zilliztech/deep-searcher

Health v2 · maintenance only

Flags: prerelease_only

Adoption not part of the score

8224 stars · 797 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

DeepSearcher is an open-source deep research tool that combines LLMs (DeepSeek, OpenAI, Claude, Qwen, etc.) with vector databases like Milvus to search, reason over, and generate reports from private data. It is a Python application suited for enterprise knowledge management and intelligent Q&A over internal documents.

Use cases

• run deep research queries over private enterprise documents
• build an intelligent Q&A system on internal knowledge bases
• index local files into a vector database for retrieval
• generate comprehensive research reports from private data
• search internal data securely without sending it to third parties
• compare answers from multiple LLM reasoning models over a private corpus

When to choose

• you need a self-hosted deep research alternative that keeps data private
• your organization already uses Milvus or Zilliz Cloud for vector storage
• you want agentic RAG with reasoning models over local documents
• you need flexible swapping of LLM and embedding providers

When to avoid

• you only need simple keyword search without LLM reasoning
• you want a fully managed SaaS research product with no setup
• your data is small enough that a plain LLM chat with file upload suffices
• you need web crawling today, as it is still under development

Facets

application · maturity active

rag search-engine vector-database llm-inference agent-framework chatbot large-language-models databases artificial-intelligence python self-hosted cli deep-research agentic-rag milvus private-data-search enterprise-knowledge-management deepseek document-loader retrieval-augmented-generation ai-agents search docker

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