add Like/Dislike collection

app.py

@@ -1,15 +1,13 @@
 import gradio as gr
+# from huggingface_hub import InferenceClient
 from openai import OpenAI
 import os
-import json
-from datetime import datetime
-from zoneinfo import ZoneInfo
-import uuid
-from pathlib import Path
-from huggingface_hub import CommitScheduler
+import requests
 
 openai_api_key = os.getenv('api_key')
 openai_api_base = os.getenv('url')
+db_url = os.getenv('db_url')
+db_api_key = os.getenv('db_api_key')
 model_name = "weblab-GENIAC/Tanuki-8x8B-dpo-v1.0"
 """
 For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
@@ -20,59 +18,27 @@ client = OpenAI(
     base_url=openai_api_base,
 )
 
-# Define the file where to save the data. Use UUID to make sure not to overwrite existing data from a previous run.
-feedback_file = Path("user_feedback/") / f"data_{uuid.uuid4()}.json"
-feedback_folder = feedback_file.parent
-
-# Schedule regular uploads. Remote repo and local folder are created if they don't already exist.
-scheduler = CommitScheduler(
-    repo_id="team-hatakeyama-phase2/8x8b-server-original-data",  # Replace with your actual repo ID
-    repo_type="dataset",
-    folder_path=feedback_folder,
-    path_in_repo="data",
-    every=60,  # Upload every 1 minutes
-)
 
-def save_or_update_conversation(conversation_id, message, response, message_index, liked=None):
-    """
-    Save or update conversation data in a JSON Lines file.
-    If the entry already exists (same id and message_index), update the 'label' field.
-    Otherwise, append a new entry.
-    """
-    with scheduler.lock:
-        # Read existing data
-        data = []
-        if feedback_file.exists():
-            with feedback_file.open("r") as f:
-                data = [json.loads(line) for line in f if line.strip()]
-
-        # Find if an entry with the same id and message_index exists
-        entry_index = next((i for i, entry in enumerate(data) if entry['id'] == conversation_id and entry['message_index'] == message_index), None)
-
-        if entry_index is not None:
-            # Update existing entry
-            data[entry_index]['label'] = liked
-        else:
-            # Append new entry
-            data.append({
-                "id": conversation_id,
-                "timestamp": datetime.now(ZoneInfo("Asia/Tokyo")).isoformat(),
-                "prompt": message,
-                "completion": response,
-                "message_index": message_index,
-                "label": liked
-            })
-
-        # Write updated data back to file
-        with feedback_file.open("w") as f:
-            for entry in data:
-                f.write(json.dumps(entry) + "\n")
+def save_conversation(history, system_message):
+    conversation_data = {
+        "conversation": history,
+        "index": (len(history) - 1, 1),  # 最新の応答のインデックス
+        "liked": None,  # 評価はnull（None）
+        "system_message": system_message,
+    }
+    headers = {
+        "X-API-Key": db_api_key
+    }
+    response = requests.post(db_url, json=conversation_data, headers=headers)
+    if response.status_code == 200:
+        print("Conversation saved successfully")
+    else:
+        print(f"Failed to save conversation: {response.status_code}")
 
 
 def respond(
     message,
     history: list[tuple[str, str]],
-    conversation_id,
     system_message,
     max_tokens,
     temperature,
@@ -90,7 +56,8 @@ def respond(
     messages.append({"role": "user", "content": message})
 
     response = ""
-    for chunk in client.chat.completions.create(
+
+    for new_response in client.chat.completions.create(
         model=model_name,
         messages=messages,
         max_tokens=max_tokens,
@@ -98,32 +65,23 @@ def respond(
         temperature=temperature,
         top_p=top_p,
     ):
-        if chunk.choices[0].delta.content is not None:
-            response += chunk.choices[0].delta.content
+        token = new_response.choices[0].delta.content
+
+        if token is not None:
+            response += (token)
         yield response
     
-    # Save conversation after the full response is generated
-    message_index = len(history)
-    save_or_update_conversation(conversation_id, message, response, message_index)
-
-def vote(data: gr.LikeData, history, conversation_id):
-    """
-    Update user feedback (like/dislike) in the local file.
-    """
-    message_index = data.index[0]
-    liked = data.liked
-    save_or_update_conversation(conversation_id, None, None, message_index, liked)
-
-def create_conversation_id():
-    return str(uuid.uuid4())
-    
+    new_history = history + [(message, response)]
+    save_conversation(new_history, system_message)
+
+
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
 
 description = """
 ### [Tanuki-8x8B-dpo-v1.0](https://huggingface.co/weblab-GENIAC/Tanuki-8x8B-dpo-v1.0)との会話(期間限定での公開)
-- 人工知能開発のため､原則として**こ���ChatBotの入出力データは全て著作権フリー(CC0)で公開する**ため､ご注意ください｡著作物､個人情報､機密情報､誹謗中傷などのデータを入力しないでください｡
+- 人工知能開発のため､原則として**このChatBotの入出力データは全て著作権フリー(CC0)で公開予定です**ので､ご注意ください｡著作物､個人情報､機密情報､誹謗中傷などのデータを入力しないでください｡
 - **上記の条件に同意する場合のみ**､以下のChatbotを利用してください｡
 """
 
@@ -133,8 +91,25 @@ FOOTER = """### 注意
 - コンテクスト長が4096までなので､あまり会話が長くなると､エラーで停止します｡ページを再読み込みしてください｡
 - GPUサーバーが不安定なので､応答しないことがあるかもしれません｡"""
 
+
+def vote(data: gr.LikeData, history):
+    vote_data = {
+        "conversation": history,
+        "index": data.index,
+        "liked": data.liked,
+        "system_message": None,
+    }
+    headers = {
+        "X-API-Key": db_api_key  # APIキーを設定
+    }
+    response = requests.post(db_url, json=vote_data, headers=headers)
+    if response.status_code == 200:
+        print("Vote recorded successfully")
+    else:
+        print(f"Failed to record vote: {response.status_code}")
+
+
 def run():
-    conversation_id = gr.State(create_conversation_id)
     chatbot = gr.Chatbot(
         elem_id="chatbot",
         scale=1,
@@ -144,7 +119,7 @@ def run():
     )
     with gr.Blocks(fill_height=True) as demo:
         gr.Markdown(HEADER)
-        chat_interface = gr.ChatInterface(
+        gr.ChatInterface(
             fn=respond,
             stop_btn="Stop Generation",
             cache_examples=False,
@@ -154,7 +129,6 @@ def run():
                 label="Parameters", open=False, render=False
             ),
             additional_inputs=[
-                conversation_id,
                 gr.Textbox(value="以下は、タスクを説明する指示です。要求を適切に満たす応答を書きなさい。",
                            label="System message(試験用: 変えると性能が低下する可能性があります。)",
                                               render=False,),
@@ -188,10 +162,11 @@ def run():
             ],
             analytics_enabled=False,
         )
-        chatbot.like(vote, [chatbot, conversation_id], None)
+        chatbot.like(vote, chatbot, None)
         gr.Markdown(FOOTER)
-    demo.queue(max_size=256, api_open=True)
-    demo.launch(share=True, quiet=True)
+    demo.queue(max_size=256, api_open=False)
+    demo.launch(share=False, quiet=True)
+
 
 if __name__ == "__main__":
-    run()
+    run()