diff --git a/docs/my-website/docs/observability/langsmith_integration.md b/docs/my-website/docs/observability/langsmith_integration.md
index c038abd821..79d047e33a 100644
--- a/docs/my-website/docs/observability/langsmith_integration.md
+++ b/docs/my-website/docs/observability/langsmith_integration.md
@@ -14,7 +14,7 @@ https://github.com/BerriAI/litellm
An all-in-one developer platform for every step of the application lifecycle
https://smith.langchain.com/
-
+
:::info
We want to learn how we can make the callbacks better! Meet the LiteLLM [founders](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version) or
diff --git a/docs/my-website/docs/proxy/logging.md b/docs/my-website/docs/proxy/logging.md
index 27f1789e0b..0d50166454 100644
--- a/docs/my-website/docs/proxy/logging.md
+++ b/docs/my-website/docs/proxy/logging.md
@@ -5,6 +5,7 @@ Log Proxy input, output, and exceptions using:
- Langfuse
- OpenTelemetry
- Custom Callbacks
+- Langsmith
- DataDog
- DynamoDB
- s3 Bucket
@@ -1086,6 +1087,50 @@ litellm_settings:
Start the LiteLLM Proxy and make a test request to verify the logs reached your callback API
+## Logging LLM IO to Langsmith
+
+1. Set `success_callback: ["langsmith"]` on litellm config.yaml
+
+If you're using a custom LangSmith instance, you can set the
+`LANGSMITH_BASE_URL` environment variable to point to your instance.
+
+```yaml
+litellm_settings:
+ success_callback: ["langsmith"]
+
+environment_variables:
+ LANGSMITH_API_KEY: "lsv2_pt_xxxxxxxx"
+ LANGSMITH_PROJECT: "litellm-proxy"
+
+ LANGSMITH_BASE_URL: "https://api.smith.langchain.com" # (Optional - only needed if you have a custom Langsmith instance)
+```
+
+
+2. Start Proxy
+
+```
+litellm --config /path/to/config.yaml
+```
+
+3. Test it!
+
+```bash
+curl --location 'http://0.0.0.0:4000/chat/completions' \
+--header 'Content-Type: application/json' \
+--data ' {
+ "model": "fake-openai-endpoint",
+ "messages": [
+ {
+ "role": "user",
+ "content": "Hello, Claude gm!"
+ }
+ ],
+ }
+'
+```
+Expect to see your log on Langfuse
+
+
## Logging LLM IO to Galileo
[BETA]
diff --git a/docs/my-website/img/langsmith_new.png b/docs/my-website/img/langsmith_new.png
new file mode 100644
index 0000000000..d5586bdbe5
Binary files /dev/null and b/docs/my-website/img/langsmith_new.png differ
diff --git a/litellm/__init__.py b/litellm/__init__.py
index 645a0bccdf..7dcc934a68 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -38,7 +38,7 @@ success_callback: List[Union[str, Callable]] = []
failure_callback: List[Union[str, Callable]] = []
service_callback: List[Union[str, Callable]] = []
_custom_logger_compatible_callbacks_literal = Literal[
- "lago", "openmeter", "logfire", "dynamic_rate_limiter"
+ "lago", "openmeter", "logfire", "dynamic_rate_limiter", "langsmith", "galileo"
]
callbacks: List[Union[Callable, _custom_logger_compatible_callbacks_literal]] = []
_langfuse_default_tags: Optional[
diff --git a/litellm/integrations/langsmith.py b/litellm/integrations/langsmith.py
index d8b01c3446..afe8be28f5 100644
--- a/litellm/integrations/langsmith.py
+++ b/litellm/integrations/langsmith.py
@@ -5,12 +5,17 @@ import os
import traceback
import types
from datetime import datetime
-from typing import Any, List, Optional
+from typing import Any, List, Optional, Union
import dotenv # type: ignore
import requests # type: ignore
from pydantic import BaseModel # type: ignore
+import litellm
+from litellm._logging import verbose_logger
+from litellm.integrations.custom_logger import CustomLogger
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
+
class LangsmithInputs(BaseModel):
model: Optional[str] = None
@@ -24,7 +29,7 @@ class LangsmithInputs(BaseModel):
custom_llm_provider: Optional[str] = None
input: Optional[List[Any]] = None
log_event_type: Optional[str] = None
- original_response: Optional[str] = None
+ original_response: Optional[Any] = None
response_cost: Optional[float] = None
# LiteLLM Virtual Key specific fields
@@ -43,7 +48,7 @@ def is_serializable(value):
return not isinstance(value, non_serializable_types)
-class LangsmithLogger:
+class LangsmithLogger(CustomLogger):
# Class variables or attributes
def __init__(self):
