app.py

import gradio as gr
import chromadb
import os
import uuid
import time
import requests
from dotenv import load_dotenv

# ==================================================
# ENV SETUP
# ==================================================
load_dotenv()

OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
GITHUB_TOKEN = os.getenv("GITHUB_TOKEN")

if not OPENROUTER_API_KEY:
    raise RuntimeError("❌ OPENROUTER_API_KEY not found in environment")

# ==================================================
# CHROMADB SETUP
# ==================================================
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
DB_PATH = os.path.join(BASE_DIR, "roadmap_db")

chroma_client = chromadb.PersistentClient(path=DB_PATH)
collection = chroma_client.get_or_create_collection(name="project_roadmaps")

print(f"✅ ChromaDB initialized at: {DB_PATH}")

# ==================================================
# OPENROUTER LLM (FREE MODEL)
# ==================================================
def generate_with_openrouter(prompt: str) -> str:
    url = "https://openrouter.ai/api/v1/chat/completions"

    headers = {
        "Authorization": f"Bearer {OPENROUTER_API_KEY}"
    }

    payload = {
        "model": "meta-llama/llama-3.3-70b-instruct:free",
        "messages": [
            {
                "role": "system",
                "content": "You are an expert AI Tech Mentor and Career Analyst."
            },
            {
                "role": "user",
                "content": prompt
            }
        ],
        "temperature": 0.7,
        "max_tokens": 1800
    }

    response = requests.post(url, headers=headers, json=payload, timeout=60)

    if response.status_code != 200:
        return f"❌ OpenRouter Error {response.status_code}\n{response.text}"

    return response.json()["choices"][0]["message"]["content"]

# ==================================================
# GITHUB ANALYSIS
# ==================================================
def analyze_github_profile(url: str) -> str:
    if not url or "github.com" not in url:
        return "No valid GitHub URL provided."

    if not GITHUB_TOKEN:
        return "GitHub token not provided. Skipping GitHub analysis."

    try:
        username = url.rstrip("/").split("/")[-1]

        headers = {
            "Authorization": f"token {GITHUB_TOKEN}",
            "Accept": "application/vnd.github.v3+json"
        }

        api_url = f"https://api.github.com/users/{username}/repos?per_page=5&sort=updated"
        response = requests.get(api_url, headers=headers, timeout=20)

        if response.status_code != 200:
            return "Failed to fetch GitHub repositories."

        repos = response.json()
        languages = set()
        summaries = []

        for repo in repos:
            lang = repo.get("language")
            if lang:
                languages.add(lang)
            summaries.append(
                f"- {repo['name']} ({lang}): {repo.get('description', 'No description')}"
            )

        return (
            f"GitHub User: {username}\n"
            f"Primary Languages: {', '.join(languages)}\n"
            f"Recent Repositories:\n" + "\n".join(summaries)
        )

    except Exception as e:
        return f"GitHub analysis error: {str(e)}"

# ==================================================
# MARKET CONTEXT
# ==================================================
def get_market_context(goal: str) -> str:
    return (
        f"The market for {goal} strongly favors scalable systems, "
        f"cloud-native deployment, automation, and real-world impact."
    )

# ==================================================
# MAIN ROADMAP FUNCTION
# ==================================================
def generate_roadmap_endpoint(github_url, career_goal, preferred_stack):
    print("📥 Received request for strategic roadmap")

    if not career_goal:
        return "❌ Career goal is required."

    cache_key = f"{career_goal}|{preferred_stack}"

    # ---- Cache lookup ----
    try:
        cached = collection.query(query_texts=[cache_key], n_results=1)
        if cached["documents"] and cached["documents"][0]:
            if cached["distances"][0][0] < 0.2:
                print("✅ Loaded from cache")
                return "**[Loaded from Cache]**\n\n" + cached["documents"][0][0]
    except Exception:
        pass

    github_data = analyze_github_profile(github_url)
    market_context = get_market_context(career_goal)

    prompt = f"""
Situation:
You are an expert AI Tech Mentor.

Rules:
- Derive project scope strictly from the career goal
- Prioritize preferred tech stack
- Use GitHub info only for enhancement
- Never suggest career or roadmap tools
- Output plain text only

GitHub Analysis:
{github_data}

Career Goal:
{career_goal}

Preferred Tech Stack:
{preferred_stack if preferred_stack else "Not specified"}

Market Context:
{market_context}

Output Format:

Title:

Project Scope:

Existing Methodology:
- Current Approach:
- Limitations:

Tech Stack:
- Core Logic:
- Infrastructure:
- Testing / Deployment:

Innovative Enhancements:
- Technological Improvement:
- Unique Value Proposition:

Learning Roadmap:
- Step 1:
- Step 2:
- Step 3:
- Step 4:

Enhancements Over Existing Methodology:
- Enhancement 1
- Enhancement 2
- Enhancement 3
"""

    print("🤖 Generating roadmap via OpenRouter (LLaMA 3.3 70B FREE)...")
    result_text = generate_with_openrouter(prompt)

    # ---- Save to cache ----
    try:
        collection.add(
            documents=[result_text],
            metadatas=[{
                "career_goal": career_goal,
                "stack": preferred_stack,
                "timestamp": str(time.time())
            }],
            ids=[str(uuid.uuid4())]
        )
        print("✅ Roadmap saved to ChromaDB")
    except Exception:
        pass

    return result_text

# ==================================================
# GRADIO UI
# ==================================================
with gr.Blocks(theme=gr.themes.Soft(primary_hue="cyan")) as demo:
    gr.Markdown(
        "# 🚀 AI Project Roadmap Generator\n"
        "Turn your career goal into a portfolio-ready project."
    )

    github_input = gr.Textbox(label="GitHub Profile URL")
    career_input = gr.Textbox(label="Career Goal")
    stack_input = gr.Textbox(label="Preferred Tech Stack (optional)")

    submit_btn = gr.Button("Generate Roadmap", variant="primary")
    output = gr.Markdown()

    submit_btn.click(
        fn=generate_roadmap_endpoint,
        inputs=[github_input, career_input, stack_input],
        outputs=output
    )

if __name__ == "__main__":
    demo.launch(debug=True)