Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -3,7 +3,7 @@ import time
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import spaces
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import torch
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import gradio as gr
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from huggingface_hub import snapshot_download
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from pathlib import Path
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@@ -11,9 +11,11 @@ from pathlib import Path
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from mistral_inference.transformer import Transformer
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from mistral_inference.generate import generate
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from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
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from mistral_common.protocol.instruct.messages import AssistantMessage, UserMessage
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from mistral_common.protocol.instruct.request import ChatCompletionRequest
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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@@ -45,18 +47,20 @@ snapshot_download(repo_id="mistralai/Ministral-8B-Instruct-2410", allow_patterns
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# tokenizer
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device = "cuda" if torch.cuda.is_available() else "cpu" # for GPU usage or "cpu" for CPU usage
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tokenizer = MistralTokenizer.from_file(f"{mistral_models_path}/tekken.json")
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model = Transformer.from_folder(
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mistral_models_path,
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device=device,
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dtype=torch.bfloat16)
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@spaces.GPU()
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def stream_chat(
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message: str,
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history: list,
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temperature: float = 0.3,
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):
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print(f'message: {message}')
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print(f'history: {history}')
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@@ -75,15 +79,27 @@ def stream_chat(
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conversation.append(UserMessage(content=message))
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print(f'history: {conversation}')
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completion_request = ChatCompletionRequest(
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tokens = tokenizer.encode_chat_completion(completion_request).tokens
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out_tokens, _ = generate(
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[tokens],
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model,
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max_tokens=
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temperature=temperature,
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eos_id=tokenizer.instruct_tokenizer.tokenizer.eos_id)
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@@ -93,44 +109,72 @@ def stream_chat(
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time.sleep(0.05)
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yield result[: i + 1]
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with gr.Blocks(theme="citrus", css=CSS) as demo:
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gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button")
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gr.
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chatbot=chatbot,
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# type="messages",
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fill_height=True,
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examples=[
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]
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cache_examples = False,
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additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
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additional_inputs=[
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gr.Slider(
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minimum=0,
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maximum=1,
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step=0.1,
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value=0.3,
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label="Temperature",
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render=False,
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),
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gr.Slider(
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minimum=128,
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maximum=8192,
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step=1,
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value=1024,
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label="Max new tokens",
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render=False,
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),
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],
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)
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if __name__ == "__main__":
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demo.launch()
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import spaces
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import torch
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import gradio as gr
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import json
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from huggingface_hub import snapshot_download
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from pathlib import Path
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from mistral_inference.transformer import Transformer
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from mistral_inference.generate import generate
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from mistral_common.protocol.instruct.tool_calls import Function, Tool
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from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
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from mistral_common.protocol.instruct.messages import AssistantMessage, UserMessage
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from mistral_common.protocol.instruct.request import ChatCompletionRequest
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from mistral_common.tokens.tokenizers.tekken import SpecialTokenPolicy
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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# tokenizer
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device = "cuda" if torch.cuda.is_available() else "cpu" # for GPU usage or "cpu" for CPU usage
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tokenizer = MistralTokenizer.from_file(f"{mistral_models_path}/tekken.json")
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tekken = tokenizer.instruct_tokenizer.tokenizer
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tekken.special_token_policy = SpecialTokenPolicy.IGNORE
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model = Transformer.from_folder(
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mistral_models_path,
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device=device,
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dtype=torch.bfloat16)
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@spaces.GPU()
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def stream_chat(
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message: str,
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history: list,
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tools: str,
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temperature: float = 0.3,
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max_tokens: int = 1024,
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):
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print(f'message: {message}')
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print(f'history: {history}')
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conversation.append(UserMessage(content=message))
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print(f'history: {conversation}')
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local_namespace = {}
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exec(tools, globals(), local_namespace)
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function_params = local_namespace.get('function_params', {})
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completion_request = ChatCompletionRequest(
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tools=[
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Tool(
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function=Function(
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**function_params
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)
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)
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] if tools else None,
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messages=conversation)
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tokens = tokenizer.encode_chat_completion(completion_request).tokens
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out_tokens, _ = generate(
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[tokens],
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model,
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max_tokens=max_tokens,
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temperature=temperature,
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eos_id=tokenizer.instruct_tokenizer.tokenizer.eos_id)
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time.sleep(0.05)
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yield result[: i + 1]
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tools_schema = """function_params = {
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name="get_current_weather",
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description="Get the current weather",
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parameters={
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA",
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},
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"format": {
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"type": "string",
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"enum": ["celsius", "fahrenheit"],
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"description": "The temperature unit to use. Infer this from the users location.",
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},
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},
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"required": ["location", "format"],
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},
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}"""
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with gr.Blocks(theme="citrus", css=CSS) as demo:
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gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button")
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chatbot = gr.Chatbot(
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height=600,
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placeholder=PLACEHOLDER,
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examples=[
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{'text': "Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option."},
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{'text': "What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter."},
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{'text': "Tell me a random fun fact about the Roman Empire."},
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{'text': "Show me a code snippet of a website's sticky header in CSS and JavaScript."},
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]
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)
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msg = gr.Textbox(
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value = "",
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label = "Chat"
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)
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with gr.Row():
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send = gr.Button(
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value = "Send",
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size="lg",
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variant = "primary",
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)
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clear = gr.ClearButton([msg, chatbot])
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with gr.Accordion(label="⚙️ Parameters", open=True,):
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tools = gr.Textbox(
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value = tools_schema,
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lable = "Tools schema",
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)
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temperature = gr.Slider(
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minimum=0,
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maximum=1,
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step=0.1,
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value=0.3,
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label="Temperature",
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),
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max_tokens = gr.Slider(
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minimum=128,
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maximum=8192,
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step=1,
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value=1024,
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label="Max new tokens",
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)
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msg.submit(fn = stream_chat, inputs = [msg, chatbot, tools, temperature, max_tokens], outputs = [chatbot])
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send.click(fn = stream_chat, inputs = [msg, chatbot, tools, temperature, max_tokens], outputs = [chatbot])
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if __name__ == "__main__":
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demo.launch()
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