TestLLM / litellm /llms /cohere /common_utils.py
Raju2024's picture
Upload 1072 files
e3278e4 verified
raw
history blame
4.79 kB
import json
from typing import List, Optional
from litellm.llms.base_llm.chat.transformation import BaseLLMException
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import (
ChatCompletionToolCallChunk,
ChatCompletionUsageBlock,
GenericStreamingChunk,
)
class CohereError(BaseLLMException):
def __init__(self, status_code, message):
super().__init__(status_code=status_code, message=message)
def validate_environment(
headers: dict,
model: str,
messages: List[AllMessageValues],
optional_params: dict,
api_key: Optional[str] = None,
) -> dict:
"""
Return headers to use for cohere chat completion request
Cohere API Ref: https://docs.cohere.com/reference/chat
Expected headers:
{
"Request-Source": "unspecified:litellm",
"accept": "application/json",
"content-type": "application/json",
"Authorization": "bearer $CO_API_KEY"
}
"""
headers.update(
{
"Request-Source": "unspecified:litellm",
"accept": "application/json",
"content-type": "application/json",
}
)
if api_key:
headers["Authorization"] = f"bearer {api_key}"
return headers
class ModelResponseIterator:
def __init__(
self, streaming_response, sync_stream: bool, json_mode: Optional[bool] = False
):
self.streaming_response = streaming_response
self.response_iterator = self.streaming_response
self.content_blocks: List = []
self.tool_index = -1
self.json_mode = json_mode
def chunk_parser(self, chunk: dict) -> GenericStreamingChunk:
try:
text = ""
tool_use: Optional[ChatCompletionToolCallChunk] = None
is_finished = False
finish_reason = ""
usage: Optional[ChatCompletionUsageBlock] = None
provider_specific_fields = None
index = int(chunk.get("index", 0))
if "text" in chunk:
text = chunk["text"]
elif "is_finished" in chunk and chunk["is_finished"] is True:
is_finished = chunk["is_finished"]
finish_reason = chunk["finish_reason"]
if "citations" in chunk:
provider_specific_fields = {"citations": chunk["citations"]}
returned_chunk = GenericStreamingChunk(
text=text,
tool_use=tool_use,
is_finished=is_finished,
finish_reason=finish_reason,
usage=usage,
index=index,
provider_specific_fields=provider_specific_fields,
)
return returned_chunk
except json.JSONDecodeError:
raise ValueError(f"Failed to decode JSON from chunk: {chunk}")
# Sync iterator
def __iter__(self):
return self
def __next__(self):
try:
chunk = self.response_iterator.__next__()
except StopIteration:
raise StopIteration
except ValueError as e:
raise RuntimeError(f"Error receiving chunk from stream: {e}")
try:
str_line = chunk
if isinstance(chunk, bytes): # Handle binary data
str_line = chunk.decode("utf-8") # Convert bytes to string
index = str_line.find("data:")
if index != -1:
str_line = str_line[index:]
data_json = json.loads(str_line)
return self.chunk_parser(chunk=data_json)
except StopIteration:
raise StopIteration
except ValueError as e:
raise RuntimeError(f"Error parsing chunk: {e},\nReceived chunk: {chunk}")
# Async iterator
def __aiter__(self):
self.async_response_iterator = self.streaming_response.__aiter__()
return self
async def __anext__(self):
try:
chunk = await self.async_response_iterator.__anext__()
except StopAsyncIteration:
raise StopAsyncIteration
except ValueError as e:
raise RuntimeError(f"Error receiving chunk from stream: {e}")
try:
str_line = chunk
if isinstance(chunk, bytes): # Handle binary data
str_line = chunk.decode("utf-8") # Convert bytes to string
index = str_line.find("data:")
if index != -1:
str_line = str_line[index:]
data_json = json.loads(str_line)
return self.chunk_parser(chunk=data_json)
except StopAsyncIteration:
raise StopAsyncIteration
except ValueError as e:
raise RuntimeError(f"Error parsing chunk: {e},\nReceived chunk: {chunk}")