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https://github.com/BerriAI/litellm.git
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fix linting
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parent
a0cb56efd5
commit
1f3aeeb6d4
1 changed files with 13 additions and 11 deletions
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@ -1,4 +1,4 @@
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import os, json
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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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@ -29,9 +29,11 @@ class AnthropicLLM:
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def validate_environment(self, api_key): # 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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if self.api_key is None:
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raise ValueError(
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"Missing Anthropic API Key - A call is being made to anthropic but no key is set either in the environment variables or via params"
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"Missing Anthropic API Key -"
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+ " A call is being made to anthropic but no key is set either"
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+ " 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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@ -73,22 +75,22 @@ class AnthropicLLM:
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**optional_params,
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}
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## LOGGING
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# LOGGING
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self.logging_obj.pre_call(
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input=prompt,
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api_key=self.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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# 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"]
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)
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print(optional_params)
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if "stream" in optional_params and optional_params["stream"] == True:
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if "stream" in optional_params and optional_params["stream"] is True:
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print("IS STREAMING")
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return response.iter_lines()
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else:
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## LOGGING
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# LOGGING
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self.logging_obj.post_call(
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input=prompt,
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api_key=self.api_key,
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@ -96,7 +98,7 @@ class AnthropicLLM:
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additional_args={"complete_input_dict": data},
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)
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print_verbose(f"raw model_response: {response.text}")
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## RESPONSE OBJECT
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# RESPONSE OBJECT
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completion_response = response.json()
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if "error" in completion_response:
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raise AnthropicError(
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@ -106,11 +108,11 @@ class AnthropicLLM:
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else:
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model_response["choices"][0]["message"]["content"] = completion_response["completion"]
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## CALCULATING USAGE
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prompt_tokens = len(self.encoding.encode(prompt)) ##[TODO] use the anthropic tokenizer here
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# CALCULATING USAGE
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prompt_tokens = len(self.encoding.encode(prompt)) # [TODO] use the anthropic tokenizer here
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completion_tokens = len(
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self.encoding.encode(model_response["choices"][0]["message"]["content"])
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) ##[TODO] use the anthropic tokenizer here
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) # [TODO] use the anthropic tokenizer here
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model_response["created"] = time.time()
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model_response["model"] = model
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