Adding new audio params

predictionguard/src/audio.py

@@ -42,25 +42,31 @@ def __init__(self, api_key, url):
     def create(
         self,
         model: str,
-        file: str
+        file: str,
+        language: Optional[str] = "auto",
+        temperature: Optional[float] = 0.0,
+        prompt: Optional[str] = "",
     ) -> Dict[str, Any]:
         """
         Creates a audio transcription request to the Prediction Guard /audio/transcriptions API
 
         :param model: The model to use
         :param file: Audio file to be transcribed
+        :param language: The language of the audio file
+        :param temperature: The temperature parameter for model transcription
+        :param prompt: A prompt to assist in transcription styling
         :result: A dictionary containing the transcribed text.
         """
 
         # Create a list of tuples, each containing all the parameters for
         # a call to _transcribe_audio
-        args = (model, file)
+        args = (model, file, language, temperature, prompt)
 
         # Run _transcribe_audio
         choices = self._transcribe_audio(*args)
         return choices
 
-    def _transcribe_audio(self, model, file):
+    def _transcribe_audio(self, model, file, language, temperature, prompt):
         """
         Function to transcribe an audio file.
         """
@@ -72,7 +78,12 @@ def _transcribe_audio(self, model, file):
 
         with open(file, "rb") as audio_file:
             files = {"file": (file, audio_file, "audio/wav")}
-            data = {"model": model}
+            data = {
+                "model": model,
+                "language": language,
+                "temperature": temperature,
+                "prompt": prompt,
+                }
 
             response = requests.request(
                 "POST", self.url + "/audio/transcriptions", headers=headers, files=files, data=data

predictionguard/src/chat.py

@@ -95,7 +95,7 @@ def create(
             str, Dict[
                 str, Dict[str, str]
             ]
-        ]] = "none",
+        ]] = None,
         tools: Optional[List[Dict[str, Union[str, Dict[str, str]]]]] = None,
         top_p: Optional[float] = 0.99,
         top_k: Optional[float] = 50,
@@ -296,22 +296,40 @@ def stream_generator(url, headers, payload, stream):
                         elif entry["type"] == "text":
                             continue
 
-        payload_dict = {
-            "model": model,
-            "messages": messages,
-            "frequency_penalty": frequency_penalty,
-            "logit_bias": logit_bias,
-            "max_completion_tokens": max_completion_tokens,
-            "parallel_tool_calls": parallel_tool_calls,
-            "presence_penalty": presence_penalty,
-            "stop": stop,
-            "stream": stream,
-            "temperature": temperature,
-            "tool_choice": tool_choice,
-            "tools": tools,
-            "top_p": top_p,
-            "top_k": top_k,
-        }
+        # TODO: Remove `tool_choice` check when null value available in API
+        if tool_choice is None:
+            payload_dict = {
+                "model": model,
+                "messages": messages,
+                "frequency_penalty": frequency_penalty,
+                "logit_bias": logit_bias,
+                "max_completion_tokens": max_completion_tokens,
+                "parallel_tool_calls": parallel_tool_calls,
+                "presence_penalty": presence_penalty,
+                "stop": stop,
+                "stream": stream,
+                "temperature": temperature,
+                "tools": tools,
+                "top_p": top_p,
+                "top_k": top_k,
+            }
+        else:
+            payload_dict = {
+                "model": model,
+                "messages": messages,
+                "frequency_penalty": frequency_penalty,
+                "logit_bias": logit_bias,
+                "max_completion_tokens": max_completion_tokens,
+                "parallel_tool_calls": parallel_tool_calls,
+                "presence_penalty": presence_penalty,
+                "stop": stop,
+                "stream": stream,
+                "temperature": temperature,
+                "tool_choice": tool_choice,
+                "tools": tools,
+                "top_p": top_p,
+                "top_k": top_k,
+            }
 
         if input:
             payload_dict["input"] = input

predictionguard/version.py

@@ -1,2 +1,2 @@
 # Setting the package version
-__version__ = "2.8.0"
+__version__ = "2.8.1"