self.langsmith_api_key = os.getenv("LANGSMITH_API_KEY")
@@ -54,84 +59,116 @@ class LangsmithLogger:
self.langsmith_base_url = os.getenv(
"LANGSMITH_BASE_URL", "https://api.smith.langchain.com"
)
+ self.async_httpx_client = AsyncHTTPHandler()
- 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 = (
- kwargs.get("litellm_params", {}).get("metadata", {}) or {}
- ) # if metadata is None
+ def _prepare_log_data(self, kwargs, response_obj, start_time, end_time):
+ import datetime
+ from datetime import timezone
+
+ metadata = kwargs.get("litellm_params", {}).get("metadata", {}) or {}
- # set user_api_key, user_team_id, user_api_key_user_id
kwargs["user_api_key"] = metadata.get("user_api_key", None)
kwargs["user_api_key_user_id"] = metadata.get("user_api_key_user_id", None)
kwargs["user_api_key_team_alias"] = metadata.get(
"user_api_key_team_alias", None
)
- # 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 fallback to the environment variable LANGSMITH_PROJECT, then to the default project_name = litellm-completion, run_name = LLMRun
project_name = metadata.get("project_name", self.langsmith_project)
run_name = metadata.get("run_name", self.langsmith_default_run_name)
run_id = metadata.get("id", None)
- print_verbose(
+ verbose_logger.debug(
f"Langsmith Logging - project_name: {project_name}, run_name {run_name}"
)
- langsmith_base_url = os.getenv(
- "LANGSMITH_BASE_URL", "https://api.smith.langchain.com"
- )
try:
- print_verbose(
- f"Langsmith Logging - Enters logging function for model {kwargs}"
- )
- import datetime
- from datetime import timezone
+ 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()
- import requests
+ # filter out kwargs to not include any dicts, langsmith throws an erros when trying to log kwargs
+ logged_kwargs = LangsmithInputs(**kwargs)
+ kwargs = logged_kwargs.model_dump()
+ new_kwargs = {}
+ for key in kwargs:
+ value = kwargs[key]
+ if key == "start_time" or key == "end_time" or value is None:
+ pass
+ elif key == "original_response" and not isinstance(value, str):
+ new_kwargs[key] = str(value)
+ elif type(value) == datetime.datetime:
+ new_kwargs[key] = value.isoformat()
+ elif type(value) != dict and is_serializable(value=value):
+ new_kwargs[key] = value
+ elif not is_serializable(value=value):
+ continue
+
+ if isinstance(response_obj, BaseModel):
try:
- start_time = kwargs["start_time"].astimezone(timezone.utc).isoformat()
- end_time = kwargs["end_time"].astimezone(timezone.utc).isoformat()
+ response_obj = response_obj.model_dump()
except:
- start_time = datetime.datetime.utcnow().isoformat()
- end_time = datetime.datetime.utcnow().isoformat()
+ response_obj = response_obj.dict() # type: ignore
- # filter out kwargs to not include any dicts, langsmith throws an erros when trying to log kwargs
- logged_kwargs = LangsmithInputs(**kwargs)
- kwargs = logged_kwargs.model_dump()
+ data = {
+ "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,
+ "session_name": project_name,
+ "start_time": start_time,
+ "end_time": end_time,
+ }
- new_kwargs = {}
- for key in kwargs:
- value = kwargs[key]
- if key == "start_time" or key == "end_time" or value is None:
- pass
- elif type(value) == datetime.datetime:
- new_kwargs[key] = value.isoformat()
- elif type(value) != dict and is_serializable(value=value):
- new_kwargs[key] = value
+ if run_id:
+ data["id"] = run_id
- if isinstance(response_obj, BaseModel):
- try:
- response_obj = response_obj.model_dump()
- except:
- response_obj = response_obj.dict() # type: ignore
+ verbose_logger.debug("Langsmith Logging data on langsmith: %s", data)
- data = {
- "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,
- "session_name": project_name,
- "start_time": start_time,
- "end_time": end_time,
- "id": run_id,
- }
+ return data
+
+ async def async_log_success_event(self, kwargs, response_obj, start_time, end_time):
+ try:
+ verbose_logger.debug(
+ "Langsmith Async Layer Logging - kwargs: %s, response_obj: %s",
+ kwargs,
+ response_obj,
+ )
+ data = self._prepare_log_data(kwargs, response_obj, start_time, end_time)
+ url = f"{self.langsmith_base_url}/runs"
+ verbose_logger.debug(f"Langsmith Logging - About to send data to {url} ...")
