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import json
from typing import Callable
from fastapi import Request
from prometheus_client import Counter, Gauge
from prometheus_fastapi_instrumentator import Instrumentator, metrics
from prometheus_fastapi_instrumentator.metrics import Info
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.types import Message
SUBSYSTEM = "model"
NAMESPACE = "turing_api"
# Define Prometheus metrics
instrumentator = Instrumentator(
should_group_status_codes=False,
should_ignore_untemplated=True,
should_respect_env_var=False,
should_instrument_requests_inprogress=True,
excluded_handlers=["/metrics"],
inprogress_name="fastapi_inprogress",
inprogress_labels=True
)
## Define custom metric for tracking requested languages
def http_requested_languages_total(
metric_name: str = "Total HTTP requested languages",
metric_description: str = "Total number of HTTP requests per programming language",
metric_namespace: str = NAMESPACE,
metric_subsystem: str = SUBSYSTEM ) -> Callable[[Info],None]:
METRIC = Counter(
metric_name,
metric_description,
namespace=metric_namespace,
subsystem=metric_subsystem,
labelnames=["language"]
)
async def instrumentation(info: Info) -> None:
try:
if info.modified_handler != "/predict":
return
lang = info.request.query_params.get("language")
except Exception:
print("Failed to get language from request")
lang = "other"
METRIC.labels(language=lang).inc()
return instrumentation
## Define custom metrics for tracking code comments in requests
http_request_code_comments_total = Counter (
"Total HTTP request code comments",
"Total number of comments in HTTP requests",
namespace=NAMESPACE,
subsystem=SUBSYSTEM,
labelnames=["language"]
)
## Define custom metrics for tracking characters in code comments
http_request_comment_characters_total = Counter(
"Total HTTP request code comment characters",
"Total number of characters in the HTTP requests",
namespace=NAMESPACE,
subsystem=SUBSYSTEM,
labelnames=["endpoint","language"]
)
## Define custom metric for tracking maximum characters per comment
http_request_maximum_characters_per_comment = Gauge(
"Maximum characters per comment",
"Maximum number of characters in a single comment from HTTP requests",
namespace=NAMESPACE,
subsystem=SUBSYSTEM,
labelnames=["language"]
)
## Middleware to extract and record metrics from request body
class PrometheusBodyMiddleware(BaseHTTPMiddleware):
async def dispatch(self, request: Request, call_next):
if request.url.path != "/predict":
return await call_next(request)
body_bytes = await request.body()
query_params = request.query_params
try:
if body_bytes:
language = query_params.get("language", "unknown")
body_json = json.loads(body_bytes)
print(f"Request body JSON: {body_json}")
texts = body_json.get("texts")
if texts:
total_characters = sum(len(example) for example in texts if example)
max_characters = max((len(example) for example in texts if example), default=0)
http_request_comment_characters_total.labels(endpoint="/predict", language=language).inc(total_characters)
http_request_maximum_characters_per_comment.labels(language=language).set(max_characters)
http_request_code_comments_total.labels(language=language).inc(len(texts))
except (json.JSONDecodeError, UnicodeDecodeError):
pass
async def receive() -> Message:
return {"type": "http.request", "body": body_bytes}
request._receive = receive
response = await call_next(request)
return response
## Register metrics with the instrumentator
instrumentator.add(
metrics.request_size(
should_include_handler=True,
should_include_method=False,
should_include_status=True,
metric_namespace=NAMESPACE,
metric_subsystem=SUBSYSTEM,
)
).add(
metrics.response_size(
should_include_handler=True,
should_include_method=False,
should_include_status=True,
metric_namespace=NAMESPACE,
metric_subsystem=SUBSYSTEM
)
).add(
http_requested_languages_total()
).add(
metrics.requests(
should_include_handler=True,
should_include_method=True,
should_include_status=True,
metric_namespace=NAMESPACE,
metric_subsystem=SUBSYSTEM
)
).add(
metrics.latency(
should_include_handler=True,
should_include_method=False,
should_include_status=True,
metric_namespace=NAMESPACE,
metric_subsystem=SUBSYSTEM
)
)
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