mirror of
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48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
#### What this does ####
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# On success, logs events to Promptlayer
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import dotenv, os
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import requests
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import requests
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dotenv.load_dotenv() # Loading env variables using dotenv
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import traceback
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class PromptLayerLogger:
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# Class variables or attributes
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def __init__(self):
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# Instance variables
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self.key = os.getenv("PROMPTLAYER_API_KEY")
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def log_event(self, kwargs, response_obj, start_time, end_time, print_verbose):
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# Method definition
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try:
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if 'litellm_logging_obj' in kwargs:
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kwargs.pop('litellm_logging_obj')
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print_verbose(
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f"Prompt Layer Logging - Enters logging function for model kwargs: {kwargs}\n, response: {response_obj}"
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)
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request_response = requests.post(
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"https://api.promptlayer.com/rest/track-request",
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json={
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"function_name": "openai.ChatCompletion.create",
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"kwargs": kwargs,
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"tags": ["hello", "world"],
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"request_response": dict(response_obj),
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"request_start_time": int(start_time.timestamp()),
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"request_end_time": int(end_time.timestamp()),
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"api_key": self.key,
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# Optional params for PromptLayer
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# "prompt_id": "<PROMPT ID>",
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# "prompt_input_variables": "<Dictionary of variables for prompt>",
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# "prompt_version":1,
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},
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)
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print_verbose(
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f"Prompt Layer Logging: success - final response object: {request_response}"
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)
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except:
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print_verbose(f"error: Prompt Layer Error - {traceback.format_exc()}")
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pass
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