Deep Searcher
Deep Searcher is a local open-source deep research solution that integrates Milvus and LangChain to provide advanced vector search and retrieval capabilities using open-source models.
About this tool
Deep Searcher
Category: SDKs & Libraries
Tags: open-source, milvus, langchain, vector-search
Description
Deep Searcher is a local open-source deep research solution that integrates Milvus (an open-source vector database) and LangChain to provide advanced vector search and retrieval capabilities using open-source models. It is designed as both a Python library and a command-line tool for agentic research workflows.
Features
- Agentic RAG (Retrieval-Augmented Generation): Automates deep research by decomposing complex queries, searching across multiple document sources, and synthesizing structured reports.
- Modular Research Pipeline:
- Define/Refine the Question: Breaks down user queries into sub-queries for more granular research.
- Query Routing: Uses an LLM to route sub-queries to only the most relevant data sources or collections in Milvus.
- Similarity Search: Retrieves relevant document chunks using vector search with Milvus.
- Reflection: The agent reflects on the completeness of its answers, determining if additional sub-queries are needed.
- Conditional Execution Flow: Automatically repeats research steps as needed, based on LLM output, until the research is complete.
- Synthesis: Combines all findings into a consistent and well-structured report.
- Flexible Data Source Configuration: Allows input of multiple source documents and manual specification of data sources (local or online).
- Embedding Model and Vector DB Selection: Embedding model and vector database can be configured via a configuration file.
- Web Crawling as a Tool: Capable of using web crawling for additional data gathering (planned for future updates).
- Open-Source: Fully open-source and designed for local or private deployment.
- Supports Multiple Inference Services: Works with most inference services, including OpenAI, Gemini, DeepSeek, and Grok 3 (coming soon).
- Efficient Inference: Demonstrates use with fast and scalable inference services (e.g., DeepSeek-R1 on SambaNova hardware), but can also run locally with open models.
Pricing
No pricing information is specified. Deep Searcher is open-source and can be self-hosted. (Inference services such as DeepSeek-R1 may have their own costs.)
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