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https://github.com/BerriAI/litellm.git
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* feat(databricks/chat/): add anthropic w/ reasoning content support via databricks Allows user to call claude-3-7-sonnet with thinking via databricks * refactor: refactor choices transformation + add unit testing * fix(databricks/chat/transformation.py): support thinking blocks on databricks response streaming * feat(databricks/chat/transformation.py): support response_format for claude models * fix(databricks/chat/transformation.py): correctly handle response_format={"type": "text"} * feat(databricks/chat/transformation.py): support 'reasoning_effort' param mapping for anthropic * fix: fix ruff errors * fix: fix linting error * test: update test * fix(databricks/chat/transformation.py): handle json mode output parsing * fix(databricks/chat/transformation.py): handle json mode on streaming * test: update test * test: update dbrx testing * test: update testing * fix(base_model_iterator.py): handle non-json chunk * test: update tests * fix: fix ruff check * fix: fix databricks config import * fix: handle _tool = none * test: skip invalid test
152 lines
4.6 KiB
Python
152 lines
4.6 KiB
Python
import json
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from abc import abstractmethod
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from typing import Optional, Union
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import litellm
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from litellm.types.utils import GenericStreamingChunk, ModelResponseStream
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class BaseModelResponseIterator:
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def __init__(
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self, streaming_response, sync_stream: bool, json_mode: Optional[bool] = False
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):
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self.streaming_response = streaming_response
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self.response_iterator = self.streaming_response
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self.json_mode = json_mode
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def chunk_parser(
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self, chunk: dict
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) -> Union[GenericStreamingChunk, ModelResponseStream]:
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return GenericStreamingChunk(
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text="",
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is_finished=False,
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finish_reason="",
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usage=None,
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index=0,
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tool_use=None,
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)
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# Sync iterator
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def __iter__(self):
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return self
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def _handle_string_chunk(
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self, str_line: str
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) -> Union[GenericStreamingChunk, ModelResponseStream]:
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# chunk is a str at this point
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stripped_chunk = litellm.CustomStreamWrapper._strip_sse_data_from_chunk(
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str_line
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)
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try:
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if stripped_chunk is not None:
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stripped_json_chunk: Optional[dict] = json.loads(stripped_chunk)
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else:
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stripped_json_chunk = None
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except json.JSONDecodeError:
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stripped_json_chunk = None
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if "[DONE]" in str_line:
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return GenericStreamingChunk(
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text="",
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is_finished=True,
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finish_reason="stop",
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usage=None,
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index=0,
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tool_use=None,
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)
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elif stripped_json_chunk:
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return self.chunk_parser(chunk=stripped_json_chunk)
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else:
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return GenericStreamingChunk(
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text="",
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is_finished=False,
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finish_reason="",
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usage=None,
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index=0,
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tool_use=None,
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)
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def __next__(self):
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try:
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chunk = self.response_iterator.__next__()
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except StopIteration:
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raise StopIteration
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except ValueError as e:
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raise RuntimeError(f"Error receiving chunk from stream: {e}")
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try:
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str_line = chunk
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if isinstance(chunk, bytes): # Handle binary data
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str_line = chunk.decode("utf-8") # Convert bytes to string
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index = str_line.find("data:")
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if index != -1:
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str_line = str_line[index:]
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# chunk is a str at this point
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return self._handle_string_chunk(str_line=str_line)
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except StopIteration:
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raise StopIteration
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except ValueError as e:
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raise RuntimeError(f"Error parsing chunk: {e},\nReceived chunk: {chunk}")
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# Async iterator
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def __aiter__(self):
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self.async_response_iterator = self.streaming_response.__aiter__()
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return self
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async def __anext__(self):
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try:
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chunk = await self.async_response_iterator.__anext__()
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except StopAsyncIteration:
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raise StopAsyncIteration
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except ValueError as e:
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raise RuntimeError(f"Error receiving chunk from stream: {e}")
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try:
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str_line = chunk
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if isinstance(chunk, bytes): # Handle binary data
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str_line = chunk.decode("utf-8") # Convert bytes to string
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index = str_line.find("data:")
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if index != -1:
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str_line = str_line[index:]
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# chunk is a str at this point
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chunk = self._handle_string_chunk(str_line=str_line)
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return chunk
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except StopAsyncIteration:
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raise StopAsyncIteration
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except ValueError as e:
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raise RuntimeError(f"Error parsing chunk: {e},\nReceived chunk: {chunk}")
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class FakeStreamResponseIterator:
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def __init__(self, model_response, json_mode: Optional[bool] = False):
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self.model_response = model_response
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self.json_mode = json_mode
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self.is_done = False
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# Sync iterator
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def __iter__(self):
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return self
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@abstractmethod
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def chunk_parser(self, chunk: dict) -> GenericStreamingChunk:
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pass
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def __next__(self):
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if self.is_done:
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raise StopIteration
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self.is_done = True
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return self.chunk_parser(self.model_response)
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# Async iterator
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def __aiter__(self):
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return self
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async def __anext__(self):
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if self.is_done:
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raise StopAsyncIteration
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self.is_done = True
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return self.chunk_parser(self.model_response)
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