update for testing

.gitignore

@@ -1,5 +1,5 @@
 log/
-
+user_feedback/
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

app.py

@@ -4,7 +4,8 @@ from datetime import datetime
 import json
 import uuid
 from pathlib import Path
-from huggingface_hub import CommitScheduler
+from huggingface_hub import CommitScheduler, login
+from datasets import load_dataset
 import gradio as gr
 import markdown
 from together import Together
@@ -94,6 +95,7 @@ def save_feedback(user_id: str, uuid: str, type: str, value, feedback_file) -> N
 
 # Load the required static content from files
 def load_static_content(file_path):
+
     with open(file_path, "r") as f:
         return f.read()
 
@@ -121,13 +123,29 @@ PERSONALITY_INT = load_static_content(PERSONALITY_INT_FILE)
 # Other constants
 FIRST_MESSAGE = "Hey"
 USER_PREFERENCE_SUMMARY = True
-DEBUG = True
+DEBUG = False
 API_TYPE = "together"
 assert API_TYPE in ["together", "local", "debug"], "The API should be either 'together' or 'local'"
 if API_TYPE == "together":
     TOGETHER_CLIENT = Together(api_key=os.getenv("TOGETHER_API_KEY"))
 
 
+def generate_username_pwd_list(data):
+    user_list = []
+    demo_list = []
+    for index, row in data.iterrows():
+        user_list.append((row["user"], str(row["pwd"])))
+        demo_list.append((row["demo"], str(row["pwd"])))
+    return user_list, demo_list
+
+
+def load_username_and_pwd():
+    dataset = load_dataset(os.getenv("USER_PWD_FILE"))
+    df = dataset["train"].to_pandas()
+    user_list, demo_list = generate_username_pwd_list(df)
+    return user_list, demo_list
+
+
 def get_context_list(synthetic_data_path):
     # Load data from the synthetic data file
     with open(synthetic_data_path, "r") as f:
@@ -233,7 +251,6 @@ def log_action(user_id, tab_name, action, details):
     if os.path.exists(log_file_dir) is False:
         os.makedirs(log_file_dir)
     log_file = os.path.join(log_file_dir, f"{tab_name}.txt")
-    print(log_file)
     with open(log_file, "a") as f:
         f.write(f"Action: {action} | Details: {details}\n")
 
@@ -242,8 +259,8 @@ def add_user_profile_to_system_instruction(
     user_id, system_instruction, user_preference_elicitation_data, summary, terminator
 ):
     exp_id = int(user_id.split("_")[-3])
-    # exp_id = 2 => No personalization
-    if exp_id == 2:
+    # exp_id = 1 => No personalization
+    if exp_id == 1:
         print("Non-personalizationかチェック:" + system_instruction)
         return system_instruction
     if summary:
@@ -268,7 +285,6 @@ def add_user_profile_to_system_instruction(
                 {"summarization": summ},
                 feedback_file_summarization,
             )
-            # print(f"Preference Summary:{summ}")
         system_instruction += f"\nUser Profile collected in the previous conversations: {user_preference_elicitation_data['summary_history']}\n"
     else:
         system_instruction += (
@@ -415,7 +431,7 @@ def create_demo():
             providing_information = likert_evaluation("The advisor provides the financial knowledge needed")
         with gr.Row():
             textbox = gr.HTML()
-            submit_ranking = gr.Button(value="Submit Ranking")
+            submit_ranking = gr.Button(value="Submit Final Evaluation")
         return {
             "first": ranking_first_comp,
             "second": ranking_second_comp,
@@ -722,8 +738,6 @@ def create_demo():
                 summary=USER_PREFERENCE_SUMMARY,
                 terminator=terminator,
             )
-        # Formatting Input
-        print(f"User Message: {message} in Tab: {tab_name}")
         # From string to list [{"role":"user", "content": message}, ...]
         history = gradio_to_huggingface_message(history)
         # We can implement context window here as we need all the system interaction. We can cut some of the early interactions if needed.
@@ -742,8 +756,6 @@ def create_demo():
         # exclude system interaction and store the others in the history
         history = huggingface_to_gradio_message(history)
         if tab_name is not None:
-            print(f"Tab: {tab_name}\nSystem Output: {outputs_text}")
-
             # Log the user message and response
             save_feedback(
                 user_id,
@@ -764,7 +776,6 @@ def create_demo():
             # Store the updated history for this tab
             tab_data["history"] = history
         if user_elicitation:
-            print(f"User Elicitation\nSystem Output: {outputs_text}")
             save_feedback(
                 user_id,
                 uuid_this_session,
@@ -802,8 +813,6 @@ def create_demo():
         if system_description_without_context is not None and system_instruction_context is not None:
             system_instruction = system_description_without_context + "\n" + system_instruction_context
         if not user_elicitation:
-            print(f"User Preference Elicitation Data: {user_preference_elicitation_data}")
-            print(f"Tab data: {tab_data}")
             system_instruction = add_user_profile_to_system_instruction(
                 user_id,
                 system_instruction,
@@ -829,7 +838,6 @@ def create_demo():
         # Format
         history = huggingface_to_gradio_message(history)
         if tab_name is not None:
-            print(f"Tab: {tab_name}\nHistory: {history}")
             # Log the user message and response
             save_feedback(
                 user_id,
@@ -850,7 +858,6 @@ def create_demo():
             # Store the updated history for this tab
             tab_data["history"] = history
         if user_elicitation:
-            print(f"User Elicitation\nHistory: {history}")
             save_feedback(
                 user_id,
                 uuid_this_session,
@@ -930,13 +937,10 @@ def create_demo():
                 {"type": tab_name, "role": "assistant", "content": outputs_text},
                 feedback_file_interaction,
             )
-            # log_action(user_id, tab_name, "Show More of the Advisor’s Answer", "User continued the conversation")
-            # log_action(user_id, tab_name, "Response", outputs_text)
 
