports: + - "${REDIS_PORT}:6379" + + api: + build: . + container_name: docuquery_api + command: uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload + volumes: + - .:/app + ports: + - "8000:8000" + environment: + - DB_HOST=db + - REDIS_HOST=redis + - GOOGLE_API_KEY=${GOOGLE_API_KEY} + - API_KEY=${API_KEY} + depends_on: + db: + condition: service_healthy + redis: + condition: service_started + + worker: + build: . + container_name: docuquery_worker + command: celery -A app.worker.celery worker --loglevel=info + volumes: + - .:/app + environment: + - DB_HOST=db + - REDIS_HOST=redis + - GOOGLE_API_KEY=${GOOGLE_API_KEY} + - API_KEY=${API_KEY} + depends_on: + db: + condition: service_healthy + redis: + condition: service_started + +volumes: + postgres_data: \ No newline at end of file diff --git a/download_model.py b/download_model.py new file mode 100644 index 0000000..c31a3b2 --- /dev/null +++ b/download_model.py @@ -0,0 +1,22 @@ +""" +Utility script to pre-download the embedding model. +Run this once before starting Celery workers to cache the model locally. +""" +import logging +from app.core.config import settings, get_embedding_model + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +def download_model(): + """Download and cache the embedding model.""" + logger.info(f"Downloading model to cache directory: {settings.MODEL_CACHE_DIR}") + + model = get_embedding_model() + + test_embeddings = list(model.embed(["test text"])) + logger.info(f"Model downloaded successfully! Test embedding shape: {len(test_embeddings[0])}") + logger.info(f"Model cached at: {settings.MODEL_CACHE_DIR}") + +if __name__ == "__main__": + download_model() diff --git a/e2e_test_upload.py b/e2e_test_upload.py new file mode 100644 index 0000000..31d82f9 --- /dev/null +++ b/e2e_test_upload.py @@ -0,0 +1,75 @@ +import asyncio +import httpx +import time +import os +from dotenv import load_dotenv + +load_dotenv() + +BASE_URL = "http://127.0.0.1:8000" +UPLOAD_ENDPOINT = "/api/v1/documents/upload" +STATUS_ENDPOINT = "/api/v1/documents/{job_id}/status" +FILE_TO_UPLOAD = "test_data/sample.zip" +API_KEY = os.getenv("API_KEY") + +async def main(): + """ + Runs a full end-to-end test of the document upload and processing pipeline. + """ + if not API_KEY: + print("Error: API_KEY not found in environment. Please set it in your .env file.") + return + + if not os.path.exists(FILE_TO_UPLOAD): + print(f"Error: Test file not found at '{FILE_TO_UPLOAD}'") + return + + headers = {"X-API-KEY": API_KEY} + + async with httpx.AsyncClient(base_url=BASE_URL, timeout=30.0, headers=headers) as client: + + print(f"Uploading file: {FILE_TO_UPLOAD}...") + with open(FILE_TO_UPLOAD, "rb") as f: + files = {"file": (os.path.basename(FILE_TO_UPLOAD), f, "application/zip")} + try: + response = await client.post(UPLOAD_ENDPOINT, files=files) + response.raise_for_status() + except httpx.RequestError as e: + print(f"Error: Could not connect to the server at {BASE_URL}. Is it running?") + return + except httpx.HTTPStatusError as e: + if e.response.status_code == 401: + print("Error: Got a 401 Unauthorized response. Is your API_KEY in .env correct?") + else: + print(f"An HTTP error occurred: {e.response.status_code} - {e.response.text}") + return + + if response.status_code == 202: + job = response.json() + job_id = job["job_id"] + print(f"File accepted. Job ID: {job_id}") + else: + print(f"Upload failed with status {response.status_code}: {response.text}") + return + + print("Polling for job completion...") + start_time = time.time() + while time.time() - start_time < 60: + status_url = STATUS_ENDPOINT.format(job_id=job_id) + status_response = await client.get(status_url) + + if status_response.status_code == 200: + job_status = status_response.json()["status"] + print(f" Current status: {job_status}") + if job_status in ["COMPLETED", "FAILED"]: + print(f"Job finished with status: {job_status}") + return + else: + print(f" Error fetching status: {status_response.status_code}") + + await asyncio.sleep(2) + + print("Error: Job did not complete within the timeout period.") + +if __name__ == "__main__": + asyncio.run(main()) \ No newline at end of file diff --git a/large_file_upload_script.py b/large_file_upload_script.py new file mode 100644 index 0000000..852f18f --- /dev/null +++ b/large_file_upload_script.py @@ -0,0 +1,540 @@ +""" +Test script to generate and upload a large markdown file in a ZIP archive to the DocuQuery API. +This tests the system's ability to handle large document uploads (target: ~400MB ZIP file). +""" + +import asyncio +import httpx +import time +import os +import sys +import zipfile +from pathlib import Path +from dotenv import load_dotenv + +load_dotenv() + +BASE_URL = "http://127.0.0.1:8000" +UPLOAD_ENDPOINT = "/api/v1/documents/upload" +STATUS_ENDPOINT = "/api/v1/documents/{job_id}/status" +QUERY_ENDPOINT = "/api/v1/query" +API_KEY = os.getenv("API_KEY") + +# Test configuration +# 50MB file will create ~29,000 chunks with 2000-char chunk size +# Processing time: ~20-25 minutes (58 batches × ~20-25 sec/batch) +TARGET_FILE_SIZE_MB = 50 +TEST_DATA_DIR = Path("test_data") +LARGE_FILE_PATH = TEST_DATA_DIR / "large_test_document.md" +LARGE_ZIP_PATH = TEST_DATA_DIR / "large_test_document.zip" + + +def generate_large_markdown_file(target_size_mb: int, output_path: Path): + """ + Generate a large markdown file with realistic content. + This file will be compressed into a ZIP archive for upload. + + Args: + target_size_mb: Target size in megabytes (uncompressed) + output_path: Path where the markdown file will be saved + """ + print(f"Generating {target_size_mb}MB markdown file (uncompressed)...") + + + output_path.parent.mkdir(parents=True, exist_ok=True) + + + sample_sections = [ + """ +# Introduction to Distributed Systems + +Distributed systems are computing systems in which components located on networked computers +communicate and coordinate their actions by passing messages. These systems are fundamental +to modern cloud computing, web services, and large-scale applications. + +## Key Characteristics + +1. **Concurrency**: Multiple components execute simultaneously +2. **Lack of Global Clock**: No single global notion of correct time +3. **Independent Failures**: Components can fail independently +4. **Scalability**: Ability to handle growing amounts of work + +## Common Challenges + +### Network Partitions +Network partitions occur when network failures prevent some nodes from communicating with others. +This is a critical consideration in distributed system design, as outlined by the CAP theorem. + +### Consistency Models +- Strong Consistency +- Eventual Consistency +- Causal Consistency +- Sequential Consistency + +### Data Replication Strategies +Replication is essential for fault tolerance and performance. Common strategies include: +- Master-Slave Replication +- Multi-Master Replication +- Quorum-based Replication + +""", + """ +# Database Architecture Patterns + +Modern database systems employ various architectural patterns to achieve scalability, +reliability, and performance. Understanding these patterns is crucial for building +robust data-intensive applications. + +## Relational Database Management Systems (RDBMS) + +### ACID Properties +- **Atomicity**: Transactions are all-or-nothing +- **Consistency**: Database remains in valid state +- **Isolation**: Concurrent transactions don't interfere +- **Durability**: Committed data persists + +### Normalization +Database normalization is the