Create app.py

app.py

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+import os
+import gradio as gr
+from langchain_openai import ChatOpenAI
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.runnables import RunnablePassthrough, chain
+
+def create_dynamic_chain(api_key):
+    llm = ChatOpenAI(model="gpt-4o-mini", api_key=api_key)
+    
+    contextualize_prompt = ChatPromptTemplate.from_messages([
+        ("system", "Convert the question into a standalone question given the chat history."),
+        ("placeholder", "{chat_history}"),
+        ("human", "{question}")
+    ])
+    
+    contextualize_question = contextualize_prompt | llm | StrOutputParser()
+    
+    @chain
+    def contextualize_if_needed(input_dict):
+        if input_dict.get("chat_history"):
+            return contextualize_question
+        return RunnablePassthrough() | (lambda x: x["question"])
+    
+    return contextualize_if_needed
+
+def process_message(message, history, api_key):
+    if not api_key:
+        return "", [{"role": "assistant", "content": "Please enter your OpenAI API key."}]
+    
+    try:
+        chain = create_dynamic_chain(api_key)
+        chat_history = [(msg["role"], msg["content"]) for msg in history]
+        
+        response = chain.invoke({
+            "question": message,
+            "chat_history": chat_history
+        })
+        
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": response})
+        
+        return "", history
+    except Exception as e:
+        return "", history + [{"role": "assistant", "content": f"Error: {str(e)}"}]
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Dynamic Chain Demo")
+    
+    api_key = gr.Textbox(
+        label="OpenAI API Key",
+        placeholder="Enter your OpenAI API key",
+        type="password"
+    )
+    
+    chatbot = gr.Chatbot(type="messages")
+    msg = gr.Textbox(label="Message")
+    clear = gr.ClearButton([msg, chatbot])
+    
+    msg.submit(
+        process_message,
+        inputs=[msg, chatbot, api_key],
+        outputs=[msg, chatbot]
+    )
+
+if __name__ == "__main__":
+    demo.launch()