Spaces:
Runtime error
Runtime error
|
Download README.md from ftn03/SearchEngineToolAgent: direct link, hf CLI and curl.
- Browser
- Download file 2.4 kB
-
https://huggingface.co/spaces/ftn03/SearchEngineToolAgent/resolve/main/README.md
- Command line
-
hf download hf://spaces/ftn03/SearchEngineToolAgent/README.md
-
curl -L -o README.md https://huggingface.co/spaces/ftn03/SearchEngineToolAgent/resolve/main/README.md
2.4 kB
metadata
title: SearchEngineToolAgent
emoji: π
colorFrom: red
colorTo: red
sdk: docker
app_port: 8501
tags:
- streamlit
pinned: false
short_description: Streamlit & Langchain AI Chatbot and Agent
Welcome to our App
A conversational AI chatbot built with Streamlit and LangChain that can search the web, Wikipedia, and Arxiv to answer your questions.
Features
- Multi-tool agent powered by LangChain's ReAct architecture
- DuckDuckGo Search for general web queries
- Wikipedia for encyclopedic knowledge
- Arxiv for scientific papers and research
- Chat interface with conversation history
- Transparent reasoning β expandable steps show the agent's thinking process and tool calls
Tech Stack
- Streamlit β Web UI and chat interface
- LangChain / LangGraph β Agent orchestration and tool management
- OpenAI GPT β Language model (easily swappable with Groq/Ollama)
- LangSmith β Optional tracing and monitoring
Setup
1. Clone the repository
git clone https://github.com/ftn03/SearchEngineToolAgent.git
cd SearchEngineToolAgent
2. Install dependencies
pip install -r requirements.txt
3. Configure environment variables
Copy the example file and fill in your API keys:
cp .env.example .env
Required keys:
| Variable | Description |
|---|---|
OPENAI_API_KEY |
OpenAI API key (for GPT models) |
GROQ_API_KEY |
Groq API key (optional, for Llama/Qwen models) |
LANGCHAIN_API_KEY |
LangSmith API key (optional, for tracing) |
LANGCHAIN_PROJECT |
LangSmith project name (optional) |
4. Run the app
streamlit run app.py
The app will open at http://localhost:8501.
How It Works
- The user asks a question in the chat input
- The LangChain agent decides which tool(s) to use
- Each step is displayed with expandable details (reasoning, tool calls, tool results)
- The final answer is displayed in the chat and saved to conversation history
Switching LLM Providers
Edit app.py to swap the model. Examples:
# OpenAI
llm = ChatOpenAI(model="gpt-5-nano-2025-08-07", streaming=True)
# Groq (Llama)
llm = ChatGroq(model="llama-3.3-70b-versatile", streaming=True)