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import gradio as gr
import numpy as np
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:
if len(files) > 10:
return "β Limit exceeded: Upload a maximum of 10 CVs."
cv_texts = [extract_text_from_file(f) for f in files]
cv_names = [f.name for f in files]
cv_vectors = get_embeddings(cv_texts)
if cv_vectors is None or np.array(cv_vectors).size == 0:
return "β No valid CVs."
faiss_index = create_faiss_index(cv_vectors)
return f"β
Uploaded and indexed {len(files)} CVs."
except Exception as e:
return f"β Error during upload: {e}"
def match_jd(jd_text, match_mode):
if faiss_index is None:
return "β Please upload CVs first."
if not jd_text.strip():
return "β οΈ Job description is empty."
try:
jd_vector = get_embeddings([jd_text])[0]
if match_mode == "Top 3 Matches":
indices = search_similar_cvs(jd_vector, faiss_index, k=3)
else: # All CVs
indices = list(range(len(cv_names)))
matched = [cv_names[i] for i in indices]
texts = [cv_texts[i] for i in indices]
summary = summarize_match(jd_text, matched, texts)
return f"β
{match_mode}:\n\n" + "\n".join(matched) + f"\n\nπ Summary:\n{summary}"
except Exception as e:
return f"β 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 "π§Ή Cleared."
with gr.Blocks() as app:
gr.Markdown("## π CV Matcher with Groq API (Flexible Matching Mode)")
# Upload
file_input = gr.File(file_types=[".pdf", ".docx"], file_count="multiple", label="π€ Upload CVs (Max 10)")
upload_button = gr.Button("π Upload & Index")
upload_status = gr.Textbox(label="Upload Status")
# Job Description & Matching
jd_input = gr.Textbox(label="π Paste Job Description", lines=8, placeholder="Paste job description here...")
match_mode = gr.Radio(["Top 3 Matches", "All Uploaded CVs"], value="Top 3 Matches", label="Matching Mode")
match_button = gr.Button("π Match CVs")
result_output = gr.Textbox(label="Match Results", lines=20)
# Clear Session
clear_button = gr.Button("π§Ή Clear All")
clear_status = gr.Textbox(label="Clear Status")
# Actions
upload_button.click(upload_cvs, inputs=[file_input], outputs=[upload_status])
match_button.click(match_jd, inputs=[jd_input, match_mode], outputs=[result_output])
clear_button.click(clear_data, inputs=[], outputs=[clear_status])
app.launch()
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