groq_api.py

import os
import requests

# Load from environment variable or fallback
GROQ_API_KEY = "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"

def summarize_match(job_description, cv_names, cv_snippets):
    if not GROQ_API_KEY:
        return "❌ GROQ_API_KEY not set."

    try:
        # Ensure 3 CVs are present (pad if needed)
        while len(cv_names) < 3:
            cv_names.append("[No CV]")
            cv_snippets.append("[No content]")

        # Truncate content safely
        job_description = job_description.strip()[:1000] or "[No description provided]"
        cv_names = [name[:60] for name in cv_names[:3]]
        cv_snippets = [(text.strip()[:1500] or "[No content]") for text in cv_snippets[:3]]

        # Compose prompt
        prompt = f"""
You are an AI recruitment assistant helping to evaluate candidates for an open job role.

Below is the job description, followed by the top 3 candidate CV snippets.

Your task is to assess how well each candidate aligns with the job. Be honest — if a candidate lacks the required skills or experience, clearly say they are not a good fit.

### Job Description:
{job_description}

### Candidate CVs:
1. {cv_names[0]}:
{cv_snippets[0]}

2. {cv_names[1]}:
{cv_snippets[1]}

3. {cv_names[2]}:
{cv_snippets[2]}

### Instructions:
- Focus on **specific skills**, **technical tools**, **relevant experience**, and **industry fit**.
- Clearly identify **who is a good match**, and **why**.
- Clearly explain **who is not a match**, and **why not**.
- Avoid general language like "strong background" unless it's backed by actual experience.

End with a short ranked list like:
1. Candidate 2 – Strong Python and ML background
2. Candidate 1 – Partial match, good general programming skills
3. Candidate 3 – Not relevant to the job
""".strip()

        # Truncate if needed to fit Groq’s limit
        if len(prompt) > 8000:
            prompt = prompt[:8000]

        # Send request to Groq API using LLaMA3
        response = requests.post(
            url="https://api.groq.com/openai/v1/chat/completions",
            headers={
                "Authorization": f"Bearer {GROQ_API_KEY}",
                "Content-Type": "application/json"
            },
            json={
                "model": "llama3-8b-8192",
                "messages": [
                    {"role": "system", "content": "You are a helpful recruitment assistant."},
                    {"role": "user", "content": prompt}
                ],
                "temperature": 0.4
            },
            timeout=30
        )

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

    except requests.exceptions.RequestException as e:
        return f"❌ Groq API error: {e}"
    except Exception as e:
        return f"❌ Unexpected error: {e}"