Merge branch 'main' into litellm_openmeter_integration

This commit is contained in:
Krish Dholakia 2024-05-01 21:19:29 -07:00 committed by GitHub
commit fffbb73465
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GPG key ID: B5690EEEBB952194
31 changed files with 227 additions and 98 deletions

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@ -40,7 +40,7 @@ jobs:
pip install "aioboto3==12.3.0" pip install "aioboto3==12.3.0"
pip install langchain pip install langchain
pip install lunary==0.2.5 pip install lunary==0.2.5
pip install "langfuse==2.7.3" pip install "langfuse==2.27.1"
pip install numpydoc pip install numpydoc
pip install traceloop-sdk==0.0.69 pip install traceloop-sdk==0.0.69
pip install openai pip install openai

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@ -7,7 +7,7 @@ repos:
rev: 7.0.0 # The version of flake8 to use rev: 7.0.0 # The version of flake8 to use
hooks: hooks:
- id: flake8 - id: flake8
exclude: ^litellm/tests/|^litellm/proxy/proxy_cli.py|^litellm/integrations/|^litellm/proxy/tests/ exclude: ^litellm/tests/|^litellm/proxy/proxy_cli.py|^litellm/proxy/tests/
additional_dependencies: [flake8-print] additional_dependencies: [flake8-print]
files: litellm/.*\.py files: litellm/.*\.py
- repo: local - repo: local

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@ -17,6 +17,7 @@ class LangFuseLogger:
): ):
try: try:
from langfuse import Langfuse from langfuse import Langfuse
import langfuse
except Exception as e: except Exception as e:
raise Exception( raise Exception(
f"\033[91mLangfuse not installed, try running 'pip install langfuse' to fix this error: {e}\n{traceback.format_exc()}\033[0m" f"\033[91mLangfuse not installed, try running 'pip install langfuse' to fix this error: {e}\n{traceback.format_exc()}\033[0m"
@ -27,14 +28,20 @@ class LangFuseLogger:
self.langfuse_host = os.getenv("LANGFUSE_HOST", "https://cloud.langfuse.com") self.langfuse_host = os.getenv("LANGFUSE_HOST", "https://cloud.langfuse.com")
self.langfuse_release = os.getenv("LANGFUSE_RELEASE") self.langfuse_release = os.getenv("LANGFUSE_RELEASE")
self.langfuse_debug = os.getenv("LANGFUSE_DEBUG") self.langfuse_debug = os.getenv("LANGFUSE_DEBUG")
self.Langfuse = Langfuse(
public_key=self.public_key, parameters = {
secret_key=self.secret_key, "public_key": self.public_key,
host=self.langfuse_host, "secret_key": self.secret_key,
release=self.langfuse_release, "host": self.langfuse_host,
debug=self.langfuse_debug, "release": self.langfuse_release,
flush_interval=flush_interval, # flush interval in seconds "debug": self.langfuse_debug,
) "flush_interval": flush_interval, # flush interval in seconds
}
if Version(langfuse.version.__version__) >= Version("2.6.0"):
parameters["sdk_integration"] = "litellm"
self.Langfuse = Langfuse(**parameters)
# set the current langfuse project id in the environ # set the current langfuse project id in the environ
# this is used by Alerting to link to the correct project # this is used by Alerting to link to the correct project
@ -369,8 +376,6 @@ class LangFuseLogger:
"headers": clean_headers, "headers": clean_headers,
} }
print_verbose(f"trace_params: {trace_params}")
trace = self.Langfuse.trace(**trace_params) trace = self.Langfuse.trace(**trace_params)
generation_id = None generation_id = None
@ -420,10 +425,8 @@ class LangFuseLogger:
"completion_start_time", None "completion_start_time", None
) )
print_verbose(f"generation_params: {generation_params}")
generation_client = trace.generation(**generation_params) generation_client = trace.generation(**generation_params)
return generation_client.trace_id, generation_id return generation_client.trace_id, generation_id
except Exception as e: except Exception as e:
verbose_logger.debug(f"Langfuse Layer Error - {traceback.format_exc()}") verbose_logger.debug(f"Langfuse Layer Error - {traceback.format_exc()}")

