mirror of
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Merge pull request #1491 from samyxdev/main
Adding PromptLayer support of tags
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@@ -2,12 +2,11 @@
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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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from pydantic import BaseModel
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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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@@ -25,16 +24,30 @@ class PromptLayerLogger:
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for optional_param in kwargs["optional_params"]:
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new_kwargs[optional_param] = kwargs["optional_params"][optional_param]
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# Extract PromptLayer tags from metadata, if such exists
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tags = []
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metadata = {}
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if "metadata" in kwargs["litellm_params"]:
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if "pl_tags" in kwargs["litellm_params"]["metadata"]:
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tags = kwargs["litellm_params"]["metadata"]["pl_tags"]
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# Remove "pl_tags" from metadata
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metadata = {k:v for k, v in kwargs["litellm_params"]["metadata"].items() if k != "pl_tags"}
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print_verbose(
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f"Prompt Layer Logging - Enters logging function for model kwargs: {new_kwargs}\n, response: {response_obj}"
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)
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# python-openai >= 1.0.0 returns Pydantic objects instead of jsons
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if isinstance(response_obj, BaseModel):
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response_obj = response_obj.model_dump()
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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": new_kwargs,
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"tags": ["hello", "world"],
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"tags": tags,
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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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@@ -45,22 +58,23 @@ class PromptLayerLogger:
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# "prompt_version":1,
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},
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)
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response_json = request_response.json()
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if not request_response.json().get("success", False):
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raise Exception("Promptlayer did not successfully log the response!")
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print_verbose(
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f"Prompt Layer Logging: success - final response object: {request_response.text}"
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)
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response_json = request_response.json()
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if "success" not in request_response.json():
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raise Exception("Promptlayer did not successfully log the response!")
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if "request_id" in response_json:
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print(kwargs["litellm_params"]["metadata"])
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if kwargs["litellm_params"]["metadata"] is not None:
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if metadata:
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response = requests.post(
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"https://api.promptlayer.com/rest/track-metadata",
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json={
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"request_id": response_json["request_id"],
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"api_key": self.key,
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"metadata": kwargs["litellm_params"]["metadata"],
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"metadata": metadata,
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},
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)
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print_verbose(
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@@ -7,11 +7,12 @@ sys.path.insert(0, os.path.abspath("../.."))
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from litellm import completion
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import litellm
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import pytest
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litellm.success_callback = ["promptlayer"]
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litellm.set_verbose = True
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import time
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# def test_promptlayer_logging():
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# try:
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# # Redirect stdout
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@@ -58,15 +59,41 @@ def test_promptlayer_logging_with_metadata():
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sys.stdout = old_stdout
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output = new_stdout.getvalue().strip()
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print(output)
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if "LiteLLM: Prompt Layer Logging: success" not in output:
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raise Exception("Required log message not found!")
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assert "Prompt Layer Logging: success" in output
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except Exception as e:
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print(e)
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pytest.fail(f"Error occurred: {e}")
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def test_promptlayer_logging_with_metadata_tags():
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try:
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# Redirect stdout
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old_stdout = sys.stdout
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sys.stdout = new_stdout = io.StringIO()
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response = completion(
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model="gpt-3.5-turbo",
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messages=[{"role": "user", "content": "Hi 👋 - i'm ai21"}],
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temperature=0.2,
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max_tokens=20,
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metadata={"model": "ai21", "pl_tags": ["env:dev"]},
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mock_response="this is a mock response"
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)
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# Restore stdout
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time.sleep(1)
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sys.stdout = old_stdout
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output = new_stdout.getvalue().strip()
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print(output)
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assert "Prompt Layer Logging: success" in output
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except Exception as e:
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pytest.fail(f"Error occurred: {e}")
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test_promptlayer_logging_with_metadata()
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test_promptlayer_logging_with_metadata_tags()
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# def test_chat_openai():
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# try:
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