+
+ headers = {"x-api-key": self.langsmith_api_key}
+ response = await self.async_httpx_client.post(
+ url=url, json=data, headers=headers
+ )
+
+ if response.status_code >= 300:
+ verbose_logger.error(
+ f"Langmsith Error: {response.status_code} - {response.text}"
+ )
+ else:
+ verbose_logger.debug(
+ "Run successfully created, response=%s", response.text
+ )
+ verbose_logger.debug(
+ f"Langsmith Layer Logging - final response object: {response_obj}. Response text from langsmith={response.text}"
+ )
+ except:
+ verbose_logger.error(f"Langsmith Layer Error - {traceback.format_exc()}")
+
+ def log_success_event(self, kwargs, response_obj, start_time, end_time):
+ try:
+ verbose_logger.debug(
+ "Langsmith Sync Layer Logging - kwargs: %s, response_obj: %s",
+ kwargs,
+ response_obj,
+ )
+ data = self._prepare_log_data(kwargs, response_obj, start_time, end_time)
+ url = f"{self.langsmith_base_url}/runs"
+ verbose_logger.debug(f"Langsmith Logging - About to send data to {url} ...")
- url = f"{langsmith_base_url}/runs"
- print_verbose(f"Langsmith Logging - About to send data to {url} ...")
response = requests.post(
url=url,
json=data,
@@ -139,16 +176,14 @@ class LangsmithLogger:
)
if response.status_code >= 300:
- print_verbose(f"Error: {response.status_code}")
+ verbose_logger.error(f"Error: {response.status_code} - {response.text}")
else:
- print_verbose("Run successfully created")
- print_verbose(
+ verbose_logger.debug("Run successfully created")
+ verbose_logger.debug(
f"Langsmith Layer Logging - final response object: {response_obj}. Response text from langsmith={response.text}"
)
- return
except:
- print_verbose(f"Langsmith Layer Error - {traceback.format_exc()}")
- pass
+ verbose_logger.error(f"Langsmith Layer Error - {traceback.format_exc()}")
def get_run_by_id(self, run_id):
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 9c8d02df98..a92e98e8b1 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -39,7 +39,6 @@ from litellm.utils import (
add_breadcrumb,
capture_exception,
customLogger,
- langsmithLogger,
liteDebuggerClient,
logfireLogger,
lunaryLogger,
@@ -89,7 +88,6 @@ alerts_channel = None
heliconeLogger = None
athinaLogger = None
promptLayerLogger = None
-langsmithLogger = None
logfireLogger = None
weightsBiasesLogger = None
customLogger = None
@@ -136,7 +134,7 @@ in_memory_trace_id_cache = ServiceTraceIDCache()
class Logging:
- global supabaseClient, liteDebuggerClient, promptLayerLogger, weightsBiasesLogger, langsmithLogger, logfireLogger, capture_exception, add_breadcrumb, lunaryLogger, logfireLogger, prometheusLogger, slack_app
+ global supabaseClient, liteDebuggerClient, promptLayerLogger, weightsBiasesLogger, logfireLogger, capture_exception, add_breadcrumb, lunaryLogger, logfireLogger, prometheusLogger, slack_app
custom_pricing: bool = False
stream_options = None
@@ -738,23 +736,6 @@ class Logging:
end_time=end_time,
print_verbose=print_verbose,
)
- if callback == "langsmith":
- print_verbose("reaches langsmith for logging!")
- if self.stream:
- if "complete_streaming_response" not in kwargs:
- continue
- else:
- print_verbose(
- "reaches langsmith for streaming logging!"
- )
- result = kwargs["complete_streaming_response"]
- langsmithLogger.log_event(
- kwargs=self.model_call_details,
- response_obj=result,
- start_time=start_time,
- end_time=end_time,
- print_verbose=print_verbose,
- )
if callback == "logfire":
global logfireLogger
verbose_logger.debug("reaches logfire for success logging!")
