Update app.py

app.py

@@ -8,34 +8,52 @@ 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}"),
+    # Chain for general questions
+    general_prompt = ChatPromptTemplate.from_messages([
+        ("system", "You are a helpful assistant that provides direct answers."),
         ("human", "{question}")
     ])
     
-    contextualize_question = contextualize_prompt | llm | StrOutputParser()
+    # Chain for mathematical calculations
+    math_prompt = ChatPromptTemplate.from_messages([
+        ("system", "You are a mathematical assistant. Solve the problem and show your work."),
+        ("human", "{question}")
+    ])
     
-    @chain
-    def contextualize_if_needed(input_dict):
-        if input_dict.get("chat_history"):
-            return contextualize_question
-        return RunnablePassthrough() | (lambda x: x["question"])
+    # Chain for coding questions
+    code_prompt = ChatPromptTemplate.from_messages([
+        ("system", "You are a coding assistant. Provide code examples and explanations."),
+        ("human", "{question}")
+    ])
+    
+    general_chain = general_prompt | llm | StrOutputParser()
+    math_chain = math_prompt | llm | StrOutputParser()
+    code_chain = code_prompt | llm | StrOutputParser()
     
-    return contextualize_if_needed
+    @chain
+    def dynamic_chain(input_dict):
+        question = input_dict["question"].lower()
+        
+        # Detect question type
+        if any(word in question for word in ["calculate", "solve", "compute", "sum", "multiply"]):
+            return math_chain
+        elif any(word in question for word in ["code", "program", "function", "python", "javascript"]):
+            return code_chain
+        return general_chain
 
-def process_message(message, history, api_key):
+    return dynamic_chain
+
+def process_message(message, history, api_key, example_select):
     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]
+        # Handle example selection
+        if example_select != "Custom Input":
+            message = EXAMPLES[example_select]
         
-        response = chain.invoke({
-            "question": message,
-            "chat_history": chat_history
-        })
+        chain = create_dynamic_chain(api_key)
+        response = chain.invoke({"question": message})
         
         history.append({"role": "user", "content": message})
         history.append({"role": "assistant", "content": response})
@@ -44,24 +62,52 @@ def process_message(message, history, api_key):
     except Exception as e:
         return "", history + [{"role": "assistant", "content": f"Error: {str(e)}"}]
 
+# Example questions for different chain types
+EXAMPLES = {
+    "General Question": "What are the main features of renewable energy?",
+    "Math Problem": "Calculate the area of a circle with radius 5 units.",
+    "Coding Question": "Write a Python function to find the factorial of a number.",
+    "Custom Input": ""
+}
+
+# Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("# Dynamic Chain Demo")
+    gr.Markdown("# Dynamic Chain Demo with Examples")
     
-    api_key = gr.Textbox(
-        label="OpenAI API Key",
-        placeholder="Enter your OpenAI API key",
-        type="password"
-    )
+    with gr.Row():
+        api_key = gr.Textbox(
+            label="OpenAI API Key",
+            placeholder="Enter your OpenAI API key",
+            type="password"
+        )
+        example_select = gr.Dropdown(
+            choices=list(EXAMPLES.keys()),
+            value="Custom Input",
+            label="Select Example"
+        )
     
     chatbot = gr.Chatbot(type="messages")
-    msg = gr.Textbox(label="Message")
+    msg = gr.Textbox(label="Message", placeholder="Type your message or select an example above")
     clear = gr.ClearButton([msg, chatbot])
     
+    # Example descriptions
+    gr.Markdown("""
+    ## Example Types:
+    1. **General Questions**: Regular queries that don't require special processing
+    2. **Math Problems**: Questions involving calculations and mathematical operations
+    3. **Coding Questions**: Programming-related queries that return code examples
+    
+    ## Try these patterns:
+    - Math: "Calculate...", "Solve...", "Compute..."
+    - Code: "Write a function...", "Program...", "Code..."
+    - General: Any other type of question
+    """)
+    
     msg.submit(
         process_message,
-        inputs=[msg, chatbot, api_key],
+        inputs=[msg, chatbot, api_key, example_select],
         outputs=[msg, chatbot]
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()