process of organizing data to reduce redundancy: +- First Normal Form (1NF) +- Second Normal Form (2NF) +- Third Normal Form (3NF) +- Boyce-Codd Normal Form (BCNF) + +## NoSQL Databases + +### Document Stores +Examples: MongoDB, CouchDB +Store data as JSON-like documents with flexible schemas. + +### Key-Value Stores +Examples: Redis, DynamoDB +Simple key-value pairs for high-performance lookups. + +### Column-Family Stores +Examples: Cassandra, HBase +Optimized for write-heavy workloads and wide-column data. + +### Graph Databases +Examples: Neo4j, Amazon Neptune +Specialized for relationship-heavy data and graph queries. + +""", + """ +# API Design Best Practices + +Application Programming Interfaces (APIs) are the backbone of modern software integration. +Well-designed APIs are intuitive, scalable, and maintainable. + +## RESTful API Principles + +### Resource-Based URLs +URLs should represent resources, not actions: +- Good: `/api/v1/users/123` +- Bad: `/api/v1/getUser?id=123` + +### HTTP Methods +- **GET**: Retrieve resources +- **POST**: Create new resources +- **PUT**: Update entire resources +- **PATCH**: Partial updates +- **DELETE**: Remove resources + +### Status Codes +Proper use of HTTP status codes: +- 200 OK: Successful GET, PUT, PATCH +- 201 Created: Successful POST +- 204 No Content: Successful DELETE +- 400 Bad Request: Client error +- 401 Unauthorized: Authentication required +- 403 Forbidden: Authenticated but not authorized +- 404 Not Found: Resource doesn't exist +- 500 Internal Server Error: Server-side error + +## Versioning Strategies + +### URL Versioning +Include version in the URL path: `/api/v1/resources` + +### Header Versioning +Use custom headers: `Accept: application/vnd.api+json;version=1` + +### Query Parameter Versioning +Include version as parameter: `/api/resources?version=1` + +## Authentication and Security + +### API Key Authentication +Simple but limited security mechanism for identifying API consumers. + +### OAuth 2.0 +Industry-standard protocol for authorization, supporting multiple grant types. + +### JWT (JSON Web Tokens) +Stateless authentication mechanism with encoded claims. + +## Rate Limiting +Protect your API from abuse: +- Per-user limits +- Per-IP limits +- Time-based windows +- Token bucket algorithm + +""", + """ +# Microservices Architecture + +Microservices architecture structures applications as collections of loosely coupled, +independently deployable services. Each service is focused on a specific business capability. + +## Core Principles + +### Single Responsibility +Each microservice should have one reason to change and handle one business capability. + +### Decentralized Data Management +Each service manages its own database, avoiding shared databases that create coupling. + +### Independent Deployment +Services can be deployed independently without affecting others. + +### Fault Isolation +Failures in one service shouldn't cascade to others. + +## Service Communication Patterns + +### Synchronous Communication +- REST over HTTP/HTTPS +- gRPC for high-performance RPC +- GraphQL for flexible querying + +### Asynchronous Communication +- Message Queues (RabbitMQ, Apache Kafka) +- Event-driven architecture +- Publish-Subscribe patterns + +## Service Discovery + +### Client-Side Discovery +Clients query a service registry to find available instances. + +### Server-Side Discovery +Load balancer queries the service registry and routes requests. + +## API Gateway Pattern +Centralized entry point for all client requests: +- Request routing +- Authentication and authorization +- Rate limiting +- Request/response transformation +- Monitoring and logging + +## Circuit Breaker Pattern +Prevent cascading failures: +- Closed: Normal