@@ -1829,7 +1810,7 @@ def set_callbacks(callback_list, function_id=None):
"""
Globally sets the callback client
"""
- global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, traceloopLogger, athinaLogger, heliconeLogger, aispendLogger, berrispendLogger, supabaseClient, liteDebuggerClient, lunaryLogger, promptLayerLogger, langFuseLogger, customLogger, weightsBiasesLogger, langsmithLogger, logfireLogger, dynamoLogger, s3Logger, dataDogLogger, prometheusLogger, greenscaleLogger, openMeterLogger
+ global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, traceloopLogger, athinaLogger, heliconeLogger, aispendLogger, berrispendLogger, supabaseClient, liteDebuggerClient, lunaryLogger, promptLayerLogger, langFuseLogger, customLogger, weightsBiasesLogger, logfireLogger, dynamoLogger, s3Logger, dataDogLogger, prometheusLogger, greenscaleLogger, openMeterLogger
try:
for callback in callback_list:
@@ -1910,8 +1891,6 @@ def set_callbacks(callback_list, function_id=None):
s3Logger = S3Logger()
elif callback == "wandb":
weightsBiasesLogger = WeightsBiasesLogger()
- elif callback == "langsmith":
- langsmithLogger = LangsmithLogger()
elif callback == "logfire":
logfireLogger = LogfireLogger()
elif callback == "aispend":
@@ -1964,6 +1943,15 @@ def _init_custom_logger_compatible_class(
_in_memory_loggers.append(_openmeter_logger)
return _openmeter_logger # type: ignore
+ elif logging_integration == "langsmith":
+ for callback in _in_memory_loggers:
+ if isinstance(callback, LangsmithLogger):
+ return callback # type: ignore
+
+ _langsmith_logger = LangsmithLogger()
+ _in_memory_loggers.append(_langsmith_logger)
+ return _langsmith_logger # type: ignore
+
elif logging_integration == "galileo":
for callback in _in_memory_loggers:
if isinstance(callback, GalileoObserve):
@@ -2032,6 +2020,10 @@ def get_custom_logger_compatible_class(
for callback in _in_memory_loggers:
if isinstance(callback, GalileoObserve):
return callback
+ elif logging_integration == "langsmith":
+ for callback in _in_memory_loggers:
+ if isinstance(callback, LangsmithLogger):
+ return callback
elif logging_integration == "logfire":
if "LOGFIRE_TOKEN" not in os.environ:
raise ValueError("LOGFIRE_TOKEN not found in environment variables")
diff --git a/litellm/tests/test_langsmith.py b/litellm/tests/test_langsmith.py
index 8af0c9cbb5..f69c964a13 100644
--- a/litellm/tests/test_langsmith.py
+++ b/litellm/tests/test_langsmith.py
@@ -4,24 +4,33 @@ import sys
sys.path.insert(0, os.path.abspath("../.."))
+import asyncio
+import logging
+import uuid
+
+import pytest
+
import litellm
from litellm import completion
+from litellm._logging import verbose_logger
from litellm.integrations.langsmith import LangsmithLogger
+verbose_logger.setLevel(logging.DEBUG)
+
litellm.set_verbose = True
import time
test_langsmith_logger = LangsmithLogger()
-def test_langsmith_logging():
+@pytest.mark.asyncio()
+async def test_langsmith_logging():
try:
- import uuid
run_id = str(uuid.uuid4())
litellm.set_verbose = True
- litellm.success_callback = ["langsmith"]
- response = completion(
+ litellm.callbacks = ["langsmith"]
+ response = await litellm.acompletion(
model="claude-instant-1.2",
messages=[{"role": "user", "content": "what llm are u"}],
max_tokens=10,
@@ -40,7 +49,7 @@ def test_langsmith_logging():
},
)
print(response)
- time.sleep(3)
+ await asyncio.sleep(3)
print("run_id", run_id)
logged_run_on_langsmith = test_langsmith_logger.get_run_by_id(run_id=run_id)
@@ -50,13 +59,15 @@ def test_langsmith_logging():
print("fields in logged_run_on_langsmith", logged_run_on_langsmith.keys())
input_fields_on_langsmith = logged_run_on_langsmith.get("inputs")
- extra_fields_on_langsmith = logged_run_on_langsmith.get("extra")
+ extra_fields_on_langsmith = logged_run_on_langsmith.get("extra").get(
+ "invocation_params"
+ )
print("\nLogged INPUT ON LANGSMITH", input_fields_on_langsmith)
print("\nextra fields on langsmith", extra_fields_on_langsmith)
