import gradio as gr
import google.generativeai as genai
import requests
import base64
import json

def fetch_github_files(github_url, personal_access_token):
    try:
        # Parse the GitHub URL
        parts = github_url.split('/')
        owner = parts[3]
        repo = parts[4].split('.git')[0]
        branch = 'main'  # You might want to make this configurable

        # List of common dependency files to look for
        dependency_files = [
            'requirements.txt',
            'package.json',
            'Gemfile',
            'pom.xml',
            'build.gradle',
            'composer.json',
            'Cargo.toml',
            'go.mod',
            'Pipfile'
        ]

        all_content = ""

        # Set up headers with the personal access token
        headers = {
            "Authorization": f"token {personal_access_token}",
            "Accept": "application/vnd.github.v3+json"
        }

        for file_path in dependency_files:
            # Construct the API URL
            api_url = f"https://api.github.com/repos/{owner}/{repo}/contents/{file_path}?ref={branch}"

            # Make the API request
            response = requests.get(api_url, headers=headers)

            if response.status_code == 200:
                content = response.json()
                if isinstance(content, dict) and 'content' in content:
                    # This is a file
                    file_content = base64.b64decode(content['content']).decode('utf-8')
                    all_content += f"\n\n--- {file_path} ---\n{file_content}"
                else:
                    # This is a directory or something else, skip it
                    continue

        if not all_content:
            return "Error: No dependency files found in the repository."

        return all_content
    except requests.exceptions.RequestException as e:
        return f"Error accessing GitHub: {str(e)}"
    except json.JSONDecodeError:
        return f"Error: Unable to parse GitHub API response for {file_path}"

def process_with_gemini(file_content, gemini_api_key):
    genai.configure(api_key=gemini_api_key)
    model = genai.GenerativeModel('gemini-2.5-pro-preview-03-25')
    
    prompt = f"""
    Analyze the following file content for open-source license information:

    {file_content}

    Please provide:
    1. A numbered with the name dependency and version as the title 
    2. 1st bullet under title has a brief summary of what the depency does
    3. 2nd bullet under title has the license name apache 2.0
    4. 3rd bullet under title has a hyperlink to the license file
    5. Provide no other information such as greeting or summary as the purpose is to catalog and document all open source licenses used.
    """

    response = model.generate_content(prompt)
    return response.text

def process_input(github_url, personal_access_token, gemini_api_key):
    if not github_url.startswith("https://github.com/"):
        return "Error: Invalid GitHub URL. Please use the format: https://github.com/username/repository.git"
    if not personal_access_token.strip():
        return "Error: Personal Access Token is empty. Please provide a valid token."
    
    file_content = fetch_github_files(github_url, personal_access_token)
    if file_content.startswith("Error:"):
        return file_content
    
    try:
        # Process the file content with Gemini
        analysis = process_with_gemini(file_content, gemini_api_key)
        return analysis
    except Exception as e:
        return f"Error processing the files: {str(e)}"

iface = gr.Interface(
    fn=process_input,
    inputs=[
        gr.Textbox(label="GitHub Repository URL (format: https://github.com/username/repository.git)"),
        gr.Textbox(label="GitHub Personal Access Token", type="password"),
        gr.Textbox(label="Gemini API Key", type="password"),
    ],
    outputs=gr.Textbox(label="License Information and Analysis"),
    title="Open Source License Extractor",
    description="Provide a GitHub repository URL to analyze open-source licenses from dependency files.",
)

if __name__ == "__main__":
    iface.launch()