adaption for NVIDIA API: stream=True

Author: einzigsue

openevolve/llm/openai.py

@@ -38,6 +38,7 @@ def __init__(
         self.client = openai.OpenAI(
             api_key=self.api_key,
             base_url=self.api_base,
+	    timeout=int(self.timeout)
         )
 
         # Only log unique models to reduce duplication
@@ -72,6 +73,16 @@ async def generate_with_context(
                 "messages": formatted_messages,
                 "max_completion_tokens": kwargs.get("max_tokens", self.max_tokens),
             }
+        elif self.api_base == "https://integrate.api.nvidia.com/v1":
+        # add the branch for NVbuild
+            params = {
+                "model": self.model,
+                "messages": formatted_messages,
+                "temperature": kwargs.get("temperature", self.temperature),
+                "top_p": kwargs.get("top_p", self.top_p),
+                "max_tokens": kwargs.get("max_tokens", self.max_tokens),
+                "stream": True
+            }
         else:
             params = {
                 "model": self.model,
@@ -130,4 +141,14 @@ async def _call_api(self, params: Dict[str, Any]) -> str:
         logger = logging.getLogger(__name__)
         logger.debug(f"API parameters: {params}")
         logger.debug(f"API response: {response.choices[0].message.content}")
-        return response.choices[0].message.content
+
+        if self.api_base == "https://integrate.api.nvidia.com/v1":
+            #print(f"{params['model']}")
+            output=""
+            for chunk in response:
+                if chunk.choices[0].delta.content is not None:
+                    output += chunk.choices[0].delta.content
+        else:
+            output=response.choices[0].message.content        
+
+        return output