task: working chainlit RAG app

chainlit.md

@@ -1,12 +1,16 @@
-# ImagineUI
+# Welcome to ImagineUI Design Assistant! 👋
 
-Welcome! I'm here to help you imagine a new design. 
+I'm here to help you find the perfect design style for your website. I can:
 
-## How to use:
-1. Describe the style you're looking for
-2. We'll discuss the design elements and requirements
-3. Add your html structure
-3. When ready, type "!generate" to create the CSS
-4. I'll provide the CSS and we can make adjustments
+1. 🎨 Discuss your design preferences and requirements
+2. 🔍 Find similar designs from CSS Zen Garden
+3. 💡 Provide design inspiration and suggestions
 
-Let's create something beautiful! 
+## How to use
+
+1. Describe your desired design style
+2. I'll ask follow-up questions to understand your needs
+3. When ready, I'll show you matching designs
+4. We can refine the search based on your feedback
+
+Just start chatting and tell me what kind of design you're looking for! 

src/app.py

@@ -1,33 +1,61 @@
 import chainlit as cl
+from langchain_openai import ChatOpenAI
+from langchain_core.messages import HumanMessage, SystemMessage
 from chains.design_rag import DesignRAG
-from agents.designer import DesignerAgent
 
-# Initialize these once at module level
+# Initialize components
 design_rag = DesignRAG()
-designer = DesignerAgent(rag=design_rag)
+conversation_history = []
+
+# System message focused on design analysis
+SYSTEM_MESSAGE = """You are a helpful design assistant that finds and explains design examples.
+For every user message, analyze their design preferences and requirements, considering:
+1. Visual style and aesthetics
+2. Color preferences and mood
+3. Layout and structural needs
+4. Key visual elements
+
+First explain how you understand their requirements, then show relevant design examples."""
 
 @cl.on_chat_start
-async def start() -> None:
-    """Initialize the chat session"""
-    # Store in user session
-    cl.user_session.set("designer", designer)
+async def init():
+    # Initialize LLM with streaming
+    global llm
+    llm = ChatOpenAI(
+        model="gpt-4",
+        temperature=0,
+        streaming=True,
+        callbacks=[cl.LangchainCallbackHandler()]
+    )
+    
+    # Store system message
+    conversation_history.append(SystemMessage(content=SYSTEM_MESSAGE))
     
     # Send welcome message
-    await cl.Message(
-        content="Welcome! I'm here to help you imagine a unique design. What style are you looking for?"
-    ).send()
+    await cl.Message(content="Hello! What kind of design are you looking for?").send()
 
 @cl.on_message
-async def main(message: cl.Message) -> None:
-    """Handle incoming messages"""
-    designer = cl.user_session.get("designer")
-    if designer is None:
-        # Reinitialize if missing
-        designer = DesignerAgent(rag=design_rag)
-        cl.user_session.set("designer", designer)
+async def main(message: cl.Message):
+    # Add user message to history
+    conversation_history.append(HumanMessage(content=message.content))
+    
+    # Get LLM's analysis of requirements
+    analysis = await llm.ainvoke(conversation_history)
     
-    # Process message through designer agent
-    response = await designer.process(message.content)
+    # Get design examples based on full conversation
+    designs = await design_rag.query_similar_designs(
+        [msg.content for msg in conversation_history],
+        num_examples=3
+    )
     
-    # Send response
-    await cl.Message(content=response).send() 
+    # Combine analysis with designs
+    response = f"{analysis.content}\n\nHere are some relevant designs:\n\n{designs}"
+    
+    # Add assistant's response to history
+    conversation_history.append(SystemMessage(content=response))
+    
+    # Send response to user
+    await cl.Message(content=response).send()
+
+if __name__ == "__main__":
+    cl.run()