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File Operations Quick Reference

Overview​

As of release 0.2.14, OGX provides comprehensive file operations and Vector Store API integration, following the OpenAI Vector Store Files API specification.

Note: For detailed overview and implementation details, see Overview in the full documentation.

Supported Providers​

Note: For complete provider details and features, see Supported Providers in the full documentation.

Inline Providers: FAISS, SQLite-vec, Milvus Remote Providers: ChromaDB, Qdrant, Weaviate, PGVector

Quick Start​

1. Upload File​

file_info = await client.files.upload(
    file=open("document.pdf", "rb"), purpose="assistants"
)

2. Create Vector Store​

vector_store = client.vector_stores.create(name="my_docs")

3. Attach File​

await client.vector_stores.files.create(
    vector_store_id=vector_store.id, file_id=file_info.id
)
results = await client.vector_stores.search(
    vector_store_id=vector_store.id, query="What is the main topic?", max_num_results=5
)

File Processing & Search​

Processing: 800 tokens default chunk size, 400 token overlap Formats: PDF, DOCX, TXT, Code files, etc. Search: Vector similarity, Hybrid (SQLite-vec), Filtered with metadata

Configuration​

Note: For detailed configuration examples and options, see Configuration Examples in the full documentation.

Basic Setup: Configure vector_io and files providers in your config.yaml

Common Use Cases​

  • RAG Systems: Document Q&A with file uploads
  • Knowledge Bases: Searchable document collections
  • Content Analysis: Document similarity and clustering
  • Research Tools: Literature review and analysis

Performance Tips​

Note: For detailed performance optimization strategies, see Performance Considerations in the full documentation.

Quick Tips: Choose provider based on your needs (speed vs. storage vs. scalability)

Troubleshooting​

Note: For comprehensive troubleshooting, see Troubleshooting in the full documentation.

Quick Fixes: Check file format compatibility, optimize chunk sizes, monitor storage

Resources​