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bulentturudu/agentsproject

Analysis updated 2026-05-18

★ 0PythonAudience · vibe coderComplexity · 2/5Setup · easy

TLDR

A Python chatbot that searches the web when it does not know an answer and remembers past conversations in a local SQLite database.

Mindmap

mindmap
  root((AgentsProject))
    What it does
      Web-searching Chatbot
      Conversation Memory
    Tech stack
      Python
      LangGraph
      GPT-4o-mini
      Tavily Search
      SQLite
    Reasoning
      ReAct Pattern
      Search When Unsure
    Setup
      OpenAI API Key
      Tavily API Key

Code map

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What do people build with it?

USE CASE 1

Build a personal chatbot that looks up current information online instead of guessing when it does not know something.

USE CASE 2

Keep a running memory of past conversations so the assistant recognizes returning users.

USE CASE 3

Learn how the ReAct reasoning pattern works by reading a small, self-contained LangGraph example.

What is it built with?

PythonLangGraphOpenAI GPT-4o-miniTavily SearchSQLite

How does it compare?

bulentturudu/agentsproject0xhassaan/nn-from-scratch3ks/embedoc
Stars00—
LanguagePythonPythonPython
Last pushed——2023-06-08
Maintenance——Dormant
Setup difficultyeasymoderatehard
Complexity2/54/51/5
Audiencevibe coderdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

Requires a paid OpenAI API key and a Tavily API key before it will run.

In plain English

This is a Python AI assistant built with LangGraph that goes beyond a simple chatbot by searching the internet when it encounters questions it cannot answer, and storing conversation history in a local database so it can remember past exchanges with you. The AI reasoning follows the ReAct pattern, a technique where the model decides whether to look something up before answering rather than guessing. Internet searches are powered by Tavily Search. Conversation memory is stored in SQLite, a lightweight local database. The AI model used is GPT-4o-mini from OpenAI. Setup requires an OpenAI API key and a Tavily API key. The README is written in Turkish.

Copy-paste prompts

Prompt 1
Walk me through setting up this LangGraph ReAct agent with an OpenAI API key and a Tavily API key in a .env file.
Prompt 2
Explain how the ReAct pattern decides when to search the internet versus answering directly from the model.
Prompt 3
Show me how conversation history is stored and retrieved from the SQLite database in this project.
Prompt 4
Help me add a new tool to this LangGraph agent besides Tavily Search.

Frequently asked questions

What is agentsproject?

A Python chatbot that searches the web when it does not know an answer and remembers past conversations in a local SQLite database.

What language is agentsproject written in?

Mainly Python. The stack also includes Python, LangGraph, OpenAI GPT-4o-mini.

How hard is agentsproject to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is agentsproject for?

Mainly vibe coder.

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