Ollama Pydantic Project
by jageenshukla
This project demonstrates how to use a local Ollama model with the Pydantic agent framework to create an intelligent agent. The agent is connected to an MCP server to utilize tools and provides a user-friendly interface using Streamlit.
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What is Ollama Pydantic Project?
This project showcases the integration of a locally hosted Ollama model with the Pydantic agent framework, enabling the creation of an intelligent agent. It connects to an MCP server for tool utilization and offers a user-friendly chatbot interface via Streamlit.
How to use Ollama Pydantic Project?
To use this project, clone the repository, set up a virtual environment, install dependencies, ensure the Ollama server and MCP server are running, and then run the Streamlit application. Interact with the chatbot through the provided URL in your browser by typing queries in the input box.
Key features of Ollama Pydantic Project
Streamlit Chatbot
Ollama Model Integration
MCP Server Tools
Pydantic Framework
Use cases of Ollama Pydantic Project
Building intelligent chatbots
Integrating local LLMs with agent frameworks
Creating data validation pipelines
Connecting agents to external tools
FAQ from Ollama Pydantic Project
How do I ensure the Ollama server is running correctly?
How do I ensure the Ollama server is running correctly?
Ensure the Ollama server is running on http://localhost:11434/v1.
What Python version is required?
What Python version is required?
Python 3.8 or higher is required.
What is an MCP server and why is it needed?
What is an MCP server and why is it needed?
An MCP server enables the agent to use tools. Refer to the MCP Server Sample for more details.
How do I install the dependencies?
How do I install the dependencies?
Activate the virtual environment and run pip install -r requirements.txt.
How do I run the Streamlit application?
How do I run the Streamlit application?
Run the command streamlit run src/streamlit_app.py.