LangChain Chatbot Projects

A collection of chatbot applications built with LangChain, exploring different LLM providers and architectures.

Projects

1. Chatbot with Groq (chatbot_using_groq/)

A simple chatbot using Groq's free API with the LLaMA 3.1 model.

Stack: LangChain, Groq, Streamlit

Setup:

pip install langchain-groq streamlit python-dotenv

Add to .env:

GROQ_API_KEY=your_groq_api_key

Run:

streamlit run chatbot_using_groq/app.py

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2. Chatbot with Ollama (chatbot_using_ollama/)

A chatbot running entirely locally using Ollama with the LLaMA 3.2 model. No API key required.

Stack: LangChain, Ollama, Streamlit

Setup:

pip install langchain-ollama streamlit python-dotenv
ollama pull llama3.2

Run:

ollama serve
streamlit run chatbot_using_ollama/app.py

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3. API Chatbot (api/)

A production-style client-server architecture with a FastAPI backend exposing multiple LLM endpoints and a Streamlit frontend.

Stack: LangChain, FastAPI, LangServe, Groq, Ollama, Streamlit

Endpoints:

• POST /essay/invoke - Generate an essay using Groq (LLaMA 3.1)
• POST /poem/invoke - Generate a poem using Ollama (LLaMA 3.2)
• POST /groq/invoke - Direct Groq LLM endpoint

Setup:

pip install langchain-groq langchain-ollama fastapi langserve uvicorn sse-starlette streamlit python-dotenv
ollama pull llama3.2

Add to .env:

GROQ_API_KEY=your_groq_api_key
LANGCHAIN_API_KEY=your_langsmith_api_key
LANGCHAIN_PROJECT=your_project_name

Run:

# Terminal 1 - start backend
python api/app.py

# Terminal 2 - start frontend
streamlit run api/client.py

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Requirements

Install all dependencies:

pip install -r requirement.txt

Environment Variables

Variable	Required For	Description
GROQ_API_KEY	Groq chatbot, API chatbot	Free API key from console.groq.com
LANGCHAIN_API_KEY	All (optional)	LangSmith tracing key
LANGCHAIN_PROJECT	All (optional)	LangSmith project name