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View file

@ -7550,7 +7550,7 @@ async def model_metrics(
"LiteLLM_SpendLogs" "LiteLLM_SpendLogs"
WHERE WHERE
"startTime" >= NOW() - INTERVAL '30 days' "startTime" >= NOW() - INTERVAL '30 days'
AND "model" = $1 AND "model" = $1 AND "cache_hit" != 'True'
GROUP BY GROUP BY
api_base, api_base,
model, model,
@ -7599,7 +7599,7 @@ async def model_metrics(
for day in _daily_entries: for day in _daily_entries:
entry = {"date": str(day)} entry = {"date": str(day)}
for model_key, latency in _daily_entries[day].items(): for model_key, latency in _daily_entries[day].items():
entry[model_key] = round(latency, 8) entry[model_key] = latency
response.append(entry) response.append(entry)
return { return {
@ -7608,6 +7608,67 @@ async def model_metrics(
} }
@router.get(
"/model/metrics/slow_responses",
description="View number of hanging requests per model_group",
tags=["model management"],
include_in_schema=False,
dependencies=[Depends(user_api_key_auth)],
)
async def model_metrics_slow_responses(
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
_selected_model_group: Optional[str] = "gpt-4-32k",
startTime: Optional[datetime] = None,
endTime: Optional[datetime] = None,
):
global prisma_client, llm_router, proxy_logging_obj
if prisma_client is None:
raise ProxyException(
message="Prisma Client is not initialized",
type="internal_error",
param="None",
code=status.HTTP_500_INTERNAL_SERVER_ERROR,
)
startTime = startTime or datetime.now() - timedelta(days=30)
endTime = endTime or datetime.now()
alerting_threshold = (
proxy_logging_obj.slack_alerting_instance.alerting_threshold or 300
)
alerting_threshold = int(alerting_threshold)
sql_query = """
SELECT
api_base,
COUNT(*) AS total_count,
SUM(CASE
WHEN ("endTime" - "startTime") >= (INTERVAL '1 SECOND' * CAST($1 AS INTEGER)) THEN 1
ELSE 0
END) AS slow_count
FROM
"LiteLLM_SpendLogs"
WHERE
"model" = $2
AND "cache_hit" != 'True'
GROUP BY
api_base
ORDER BY
slow_count DESC;
"""
db_response = await prisma_client.db.query_raw(
sql_query, alerting_threshold, _selected_model_group
)
if db_response is not None:
for row in db_response:
_api_base = row.get("api_base") or ""
if "/openai/" in _api_base:
_api_base = _api_base.split("/openai/")[0]
row["api_base"] = _api_base
return db_response
@router.get( @router.get(
"/model/metrics/exceptions", "/model/metrics/exceptions",
description="View number of failed requests per model on config.yaml", description="View number of failed requests per model on config.yaml",

View file

@ -57,7 +57,7 @@ def test_completion_custom_provider_model_name():
messages=messages, messages=messages,
logger_fn=logger_fn, logger_fn=logger_fn,
) )
# Add any assertions here to, check the response # Add any assertions here to,check the response
print(response) print(response)
print(response["choices"][0]["finish_reason"]) print(response["choices"][0]["finish_reason"])
except litellm.Timeout as e: except litellm.Timeout as e:

View file

@ -1,6 +1,6 @@
[tool.poetry] [tool.poetry]
name = "litellm" name = "litellm"
version = "1.35.34" version = "1.35.35"
description = "Library to easily interface with LLM API providers" description = "Library to easily interface with LLM API providers"
authors = ["BerriAI"] authors = ["BerriAI"]
license = "MIT" license = "MIT"
@ -80,7 +80,7 @@ requires = ["poetry-core", "wheel"]
build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"
[tool.commitizen] [tool.commitizen]
version = "1.35.34" version = "1.35.35"
version_files = [ version_files = [
"pyproject.toml:^version" "pyproject.toml:^version"
] ]

