File size: 5,080 Bytes
e3278e4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 |
import json
from typing import Any, Callable, Optional, Union
import httpx
import litellm
from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
from litellm.llms.custom_httpx.http_handler import (
AsyncHTTPHandler,
HTTPHandler,
get_async_httpx_client,
)
from litellm.types.llms.bedrock import CohereEmbeddingRequest
from litellm.types.utils import EmbeddingResponse
from .transformation import CohereEmbeddingConfig
def validate_environment(api_key, headers: dict):
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 CohereError(Exception):
def __init__(self, status_code, message):
self.status_code = status_code
self.message = message
self.request = httpx.Request(
method="POST", url="https://api.cohere.ai/v1/generate"
)
self.response = httpx.Response(status_code=status_code, request=self.request)
super().__init__(
self.message
) # Call the base class constructor with the parameters it needs
async def async_embedding(
model: str,
data: Union[dict, CohereEmbeddingRequest],
input: list,
model_response: litellm.utils.EmbeddingResponse,
timeout: Optional[Union[float, httpx.Timeout]],
logging_obj: LiteLLMLoggingObj,
optional_params: dict,
api_base: str,
api_key: Optional[str],
headers: dict,
encoding: Callable,
client: Optional[AsyncHTTPHandler] = None,
):
## LOGGING
logging_obj.pre_call(
input=input,
api_key=api_key,
additional_args={
"complete_input_dict": data,
"headers": headers,
"api_base": api_base,
},
)
## COMPLETION CALL
if client is None:
client = get_async_httpx_client(
llm_provider=litellm.LlmProviders.COHERE,
params={"timeout": timeout},
)
try:
response = await client.post(api_base, headers=headers, data=json.dumps(data))
except httpx.HTTPStatusError as e:
## LOGGING
logging_obj.post_call(
input=input,
api_key=api_key,
additional_args={"complete_input_dict": data},
original_response=e.response.text,
)
raise e
except Exception as e:
## LOGGING
logging_obj.post_call(
input=input,
api_key=api_key,
additional_args={"complete_input_dict": data},
original_response=str(e),
)
raise e
## PROCESS RESPONSE ##
return CohereEmbeddingConfig()._transform_response(
response=response,
api_key=api_key,
logging_obj=logging_obj,
data=data,
model_response=model_response,
model=model,
encoding=encoding,
input=input,
)
def embedding(
model: str,
input: list,
model_response: EmbeddingResponse,
logging_obj: LiteLLMLoggingObj,
optional_params: dict,
headers: dict,
encoding: Any,
data: Optional[Union[dict, CohereEmbeddingRequest]] = None,
complete_api_base: Optional[str] = None,
api_key: Optional[str] = None,
aembedding: Optional[bool] = None,
timeout: Optional[Union[float, httpx.Timeout]] = httpx.Timeout(None),
client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
):
headers = validate_environment(api_key, headers=headers)
embed_url = complete_api_base or "https://api.cohere.ai/v1/embed"
model = model
data = data or CohereEmbeddingConfig()._transform_request(
model=model, input=input, inference_params=optional_params
)
## ROUTING
if aembedding is True:
return async_embedding(
model=model,
data=data,
input=input,
model_response=model_response,
timeout=timeout,
logging_obj=logging_obj,
optional_params=optional_params,
api_base=embed_url,
api_key=api_key,
headers=headers,
encoding=encoding,
client=(
client
if client is not None and isinstance(client, AsyncHTTPHandler)
else None
),
)
## LOGGING
logging_obj.pre_call(
input=input,
api_key=api_key,
additional_args={"complete_input_dict": data},
)
## COMPLETION CALL
if client is None or not isinstance(client, HTTPHandler):
client = HTTPHandler(concurrent_limit=1)
response = client.post(embed_url, headers=headers, data=json.dumps(data))
return CohereEmbeddingConfig()._transform_response(
response=response,
api_key=api_key,
logging_obj=logging_obj,
data=data,
model_response=model_response,
model=model,
encoding=encoding,
input=input,
)
|