community: Add arguments to whisper parser (#20378)

**Description:** Added a few additional arguments to the whisper parser,
which can be consumed by the underlying API.
The prompt is especially important to fine-tune transcriptions.

---------

Co-authored-by: Roi Perlman <roi@fivesigmalabs.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>

libs/community/langchain_community/document_loaders/parsers/audio.py

@@ -1,7 +1,7 @@
 import logging
 import os
 import time
-from typing import Dict, Iterator, Optional, Tuple
+from typing import Any, Dict, Iterator, Literal, Optional, Tuple, Union
 
 from langchain_core.documents import Document
 
@@ -31,12 +31,32 @@ class OpenAIWhisperParser(BaseBlobParser):
         *,
         chunk_duration_threshold: float = 0.1,
         base_url: Optional[str] = None,
+        language: Union[str, None] = None,
+        prompt: Union[str, None] = None,
+        response_format: Union[
+            Literal["json", "text", "srt", "verbose_json", "vtt"], None
+        ] = None,
+        temperature: Union[float, None] = None,
     ):
         self.api_key = api_key
         self.chunk_duration_threshold = chunk_duration_threshold
         self.base_url = (
             base_url if base_url is not None else os.environ.get("OPENAI_API_BASE")
         )
+        self.language = language
+        self.prompt = prompt
+        self.response_format = response_format
+        self.temperature = temperature
+
+    @property
+    def _create_params(self) -> Dict[str, Any]:
+        params = {
+            "language": self.language,
+            "prompt": self.prompt,
+            "response_format": self.response_format,
+            "temperature": self.temperature,
+        }
+        return {k: v for k, v in params.items() if v is not None}
 
     def lazy_parse(self, blob: Blob) -> Iterator[Document]:
         """Lazily parse the blob."""
@@ -95,7 +115,7 @@ class OpenAIWhisperParser(BaseBlobParser):
                 try:
                     if is_openai_v1():
                         transcript = client.audio.transcriptions.create(
-                            model="whisper-1", file=file_obj
+                            model="whisper-1", file=file_obj, **self._create_params
                         )
                     else:
                         transcript = openai.Audio.transcribe("whisper-1", file_obj)