mirror of
https://github.com/BerriAI/litellm.git
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* remove unused imports * fix AmazonConverseConfig * fix test * fix import * ruff check fixes * test fixes * fix testing * fix imports
133 lines
4.1 KiB
Python
133 lines
4.1 KiB
Python
import json
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from abc import abstractmethod
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from typing import Optional
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from litellm.types.utils import GenericStreamingChunk
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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(self, chunk: dict) -> GenericStreamingChunk:
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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(self, str_line: str) -> GenericStreamingChunk:
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# chunk is a str at this point
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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 str_line.startswith("data:"):
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data_json = json.loads(str_line[5:])
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return self.chunk_parser(chunk=data_json)
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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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return self._handle_string_chunk(str_line=str_line)
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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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