666ghj/DeepSearchAgent-Demo

Health v2 · maintenance only

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1223 stars · 309 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A framework-free Python implementation of a deep search AI agent that generates high-quality research reports through multi-round web searching and reflection. It integrates LLMs like DeepSeek and OpenAI with the Tavily search engine and includes a Streamlit web interface.

Use cases

• build a deep research agent from scratch without langchain
• generate research reports automatically from a query
• implement multi-round search and reflection with an LLM
• compare deepseek and openai models for research tasks
• run a streamlit app for AI-powered web research
• learn how deep search agents work internally

When to choose

• you want a minimal, dependency-light deep research agent you can read and modify
• you need multi-LLM support with Tavily web search
• you want a working Streamlit UI for research report generation
• you are learning agent architecture like reflection loops and state management

When to avoid

• you need a production-grade, battle-tested deep research pipeline
• you require heavy framework integrations like LangChain or LangGraph
• you need search providers other than Tavily without writing adapters
• you need non-Python environments or offline research without an LLM API

Facets

library · maturity active

agent-framework rag search-engine llm-inference web-scraping artificial-intelligence large-language-models python cross-platform deep-search deep-research reflection-loop framework-free tavily deepseek streamlit research-reports multi-step-agent ai-agents retrieval-augmented-generation search natural-language-processing web-server

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