mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 18:54:30 +00:00
remove init AnthropicClient for completion calls
This commit is contained in:
ishaan-jaff
parent
2dc1c35a05
commit
bc065f08df
2 changed files with 119 additions and 136 deletions
|
|
@ -1,16 +1,15 @@
|
|||
import os, json
|
||||
import os
|
||||
import json
|
||||
from enum import Enum
|
||||
import requests
|
||||
import time
|
||||
from typing import Callable
|
||||
from litellm.utils import ModelResponse
|
||||
|
||||
|
||||
class AnthropicConstants(Enum):
|
||||
HUMAN_PROMPT = "\n\nHuman:"
|
||||
AI_PROMPT = "\n\nAssistant:"
|
||||
|
||||
|
||||
class AnthropicError(Exception):
|
||||
def __init__(self, status_code, message):
|
||||
self.status_code = status_code
|
||||
|
|
@ -19,45 +18,33 @@ class AnthropicError(Exception):
|
|||
self.message
|
||||
) # Call the base class constructor with the parameters it needs
|
||||
|
||||
|
||||
class AnthropicLLM:
|
||||
def __init__(
|
||||
self, encoding, default_max_tokens_to_sample, logging_obj, api_key=None
|
||||
):
|
||||
self.encoding = encoding
|
||||
self.default_max_tokens_to_sample = default_max_tokens_to_sample
|
||||
self.completion_url = "https://api.anthropic.com/v1/complete"
|
||||
self.api_key = api_key
|
||||
self.logging_obj = logging_obj
|
||||
self.validate_environment(api_key=api_key)
|
||||
|
||||
def validate_environment(
|
||||
self, api_key
|
||||
): # set up the environment required to run the model
|
||||
# set the api key
|
||||
if self.api_key == None:
|
||||
# makes headers for API call
|
||||
def validate_environment(api_key):
|
||||
if api_key is None:
|
||||
raise ValueError(
|
||||
"Missing Anthropic API Key - A call is being made to anthropic but no key is set either in the environment variables or via params"
|
||||
)
|
||||
self.api_key = api_key
|
||||
self.headers = {
|
||||
headers = {
|
||||
"accept": "application/json",
|
||||
"anthropic-version": "2023-06-01",
|
||||
"content-type": "application/json",
|
||||
"x-api-key": self.api_key,
|
||||
"x-api-key": api_key,
|
||||
}
|
||||
return headers
|
||||
|
||||
def completion(
|
||||
self,
|
||||
def completion(
|
||||
model: str,
|
||||
messages: list,
|
||||
model_response: ModelResponse,
|
||||
print_verbose: Callable,
|
||||
encoding,
|
||||
api_key,
|
||||
logging_obj,
|
||||
optional_params=None,
|
||||
litellm_params=None,
|
||||
logger_fn=None,
|
||||
): # logic for parsing in - calling - parsing out model completion calls
|
||||
model = model
|
||||
):
|
||||
headers = validate_environment(api_key)
|
||||
prompt = f"{AnthropicConstants.HUMAN_PROMPT.value}"
|
||||
for message in messages:
|
||||
if "role" in message:
|
||||
|
|
@ -72,12 +59,10 @@ class AnthropicLLM:
|
|||
else:
|
||||
prompt += f"{AnthropicConstants.HUMAN_PROMPT.value}{message['content']}"
|
||||
prompt += f"{AnthropicConstants.AI_PROMPT.value}"
|
||||
if "max_tokens" in optional_params and optional_params["max_tokens"] != float(
|
||||
"inf"
|
||||
):
|
||||
if "max_tokens" in optional_params and optional_params["max_tokens"] != float("inf"):
|
||||
max_tokens = optional_params["max_tokens"]
|
||||
else:
|
||||
max_tokens = self.default_max_tokens_to_sample
|
||||
max_tokens = 256 # required anthropic param, default to 256 if user does not provide an input
|
||||
data = {
|
||||
"model": model,
|
||||
"prompt": prompt,
|
||||
|
|
@ -86,28 +71,29 @@ class AnthropicLLM:
|
|||
}
|
||||
|
||||
## LOGGING
|
||||
self.logging_obj.pre_call(
|
||||
logging_obj.pre_call(
|
||||
input=prompt,
|
||||
api_key=self.api_key,
|
||||
api_key=api_key,
|
||||
additional_args={"complete_input_dict": data},
|
||||
)
|
||||
|
||||
## COMPLETION CALL
|
||||
if "stream" in optional_params and optional_params["stream"] == True:
|
||||
response = requests.post(
|
||||
self.completion_url,
|
||||
headers=self.headers,
|
||||
"https://api.anthropic.com/v1/complete",
|
||||
headers=headers,
|
||||
data=json.dumps(data),
|
||||
stream=optional_params["stream"],
|
||||
)
|
||||
return response.iter_lines()
|
||||
else:
|
||||
response = requests.post(
|
||||
self.completion_url, headers=self.headers, data=json.dumps(data)
|
||||
"https://api.anthropic.com/v1/complete", headers=headers, data=json.dumps(data)
