Spaces:
Sleeping
Sleeping
入出力の保存、応答の評価、データセットのアップロード機能を追加
#1
by
misdelivery
- opened
app.py
CHANGED
@@ -1,7 +1,13 @@
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import gradio as gr
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# from huggingface_hub import InferenceClient
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from openai import OpenAI
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import os
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openai_api_key = os.getenv('api_key')
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openai_api_base = os.getenv('url')
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model_name = "weblab-GENIAC/Tanuki-8x8B-dpo-v1.0"
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@@ -14,6 +20,54 @@ client = OpenAI(
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base_url=openai_api_base,
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)
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def respond(
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message,
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@@ -35,8 +89,7 @@ def respond(
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messages.append({"role": "user", "content": message})
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response = ""
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-
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for message in client.chat.completions.create(
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model=model_name,
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messages=messages,
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max_tokens=max_tokens,
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@@ -44,24 +97,33 @@ def respond(
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temperature=temperature,
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top_p=top_p,
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):
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# response += token
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if token is not None:
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response += (token)
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if response.find("### 指示:")>0:
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response=response.replace("### 指示:","")
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break
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yield response
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-
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"""
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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"""
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description = """
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### [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)
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- 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)
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- **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。
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"""
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@@ -71,8 +133,8 @@ FOOTER = """### 注意
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- 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。
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- GPUサーバー���不安定なので、応答しないことがあるかもしれません。"""
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def run():
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chatbot = gr.Chatbot(
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elem_id="chatbot",
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scale=1,
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)
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with gr.Blocks(fill_height=True) as demo:
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gr.Markdown(HEADER)
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gr.ChatInterface(
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fn=respond,
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stop_btn="Stop Generation",
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cache_examples=False,
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@@ -92,9 +154,11 @@ def run():
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label="Parameters", open=False, render=False
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),
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additional_inputs=[
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-
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render=False,),
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gr.Slider(
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minimum=1,
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maximum=4096,
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],
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analytics_enabled=False,
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)
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gr.Markdown(FOOTER)
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demo.queue(max_size=256, api_open=
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demo.launch(share=
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-
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if __name__ == "__main__":
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run()
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import gradio as gr
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from openai import OpenAI
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import os
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import json
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from datetime import datetime
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from zoneinfo import ZoneInfo
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import uuid
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from pathlib import Path
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from huggingface_hub import CommitScheduler
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openai_api_key = os.getenv('api_key')
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openai_api_base = os.getenv('url')
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model_name = "weblab-GENIAC/Tanuki-8x8B-dpo-v1.0"
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base_url=openai_api_base,
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)
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# Define the file where to save the data. Use UUID to make sure not to overwrite existing data from a previous run.
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feedback_file = Path("user_feedback/") / f"data_{uuid.uuid4()}.json"
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feedback_folder = feedback_file.parent
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# Schedule regular uploads. Remote repo and local folder are created if they don't already exist.
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scheduler = CommitScheduler(
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repo_id="kanhatakeyama/TanukiChat", # Replace with your actual repo ID
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repo_type="dataset",
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folder_path=feedback_folder,
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path_in_repo="data",
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every=1, # Upload every 1 minutes
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)
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def save_or_update_conversation(conversation_id, message, response, message_index, liked=None):
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"""
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Save or update conversation data in a JSON Lines file.
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If the entry already exists (same id and message_index), update the 'label' field.
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Otherwise, append a new entry.
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"""
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with scheduler.lock:
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# Read existing data
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data = []
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if feedback_file.exists():
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with feedback_file.open("r") as f:
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data = [json.loads(line) for line in f if line.strip()]
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# Find if an entry with the same id and message_index exists
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entry_index = next((i for i, entry in enumerate(data) if entry['id'] == conversation_id and entry['message_index'] == message_index), None)
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if entry_index is not None:
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# Update existing entry
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data[entry_index]['label'] = liked
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else:
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# Append new entry
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data.append({
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"id": conversation_id,
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"timestamp": datetime.now(ZoneInfo("Asia/Tokyo")).isoformat(),
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"prompt": message,
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"completion": response,
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"message_index": message_index,
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"label": liked
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})
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# Write updated data back to file
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with feedback_file.open("w") as f:
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for entry in data:
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f.write(json.dumps(entry) + "\n")
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def respond(
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message,
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messages.append({"role": "user", "content": message})
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response = ""
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for chunk in client.chat.completions.create(
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model=model_name,
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messages=messages,
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max_tokens=max_tokens,
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temperature=temperature,
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top_p=top_p,
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):
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if chunk.choices[0].delta.content is not None:
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response += chunk.choices[0].delta.content
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yield response
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# Save conversation after the full response is generated
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message_index = len(history)
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save_or_update_conversation(conversation_id, message, response, message_index)
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def vote(data: gr.LikeData, history, conversation_id):
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"""
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Update user feedback (like/dislike) in the local file.
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"""
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message_index = data.index[0]
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liked = data.liked
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save_or_update_conversation(conversation_id, None, None, message_index, liked)
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def create_conversation_id():
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return str(uuid.uuid4())
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"""
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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"""
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description = """
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### [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)
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- 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。
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- データセットはこちらで公開しています。 https://huggingface.co/datasets/kanhatakeyama/TanukiChat
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- **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。
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"""
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- 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。
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- GPUサーバー���不安定なので、応答しないことがあるかもしれません。"""
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def run():
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conversation_id = gr.State(create_conversation_id)
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chatbot = gr.Chatbot(
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elem_id="chatbot",
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scale=1,
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)
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with gr.Blocks(fill_height=True) as demo:
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gr.Markdown(HEADER)
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chat_interface = gr.ChatInterface(
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fn=respond,
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stop_btn="Stop Generation",
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cache_examples=False,
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label="Parameters", open=False, render=False
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),
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additional_inputs=[
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additional_inputs=[
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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。",
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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。)",
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render=False,),
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conversation_id,
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gr.Slider(
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minimum=1,
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maximum=4096,
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],
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analytics_enabled=False,
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)
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chatbot.like(vote, [chatbot, conversation_id], None)
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gr.Markdown(FOOTER)
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demo.queue(max_size=256, api_open=True)
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demo.launch(share=True, quiet=True)
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if __name__ == "__main__":
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run()
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