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import gradio as gr |
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from transformers import load_tool, ReactCodeAgent, HfEngine, Tool |
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from gradio_agentchatbot import ( |
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AgentChatbot, |
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stream_from_transformers_agent, |
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ChatMessage, |
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) |
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from dotenv import load_dotenv |
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from langchain.agents import load_tools |
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from pathlib import Path |
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current_dir = Path(__file__).parent |
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load_dotenv() |
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image_generation_tool = load_tool("m-ric/text-to-image") |
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search_tool = Tool.from_langchain(load_tools(["serpapi"])[0]) |
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llm_engine = HfEngine("meta-llama/Meta-Llama-3-70B-Instruct") |
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agent = ReactCodeAgent( |
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tools=[image_generation_tool, search_tool], llm_engine=llm_engine |
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) |
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def interact_with_agent(prompt, messages): |
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messages.append(ChatMessage(role="user", content=prompt)) |
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yield messages |
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for msg in stream_from_transformers_agent(agent, prompt): |
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messages.append(msg) |
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yield messages |
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yield messages |
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with gr.Blocks() as demo: |
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with gr.Tabs(): |
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with gr.Tab("Demo"): |
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gr.Markdown("# Chat with an LLM Agent 🤖 and see its thoughts 💭") |
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chatbot = AgentChatbot( |
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label="Agent", |
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avatar_images=[ |
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None, |
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"https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png", |
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], |
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) |
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text_input = gr.Textbox(lines=1, label="Chat Message") |
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text_input.submit(interact_with_agent, [text_input, chatbot], [chatbot]) |
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with gr.Tab("Docs"): |
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gr.Markdown(Path(current_dir / "docs.md").read_text()) |
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if __name__ == "__main__": |
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demo.launch() |
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