|
||||
)
|
||||
## LOGGING
|
||||
self.logging_obj.post_call(
|
||||
logging_obj.post_call(
|
||||
input=prompt,
|
||||
api_key=self.api_key,
|
||||
api_key=api_key,
|
||||
original_response=response.text,
|
||||
additional_args={"complete_input_dict": data},
|
||||
)
|
||||
|
|
@ -116,23 +102,25 @@ class AnthropicLLM:
|
|||
try:
|
||||
completion_response = response.json()
|
||||
except:
|
||||
raise AnthropicError(message=response.text, status_code=response.status_code)
|
||||
raise AnthropicError(
|
||||
message=response.text, status_code=response.status_code
|
||||
)
|
||||
if "error" in completion_response:
|
||||
raise AnthropicError(
|
||||
message=str(completion_response["error"]),
|
||||
status_code=response.status_code,
|
||||
)
|
||||
else:
|
||||
model_response["choices"][0]["message"][
|
||||
"content"
|
||||
] = completion_response["completion"]
|
||||
model_response["choices"][0]["message"]["content"] = completion_response[
|
||||
"completion"
|
||||
]
|
||||
|
||||
## CALCULATING USAGE
|
||||
prompt_tokens = len(
|
||||
self.encoding.encode(prompt)
|
||||
encoding.encode(prompt)
|
||||
) ##[TODO] use the anthropic tokenizer here
|
||||
completion_tokens = len(
|
||||
self.encoding.encode(model_response["choices"][0]["message"]["content"])
|
||||
encoding.encode(model_response["choices"][0]["message"]["content"])
|
||||
) ##[TODO] use the anthropic tokenizer here
|
||||
|
||||
model_response["created"] = time.time()
|
||||
|
|
@ -144,7 +132,6 @@ class AnthropicLLM:
|
|||
}
|
||||
return model_response
|
||||
|
||||
def embedding(
|
||||
self,
|
||||
): # logic for parsing in - calling - parsing out model embedding calls
|
||||
def embedding():
|
||||
# logic for parsing in - calling - parsing out model embedding calls
|
||||
pass
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ from litellm.utils import (
|
|||
read_config_args,
|
||||
completion_with_fallbacks,
|
||||
)
|
||||
from .llms.anthropic import AnthropicLLM
|
||||
from .llms import anthropic
|
||||
from .llms.huggingface_restapi import HuggingfaceRestAPILLM
|
||||
from .llms.baseten import BasetenLLM
|
||||
from .llms.ai21 import AI21LLM
|
||||
|
|
@ -61,7 +61,6 @@ async def acompletion(*args, **kwargs):
|
|||
|
||||
|
||||
@client
|
||||
# @retry(wait=wait_random_exponential(min=1, max=60), stop=stop_after_attempt(2), reraise=True, retry_error_callback=lambda retry_state: setattr(retry_state.outcome, 'retry_variable', litellm.retry)) # retry call, turn this off by setting `litellm.retry = False`
|
||||
@timeout( # type: ignore
|
||||
600
|
||||
) ## set timeouts, in case calls hang (e.g. Azure) - default is 600s, override with `force_timeout`
|
||||
|
|
@ -79,7 +78,6 @@ def completion(
|
|||
max_tokens=float("inf"),
|
||||
presence_penalty=0,
|
||||
frequency_penalty=0,
|
||||
num_beams=1,
|
||||
logit_bias={},
|
||||
user="",
|
||||
deployment_id=None,
|
||||
|
|
@ -89,6 +87,7 @@ def completion(
|
|||
api_key=None,
|
||||
api_version=None,
|
||||
force_timeout=600,
|
||||
num_beams=1,
|
||||
logger_fn=None,
|
||||
verbose=False,
|
||||
azure=False,
|
||||
|
|
@ -407,13 +406,7 @@ def completion(
|
|||
anthropic_key = (
|
||||
api_key or litellm.anthropic_key or os.environ.get("ANTHROPIC_API_KEY")
|
||||
)
|
||||
anthropic_client = AnthropicLLM(
|
||||
encoding=encoding,
|
||||
default_max_tokens_to_sample=litellm.max_tokens,
|
||||
api_key=anthropic_key,
|
||||
logging_obj=logging, # model call logging done inside the class as we make need to modify I/O to fit anthropic's requirements
|
||||
)
|
||||
model_response = anthropic_client.completion(
|
||||
model_response = anthropic.completion(
|
||||
model=model,
|
||||
messages=messages,
|
||||
model_response=model_response,
|
||||
|
|
@ -421,6 +414,9 @@ def completion(
|
|||
optional_params=optional_params,
|
||||
litellm_params=litellm_params,
|
||||
logger_fn=logger_fn,
|
||||
encoding=encoding, # for calculating input/output tokens
|
||||
api_key=anthropic_key,
|
||||
logging_obj=logging,
|
||||
)
|
||||
if "stream" in optional_params and optional_params["stream"] == True:
|
||||
# don't try to access stream object,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue