FLAMEHAVEN FileSearch

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Overview

Self-hosted RAG file search engine (FastAPI) with keyword/semantic/hybrid modes, citations, API keys, and Docker quickstart.

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FLAMEHAVEN FileSearch is an open-source, self-hosted RAG document search engine you can run locally (Docker or Python). It supports multi-format ingestion (PDF, DOCX, TXT, MD) and provides keyword, semantic, and hybrid search modes (with typo correction). Results include source attribution, and the API includes production features like API-key authentication with permissions, rate limiting, audit logging, batch search, and an admin dashboard. It integrates with Google Gemini (via GEMINI_API_KEY) and supports a lightweight local store plus optional components such as Redis caching and Postgres/pgvector for higher-performance deployments.

Autonomy level

16%

Reasoning: Flamehaven FileSearch operates as a retrieval-augmented generation (RAG) tool rather than an autonomous agent. It requires explicit human input for setup, configuration, and query submission. The system is fundamentally passive—it processes documents and responds to semantic search queries but does not independently initiate actions, learn from int...

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Some of the use cases of FLAMEHAVEN FileSearch:

Self-hosting private semantic search over internal documents without sending data to third parties.
Adding RAG-style retrieval (with citations/source links) to apps via REST API or Python SDK.
Indexing and searching PDFs/DOCX/TXT/Markdown using keyword, semantic, or hybrid modes.
Running a production-ready search service with API keys, quotas, audit logs, and monitoring endpoints.

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Pricing model:

free

Code access:

open-source

Popularity level: 53%

Industries:

Software Development Business Automation Research

Tags:

rag semantic search document search fastapi docker api key auth hybrid search sqlite pgvector gemini source attribution

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