Update app.py
Browse filesMake the step towards effectively let it work as an agent
app.py
CHANGED
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@@ -2,6 +2,7 @@ import gradio as gr
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from huggingface_hub import InferenceClient
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from smolagents import CodeAgent, HfApiModel, tool
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from tools.final_answer import FinalAnswerTool
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@tool
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def search_wikipedia_pages(search_string: str) -> str:
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@@ -21,64 +22,81 @@ def search_wikipedia_pages(search_string: str) -> str:
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final_answer = FinalAnswerTool()
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max_tokens,
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temperature,
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top_p,
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):
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messages = [{"role": "system", "content": system_message}]
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for val in history:
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if val[0]:
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messages.append({"role": "user", "content": val[0]})
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if val[1]:
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messages.append({"role": "assistant", "content": val[1]})
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messages.append({"role": "user", "content": message})
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response = ""
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for message in client.chat_completion(
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messages,
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max_tokens=max_tokens,
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stream=True,
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temperature=temperature,
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top_p=top_p,
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):
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token = message.choices[0].delta.content
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response += token
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yield response
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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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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(
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minimum=0.1,
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maximum=1.0,
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value=0.95,
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step=0.05,
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label="Top-p (nucleus sampling)",
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),
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],
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)
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if __name__ == "__main__":
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from huggingface_hub import InferenceClient
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from smolagents import CodeAgent, HfApiModel, tool
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from tools.final_answer import FinalAnswerTool
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from Gradio_UI import GradioUI
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@tool
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def search_wikipedia_pages(search_string: str) -> str:
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final_answer = FinalAnswerTool()
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agent = CodeAgent(
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model=model,
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tools=[final_answer, search_wikipedia_pages],
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max_steps=6,
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verbosity_level=1,
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grammar=None,
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planning_interval=None,
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name=None,
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description=None,
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prompt_templates=prompt_templates
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)
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GradioUI(agent).launch()
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# """
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# 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
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# """
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# client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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# def respond(
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# message,
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# history: list[tuple[str, str]],
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# system_message,
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# max_tokens,
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# temperature,
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# top_p,
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# ):
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# messages = [{"role": "system", "content": system_message}]
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# for val in history:
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# if val[0]:
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# messages.append({"role": "user", "content": val[0]})
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# if val[1]:
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# messages.append({"role": "assistant", "content": val[1]})
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# messages.append({"role": "user", "content": message})
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# response = ""
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# for message in client.chat_completion(
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# messages,
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# max_tokens=max_tokens,
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# stream=True,
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# temperature=temperature,
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# top_p=top_p,
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# ):
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# token = message.choices[0].delta.content
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# response += token
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# yield response
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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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# demo = gr.ChatInterface(
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# respond,
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# additional_inputs=[
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# gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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# gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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# gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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# gr.Slider(
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# minimum=0.1,
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# maximum=1.0,
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# value=0.95,
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# step=0.05,
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# label="Top-p (nucleus sampling)",
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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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