Here’s how to structure a well-organized GitHub repository for your project.

1. Repository Structure

AI_Agent_Project/
├── app.py                  # Main application file for Streamlit
├── requirements.txt        # Dependencies for the project
├── config.py               # Configuration for API keys and environment variables
├── .env                    # API keys and credentials (not uploaded to GitHub)
├── utils/                  # Utility modules
│   ├── data_handler.py     # Handles CSV and Google Sheets data
│   ├── search_api.py       # Handles web search API integration
│   ├── llm_processing.py   # Processes data with OpenAI GPT
│   └── utils.py            # Additional helper functions
├── README.md               # Project documentation
└── .gitignore              # Files/folders to ignore (e.g., .env, __pycache__)

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2. README.md File

The README.md file is the most important part of your repository. It provides an overview of the project, setup instructions, usage details, and features.

Here’s a template for your README.md:

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README.md

AI Agent for Web Search and Information Extraction

Overview

This project is a Streamlit-based AI application that allows users to:

1. Upload a CSV file or connect to a Google Sheet.
2. Use a custom prompt to search and retrieve information for each entity (e.g., companies).
3. Process search results with OpenAI GPT (e.g., extract emails or other data).
4. View and download structured results.

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Features

• Upload CSV files or connect to Google Sheets.
• Perform automated web searches for entities using a custom prompt.
• Extract information using OpenAI GPT-3.5/4.
• View and download the results in CSV format.

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Setup Instructions

Prerequisites

1. Python 3.8 or above.
2. API keys for:
   • OpenAI: Sign up.
   • SerpAPI (or another search API): Sign up.
   • Google Sheets API: Guide to create credentials.

Steps to Set Up

1. Clone the repository:

   git clone https://github.com/your_username/AI_Agent_Project.git
   cd AI_Agent_Project

2. Install dependencies:

   pip install -r requirements.txt

3. Create a .env file in the project root and add your credentials:

   OPENAI_API_KEY=your_openai_api_key
   SEARCH_API_KEY=your_search_api_key
   GOOGLE_CREDENTIALS_FILE=path_to_your_google_service_account.json
   

4. Run the app:

   streamlit run app.py

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Usage

1. Open the app in your browser (e.g., http://localhost:8501).
2. Upload a CSV file with entities (e.g., company names).
3. Enter a custom prompt (e.g., "Get me the email address of {entity}").
4. Click "Run Search and Extraction."
5. View the extracted data and download it as a CSV file.

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File Descriptions

File/Folder	Description
app.py	Main application file for Streamlit.
config.py	Loads API keys and configuration from .env.
requirements.txt	Lists all Python dependencies required for the project.
.env	Stores sensitive API keys (ignored in .gitignore).
utils/data_handler.py	Functions to handle CSV uploads and Google Sheets integration.
utils/search_api.py	Handles integration with SerpAPI or another web search API.
utils/llm_processing.py	Uses OpenAI GPT to process search results and extract relevant information.
utils/utils.py	Contains helper functions for error handling or formatting.

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Dependencies

• Python Libraries:
  • streamlit: For building the dashboard interface.
  • pandas: For handling CSV and structured data.
  • openai: For interacting with OpenAI GPT.
  • google-auth, google-auth-oauthlib, google-api-python-client: For Google Sheets integration.
  • requests: For working with web APIs.
  • python-dotenv: For managing environment variables.

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Acknowledgments

• OpenAI for GPT-3.5/4.
• SerpAPI for search engine result extraction.
• Google Sheets API for data integration.

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3. .gitignore File

Ensure your sensitive files (like .env) and unnecessary files (e.g., __pycache__) are not pushed to GitHub.

Example .gitignore:

.env
__pycache__/
*.pyc
*.pyo
*.log
*.json

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4. Upload to GitHub

1. Initialize Git:

   git init

2. Add Files and Commit:

   git add .
   git commit -m "Initial commit for AI Agent Project"

3. Push to GitHub: Create a new repository on GitHub (e.g., AI_Agent_Project) and push the code:

   git remote add origin https://github.com/your_username/AI_Agent_Project.git
   git branch -M main
   git push -u origin main

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5. Verify and Share

1. Confirm the repository is accessible on GitHub.
2. Share the link to your repository for others to test or evaluate.

Let me know if you have further questions!!!!!!