Update main.py

main.py

@@ -16,7 +16,7 @@ class Validation(BaseModel):
     user_prompt: str  # User's input prompt
     system_prompt: str  # System's guiding prompt
     max_tokens: int = 1024,
-    temperature: float = 0.001,
+    temperature: float = 0.01,
     top_p: float = 0.9,
     repeat_penalty: float = 1.1,
     top_k: int = 40
@@ -33,7 +33,16 @@ async def generate_response(item: Validation):
 { item.user_prompt }<|eot_id|> \n <|start_header_id|>assistant<|end_header_id|>"""
     
     # Call the Llama model to generate a response
-    output = llm(prompt, max_tokens = item.max_tokens,temperature = item.temperature , top_p = item.top_p , repeat_penalty = item.repeat_penalty, top_k = item.top_k ,echo=True)  # Update parameters as needed
+    max_tokens = int(item.max_tokens)
+    temperature = float(item.temperature)
+    top_p = float(item.top_p)
+    repeat_penalty = float(item.repeat_penalty)  # Explicitly cast to float
+    top_k = int(item.top_k)
+
+    # Call the Llama model to generate a response
+    output = llm(prompt, max_tokens=max_tokens, temperature=temperature, top_p=top_p,
+                 repeat_penalty=repeat_penalty, top_k=top_k, echo=True)
+
     
     # Extract and return the text from the response
     return output['choices'][0]['text']