Create Llama 3.1 8B fine-tuned chat space

app.py

@@ -3,7 +3,6 @@ import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
 from peft import PeftModel
 import warnings
-import os
 warnings.filterwarnings("ignore")
 
 # 模型配置
@@ -65,7 +64,7 @@ def generate_response(prompt, max_tokens=200, temperature=0.7, top_p=0.9):
         return "❌ Model not loaded. Please check the logs or try again."
     
     try:
-        # 格式化输入
+        # 格式化输入 - 移除多余的字符串插值
         formatted_prompt = prompt.strip()
         
         # 编码输入
@@ -115,68 +114,105 @@ def chat_interface(message, history, max_tokens, temperature, top_p):
         history.append((message, error_msg))
         return history, ""
 
-# 创建 Gradio 应用 - 简化版本以避免兼容性问题
-def create_interface():
-    with gr.Blocks(title="Robot Task Planning - Llama 3.1 8B") as demo:
-        gr.Markdown("""
-        # 🤖 Llama 3.1 8B - Robot Task Planning
-        
-        This is a fine-tuned version of Meta's Llama 3.1 8B model specialized for **robot task planning** using QLoRA technique.
-        
-        **Model**: [YongdongWang/llama-3.1-8b-dart-qlora](https://huggingface.co/YongdongWang/llama-3.1-8b-dart-qlora)
-        
-        ⚠️ **Note**: Model loading may take a few minutes on first startup.
-        """)
-        
-        # 聊天界面
-        chatbot = gr.Chatbot(label="Task Planning Results", height=400)
-        msg = gr.Textbox(
-            label="Robot Command",
-            placeholder="Enter robot task command (e.g., 'Deploy Excavator 1 to Soil Area 1')...",
-            lines=2
-        )
-        
-        # 控制按钮
-        with gr.Row():
-            send_btn = gr.Button("Generate Tasks", variant="primary")
-            clear_btn = gr.Button("Clear")
-        
-        # 生成参数 - 简化版本
-        with gr.Accordion("⚙️ Generation Settings", open=False):
-            max_tokens = gr.Slider(50, 500, 200, label="Max Tokens")
-            temperature = gr.Slider(0.1, 2.0, 0.7, label="Temperature")
-            top_p = gr.Slider(0.1, 1.0, 0.9, label="Top-p")
-        
-        # 示例 - 简化版本
-        with gr.Accordion("💡 Example Commands", open=False):
-            examples = [
-                "Deploy Excavator 1 to Soil Area 1 for excavation.",
-                "Send Dump Truck 1 to collect material, then unload at storage area.",
-                "Move all robots to avoid Puddle 1 after inspection.",
-                "Deploy multiple excavators to different soil areas simultaneously.",
-                "Coordinate dump trucks to transport materials from excavation site to storage.",
-            ]
+# 创建 Gradio 应用
+with gr.Blocks(title="Robot Task Planning - Llama 3.1 8B", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""
+    # 🤖 Llama 3.1 8B - Robot Task Planning
+    
+    This is a fine-tuned version of Meta's Llama 3.1 8B model specialized for **robot task planning** using QLoRA technique.
+    
+    **Capabilities**: Convert natural language robot commands into structured task sequences for excavators, dump trucks, and other construction robots.
+    
+    **Model**: [YongdongWang/llama-3.1-8b-dart-qlora](https://huggingface.co/YongdongWang/llama-3.1-8b-dart-qlora)
+    
+    ⚠️ **Note**: Model loading may take a few minutes on first startup.
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=3):
+            chatbot = gr.Chatbot(
+                label="Task Planning Results",
+                height=400,
+                show_label=True,
+                container=True,
+                bubble_full_width=False
+            )
             
-            for example in examples:
-                example_btn = gr.Button(example, size="sm")
-                example_btn.click(lambda x=example: x, outputs=msg)
-        
-        # 事件处理
-        def submit_message(message, history, max_tokens, temperature, top_p):
-            return chat_interface(message, history, max_tokens, temperature, top_p)
+            msg = gr.Textbox(
+                label="Robot Command",
+                placeholder="Enter robot task command (e.g., 'Deploy Excavator 1 to Soil Area 1')...",
+                lines=2,
+                max_lines=5,
+                show_label=True,
+                container=True
+            )
+            
+            with gr.Row():
+                send_btn = gr.Button("Generate Tasks", variant="primary", size="sm")
+                clear_btn = gr.Button("Clear", variant="secondary", size="sm")
         
-        msg.submit(submit_message, [msg, chatbot, max_tokens, temperature, top_p], [chatbot, msg])
-        send_btn.click(submit_message, [msg, chatbot, max_tokens, temperature, top_p], [chatbot, msg])
-        clear_btn.click(lambda: ([], ""), outputs=[chatbot, msg])
+        with gr.Column(scale=1):
+            gr.Markdown("### ⚙️ Generation Settings")
+            
+            max_tokens = gr.Slider(
+                minimum=50,
+                maximum=500,
+                value=200,
+                step=10,
+                label="Max Tokens",
+                info="Maximum number of tokens to generate"
+            )
+            
+            temperature = gr.Slider(
+                minimum=0.1,
+                maximum=2.0,
+                value=0.7,
+                step=0.1,
+                label="Temperature",
+                info="Controls randomness (lower = more focused)"
+            )
+            
+            top_p = gr.Slider(
+                minimum=0.1,
+                maximum=1.0,
+                value=0.9,
+                step=0.05,
+                label="Top-p",
+                info="Nucleus sampling threshold"
+            )
     
-    return demo
+    # 示例对话
+    gr.Examples(
+        examples=[
+            ["Deploy Excavator 1 to Soil Area 1 for excavation."],
+            ["Send Dump Truck 1 to collect material, then unload at storage area."],
+            ["Move all robots to avoid Puddle 1 after inspection."],
+            ["Deploy multiple excavators to different soil areas simultaneously."],
+            ["Coordinate dump trucks to transport materials from excavation site to storage."],
+            ["Send robot to inspect rock area, then avoid with all other robots."],
+            ["Return all robots to start position after completing tasks."],
+        ],
+        inputs=msg,
+        label="💡 Example Robot Commands"
+    )
+    
+    # 事件处理
+    msg.submit(
+        chat_interface,
+        inputs=[msg, chatbot, max_tokens, temperature, top_p],
+        outputs=[chatbot, msg]
+    )
+    
+    send_btn.click(
+        chat_interface,
+        inputs=[msg, chatbot, max_tokens, temperature, top_p],
+        outputs=[chatbot, msg]
+    )
+    
+    clear_btn.click(
+        lambda: ([], ""),
+        outputs=[chatbot, msg]
+    )
 
 if __name__ == "__main__":
-    demo = create_interface()
-    # 修复启动配置 - 关键修复！
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860,
-        share=True,  # 这是关键！
-        show_error=True
-    )
+    demo.launch()

requirements.txt

@@ -1,8 +1,7 @@
-gradio==4.20.0
+gradio==4.44.0
 transformers==4.44.2
 torch==2.1.0
 peft==0.7.1
 bitsandbytes==0.41.3
 accelerate==0.24.1
 scipy==1.11.4
-packaging