fix the prompt error

app.py

@@ -5,7 +5,7 @@ import pandas as pd
 from openai import OpenAI
 import gradio as gr
 
-input_file = "profile-generation/data/sample_gpg_data.jsonl"
+input_file = "./data/sample_gpg_data.jsonl"
 user_df = pd.read_json(input_file, lines=True)
 
 user_ids = user_df["user_id"].unique().tolist()
@@ -61,13 +61,13 @@ def get_books(user_id):
             max_tokens=150
         ).choices[0].message.content.strip()
         profile_cache[cache_key] = profile_response
-        candidates_options = user_info.get("candidate_options", [])
+        candidates_options = list(user_info.get("candidate_options", []))
         rec_prompt = build_recommendation_prompt(profile_response, candidates_options)
         choice = extract_choice(rec_prompt)
-        predicted_book = candidates_options.values[choice-1] if choice and 1 <= choice <= len(candidates_options) else None
+        predicted_book = candidates_options[choice-1] if choice and 1 <= choice <= len(candidates_options) else None
         target_book = user_info.get("target_asin", '')
         print("target_book:", target_book)
-    return f"{user_id}", df, guidance_response, profile_response, rec_prompt, pd.DataFrame(candidates_options.values[0]), target_book.values, predicted_book[0]['asin']
+    return f"{user_id}", df, guidance_response, profile_response, rec_prompt, pd.DataFrame(candidates_options[0]), target_book.values, predicted_book[0]['asin']
 
 def extract_choice(response_text):
     for token in response_text.split():
@@ -90,8 +90,10 @@ def profile_prompt(titles, guidance):
 
 def build_recommendation_prompt(profile, candidates):
     prompt = f"""A user has the following reading preference:\n"{profile}"\n\nHere are some books they might consider next:\n"""
+    if len(candidates) == 1 and isinstance(candidates[0], list):
+        candidates = candidates[0]
     for i, book in enumerate(candidates, start=1):
-        prompt += f"[{i}] {book[0].get('title', 'Unknown Title')}\n"
+        prompt += f"[{i}] {book.get('title', 'Unknown Title')}\n"
     prompt += "\nWhich of these books best matches the user's preference? Respond ONLY with the number [1-4]."
     return prompt
 
@@ -111,7 +113,7 @@ with gr.Blocks() as demo:
     output_theme = gr.Textbox(label="User Books Theme", lines=8, show_label=False)
     gr.Markdown("## User Profile")
     output_profile = gr.Textbox(label="User Profile", show_label=False, lines=6)
-    output_rec_prompt = gr.Textbox(label="Recommendation Prompt")
+    output_rec_prompt = gr.Textbox(label="Recommendation Prompt", lines=8)
     output_candidate_options = gr.DataFrame(label="Candidate Books")
     output_target_id = gr.Textbox(label="Target Book")
     output_predicted_book = gr.Textbox(label="Predicted Book")