operation +- Open: Requests fail immediately +- Half-Open: Test if service recovered + +""", + """ +# Cloud Computing Fundamentals + +Cloud computing provides on-demand access to computing resources over the internet, +enabling scalability, flexibility, and cost optimization. + +## Service Models + +### Infrastructure as a Service (IaaS) +Virtualized computing resources over the internet. +Examples: AWS EC2, Google Compute Engine, Azure Virtual Machines + +### Platform as a Service (PaaS) +Complete development and deployment environment in the cloud. +Examples: Heroku, Google App Engine, AWS Elastic Beanstalk + +### Software as a Service (SaaS) +Software applications delivered over the internet. +Examples: Salesforce, Google Workspace, Microsoft 365 + +## Deployment Models + +### Public Cloud +Services offered over the public internet and shared across organizations. + +### Private Cloud +Cloud infrastructure operated solely for a single organization. + +### Hybrid Cloud +Combination of public and private clouds with data and application portability. + +### Multi-Cloud +Use of multiple cloud computing services from different providers. + +## Key Services + +### Compute Services +- Virtual Machines +- Container Services (ECS, Kubernetes) +- Serverless Functions (Lambda, Cloud Functions) + +### Storage Services +- Object Storage (S3, Cloud Storage) +- Block Storage (EBS, Persistent Disk) +- File Storage (EFS, Filestore) + +### Database Services +- Relational (RDS, Cloud SQL) +- NoSQL (DynamoDB, Firestore) +- Data Warehousing (Redshift, BigQuery) + +### Networking Services +- Virtual Private Cloud (VPC) +- Load Balancers +- Content Delivery Networks (CDN) +- DNS Management + +## Cost Optimization Strategies + +### Right-Sizing +Match instance types to actual workload requirements. + +### Reserved Instances +Commit to long-term usage for discounted rates. + +### Spot Instances +Use spare capacity at reduced rates for fault-tolerant workloads. + +### Auto-Scaling +Automatically adjust resources based on demand. + +""" + ] + + target_size_bytes = target_size_mb * 1024 * 1024 + current_size = 0 + section_index = 0 + + with open(output_path, 'w', encoding='utf-8') as f: + header = f"# Large Test Document ({target_size_mb}MB Uncompressed)\n\n" + header += "This is a generated test document to verify the DocuQuery API's ability to handle large ZIP files.\n" + header += "The document will be compressed into a ZIP archive before upload.\n\n" + f.write(header) + current_size += len(header.encode('utf-8')) + + iteration = 0 + while current_size < target_size_bytes: + if iteration % 100 == 0: + marker = f"\n## Section Group {iteration // 100}\n\n" + f.write(marker) + current_size += len(marker.encode('utf-8')) + + section = sample_sections[section_index] + f.write(section) + current_size += len(section.encode('utf-8')) + + section_index = (section_index + 1) % len(sample_sections) + iteration += 1 + + if iteration % 1000 == 0: + progress_mb = current_size / (1024 * 1024) + print(f" Progress: {progress_mb:.1f}MB / {target_size_mb}MB") + + final_size_mb = os.path.getsize(output_path) / (1024 * 1024) + print(f"✓ Generated file: {output_path}") + print(f"✓ File size: {final_size_mb:.2f}MB") + return output_path + + +def create_zip_file(markdown_path: Path, zip_path: Path): + """ + Create a ZIP file containing the markdown document. + + Args: + markdown_path: Path to the markdown file to compress + zip_path: Path where the ZIP file will be saved + """ + print(f"\nCreating ZIP archive...") + + zip_path.parent.mkdir(parents=True, exist_ok=True) + + with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED, compresslevel=9) as zipf: + zipf.write(markdown_path, markdown_path.name) + + zip_size_mb = os.path.getsize(zip_path) / (1024 * 1024) + md_size_mb = os.path.getsize(markdown_path) / (1024 * 1024) + compression_ratio = (1 - zip_size_mb / md_size_mb) * 100 + + print(f"✓ Created ZIP file: {zip_path}") + print(f"✓ ZIP size: {zip_size_mb:.2f}MB") + print(f"✓ Compression ratio: {compression_ratio:.1f}%") + + return zip_path + + +async def upload_file(file_path: Path, client: httpx.AsyncClient): + """Upload a file to the API and return the job ID.""" + print(f"\nUploading file: {file_path.name}...") + print(f"File size: {os.path.getsize(file_path) / (1024 * 1024):.2f}MB") + + with open(file_path, "rb") as f: + files = {"file": (file_path.name, f, "application/zip")} + + try: + response = await client.post(UPLOAD_ENDPOINT, files=files, timeout=300.0) + response.raise_for_status() + except httpx.RequestError as e: + print(f"✗ Error: Could not connect to the server at {BASE_URL}. Is it running?") + print(f" Details: {e}") + return None + except httpx.HTTPStatusError as e: + if e.response.status_code == 401: + print("✗ Error: Got a 401 Unauthorized response. Is your API_KEY in .env correct?") + elif e.response.status_code == 400: + print(f"✗ Error: Bad request - {e.response.text}") + else: + print(f"✗ An HTTP error occurred: {e.response.status_code} - {e.response.text}") + return None + + if response.status_code == 202: + job = response.json() + job_id = job["job_id"] + print(f"✓ File accepted. Job ID: {job_id}") + return job_id + else: + print(f"✗ Upload failed with status {response.status_code}: {response.text}") + return None + + +async def poll_job_status(job_id: str, client: httpx.AsyncClient, timeout: int = 300): + """Poll the job status until completion or timeout.""" + print(f"\nPolling for job completion (timeout: {timeout}s)...") + start_time = time.time() + last_status = None + + while time.time() - start_time < timeout: + status_url = STATUS_ENDPOINT.format(job_id=job_id) + + try: + status_response = await client.get(status_url) + status_response.raise_for_status() + except Exception as e: + print(f" Error fetching status: {e}") + await asyncio.sleep(5) + continue + + if status_response.status_code == 200: + job_data = status_response.json() + job_status = job_data["status"] + + if job_status != last_status: + elapsed = time.time() - start_time + print(f" [{elapsed:.1f}s] Status: {job_status}") + last_status = job_status + + if job_status == "COMPLETED": + print(f"✓ Job completed successfully!") + return True + elif job_status == "FAILED": + print(f"✗ Job failed.") + return False + + await asyncio.sleep(5) + + print(f"✗ Error: Job did not complete within {timeout}s timeout.") + return False + + +async def test_query(client: httpx.AsyncClient, question: str): + """Test querying the knowledge base.""" + print(f"\nTesting query: '{question}'") + + try: + response = await client.post( + QUERY_ENDPOINT, + json={"question": question}, + timeout=60.0 + ) + response.raise_for_status() + + result = response.json() + print(f"✓ Query successful!") + print(f" Answer: {result['answer'][:200]}...") + print(f" Sources: {len(result['sources'])} chunks") + return True + except Exception as e: + print(f"✗ Query failed: {e}") + return False + + +async def main(): + """Main test orchestration.""" + print("=" * 70) + print("Large File Upload Test for DocuQuery API") + print("=" * 70) + + if not API_KEY: + print("✗ Error: API_KEY not found in environment. Please set it in your .env file.") + return 1 + + print(f"\n[Step 1] Generating {TARGET_FILE_SIZE_MB}MB markdown file...") + try: + md_path = generate_large_markdown_file(TARGET_FILE_SIZE_MB, LARGE_FILE_PATH) + except Exception as e: + print(f"✗ Error generating markdown file: {e}") + return 1 + + print(f"\n[Step 2] Creating ZIP archive...") + try: + zip_path = create_zip_file(md_path, LARGE_ZIP_PATH) + except Exception as e: + print(f"✗ Error creating ZIP file: {e}") + return 1 + + print(f"\n[Step 3] Uploading ZIP file to API...") + headers = {"X-API-KEY": API_KEY} + + async with httpx.AsyncClient(base_url=BASE_URL, headers=headers) as client: + job_id = await upload_file(zip_path, client) + + if not job_id: + print("\n✗ Test FAILED: Could not upload file") + return 1 + + print(f"\n[Step 4] Monitoring document processing...") + success = await poll_job_status(job_id, client, timeout=1800) # 30 minute timeout for 50MB + + if not success: + print("\n✗ Test FAILED: Document processing failed or timed out") + return 1 + + print(f"\n[Step 5] Testing query capabilities...") + query_success = await test_query( + client, + "What are the key characteristics of distributed systems?" + ) + + if not query_success: + print("\n⚠ Warning: Document processed but query failed") + return 1 + + # Success! + zip_size_mb = os.path.getsize(LARGE_ZIP_PATH) / (1024 * 1024) + print("\n" + "=" * 70) + print("✓ ALL TESTS PASSED!") + print(f"✓ Successfully uploaded and processed a {zip_size_mb:.2f}MB ZIP file") + print(f"✓ Containing {TARGET_FILE_SIZE_MB}MB of markdown content") + print("=" * 70) + return 0 + + +if __name__ == "__main__": + try: + exit_code = asyncio.run(main()) + sys.exit(exit_code) + except KeyboardInterrupt: + print("\n\nTest interrupted by user.") + sys.exit(1) + except Exception as e: + print(f"\n✗ Unexpected error: {e}") + import traceback + traceback.print_exc() + sys.exit(1) diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..70ab813 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,44 @@ +[project] +name = "docuquery-api" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "aiofiles>=25.1.0", + "aiosqlite>=0.21.0", + "alembic>=1.17.1", + "anyio>=4.11.0", + "asyncpg>=0.30.0", + "celery>=5.5.3", + "fastapi[standard]>=0.120.3", + "httpx>=0.28.1", + "fastembed>=0.2.7", + "langchain-core>=0.2.22", + "langchain-text-splitters>=0.2.2", + "pgvector>=0.4.1", + "pydantic-settings>=2.11.0", + "pytest>=8.4.2", + "pytest-asyncio>=1.2.0", + "pytest-mock>=3.15.1", + "pytest-tornasync>=0.6.0.post2", + "pytest-trio>=0.8.0", + "pytest-twisted>=1.14.3", + "python-dotenv>=1.2.1", + "python-json-logger>=4.0.0", + "redis>=7.0.1", + "sqlalchemy>=2.0", + "twisted>=25.5.0", + "google-generativeai>=0.8.5", + "slowapi>=0.1.9", + "starlette-prometheus>=0.10.0", + "psycopg2-binary>=2.9.11", +] +[project.optional-dependencies] +test = [ + "pytest>=8.4.0", + "pytest-asyncio>=0.24.0", + "httpx>=0.28.1", +] +[tool.setuptools] +packages = ["app"] diff --git a/pytest.ini b/pytest.ini new file mode 100644 index 0000000..d280de0 --- /dev/null +++ b/pytest.ini @@ -0,0 +1,2 @@ +[pytest] +asyncio_mode = auto \ No newline at end of file diff --git a/sentence_file.py b/sentence_file.py new file mode 100644 index 0000000..cd040eb --- /dev/null +++ b/sentence_file.py @@ -0,0 +1,4 @@ +from fastembed import TextEmbedding + +for item in TextEmbedding.list_supported_models(): + print(f"model = {item.get('model')}\nsize = {item.get('size_in_GB')}") diff --git a/test_rate_limit.py b/test_rate_limit.py new file mode 100644 index 0000000..aa5d0f3 --- /dev/null +++ b/test_rate_limit.py @@ -0,0 +1,39 @@ +import requests +import os +import time +import logging +from dotenv import load_dotenv + +load_dotenv() +logger = logging.getLogger(__name__) +API_KEY = os.getenv("API_KEY") +HEADERS = {"X-API-KEY": API_KEY} +QUERY_URL = "http://127.0.0.1:8000/api/v1/query" + +def test_limit(): + """ + Tests the rate limit for the synchronous /query endpoint. + """ + if not API_KEY: + logger.error("Error: API_KEY not found in environment. 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