Article Analysis Assistant

This project is an advanced article analysis assistant that leverages AI tools to perform thorough research and analysis on articles. It uses a combination of Bing search and a custom research assistant to gather and synthesize information, providing comprehensive insights into the content.

Features

• Bing Search Integration: Uses Bing to search for additional information on topics discussed in the article.
• Research Assistant: Generates detailed reports on subjects that require deeper understanding.
• RSS Feed and Article Parsing: Fetches and processes content from RSS feeds or direct article URLs.
• Title Generation: Automatically generates concise and informative titles for articles.
• Streamlined Analysis: Utilizes a structured prompt to guide the AI's analysis process, ensuring thorough exploration and reasoning.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/article-analysis-assistant.git
   cd article-analysis-assistant

2. Install the required dependencies:

   pip install -r requirements.txt

3. Set up environment variables in a .env file:

   OPENAI_API_KEY=<your_openai_api_key>
   TAVILY_API_KEY=<your_tavily_api_key>
   AZURE_OPENAI_API_KEY=<your_azure_openai_api_key>
   AZURE_OPENAI_ENDPOINT=<your_azure_openai_endpoint>
   AZURE_OPENAI_DEPLOYMENT_NAME=<your_azure_openai_deployment_name>
   AZURE_OPENAI_API_VERSION=<your_azure_openai_api_version>
   BING_SEARCH_URL=<your_bing_search_url>
   BING_SUBSCRIPTION_KEY=<your_bing_subscription_key>
   LANGSMITH_TRACING=<true_or_false>
   LANGSMITH_ENDPOINT=<your_langsmith_endpoint>
   LANGSMITH_API_KEY=<your_langsmith_api_key>
   LANGSMITH_PROJECT=<your_langsmith_project>
   

Usage

1. Run the main script:

   python main.py

2. Enter an RSS feed URL or an article URL when prompted.

3. The assistant will fetch the content, perform analysis, and save the results in the results directory.

File Structure

• main.py: The main script that orchestrates the article analysis process.
• prompt.txt: Contains the structured prompt used to guide the AI's analysis.
• feedParser.py: Handles fetching and parsing of RSS feeds and articles.
• results/: Directory where analysis results are saved.