README.md

metadata

title: LeadGenAI
emoji: 📊
colorFrom: blue
colorTo: purple
sdk_version: 1.26.0
app_file: app.py
pinned: false
license: apache-2.0
sdk: streamlit
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/66743e7056cf3c354860fabb/yZH3E8P6M0y3KJDlagO_p.png
short_description: LinkedIn Lead Generation and Business Optimization App

LeadGenAI - LinkedIn Lead Generation and Business Optimization App

LeadGenAI is a Streamlit-based application that empowers users to generate leads from LinkedIn and optimize their business strategies using the power of IBM Watsonx AI. This application offers two core functionalities: lead generation based on specific criteria and AI-powered business plan generation.

Features

Lead Generation:

• Targeted Search: Filter LinkedIn profiles based on criteria like country, industry, and company.
• Data Extraction: Extract key information such as name, location, company, position, and about section.
• Data Export: Download leads as CSV and PDF files for easy access and sharing.
• Session History: Access and download previous lead generation sessions.

Business Optimization:

• AI-Powered Business Plans: Generate comprehensive business plans based on user-provided requirements.
• Detailed Insights: Receive detailed business plans including concept, target audience, revenue model, key differentiators, and potential challenges.
• Lead Targeting: Get specific lead suggestions with links to Twitter, LinkedIn, and company websites.
• Session History: Review and download past business plan generation sessions.

Installation

1. Clone the Repository:

   git clone https://huggingface.co/spaces/mmfarabi/LeadGenAI
   

2. Create a Virtual Environment (Recommended):

   python3 -m venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   

3. Install Dependencies:

   pip install -r requirements.txt
   

   requirements.txt should contain the following:

   streamlit==1.26.0
   pandas==2.0.3
   fpdf==1.7.2
   ibm-watsonx-ai
   

4. IBM Watsonx Credentials: You will need an IBM Watsonx account and API key. Store these credentials securely. The app currently stores credentials directly in the get_credentials() function, but this should be updated to a more secure method such as environment variables or a secrets management tool. Update the placeholder values in the get_credentials() function with your actual credentials:

   def get_credentials():
       return {
           "url": "YOUR_WATSONX_URL",
           "apikey": "YOUR_WATSONX_API_KEY"
       }
   

5. Data Files: Ensure the LinkedIn_profiles_info_modified.json and LinkedIn_company_info_modified.json files are present in the same directory as the application. These files contain the LinkedIn data. The format is expected to be JSON. If the files do not start with [, the app will attempt to convert them to a valid JSON array.

Usage

1. Run the App:

   streamlit run app.py
   

2. Lead Generation:

   • Enter your lead search criteria in the text area.
   • Select the desired number of leads.
   • Click "Generate Leads".

3. Business Optimization:

   • Enter your business idea requirements in the text area.
   • Click "Generate Idea & Leads".
   • Download the generated business plan as a PDF.

4. Accessing Past Sessions: Use the tabs to navigate to "Lead Sessions" or "Plan Sessions" to view and download data from previous runs.

Technologies Used

• Streamlit: For building the interactive web application.
• Pandas: For data manipulation and analysis.
• FPDF: For generating PDF reports.
• IBM Watsonx AI: For generating business plans and ideas.
• SQLite: For storing session data.
• JSON: For data storage and exchange.

License

Apache License Version 2.0