Debugging shit

app.py

@@ -13,6 +13,7 @@ import textwrap
 from datasets import load_dataset
 from fastapi.responses import StreamingResponse
 import random
+import asyncio
 
 # Set up logging
 logging.basicConfig(level=logging.INFO)
@@ -115,10 +116,10 @@ Here's the complete Python function implementation:
     formatted_code = extract_and_format_code(generated_text)
     return {"solution": formatted_code}
 
-def stream_solution(instruction: str, token: str):
+async def stream_solution(instruction: str, token: str):
     if not verify_token(token):
         raise Exception("Invalid token")
-    
+
     system_prompt = "You are a Python coding assistant specialized in solving LeetCode problems. Provide only the complete implementation of the given function. Ensure proper indentation and formatting. Do not include any explanations or multiple solutions."
     full_prompt = f"""### Instruction:
 {system_prompt}
@@ -132,23 +133,19 @@ Here's the complete Python function implementation:
 
 ```python
 """
-    generated_text = ""
-    def generate():
-        
+    async def generate():
+        generated_text = ""
         try:
             for chunk in llm(full_prompt, stream=True, **generation_kwargs):
-                    token = chunk["choices"][0]["text"]
-                    generated_text += token
-                    logger.info(f"Generated text: {generated_text}")
-                    yield token
+                token = chunk["choices"][0]["text"]
+                generated_text += token
+                logger.info(f"Generated text: {generated_text}")
+                yield token  # Yield individual tokens for streaming
         except Exception as e:
             logger.error(f"Error generating solution: {e}")
             yield {"error": "Error generating solution"}
 
-    formatted_code = extract_and_format_code(generated_text)
-    logger.info(f"Formatted code: {formatted_code}")
-    logger.info(f"Formatted code length: {len(formatted_code)}")
-    yield {"response": formatted_code}
+    return generate()  # Return the async generator
 
 def random_problem(token: str) -> Dict[str, Any]:
     if not verify_token(token):
@@ -174,7 +171,7 @@ generate_interface = gr.Interface(
 stream_interface = gr.Interface(
     fn=stream_solution,
     inputs=[gr.Textbox(label="Problem Instruction"), gr.Textbox(label="JWT Token")],
-    outputs=gr.JSON(),
+    outputs=gr.Text(),  # Use gr.Text for streaming text
     title="Stream Solution API",
     description="Provide a LeetCode problem instruction and a valid JWT token to stream a solution."
 )
@@ -193,5 +190,19 @@ demo = gr.TabbedInterface(
     ["Generate Solution", "Stream Solution", "Random Problem"]
 )
 
+# Run the Gradio app
+async def run(interface):
+    async with gr.Gradio().launch(interface) as app:
+        while True:  # Continuous loop for handling new requests
+            instruction = await app.textboxes.get("Problem Instruction")
+            token = await app.textboxes.get("JWT Token")
+
+            try:
+                async for generated_token in await stream_solution(instruction, token):
+                    await app.text.write(generated_token)  # Update text box with each token
+            except Exception as e:
+                await app.text.write(f"Error: {e}")
+
 if __name__ == "__main__":
-    demo.launch(share=True)
+    loop = asyncio.get_event_loop()
+    loop.run_until_complete(run(demo))