VC productivity, TEAM 7

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This project was built as part of the Data-Driven VC Hackathon organized by Red River West & Bivwak! by BNP Paribas -- Include the part above --

Overview

This project is a comprehensive application designed to process, analyze, and generate reports based on historical data, benchmark datasets, and insights from a Deck PDF file. The application integrates multiple functionalities, including processing email attachments, generating reports, and interacting with cloud-based APIs.

Prerequisites

Ensure you have the following installed:

1. Python: Version 3.8 or higher.
2. pip: Python package installer.

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Setting up the Environment

Step 1: Create a .env File

In the root directory of your project, create a file named .env and include the following environment variables:

SIMILARWEB_API_KEY = ""
HARMONIC_API_KEY = ""
PEOPLE_DATA_LABS_API_KEY = ""
PREDICT_LEADS_API_KEY = ""
PREDICT_LEADS_API_TOKEN = ""
OPENAI_API_KEY = ""
GMAIL_USER = ""
GMAIL_PASSWORD = ""

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Step 2: Generate a Gmail App Password

1. Sign in to Your Google Account: Go to Google Account.
2. Enable 2-Factor Authentication (2FA):
   • Navigate to the Security section.
   • Under Signing in to Google, enable 2-Step Verification if it’s not already enabled.
3. Generate an App Password:
   • In the Security section, locate App Passwords under the "Signing in to Google" section.
   • You may need to re-enter your password.
   • Click Generate. A 16-character app password will be displayed.
   • Copy and use this password as the GMAIL_PASSWORD value in your .env file.

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Application Functionality

Process Email Attachments:

• Scans incoming emails from a specified Gmail account.
• Processes attachments such as Excel, CSV, and PDF files.

Generate Reports:

• Produces detailed PDF reports based on the provided data:
  • Hierarchical PDF Report: Summarizes insights from the Deck PDF and historical datasets, focusing on trends and organizational data.
  • Benchmark PDF Report: Compares the subject company with competitive enterprises using benchmark data.
• Reports include visualizations, graphs, and summaries.

Send Reports:

• Sends the generated PDF reports back to specified recipients via email.

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File Structure

.
├── LICENSE
├── README.md
├── apis
│   ├── harmonic_api.py
│   ├── people_data_labs_api.py
│   ├── predict_leads_api.py
│   └── similarweb_api.py
├── backend.py
├── benchmark_pipeline.py
├── csv_file
│   └── harmonic_db.csv
├── dataset
│   ├── benchmark_db.csv
│   ├── grub.py
│   └── portcos_historical_db.csv
├── generator
│   ├── gpt.py
│   └── preprocess.py
├── historical_pipeline.py
├── main.py
├── pdf_report
│   ├── generate_benchmark_pdf.py
│   └── generate_historical_pdf.py
├── requirements.txt
└── utils
    └── preprocessing.py

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Contributing

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Submit a pull request with a detailed description of your changes.

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Running the Application

1. Install Dependencies:

   pip install -r requirements.txt

2. Run the Application:

   python main.py

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License

This project is licensed under the terms of the LICENSE file.