             # Update history for this tab
             tab_data["history"] = history
         if user_elicitation:
-            print(f"User Elicitation\nSystem Output: {outputs_text}")
             save_feedback(
                 user_id,
                 uuid_this_session,
@@ -957,7 +961,6 @@ def create_demo():
     def respond_evaluation(user_id, tab_data, evals, tab_name, evaluation_send_button, textbox):
 
         # dropdown, readon_button, multi-evaluator
-        print(f"Tab: {tab_name}\nEvaluation: {evals}")
         if evals["likelihood"] is None or evals["confidence"] is None or evals["familiarity"] is None:
             return (
                 tab_data,
@@ -1093,7 +1096,6 @@ def create_demo():
         user_in_narrative_id = user_id.split("_")[-1]
         narrative_id = user_id.split("_")[-2]
         experiment_id = user_id.split("_")[-3]
-        print(f"User ID: {user_id}, User in Narrative ID: {user_in_narrative_id}, Narrative ID: {narrative_id}")
         return user_id, user_in_narrative_id, narrative_id, experiment_id
 
     def get_inst_without_context(experiment_id):
@@ -1113,8 +1115,6 @@ def create_demo():
     def get_stock_related_context(narrative_id, user_in_narrative_id):
         raw_context_list = build_raw_context_list(context_info_list[int(narrative_id)])
         stock_context_list = build_context(context_info_list[int(narrative_id)])
-        print("Raw Context List: ", len(raw_context_list))
-        print("Stock Context List: ", len(stock_context_list))
         raw_context_list = reorder_list_based_on_user_in_narrative_id(user_in_narrative_id, raw_context_list)
         stock_context_list = reorder_list_based_on_user_in_narrative_id(user_in_narrative_id, stock_context_list)
         return raw_context_list, stock_context_list
@@ -1124,8 +1124,6 @@ def create_demo():
         user_id, user_in_narrative_id, narrative_id, experiment_id = set_user_id(request)
         # System instruction without prompt
         system_description_without_context = get_inst_without_context(experiment_id)
-        print(f"Experiment ID: {experiment_id}")
-        print(f"System Description: {system_description_without_context}")
         # Stock related context
         raw_context_list, stock_context_list = get_stock_related_context(narrative_id, user_in_narrative_id)
         # User Narrative
@@ -1353,13 +1351,8 @@ if __name__ == "__main__":
     # Global variables
     terminator = ["<eos>", "<unk>", "<sep>", "<pad>", "<cls>", "<mask>"]
     demo = create_demo()
-    demo_user_pwd_list = [(f"demo_{i}_{j}_1", f"demo_{i}_{j}_1") for i in range(1, 5) for j in range(1, 4)]
+    user_list, demo_list = load_username_and_pwd()
     demo.launch(
-        share=True,
-        auth=demo_user_pwd_list
-        + [
-            ("user_1_1_1", "pw1"),
-            ("user_2_1_1", "pw2"),
-            ("user_3_1_1", "pw3"),
-        ],
+        share=False,
+        auth=user_list + demo_list,
     )