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https://github.com/BerriAI/litellm.git
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fix aleph alpha client init
This commit is contained in:
ishaan-jaff
parent
5ae420317e
commit
b8b7d9bf44
3 changed files with 108 additions and 122 deletions
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@ -1,4 +1,5 @@
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import os, json
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import os
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import json
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from enum import Enum
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import requests
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import time
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@ -13,43 +14,30 @@ class AlephAlphaError(Exception):
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self.message
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) # Call the base class constructor with the parameters it needs
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class AlephAlphaLLM:
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def __init__(
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self, encoding, default_max_tokens_to_sample, logging_obj, api_key=None
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):
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self.encoding = encoding
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self.default_max_tokens_to_sample = default_max_tokens_to_sample
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self.completion_url = "https://api.aleph-alpha.com/complete"
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self.api_key = api_key
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self.logging_obj = logging_obj
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self.validate_environment(api_key=api_key)
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def validate_environment(
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self, api_key
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): # set up the environment required to run the model
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# set the api key
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if self.api_key == None:
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raise ValueError(
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"Missing Aleph Alpha API Key - A call is being made to Aleph Alpha but no key is set either in the environment variables or via params"
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)
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self.api_key = api_key
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self.headers = {
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def validate_environment(api_key):
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headers = {
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"accept": "application/json",
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"content-type": "application/json",
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"Authorization": "Bearer " + self.api_key,
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}
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if api_key:
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headers["Authorization"] = f"Bearer {api_key}"
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return headers
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def completion(
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self,
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model: str,
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messages: list,
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model_response: ModelResponse,
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print_verbose: Callable,
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encoding,
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api_key,
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logging_obj,
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optional_params=None,
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litellm_params=None,
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logger_fn=None,
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): # logic for parsing in - calling - parsing out model completion calls
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default_max_tokens_to_sample=None,
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):
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headers = validate_environment(api_key)
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completion_url = "https://api.aleph-alpha.com/complete"
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model = model
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prompt = ""
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if "control" in model: # follow the ###Instruction / ###Response format
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@ -77,27 +65,27 @@ class AlephAlphaLLM:
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data = {
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"model": model,
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"prompt": prompt,
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"maximum_tokens": optional_params["maximum_tokens"] if "maximum_tokens" in optional_params else self.default_max_tokens_to_sample, # required input
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"maximum_tokens": optional_params["maximum_tokens"] if "maximum_tokens" in optional_params else default_max_tokens_to_sample, # required input
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**optional_params,
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}
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## LOGGING
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self.logging_obj.pre_call(
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logging_obj.pre_call(
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input=prompt,
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api_key=self.api_key,
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api_key=api_key,
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additional_args={"complete_input_dict": data},
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)
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## COMPLETION CALL
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response = requests.post(
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self.completion_url, headers=self.headers, data=json.dumps(data), stream=optional_params["stream"] if "stream" in optional_params else False
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completion_url, headers=headers, data=json.dumps(data), stream=optional_params["stream"] if "stream" in optional_params else False
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)
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if "stream" in optional_params and optional_params["stream"] == True:
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return response.iter_lines()
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else:
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## LOGGING
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self.logging_obj.post_call(
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logging_obj.post_call(
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input=prompt,
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api_key=self.api_key,
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api_key=api_key,
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original_response=response.text,
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additional_args={"complete_input_dict": data},
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)
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@ -117,10 +105,10 @@ class AlephAlphaLLM:
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## CALCULATING USAGE - baseten charges on time, not tokens - have some mapping of cost here.
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prompt_tokens = len(
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self.encoding.encode(prompt)
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encoding.encode(prompt)
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)
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completion_tokens = len(
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self.encoding.encode(model_response["choices"][0]["message"]["content"])
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encoding.encode(model_response["choices"][0]["message"]["content"])
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)
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model_response["created"] = time.time()
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@ -132,7 +120,6 @@ class AlephAlphaLLM:
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}
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return model_response
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def embedding(
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self,
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): # logic for parsing in - calling - parsing out model embedding calls
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def embedding():
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# logic for parsing in - calling - parsing out model embedding calls
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pass
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@ -25,8 +25,8 @@ from .llms import ai21
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from .llms import sagemaker
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from .llms import bedrock
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from .llms import huggingface_restapi
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from .llms import aleph_alpha
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from .llms.baseten import BasetenLLM
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from .llms.aleph_alpha import AlephAlphaLLM
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import tiktoken
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from concurrent.futures import ThreadPoolExecutor
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@ -427,17 +427,10 @@ def completion(
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response = model_response
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elif model in litellm.aleph_alpha_models:
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aleph_alpha_key = (
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api_key or litellm.aleph_alpha_key or os.environ.get("ALEPH_ALPHA_API_KEY")
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api_key or litellm.aleph_alpha_key or get_secret("ALEPH_ALPHA_API_KEY") or get_secret("ALEPHALPHA_API_KEY")
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)
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aleph_alpha_client = AlephAlphaLLM(
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encoding=encoding,
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default_max_tokens_to_sample=litellm.max_tokens,
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api_key=aleph_alpha_key,
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logging_obj=logging # model call logging done inside the class as we make need to modify I/O to fit aleph alpha's requirements
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)
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model_response = aleph_alpha_client.completion(
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model_response = aleph_alpha.completion(
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model=model,
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messages=messages,
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model_response=model_response,
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@ -445,6 +438,10 @@ def completion(
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optional_params=optional_params,
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litellm_params=litellm_params,
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logger_fn=logger_fn,
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encoding=encoding,
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default_max_tokens_to_sample=litellm.max_tokens,
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api_key=aleph_alpha_key,
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logging_obj=logging # model call logging done inside the class as we make need to modify I/O to fit aleph alpha's requirements
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)
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if "stream" in optional_params and optional_params["stream"] == True:
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@ -64,6 +64,7 @@ def test_completion_claude():
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_aleph_alpha()
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# def test_completion_aleph_alpha_control_models():
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@ -75,6 +76,7 @@ def test_completion_claude():
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# print(response)
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# except Exception as e:
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# pytest.fail(f"Error occurred: {e}")
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# test_completion_aleph_alpha_control_models()
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def test_completion_with_litellm_call_id():
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try:
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@ -126,8 +128,8 @@ def test_completion_claude_stream():
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# if "loading" in str(e):
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# pass
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# pytest.fail(f"Error occurred: {e}")
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# # test_completion_hf_api()
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# test_completion_hf_api()
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# def test_completion_hf_deployed_api():
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# try:
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