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Fix Gradio compatibility issues and startup configuration
Browse files- app.py +62 -98
- requirements.txt +2 -1
app.py
CHANGED
@@ -3,6 +3,7 @@ import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
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from peft import PeftModel
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import warnings
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warnings.filterwarnings("ignore")
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# 模型配置
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@@ -64,7 +65,7 @@ def generate_response(prompt, max_tokens=200, temperature=0.7, top_p=0.9):
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return "❌ Model not loaded. Please check the logs or try again."
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try:
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# 格式化输入
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formatted_prompt = prompt.strip()
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# 编码输入
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@@ -114,105 +115,68 @@ def chat_interface(message, history, max_tokens, temperature, top_p):
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history.append((message, error_msg))
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return history, ""
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# 创建 Gradio 应用
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gr.
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This is a fine-tuned version of Meta's Llama 3.1 8B model specialized for **robot task planning** using QLoRA technique.
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**Capabilities**: Convert natural language robot commands into structured task sequences for excavators, dump trucks, and other construction robots.
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**Model**: [YongdongWang/llama-3.1-8b-dart-qlora](https://huggingface.co/YongdongWang/llama-3.1-8b-dart-qlora)
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⚠️ **Note**: Model loading may take a few minutes on first startup.
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""")
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with gr.Row():
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with gr.Column(scale=3):
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chatbot = gr.Chatbot(
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label="Task Planning Results",
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height=400,
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show_label=True,
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container=True,
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bubble_full_width=False
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)
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msg = gr.Textbox(
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label="Robot Command",
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placeholder="Enter robot task command (e.g., 'Deploy Excavator 1 to Soil Area 1')...",
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lines=2,
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max_lines=5,
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show_label=True,
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container=True
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)
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with gr.Row():
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send_btn = gr.Button("Generate Tasks", variant="primary", size="sm")
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clear_btn = gr.Button("Clear", variant="secondary", size="sm")
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examples=[
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["Deploy Excavator 1 to Soil Area 1 for excavation."],
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["Send Dump Truck 1 to collect material, then unload at storage area."],
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["Move all robots to avoid Puddle 1 after inspection."],
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["Deploy multiple excavators to different soil areas simultaneously."],
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["Coordinate dump trucks to transport materials from excavation site to storage."],
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["Send robot to inspect rock area, then avoid with all other robots."],
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["Return all robots to start position after completing tasks."],
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],
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inputs=msg,
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label="💡 Example Robot Commands"
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)
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# 事件处理
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msg.submit(
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chat_interface,
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inputs=[msg, chatbot, max_tokens, temperature, top_p],
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outputs=[chatbot, msg]
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)
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send_btn.click(
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chat_interface,
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inputs=[msg, chatbot, max_tokens, temperature, top_p],
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outputs=[chatbot, msg]
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)
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lambda: ([], ""),
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outputs=[chatbot, msg]
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)
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if __name__ == "__main__":
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demo
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from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
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from peft import PeftModel
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import warnings
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import os
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warnings.filterwarnings("ignore")
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# 模型配置
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return "❌ Model not loaded. Please check the logs or try again."
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try:
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# 格式化输入
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formatted_prompt = prompt.strip()
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# 编码输入
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history.append((message, error_msg))
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return history, ""
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# 创建 Gradio 应用 - 简化版本以避免兼容性问题
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def create_interface():
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with gr.Blocks(title="Robot Task Planning - Llama 3.1 8B") as demo:
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gr.Markdown("""
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# 🤖 Llama 3.1 8B - Robot Task Planning
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This is a fine-tuned version of Meta's Llama 3.1 8B model specialized for **robot task planning** using QLoRA technique.
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**Model**: [YongdongWang/llama-3.1-8b-dart-qlora](https://huggingface.co/YongdongWang/llama-3.1-8b-dart-qlora)
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⚠️ **Note**: Model loading may take a few minutes on first startup.
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""")
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# 聊天界面
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chatbot = gr.Chatbot(label="Task Planning Results", height=400)
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msg = gr.Textbox(
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label="Robot Command",
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placeholder="Enter robot task command (e.g., 'Deploy Excavator 1 to Soil Area 1')...",
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lines=2
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)
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# 控制按钮
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with gr.Row():
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send_btn = gr.Button("Generate Tasks", variant="primary")
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clear_btn = gr.Button("Clear")
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# 生成参数 - 简化版本
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with gr.Accordion("⚙️ Generation Settings", open=False):
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max_tokens = gr.Slider(50, 500, 200, label="Max Tokens")
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temperature = gr.Slider(0.1, 2.0, 0.7, label="Temperature")
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top_p = gr.Slider(0.1, 1.0, 0.9, label="Top-p")
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# 示例 - 简化版本
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with gr.Accordion("💡 Example Commands", open=False):
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examples = [
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"Deploy Excavator 1 to Soil Area 1 for excavation.",
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"Send Dump Truck 1 to collect material, then unload at storage area.",
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"Move all robots to avoid Puddle 1 after inspection.",
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"Deploy multiple excavators to different soil areas simultaneously.",
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"Coordinate dump trucks to transport materials from excavation site to storage.",
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]
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for example in examples:
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example_btn = gr.Button(example, size="sm")
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example_btn.click(lambda x=example: x, outputs=msg)
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# 事件处理
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def submit_message(message, history, max_tokens, temperature, top_p):
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return chat_interface(message, history, max_tokens, temperature, top_p)
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msg.submit(submit_message, [msg, chatbot, max_tokens, temperature, top_p], [chatbot, msg])
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send_btn.click(submit_message, [msg, chatbot, max_tokens, temperature, top_p], [chatbot, msg])
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clear_btn.click(lambda: ([], ""), outputs=[chatbot, msg])
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return demo
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if __name__ == "__main__":
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demo = create_interface()
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# 修复启动配置 - 关键修复!
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demo.launch(
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server_name="0.0.0.0",
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server_port=7860,
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share=True, # 这是关键!
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show_error=True
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)
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requirements.txt
CHANGED
@@ -1,7 +1,8 @@
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gradio==4.
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transformers==4.44.2
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torch==2.1.0
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peft==0.7.1
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bitsandbytes==0.41.3
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accelerate==0.24.1
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scipy==1.11.4
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gradio==4.20.0
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transformers==4.44.2
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torch==2.1.0
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peft==0.7.1
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bitsandbytes==0.41.3
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accelerate==0.24.1
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scipy==1.11.4
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packaging
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