View file

@ -17,7 +17,7 @@ google-cloud-aiplatform==1.47.0 # for vertex ai calls
anthropic[vertex]==0.21.3 anthropic[vertex]==0.21.3
google-generativeai==0.5.0 # for vertex ai calls google-generativeai==0.5.0 # for vertex ai calls
async_generator==1.10.0 # for async ollama calls async_generator==1.10.0 # for async ollama calls
langfuse==2.7.3 # for langfuse self-hosted logging langfuse==2.27.1 # for langfuse self-hosted logging
datadog-api-client==2.23.0 # for datadog logging datadog-api-client==2.23.0 # for datadog logging
prometheus_client==0.20.0 # for /metrics endpoint on proxy prometheus_client==0.20.0 # for /metrics endpoint on proxy
orjson==3.9.15 # fast /embedding responses orjson==3.9.15 # fast /embedding responses

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1:null 1:null

View file

@ -18,7 +18,7 @@ import {
} from "@tremor/react"; } from "@tremor/react";
import { TabPanel, TabPanels, TabGroup, TabList, Tab, TextInput, Icon } from "@tremor/react"; import { TabPanel, TabPanels, TabGroup, TabList, Tab, TextInput, Icon } from "@tremor/react";
import { Select, SelectItem, MultiSelect, MultiSelectItem } from "@tremor/react"; import { Select, SelectItem, MultiSelect, MultiSelectItem } from "@tremor/react";
import { modelInfoCall, userGetRequesedtModelsCall, modelCreateCall, Model, modelCostMap, modelDeleteCall, healthCheckCall, modelUpdateCall, modelMetricsCall, modelExceptionsCall } from "./networking"; import { modelInfoCall, userGetRequesedtModelsCall, modelCreateCall, Model, modelCostMap, modelDeleteCall, healthCheckCall, modelUpdateCall, modelMetricsCall, modelExceptionsCall, modelMetricsSlowResponsesCall } from "./networking";
import { BarChart, AreaChart } from "@tremor/react"; import { BarChart, AreaChart } from "@tremor/react";
import { import {
Button as Button2, Button as Button2,
@ -205,6 +205,7 @@ const ModelDashboard: React.FC<ModelDashboardProps> = ({
const [modelExceptions, setModelExceptions] = useState<any[]>([]); const [modelExceptions, setModelExceptions] = useState<any[]>([]);
const [allExceptions, setAllExceptions] = useState<any[]>([]); const [allExceptions, setAllExceptions] = useState<any[]>([]);
const [failureTableData, setFailureTableData] = useState<any[]>([]); const [failureTableData, setFailureTableData] = useState<any[]>([]);
const [slowResponsesData, setSlowResponsesData] = useState<any[]>([]);
const EditModelModal: React.FC<EditModelModalProps> = ({ visible, onCancel, model, onSubmit }) => { const EditModelModal: React.FC<EditModelModalProps> = ({ visible, onCancel, model, onSubmit }) => {
const [form] = Form.useForm(); const [form] = Form.useForm();
@ -479,39 +480,51 @@ const handleEditSubmit = async (formValues: Record<string, any>) => {
setAllExceptions(modelExceptionsResponse.exception_types); setAllExceptions(modelExceptionsResponse.exception_types);
let modelMetricsData = modelMetricsResponse.data; const slowResponses = await modelMetricsSlowResponsesCall(
let successdeploymentToSuccess: Record<string, number> = {}; accessToken,
for (let i = 0; i < modelMetricsData.length; i++) { userID,
let element = modelMetricsData[i]; userRole,
let _model_name = element.model; null
let _num_requests = element.num_requests; )
successdeploymentToSuccess[_model_name] = _num_requests
} console.log("slowResponses:", slowResponses)
console.log("successdeploymentToSuccess:", successdeploymentToSuccess)
setSlowResponsesData(slowResponses);
// let modelMetricsData = modelMetricsResponse.data;
// let successdeploymentToSuccess: Record<string, number> = {};
// for (let i = 0; i < modelMetricsData.length; i++) {
// let element = modelMetricsData[i];
