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#### What this does ####
# On success, logs events to Langsmith
import dotenv, os
import requests
import requests
from datetime import datetime
dotenv.load_dotenv() # Loading env variables using dotenv
import traceback
class LangsmithLogger:
# Class variables or attributes
def __init__(self):
self.langsmith_api_key = os.getenv("LANGSMITH_API_KEY")
def log_event(self, kwargs, response_obj, start_time, end_time, print_verbose):
# Method definition
# inspired by Langsmith http api here: https://github.com/langchain-ai/langsmith-cookbook/blob/main/tracing-examples/rest/rest.ipynb
metadata = {}
if "litellm_params" in kwargs:
metadata = kwargs["litellm_params"].get("metadata", {})
# set project name and run_name for langsmith logging
# users can pass project_name and run name to litellm.completion()
# Example: litellm.completion(model, messages, metadata={"project_name": "my-litellm-project", "run_name": "my-langsmith-run"})
# if not set litellm will use default project_name = litellm-completion, run_name = LLMRun
project_name = metadata.get("project_name", "litellm-completion")
run_name = metadata.get("run_name", "LLMRun")
print_verbose(
f"Langsmith Logging - project_name: {project_name}, run_name {run_name}"
)
try:
print_verbose(
f"Langsmith Logging - Enters logging function for model {kwargs}"
)
import requests
import datetime
from datetime import timezone
try:
start_time = kwargs["start_time"].astimezone(timezone.utc).isoformat()
end_time = kwargs["end_time"].astimezone(timezone.utc).isoformat()
except:
start_time = datetime.datetime.utcnow().isoformat()
end_time = datetime.datetime.utcnow().isoformat()
# filter out kwargs to not include any dicts, langsmith throws an erros when trying to log kwargs
new_kwargs = {}
for key in kwargs:
value = kwargs[key]
if key == "start_time" or key == "end_time":
pass
elif type(value) != dict:
new_kwargs[key] = value
requests.post(
"https://api.smith.langchain.com/runs",
json={
"name": run_name,
"run_type": "llm", # this should always be llm, since litellm always logs llm calls. Langsmith allow us to log "chain"
"inputs": {**new_kwargs},
"outputs": response_obj.json(),
"session_name": project_name,
"start_time": start_time,
"end_time": end_time,
},
headers={"x-api-key": self.langsmith_api_key},
)
print_verbose(
f"Langsmith Layer Logging - final response object: {response_obj}"
)
except:
# traceback.print_exc()
print_verbose(f"Langsmith Layer Error - {traceback.format_exc()}")
pass
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