Update app.py

app.py

@@ -1,33 +1,135 @@
-import gradio as gr
-import random
-from smolagents import GradioUI, CodeAgent, HfApiModel
+# import gradio as gr
+# import random
+# from smolagents import GradioUI, CodeAgent, HfApiModel
+
+# # Import our custom tools from their modules
+# from tools import DuckDuckGoSearchTool, WeatherInfoTool, HubStatsTool
+# from retriever import load_guest_dataset
+
+# # Initialize the Hugging Face model
+# model = HfApiModel()
+
+# # Initialize the web search tool
+# search_tool = DuckDuckGoSearchTool()
 
-# Import our custom tools from their modules
-from tools import DuckDuckGoSearchTool, WeatherInfoTool, HubStatsTool
-from retriever import load_guest_dataset
+# # Initialize the weather tool
+# weather_info_tool = WeatherInfoTool()
 
-# Initialize the Hugging Face model
-model = HfApiModel()
+# # Initialize the Hub stats tool
+# hub_stats_tool = HubStatsTool()
 
-# Initialize the web search tool
-search_tool = DuckDuckGoSearchTool()
+# # Load the guest dataset and initialize the guest info tool
+# guest_info_tool = load_guest_dataset()
 
-# Initialize the weather tool
-weather_info_tool = WeatherInfoTool()
+# # Create Alfred with all the tools
+# alfred = CodeAgent(
+#     tools=[guest_info_tool, weather_info_tool, hub_stats_tool, search_tool], 
+#     model=model,
+#     add_base_tools=True,  # Add any additional base tools
+#     planning_interval=3   # Enable planning every 3 steps
+# )
+
+# if __name__ == "__main__":
+#     GradioUI(alfred).launch()
+
+
+import gradio as gr
+from tool import run_agentic_rag  # 从tool模块导入工作流运行函数
+import time
 
-# Initialize the Hub stats tool
-hub_stats_tool = HubStatsTool()
+def format_history(history):
+    """格式化执行历史用于显示"""
+    formatted = []
+    for entry in history:
+        step = entry.get("step", "")
+        status = entry.get("status", "")
+        action = entry.get("action", "")
+        details = ""
+        
+        if step == "检索" and status == "完成":
+            docs = entry.get("documents", [])
+            details = f"检索到 {len(docs)} 个文档"
+        
+        elif step == "生成" and status == "完成":
+            answer = entry.get("answer", "")
+            details = f"生成答案: {answer[:100]}..." if len(answer) > 100 else f"生成答案: {answer}"
+        
+        elif step == "验证" and status == "完成":
+            verif = entry.get("verification", {})
+            valid = verif.get("valid", False)
+            feedback = verif.get("feedback", "")
+            details = f"结果: {'通过' if valid else '失败'}, 反馈: {feedback}"
+        
+        elif step == "准备重试" and status == "完成":
+            feedback = entry.get("feedback", "")
+            details = f"反馈: {feedback}"
+        
+        elif "action" in entry:
+            details = entry["action"]
+        
+        formatted.append(f"{step}: {status} {details}")
+    
+    return "\n".join(formatted)
 
-# Load the guest dataset and initialize the guest info tool
-guest_info_tool = load_guest_dataset()
+def process_query(question):
+    """处理用户查询"""
+    start_time = time.time()
+    
+    # 执行RAG工作流
+    result = run_agentic_rag(question)
+    
+    # 准备结果显示
+    documents = "\n\n".join([
+        f"文档 {i+1}:\n{doc[:200]}..." if len(doc) > 200 else f"文档 {i+1}:\n{doc}"
+        for i, doc in enumerate(result["documents"])
+    ])
+    
+    end_time = time.time()
+    process_time = f"{end_time - start_time:.2f}秒"
+    
+    return {
+        "answer": result["answer"],
+        "documents": documents,
+        "history": format_history(result["history"]),
+        "stats": f"重试次数: {result['retries_used']} | 处理时间: {process_time}"
+    }
 
-# Create Alfred with all the tools
-alfred = CodeAgent(
-    tools=[guest_info_tool, weather_info_tool, hub_stats_tool, search_tool], 
-    model=model,
-    add_base_tools=True,  # Add any additional base tools
-    planning_interval=3   # Enable planning every 3 steps
-)
+# 创建Gradio界面
+with gr.Blocks(title="Agentic RAG with LangGraph") as demo:
+    gr.Markdown("# 🧠 Agentic RAG 系统 (LangGraph 实现)")
+    gr.Markdown("使用LangGraph实现的带有自我验证和重试机制的RAG系统")
+    
+    with gr.Row():
+        with gr.Column():
+            question = gr.Textbox(
+                label="输入问题",
+                placeholder="在此输入您的问题...",
+                lines=3
+            )
+            submit_btn = gr.Button("提交", variant="primary")
+        
+        with gr.Column():
+            answer = gr.Textbox(label="最终答案", interactive=False, lines=5)
+            documents = gr.Textbox(label="相关文档", interactive=False, lines=10)
+            history = gr.Textbox(label="执行历史", interactive=False, lines=15)
+            stats = gr.Textbox(label="统计信息", interactive=False)
+    
+    # 事件处理
+    submit_btn.click(
+        fn=process_query,
+        inputs=[question],
+        outputs=[answer, documents, history, stats]
+    )
+    
+    # 示例问题
+    gr.Examples(
+        examples=[
+            "量子纠缠是什么？它有哪些实际应用？",
+            "解释Transformer架构的核心创新点",
+            "如何在PyTorch中实现一个简单的神经网络？"
+        ],
+        inputs=question
+    )
 
 if __name__ == "__main__":
-    GradioUI(alfred).launch()
+    demo.launch()