// let _model_name = element.model;
// let _num_requests = element.num_requests;
// successdeploymentToSuccess[_model_name] = _num_requests
// }
// console.log("successdeploymentToSuccess:", successdeploymentToSuccess)
let failureTableData = []; // let failureTableData = [];
let _failureData = modelExceptionsResponse.data; // let _failureData = modelExceptionsResponse.data;
for (let i = 0; i < _failureData.length; i++) { // for (let i = 0; i < _failureData.length; i++) {
const model = _failureData[i]; // const model = _failureData[i];
let _model_name = model.model; // let _model_name = model.model;
let total_exceptions = model.total_exceptions; // let total_exceptions = model.total_exceptions;
let total_Requests = successdeploymentToSuccess[_model_name]; // let total_Requests = successdeploymentToSuccess[_model_name];
if (total_Requests == null) { // if (total_Requests == null) {
total_Requests = 0 // total_Requests = 0
} // }
let _data = { // let _data = {
model: _model_name, // model: _model_name,
total_exceptions: total_exceptions, // total_exceptions: total_exceptions,
total_Requests: total_Requests, // total_Requests: total_Requests,
failure_rate: total_Requests / total_exceptions // failure_rate: total_Requests / total_exceptions
} // }
failureTableData.push(_data); // failureTableData.push(_data);
// sort failureTableData by failure_rate // // sort failureTableData by failure_rate
failureTableData.sort((a, b) => b.failure_rate - a.failure_rate); // failureTableData.sort((a, b) => b.failure_rate - a.failure_rate);
setFailureTableData(failureTableData); // setFailureTableData(failureTableData);
console.log("failureTableData:", failureTableData); // console.log("failureTableData:", failureTableData);
} // }
} catch (error) { } catch (error) {
console.error("There was an error fetching the model data", error); console.error("There was an error fetching the model data", error);
@ -691,6 +704,18 @@ const handleEditSubmit = async (formValues: Record<string, any>) => {
setModelExceptions(modelExceptionsResponse.data); setModelExceptions(modelExceptionsResponse.data);
setAllExceptions(modelExceptionsResponse.exception_types); setAllExceptions(modelExceptionsResponse.exception_types);
const slowResponses = await modelMetricsSlowResponsesCall(
accessToken,
userID,
userRole,
modelGroup
)
console.log("slowResponses:", slowResponses)
setSlowResponsesData(slowResponses);
} catch (error) { } catch (error) {
console.error("Failed to fetch model metrics", error); console.error("Failed to fetch model metrics", error);
} }
@ -720,17 +745,20 @@ const handleEditSubmit = async (formValues: Record<string, any>) => {
return ( return (
<div className="w-150 rounded-tremor-default border border-tremor-border bg-tremor-background p-2 text-tremor-default shadow-tremor-dropdown"> <div className="w-150 rounded-tremor-default border border-tremor-border bg-tremor-background p-2 text-tremor-default shadow-tremor-dropdown">
{date && <p className="text-tremor-content-emphasis mb-2">Date: {date}</p>} {date && <p className="text-tremor-content-emphasis mb-2">Date: {date}</p>}
{sortedPayload.map((category: any, idx: number) => ( {sortedPayload.map((category: any, idx: number) => {
<div key={idx} className="flex justify-between"> const roundedValue = parseFloat(category.value.toFixed(5));
<div className="flex items-center space-x-2"> const displayValue =
<div className={`w-2 h-2 mt-1 rounded-full bg-${category.color}-500`} /> roundedValue === 0 && category.value > 0 ? "<0.00001" : roundedValue.toFixed(5);
<p className="text-tremor-content">{category.dataKey}</p> return (
