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pydantic-ai-researcher

Created By
ibagur7 months ago
pydantic-ai-researcher is a research system that orchestrates an asynchronous loop between two specialized agents: a research agent and an evaluator agent. The research agent answers complex queries using external MCP servers, while the evaluator agent assesses and refines these answers, iterating until a satisfactory response is attained.
Overview

what is pydantic-ai-researcher?

pydantic-ai-researcher is a research system that orchestrates an asynchronous loop between two specialized agents: a research agent and an evaluator agent. The research agent answers complex queries using external MCP servers, while the evaluator agent assesses and refines these answers, iterating until a satisfactory response is attained.

how to use pydantic-ai-researcher?

To use pydantic-ai-researcher, ensure Python 3.x is installed, install the required packages using Pipenv or pip, configure the necessary environment variables in a .env file, and run the project with the command python main.py. You can then type your research queries in the interactive prompt.

key features of pydantic-ai-researcher?

  • Asynchronous Research Loop: Iterative evaluation and improvement of research answers.
  • Dual Agent System: Utilizes a research agent for data gathering and an evaluator agent for feedback.
  • Pluggable MCP Servers: Integrates with multiple MCP servers (Tavily, Brave Search, arXiv) for diverse data sources.
  • Environment Configurable: Uses environment variables and .env files for API key configuration.
  • Easy Setup: Straightforward installation via Pipfile or requirements.txt.

use cases of pydantic-ai-researcher?

  1. Conducting in-depth research on complex topics by leveraging multiple data sources.
  2. Iteratively refining answers to ensure high-quality responses to research queries.
  3. Utilizing external APIs to gather diverse information for academic or professional research.

FAQ from pydantic-ai-researcher?

  • What is the purpose of the dual agent system?

The dual agent system allows for initial data gathering and subsequent evaluation to improve the quality of answers.

  • How do I configure the environment variables?

You need to create a .env file at the project root and define the required API keys for the services you wish to use.

  • Can I use this project for any type of research?

Yes, as long as you have access to the necessary MCP servers and APIs, you can use it for various research topics.

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