do multiple passes for video claude

backend/llm.py

@@ -3,6 +3,8 @@ from anthropic import AsyncAnthropic
 from openai import AsyncOpenAI
 from openai.types.chat import ChatCompletionMessageParam, ChatCompletionChunk
 
+from utils import pprint_prompt
+
 MODEL_GPT_4_VISION = "gpt-4-vision-preview"
 MODEL_CLAUDE_SONNET = "claude-3-sonnet-20240229"
 MODEL_CLAUDE_OPUS = "claude-3-opus-20240229"
@@ -113,34 +115,57 @@ async def stream_claude_response_native(
 
     client = AsyncAnthropic(api_key=api_key)
 
-    # Base parameters
+    # Base model parameters
     max_tokens = 4096
     temperature = 0.0
 
-    # Stream Claude response
+    # Multi-pass flow
+    current_pass_num = 1
+    max_passes = 2
+
+    prefix = "<thinking>"
+    response = None
+
+    while current_pass_num <= max_passes:
+        current_pass_num += 1
 
         # Set up message depending on whether we have a <thinking> prefix
-    messages = (
+        messages_to_send = (
-        messages + [{"role": "assistant", "content": "<thinking>"}]
+            messages + [{"role": "assistant", "content": prefix}]
             if include_thinking
             else messages
         )
 
+        pprint_prompt(messages_to_send)
+
         async with client.messages.stream(
             model=model,
             max_tokens=max_tokens,
             temperature=temperature,
             system=system_prompt,
-        messages=messages,  # type: ignore
+            messages=messages_to_send,  # type: ignore
         ) as stream:
             async for text in stream.text_stream:
+                print(text, end="", flush=True)
                 await callback(text)
 
         # Return final message
         response = await stream.get_final_message()
 
+        # Set up messages array for next pass
+        messages += [
+            {"role": "assistant", "content": str(prefix) + response.content[0].text},
+            {
+                "role": "user",
+                "content": "You've done a good job with a first draft. Improve this further based on the original instructions so that the app is fully functional and looks like the original video of the app we're trying to replicate.",
+            },
+        ]
+
         print(
             f"Token usage: Input Tokens: {response.usage.input_tokens}, Output Tokens: {response.usage.output_tokens}"
         )
 
+    if not response:
+        raise Exception("No HTML response found in AI response")
+    else:
         return response.content[0].text