Metadata-Version: 2.2
Name: researchbriefagent
Version: 0.1.2
Summary: A Python package for creating a research brief agent
Home-page: https://github.com/Vikhram-S/researchbriefagent
Author: Vikhram S
Author-email: vikhrams@saveetha.ac.in
License: MIT
Project-URL: Bug Tracker, https://github.com/Vikhram-S/researchbriefagent
Project-URL: Documentation, https://pypi.org/project/researchbriefagent/
Project-URL: Source Code, https://github.com/Vikhram-S/researchbriefagent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7, <3.14
Description-Content-Type: text/markdown
Requires-Dist: langchain-community
Requires-Dist: langgraph
Requires-Dist: langchain-anthropic
Requires-Dist: tavily-python
Requires-Dist: langgraph-checkpoint-sqlite
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: project-url
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# Research Brief Agent

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A Python library for an AI agent that generates concise research briefs from web searches using LangChain, Anthropic's Claude, and Tavily search.

## Overview

The `ResearchBriefAgent` automates the process of researching a topic and producing a structured brief, including key points and sources. Built with LangChain's ecosystem, it leverages Anthropic's Claude model for reasoning and Tavily for web search, with SQLite-backed memory for context persistence.

## Features

- **Topic-Based Research**: Generate briefs on any topic with a single function call.
- **Structured Output**: Receive formatted briefs with key points and cited sources.
- **Memory Persistence**: Retain conversation context across queries using SQLite checkpointing.
- **Extensible**: Built on LangChain, allowing integration with additional tools and models.

## Installation

Install the library via PyPI:

```bash
pip install researchbriefagent
```
# Usage
```
from researchbriefagent import ResearchBriefAgent
agent = ResearchBriefAgent(anthropic_api_key="your_anthropic_api_key", tavily_api_key="your_tavily_api_key")
brief = agent.generate_brief("Impact of renewable energy on climate change")
print(brief)
```
Example Output:
## Research Brief: Impact of renewable energy on climate change
### Key Points
- Reduces greenhouse gas emissions by replacing fossil fuels.
- Solar and wind power adoption has surged globally.
- Critical for limiting warming to 1.5°C.
### Sources
- https://www.iea.org/reports/renewables-2023
- https://www.un.org/en/climatechange/renewable-energy
## Requirements
Python: 3.8 or higher
Dependencies: langchain-community, langgraph, langchain-anthropic, tavily-python, langgraph-checkpoint-sqlite
API Keys: Obtain from Anthropic and Tavily
Setup
Clone the repo:
```
git clone https://github.com/yourusername/researchbriefagent.git
cd researchbriefagent
```
Install dependencies:
```
pip install -r requirements.txt
```

Or install from PyPI:
```
pip install researchbriefagent
```

# Contributing
Contributions are welcome! Fork the repo, create a feature branch, commit changes, and open a pull request. See CONTRIBUTING.md for details (to be added).

# License
MIT License - see LICENSE for details.

# Contact
Email: vikhrams@saveetha.ac.in

Issues: GitHub

# Acknowledgments
Built with LangChain and Anthropic.
Search powered by Tavily.

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