two version of R2R are here HEAD master

1 files changed, 74 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/core/parsers/media/audio_parser.py b/.venv/lib/python3.12/site-packages/core/parsers/media/audio_parser.py
new file mode 100644
index 00000000..7d5f9f1d
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/core/parsers/media/audio_parser.py
@@ -0,0 +1,74 @@
+# type: ignore
+import logging
+import os
+import tempfile
+from typing import AsyncGenerator
+
+from litellm import atranscription
+
+from core.base.parsers.base_parser import AsyncParser
+from core.base.providers import (
+    CompletionProvider,
+    DatabaseProvider,
+    IngestionConfig,
+)
+
+logger = logging.getLogger()
+
+
+class AudioParser(AsyncParser[bytes]):
+    """A parser for audio data using Whisper transcription."""
+
+    def __init__(
+        self,
+        config: IngestionConfig,
+        database_provider: DatabaseProvider,
+        llm_provider: CompletionProvider,
+    ):
+        self.database_provider = database_provider
+        self.llm_provider = llm_provider
+        self.config = config
+        self.atranscription = atranscription
+
+    async def ingest(  # type: ignore
+        self, data: bytes, **kwargs
+    ) -> AsyncGenerator[str, None]:
+        """Ingest audio data and yield a transcription using Whisper via
+        LiteLLM.
+
+        Args:
+            data: Raw audio bytes
+            *args, **kwargs: Additional arguments passed to the transcription call
+
+        Yields:
+            Chunks of transcribed text
+        """
+        try:
+            # Create a temporary file to store the audio data
+            with tempfile.NamedTemporaryFile(
+                suffix=".wav", delete=False
+            ) as temp_file:
+                temp_file.write(data)
+                temp_file_path = temp_file.name
+
+            # Call Whisper transcription
+            response = await self.atranscription(
+                model=self.config.audio_transcription_model
+                or self.config.app.audio_lm,
+                file=open(temp_file_path, "rb"),
+                **kwargs,
+            )
+
+            # The response should contain the transcribed text directly
+            yield response.text
+
+        except Exception as e:
+            logger.error(f"Error processing audio with Whisper: {str(e)}")
+            raise
+
+        finally:
+            # Clean up the temporary file
+            try:
+                os.unlink(temp_file_path)
+            except Exception as e:
+                logger.warning(f"Failed to delete temporary file: {str(e)}")