Update AzureOpenAI provider to match gpt-5 model family API specs #494

Author: valentinfrlch

custom_components/llmvision/providers.py

@@ -635,13 +635,14 @@ async def _make_request(self, data: dict) -> str:
 
     def _prepare_vision_data(self, call: Any) -> dict:
         default_parameters = self._get_default_parameters(call)
+        tokens_key = "max_completion_tokens" if self.model in ["gpt-5", "gpt-5-mini", "gpt-5-nano"] else "max_tokens"
         payload = {
             "messages": [{"role": "user", "content": []}],
-            "max_tokens": call.max_tokens,
             "temperature": default_parameters.get("temperature"),
             "top_p": default_parameters.get("top_p"),
             "stream": False,
         }
+        payload[tokens_key] = call.max_tokens
         for image, filename in zip(call.base64_images, call.filenames):
             tag = (
                 ("Image " + str(call.base64_images.index(image) + 1))
@@ -702,16 +703,17 @@ def _prepare_vision_data(self, call: Any) -> dict:
     def _prepare_text_data(self, call: Any) -> dict:
         default_parameters = self._get_default_parameters(call)
         title_prompt = self._get_title_prompt()
+        tokens_key = "max_completion_tokens" if self.model in ["gpt-5", "gpt-5-mini", "gpt-5-nano"] else "max_tokens"
         payload = {
             "messages": [
                 {"role": "user", "content": [{"type": "text", "text": title_prompt}]},
                 {"role": "user", "content": [{"type": "text", "text": call.message}]},
             ],
-            "max_tokens": call.max_tokens,
             "temperature": default_parameters.get("temperature"),
             "top_p": default_parameters.get("top_p"),
             "stream": False,
         }
+        payload[tokens_key] = call.max_tokens
 
         # Add structured output format if requested
         if call.response_format == "json" and call.structure:
@@ -751,12 +753,13 @@ async def validate(self) -> None | ServiceValidationError:
             api_version=self.endpoint.get("api_version"),
         )
         headers = self._generate_headers()
+        tokens_key = "max_completion_tokens" if self.model in ["gpt-5", "gpt-5-mini", "gpt-5-nano"] else "max_tokens"
         data = {
             "messages": [{"role": "user", "content": [{"type": "text", "text": "Hi"}]}],
-            "max_tokens": 1,
             "temperature": 0.5,
             "stream": False,
         }
+        data[tokens_key] = 1
         await self._post(url=endpoint, headers=headers, data=data)
 
     def supports_structured_output(self) -> bool: