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// 61d agoOPENSOURCE RELEASE
Agentic File Search replaces RAG with autonomous agents
Agentic File Search reimagines document retrieval by replacing pre-computed embeddings with an autonomous AI agent powered by Gemini 1.5 Flash and Docling. The system navigates file structures natively using specialized tools to follow complex cross-references that traditional semantic search misses.
// ANALYSIS
- –Agents are replacing static RAG pipelines: This project perfectly illustrates the industry shift from brittle vector search toward capable agents that can utilize standard file system tools to find answers.
- –High accuracy with low latency: By leveraging Gemini 1.5 Flash and structured JSON outputs, the system achieves complex multi-hop reasoning efficiently and at a low cost of roughly $0.001 per query.
- –Broad enterprise format support: The integration of Docling enables seamless processing of diverse formats (PDF, DOCX, PPTX, XLSX) without requiring complex, custom pre-processing pipelines.
- –Transparent and auditable reasoning: The included FastAPI/WebSocket Web UI provides real-time execution logs and citations, making the agent's thought process transparent to the user.
// TAGS
agentic-file-searchagentragdocument-searchgeminiopen-sourcepython
DISCOVERED
61d ago
2026-03-28
PUBLISHED
61d ago
2026-03-28
RELEVANCE
6/ 10
AUTHOR
Prompt Engineering
