Update app.py

app.py

@@ -9,7 +9,7 @@ from functools import lru_cache
 # CONFIG
 # ----------------------------
 JSON_FILE = "form-submissions-1.json"
-MODEL_ID = "HuggingFaceH4/sgpt-3.5-mini"  # you can replace with other Hugging Face LLM
+MODEL_ID = "HuggingFaceH4/sgpt-3.5-mini"
 HF_API_TOKEN = os.environ.get("HF_API_TOKEN")
 FILTERED_CSV = "/tmp/filtered_candidates.csv"
 OUTPUT_FILE = "/tmp/outputs.csv"
@@ -92,12 +92,12 @@ def filter_by_roles(category_name):
 
     df = pd.DataFrame(filtered)
     df.to_csv(FILTERED_CSV, index=False)
-    return df, gr.File.update(value=FILTERED_CSV)
+    return df, FILTERED_CSV
 
 # ----------------------------
-# Step 2: LLM recommendations (read from filtered CSV)
+# Step 2: LLM recommendations
 # ----------------------------
-def llm_recommendations_gr(category_name):
+def llm_recommendations(category_name):
     job_titles = CATEGORIES[category_name]
 
     if not os.path.exists(FILTERED_CSV):
@@ -115,7 +115,7 @@ def llm_recommendations_gr(category_name):
     for i in range(0, len(filtered_candidates), BATCH_SIZE):
         batch = filtered_candidates[i:i+BATCH_SIZE]
         for person in batch:
-            # Only send necessary info to LLM
+            # Only send necessary info
             candidate_info = {
                 "Name": person.get("Name"),
                 "Roles": person.get("Roles"),
@@ -141,7 +141,7 @@ def llm_recommendations_gr(category_name):
     df_top5 = df_rec.head(5)
     df_top5.to_csv(OUTPUT_FILE, index=False)
 
-    return df_top5, gr.File.update(value=OUTPUT_FILE)
+    return df_top5, OUTPUT_FILE
 
 # ----------------------------
 # Show first 5 raw JSON candidates
@@ -172,7 +172,7 @@ with gr.Blocks() as app:
     llm_button = gr.Button("Get LLM Recommendations")
     llm_df = gr.Dataframe(label="Top 5 Recommended Candidates")
     download_llm = gr.File(label="Download Recommendations CSV", file_types=[".csv"])
-    llm_button.click(llm_recommendations_gr, inputs=[category_dropdown], outputs=[llm_df, download_llm])
+    llm_button.click(llm_recommendations, inputs=[category_dropdown], outputs=[llm_df, download_llm])
 
 if __name__ == "__main__":
     app.launch()