azure_ai.py

import os
from dotenv import load_dotenv
from openai import AzureOpenAI

load_dotenv()

client = AzureOpenAI(
    api_version="2025-01-01-preview",
    azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT").strip(),
    api_key=os.getenv("AZURE_OPENAI_KEY").strip()
)

def enhance_with_ai(repo_info):
    file_summaries = "\n".join([
        f"### {name}\n```{content[:500]}```"
        for name, content in list(repo_info['files'].items())[:10]
    ])

    system_prompt = """You are a senior open-source developer and technical writer who has authored
documentation for projects with 50,000+ GitHub stars (e.g., FastAPI, LangChain, Streamlit).
Your README output must:
- Feel like a polished, production-grade open-source project
- Use Mermaid diagrams: sequenceDiagram for API/data flow, flowchart LR for architecture. 
- In Mermaid Diagrams, Dont use any Use only text dont use any symbol like .,*£_-+()/ and HTML tags in Mermaid and Follow correct Mermaid Syntax
- Mermaid diagrams should change according to project working refer the sample one present in user input
- Include shields.io badges, tables, and collapsible sections where appropriate
- Be scannable: a developer should understand the project in under 60 seconds
- Never truncate — every section must be fully written
- Use emojis only in section headers, not inline text"""

    user_prompt = f"""
Generate a world-class GitHub README.md for this project.
PROJECT CONTEXT
---------------
Name        : {repo_info['name']}
Description : {repo_info['description']}
Topics      : {', '.join(repo_info['topics'])}
User        : {repo_info['owner']['login']}
FILES (sampled for context):
{file_summaries}
---------------
Follow this EXACT structure and do not skip any section:
1. Hero Section
   - H1 title with a one-line tagline below it
   - A short 2-line summary of what the project does
2. Table of Contents
   - Linked TOC to every section
3. Introduction
   - The problem this project solves (2-3 sentences)
   - Who benefits from it
   - A "Why {repo_info['name']}?" comparison table vs alternatives:
     | Feature | {repo_info['name']} | Alternative A | Alternative B |
4. Features
   - 6-8 bullet points, each starting with a relevant emoji
   - Group under: Core Features, Developer Experience, Deployment
5. Architecture
   - A Mermaid flowchart LR showing system components:
     ```mermaid
     flowchart LR
         A[Input Layer] --> B[Processing Layer]
         B --> C[Output Layer]
     ```
   - A component breakdown table after the diagram:
     | Component | Role | Technology |
6. Workflow
   - A Mermaid sequenceDiagram showing the request/response or data flow:
     ```mermaid
     sequenceDiagram
         actor User
         participant App
         participant Backend
         User->>App: action
         App->>Backend: request
         Backend-->>App: response
         App-->>User: result
     ```
   - Numbered step-by-step explanation below the diagram
7. Tech Stack
   | Layer | Technology | Purpose |
8. Installation
   - Prerequisites block
   - Quick Start in 3 steps max:
     ```bash
     git clone https://github.com/user/{repo_info['name']}.git
     cd {repo_info['name']}
     pip install -r requirements.txt
     ```
   - Environment setup:
     ```bash
     cp .env.example .env
     # Fill in your values
     ```
     
9. Project Structure
    ```
    {repo_info['name']}/
    
    ```
    
10. Usage
   - Basic example with code block
   - Advanced example with code block
    
Write the complete README now. Do not summarize, skip, or truncate any section.
"""

    response = client.chat.completions.create(
        model=os.getenv("AZURE_DEPLOYMENT_NAME").strip(),
        messages=[
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_prompt}
        ],
        temperature=0.7,
        max_tokens=4000
    )

    return response.choices[0].message.content