- assert input_fields_on_langsmith is not None
+ assert isinstance(input_fields_on_langsmith, dict)
assert "api_key" not in input_fields_on_langsmith
assert "api_key" not in extra_fields_on_langsmith
@@ -67,6 +78,7 @@ def test_langsmith_logging():
except Exception as e:
print(e)
+ pytest.fail(f"Error occurred: {e}")
# test_langsmith_logging()
@@ -75,6 +87,7 @@ def test_langsmith_logging():
def test_langsmith_logging_with_metadata():
try:
litellm.success_callback = ["langsmith"]
+ litellm.set_verbose = True
response = completion(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "what llm are u"}],
@@ -83,28 +96,66 @@ def test_langsmith_logging_with_metadata():
)
print(response)
time.sleep(3)
+
except Exception as e:
+ pytest.fail(f"Error occurred: {e}")
print(e)
-# test_langsmith_logging_with_metadata()
-
-
-def test_langsmith_logging_with_streaming_and_metadata():
+@pytest.mark.parametrize("sync_mode", [False, True])
+@pytest.mark.asyncio
+async def test_langsmith_logging_with_streaming_and_metadata(sync_mode):
try:
litellm.success_callback = ["langsmith"]
- response = completion(
- model="gpt-3.5-turbo",
- messages=[{"role": "user", "content": "what llm are u"}],
- max_tokens=10,
- temperature=0.2,
- stream=True,
+ litellm.set_verbose = True
+ run_id = str(uuid.uuid4())
+
+ messages = [{"role": "user", "content": "what llm are u"}]
+ if sync_mode is True:
+ response = completion(
+ model="gpt-3.5-turbo",
+ messages=messages,
+ max_tokens=10,
+ temperature=0.2,
+ stream=True,
+ metadata={"id": run_id},
+ )
+ for chunk in response:
+ continue
+ time.sleep(3)
+ else:
+ response = await litellm.acompletion(
+ model="gpt-3.5-turbo",
+ messages=messages,
+ max_tokens=10,
+ temperature=0.2,
+ mock_response="This is a mock request",
+ stream=True,
+ metadata={"id": run_id},
+ )
+ async for chunk in response:
+ continue
+ await asyncio.sleep(3)
+
+ print("run_id", run_id)
+ logged_run_on_langsmith = test_langsmith_logger.get_run_by_id(run_id=run_id)
+
+ print("logged_run_on_langsmith", logged_run_on_langsmith)
+
+ print("fields in logged_run_on_langsmith", logged_run_on_langsmith.keys())
+
+ input_fields_on_langsmith = logged_run_on_langsmith.get("inputs")
+
+ extra_fields_on_langsmith = logged_run_on_langsmith.get("extra").get(
+ "invocation_params"
)
- for chunk in response:
- continue
- time.sleep(3)
+
+ assert logged_run_on_langsmith.get("run_type") == "llm"
+ print("\nLogged INPUT ON LANGSMITH", input_fields_on_langsmith)
+
+ print("\nextra fields on langsmith", extra_fields_on_langsmith)
+
+ assert isinstance(input_fields_on_langsmith, dict)
except Exception as e:
+ pytest.fail(f"Error occurred: {e}")
print(e)
-
-
-# test_langsmith_logging_with_streaming_and_metadata()
diff --git a/litellm/utils.py b/litellm/utils.py
index b9c3f983ca..a02a276b77 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -417,6 +417,21 @@ def function_setup(
# we only support async dynamo db logging for acompletion/aembedding since that's used on proxy
litellm._async_success_callback.append(callback)
removed_async_items.append(index)
+ elif callback == "langsmith":
+ callback_class = litellm.litellm_core_utils.litellm_logging._init_custom_logger_compatible_class( # type: ignore
+ callback, internal_usage_cache=None, llm_router=None
+ )
+
+ # don't double add a callback
+ if not any(
+ isinstance(cb, type(callback_class)) for cb in litellm.callbacks
+ ):
+ litellm.callbacks.append(callback_class) # type: ignore
+ litellm.input_callback.append(callback_class) # type: ignore
+ litellm.success_callback.append(callback_class) # type: ignore
+ litellm.failure_callback.append(callback_class) # type: ignore
+ litellm._async_success_callback.append(callback_class) # type: ignore
+ litellm._async_failure_callback.append(callback_class) # type: ignore
# Pop the async items from success_callback in reverse order to avoid index issues
for index in reversed(removed_async_items):