app.py

# app.py
import os
import gradio as gr
from text_extractor import extract_text_from_file
from embedder import get_embeddings
from vector_store import create_faiss_index, search_similar_cvs
from groq_api import summarize_match

# Global storage
cv_texts = []
cv_names = []
cv_vectors = []
faiss_index = None

def upload_cvs(files):
    global cv_texts, cv_names, cv_vectors, faiss_index

    try:
        cv_texts = [extract_text_from_file(f.name) for f in files]
        cv_names = [f.name for f in files]
        cv_vectors = get_embeddings(cv_texts)

        import numpy as np
        if cv_vectors is None or np.array(cv_vectors).size == 0:
            return "❌ No valid CVs extracted or embedded."

        faiss_index = create_faiss_index(cv_vectors)
        return f"✅ Uploaded and indexed {len(files)} CVs."
    except Exception as e:
        return f"❌ Error during upload: {e}"

def match_jd(jd_text):
    global faiss_index

    try:
        if not faiss_index:
            return "❌ Please upload CVs first."

        if not jd_text.strip():
            return "❌ Job description is empty."

        jd_vector = get_embeddings([jd_text])[0]
        top_k_indices = search_similar_cvs(jd_vector, faiss_index, k=3)

        # Get readable file names and snippets of CVs
        matched_names = [os.path.basename(cv_names[i]) for i in top_k_indices]
        matched_texts = [cv_texts[i][:500] for i in top_k_indices]  # limit for Groq prompt

        summary = summarize_match(jd_text, matched_names, matched_texts)
        return f"✅ Top Matches:\n{matched_names}\n\n📝 Summary:\n{summary}"

    except Exception as e:
        return f"❌ Error during matching: {e}"

def clear_data():
    global cv_texts, cv_names, cv_vectors, faiss_index
    cv_texts, cv_names, cv_vectors, faiss_index = [], [], [], None
    return "🧹 Data cleared."

# Gradio Interfaces
iface = gr.Interface(
    fn=match_jd,
    inputs=[gr.Textbox(lines=10, label="Paste Job Description")],
    outputs="text",
    title="CV Matcher with Groq",
    description="Upload CVs, enter a Job Description, and get top matches and summary."
)

upload = gr.Interface(
    fn=upload_cvs,
    inputs=gr.File(file_types=[".pdf", ".docx"], file_count="multiple"),
    outputs="text",
    title="Upload CVs"
)

clear = gr.Interface(fn=clear_data, inputs=[], outputs="text", title="Reset Data")

app = gr.TabbedInterface([upload, iface, clear], ["Upload CVs", "Match JD", "Clear Data"])

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