Create app.py

app.py

@@ -0,0 +1,85 @@
+import gradio as gr
+import os
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.prompts import PromptTemplate
+from langchain_openai import ChatOpenAI
+
+def create_chains(openai_key):
+    os.environ["OPENAI_API_KEY"] = openai_key
+    
+    # Create the classifier chain
+    classifier_prompt = PromptTemplate.from_template(
+        """Given the user question below, classify it as either being about `LangChain`, `OpenAI`, or `Other`.
+        Do not respond with more than one word.
+        
+        <question>
+        {question}
+        </question>
+        
+        Classification:"""
+    )
+    
+    classifier_chain = classifier_prompt | ChatOpenAI(model="gpt-4") | StrOutputParser()
+    
+    # Create specialized chains
+    langchain_chain = (
+        PromptTemplate.from_template(
+            """You are an expert in LangChain. 
+            Always answer questions starting with "As a LangChain expert". 
+            Question: {question}
+            Answer:"""
+        ) | ChatOpenAI(model="gpt-4")
+    )
+    
+    openai_chain = (
+        PromptTemplate.from_template(
+            """You are an expert in OpenAI. 
+            Always answer questions starting with "As an OpenAI expert". 
+            Question: {question}
+            Answer:"""
+        ) | ChatOpenAI(model="gpt-4")
+    )
+    
+    general_chain = (
+        PromptTemplate.from_template(
+            """Respond to the following question:
+            Question: {question}
+            Answer:"""
+        ) | ChatOpenAI(model="gpt-4")
+    )
+    
+    return classifier_chain, langchain_chain, openai_chain, general_chain
+
+def route_question(question, openai_key):
+    try:
+        classifier_chain, langchain_chain, openai_chain, general_chain = create_chains(openai_key)
+        
+        # Classify the question
+        classification = classifier_chain.invoke({"question": question})
+        
+        # Route to appropriate chain
+        if "langchain" in classification.lower():
+            response = langchain_chain.invoke({"question": question})
+        elif "openai" in classification.lower():
+            response = openai_chain.invoke({"question": question})
+        else:
+            response = general_chain.invoke({"question": question})
+        
+        return f"Classification: {classification}\nResponse: {response.content}"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=route_question,
+    inputs=[
+        gr.Textbox(label="Enter your question"),
+        gr.Textbox(label="OpenAI API Key", type="password")
+    ],
+    outputs=gr.Textbox(label="Response"),
+    title="LangChain Router Demo",
+    description="This demo shows how routing works in LangChain. Ask questions about LangChain, OpenAI, or any other topic."
+)
+
+if __name__ == "__main__":
+    demo.launch()