<div key={idx} className="flex justify-between">
<div className="flex items-center space-x-2">
<div className={`w-2 h-2 mt-1 rounded-full bg-${category.color}-500`} />
<p className="text-tremor-content">{category.dataKey}</p>
</div>
<p className="font-medium text-tremor-content-emphasis text-righ ml-2">{displayValue}</p>
</div> </div>
<p className="font-medium text-tremor-content-emphasis text-righ ml-2"> );
{category.value.toFixed(5)} })}
</p>
</div>
))}
</div> </div>
); );
}; };
@ -1107,7 +1135,7 @@ const handleEditSubmit = async (formValues: Record<string, any>) => {
<Grid numItems={2}> <Grid numItems={2}>
<Col> <Col>
<Card className="mr-2"> <Card className="mr-2 max-h-[400px] min-h-[400px]">
<Title>Avg Latency per Token</Title><p className="text-gray-500 italic"> (seconds/token)</p> <Title>Avg Latency per Token</Title><p className="text-gray-500 italic"> (seconds/token)</p>
<Text className="text-gray-500 italic mt-1 mb-1">average Latency for successfull requests divided by the total tokens</Text> <Text className="text-gray-500 italic mt-1 mb-1">average Latency for successfull requests divided by the total tokens</Text>
{ modelMetrics && modelMetricsCategories && ( { modelMetrics && modelMetricsCategories && (
@ -1123,29 +1151,26 @@ const handleEditSubmit = async (formValues: Record<string, any>) => {
/> />
)} )}
</Card> </Card>
</Col> </Col>
<Col> <Col>
<Card className="ml-2"> <Card className="ml-2 max-h-[400px] min-h-[400px] overflow-y-auto">
<Table> <Table>
<TableHead> <TableHead>
<TableRow> <TableRow>
<TableHeaderCell>Model</TableHeaderCell> <TableHeaderCell>Deployment</TableHeaderCell>
<TableHeaderCell>Success Requests</TableHeaderCell> <TableHeaderCell>Success Responses</TableHeaderCell>
<TableHeaderCell>Error Requests</TableHeaderCell> <TableHeaderCell>Slow Responses <p>Success Responses taking 600+s</p></TableHeaderCell>
<TableHeaderCell>Failure %</TableHeaderCell>
</TableRow> </TableRow>
</TableHead> </TableHead>
<TableBody> <TableBody>
{failureTableData.map((metric, idx) => ( {slowResponsesData.map((metric, idx) => (
<TableRow key={idx}> <TableRow key={idx}>
<TableCell>{metric.model}</TableCell> <TableCell>{metric.api_base}</TableCell>
<TableCell>{metric.total_Requests}</TableCell> <TableCell>{metric.total_count}</TableCell>
<TableCell>{metric.total_exceptions}</TableCell> <TableCell>{metric.slow_count}</TableCell>
<TableCell>{metric.failure_rate}%</TableCell>
</TableRow> </TableRow>
))} ))}

View file

@ -475,6 +475,46 @@ export const modelMetricsCall = async (
}; };
export const modelMetricsSlowResponsesCall = async (
accessToken: String,
userID: String,
userRole: String,
modelGroup: String | null,
) => {
/**
* Get all models on proxy
*/
try {
let url = proxyBaseUrl ? `${proxyBaseUrl}/model/metrics/slow_responses` : `/model/metrics/slow_responses`;
if (modelGroup) {
url = `${url}?_selected_model_group=${modelGroup}`
}
// message.info("Requesting model data");
const response = await fetch(url, {
method: "GET",
headers: {
Authorization: `Bearer ${accessToken}`,
"Content-Type": "application/json",
},
});
if (!response.ok) {
const errorData = await response.text();
message.error(errorData, 20);
throw new Error("Network response was not ok");
}
const data = await response.json();
// message.info("Received model data");
return data;
// Handle success - you might want to update some state or UI based on the created key
} catch (error) {
console.error("Failed to create key:", error);
throw error;
}
};
export const modelExceptionsCall = async ( export const modelExceptionsCall = async (
accessToken: String, accessToken: String,
userID: String, userID: String,