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# This file was auto-generated by Fern from our API Definition.
import typing
from json.decoder import JSONDecodeError
from ...core.api_error import ApiError
from ...core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
from ...core.pydantic_utilities import pydantic_v1
from ...core.request_options import RequestOptions
from ..commons.errors.access_denied_error import AccessDeniedError
from ..commons.errors.error import Error
from ..commons.errors.method_not_allowed_error import MethodNotAllowedError
from ..commons.errors.not_found_error import NotFoundError
from ..commons.errors.unauthorized_error import UnauthorizedError
from .types.metrics_response import MetricsResponse
class MetricsClient:
def __init__(self, *, client_wrapper: SyncClientWrapper):
self._client_wrapper = client_wrapper
def metrics(
self, *, query: str, request_options: typing.Optional[RequestOptions] = None
) -> MetricsResponse:
"""
Get metrics from the Langfuse project using a query object.
Consider using the [v2 metrics endpoint](/api-reference#tag/metricsv2/GET/api/public/v2/metrics) for better performance.
For more details, see the [Metrics API documentation](https://langfuse.com/docs/metrics/features/metrics-api).
Parameters
----------
query : str
JSON string containing the query parameters with the following structure:
```json
{
"view": string, // Required. One of "traces", "observations", "scores-numeric", "scores-categorical"
"dimensions": [ // Optional. Default: []
{
"field": string // Field to group by, e.g. "name", "userId", "sessionId"
}
],
"metrics": [ // Required. At least one metric must be provided
{
"measure": string, // What to measure, e.g. "count", "latency", "value"
"aggregation": string // How to aggregate, e.g. "count", "sum", "avg", "p95", "histogram"
}
],
"filters": [ // Optional. Default: []
{
"column": string, // Column to filter on
"operator": string, // Operator, e.g. "=", ">", "<", "contains"
"value": any, // Value to compare against
"type": string, // Data type, e.g. "string", "number", "stringObject"
"key": string // Required only when filtering on metadata
}
],
"timeDimension": { // Optional. Default: null. If provided, results will be grouped by time
"granularity": string // One of "minute", "hour", "day", "week", "month", "auto"
},
"fromTimestamp": string, // Required. ISO datetime string for start of time range
"toTimestamp": string, // Required. ISO datetime string for end of time range
"orderBy": [ // Optional. Default: null
{
"field": string, // Field to order by
"direction": string // "asc" or "desc"
}
],
"config": { // Optional. Query-specific configuration
"bins": number, // Optional. Number of bins for histogram (1-100), default: 10
"row_limit": number // Optional. Row limit for results (1-1000)
}
}
```
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
MetricsResponse
Examples
--------
from langfuse.client import FernLangfuse
client = FernLangfuse(
x_langfuse_sdk_name="YOUR_X_LANGFUSE_SDK_NAME",
x_langfuse_sdk_version="YOUR_X_LANGFUSE_SDK_VERSION",
x_langfuse_public_key="YOUR_X_LANGFUSE_PUBLIC_KEY",
username="YOUR_USERNAME",
password="YOUR_PASSWORD",
base_url="https://yourhost.com/path/to/api",
)
client.metrics.metrics(
query="query",
)
"""
_response = self._client_wrapper.httpx_client.request(
"api/public/metrics",
method="GET",
params={"query": query},
request_options=request_options,
)
try:
if 200 <= _response.status_code < 300:
return pydantic_v1.parse_obj_as(MetricsResponse, _response.json()) # type: ignore
if _response.status_code == 400:
raise Error(pydantic_v1.parse_obj_as(typing.Any, _response.json())) # type: ignore
if _response.status_code == 401:
raise UnauthorizedError(
pydantic_v1.parse_obj_as(typing.Any, _response.json())
) # type: ignore
if _response.status_code == 403:
raise AccessDeniedError(
pydantic_v1.parse_obj_as(typing.Any, _response.json())
) # type: ignore
if _response.status_code == 405:
raise MethodNotAllowedError(
pydantic_v1.parse_obj_as(typing.Any, _response.json())
) # type: ignore
if _response.status_code == 404:
raise NotFoundError(
pydantic_v1.parse_obj_as(typing.Any, _response.json())
) # type: ignore
_response_json = _response.json()
except JSONDecodeError:
raise ApiError(status_code=_response.status_code, body=_response.text)
raise ApiError(status_code=_response.status_code, body=_response_json)
class AsyncMetricsClient:
def __init__(self, *, client_wrapper: AsyncClientWrapper):
self._client_wrapper = client_wrapper
async def metrics(
self, *, query: str, request_options: typing.Optional[RequestOptions] = None
) -> MetricsResponse:
"""
Get metrics from the Langfuse project using a query object.
Consider using the [v2 metrics endpoint](/api-reference#tag/metricsv2/GET/api/public/v2/metrics) for better performance.
For more details, see the [Metrics API documentation](https://langfuse.com/docs/metrics/features/metrics-api).
Parameters
----------
query : str
JSON string containing the query parameters with the following structure:
```json
{
"view": string, // Required. One of "traces", "observations", "scores-numeric", "scores-categorical"
"dimensions": [ // Optional. Default: []
{
"field": string // Field to group by, e.g. "name", "userId", "sessionId"
}
],
"metrics": [ // Required. At least one metric must be provided
{
"measure": string, // What to measure, e.g. "count", "latency", "value"
"aggregation": string // How to aggregate, e.g. "count", "sum", "avg", "p95", "histogram"
}
],
"filters": [ // Optional. Default: []
{
"column": string, // Column to filter on
"operator": string, // Operator, e.g. "=", ">", "<", "contains"
"value": any, // Value to compare against
"type": string, // Data type, e.g. "string", "number", "stringObject"
"key": string // Required only when filtering on metadata
}
],
"timeDimension": { // Optional. Default: null. If provided, results will be grouped by time
"granularity": string // One of "minute", "hour", "day", "week", "month", "auto"
},
"fromTimestamp": string, // Required. ISO datetime string for start of time range
"toTimestamp": string, // Required. ISO datetime string for end of time range
"orderBy": [ // Optional. Default: null
{
"field": string, // Field to order by
"direction": string // "asc" or "desc"
}
],
"config": { // Optional. Query-specific configuration
"bins": number, // Optional. Number of bins for histogram (1-100), default: 10
"row_limit": number // Optional. Row limit for results (1-1000)
}
}
```
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
Returns
-------
MetricsResponse
Examples
--------
import asyncio
from langfuse.client import AsyncFernLangfuse
client = AsyncFernLangfuse(
x_langfuse_sdk_name="YOUR_X_LANGFUSE_SDK_NAME",
x_langfuse_sdk_version="YOUR_X_LANGFUSE_SDK_VERSION",
x_langfuse_public_key="YOUR_X_LANGFUSE_PUBLIC_KEY",
username="YOUR_USERNAME",
password="YOUR_PASSWORD",
base_url="https://yourhost.com/path/to/api",
)
async def main() -> None:
await client.metrics.metrics(
query="query",
)
asyncio.run(main())
"""
_response = await self._client_wrapper.httpx_client.request(
"api/public/metrics",
method="GET",
params={"query": query},
request_options=request_options,
)
try:
if 200 <= _response.status_code < 300:
return pydantic_v1.parse_obj_as(MetricsResponse, _response.json()) # type: ignore
if _response.status_code == 400:
raise Error(pydantic_v1.parse_obj_as(typing.Any, _response.json())) # type: ignore
if _response.status_code == 401:
raise UnauthorizedError(
pydantic_v1.parse_obj_as(typing.Any, _response.json())
) # type: ignore
if _response.status_code == 403:
raise AccessDeniedError(
pydantic_v1.parse_obj_as(typing.Any, _response.json())
) # type: ignore
if _response.status_code == 405:
raise MethodNotAllowedError(
pydantic_v1.parse_obj_as(typing.Any, _response.json())
) # type: ignore
if _response.status_code == 404:
raise NotFoundError(
pydantic_v1.parse_obj_as(typing.Any, _response.json())
) # type: ignore
_response_json = _response.json()
except JSONDecodeError:
raise ApiError(status_code=_response.status_code, body=_response.text)
raise ApiError(status_code=_response.status_code, body=_response_json)