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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11To identify which tenant’s audio upload failed without logging the audio, resolve the tenant and assign a request ID before body parsing where your architecture allows, then log bounded, structured metadata when parsing fails. Multipart requests are boundary-delimited parts—not JSON—and a FastAPI endpoint must declare file and form fields that match the client’s field names. Protect the parser with part/count limits and the entire request with a separate body-size limit.
What makes a multipart request malformed?
Under RFC 7578 (published July 2015), multipart/form-data is a sequence of parts separated by a boundary. The boundary is specified as a parameter of the request’s Content-Type header, and each part must have a Content-Disposition header with disposition type form-data and a name parameter. A file part may include a filename, but the RFC allows the filename to be omitted.
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Common framing and contract failures include a missing or mismatched boundary, a body cut off before the closing boundary, an unexpected content type, or a part name the endpoint does not accept. A request can also be valid multipart but fail the endpoint contract because a required file part is absent or the client used the wrong field name. Treat those as distinguishable errors rather than labelling every upload failure “bad audio.”
Do not trust a client-supplied filename as a filesystem path or use it blindly: RFC 7578 warns receivers about path information in filenames. The RFC also notes that form data may contain confidential or personally identifying information and that uploaded files can contain arbitrary executable content.
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Declare the speech endpoint as multipart in FastAPI
FastAPI documents File and UploadFile for uploaded files and Form for accompanying text fields. Incoming uploads require the python-multipart dependency. Declare the request according to its actual encoding; a request encoded as multipart/form-data cannot simultaneously be parsed as the endpoint’s ordinary JSON Body, because one request body has one encoding.
For example, an endpoint taking a file and a model field can be shaped like this:
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from typing import Annotated
from fastapi import FastAPI, File, Form, UploadFile
app = FastAPI()
@app.post("/transcribe")
async def transcribe(
file: Annotated[UploadFile, File()],
model: Annotated[str, Form()],
):
return {"filename": file.filename, "model": model}This is a shape example, not a recommendation to return or log a client filename. The client’s multipart field names must be file and model to match the declared parameters. If the client instead sends audio, either change the client or declare the corresponding field name in the API contract.
OpenAI’s speech-to-text guide describes transcription at /v1/audio/transcriptions using multipart form data with a file and a model field; its API reference also demonstrates a multipart transcription request. The guide lists mp3, mp4, mpeg, mpga, m4a, wav, and webm, and states a file limit of 25 MB. That is a downstream OpenAI guide constraint, not a limit imposed automatically by FastAPI or by your own ingress layer. Confirm the current model and endpoint contract when implementing, and set your inbound allowance to suit your application.
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Set parser limits and whole-request limits separately
Starlette exposes form parsing through request.form(max_files=..., max_fields=..., max_part_size=...). Its documentation says file and field count limits help protect against resource exhaustion caused by parsing many parts. The max_part_size setting limits non-file fields; it is not a cap on the size of an uploaded file. Uploaded file content is spooled to temporary storage.
| Control | What it constrains | What it does not do |
|---|---|---|
max_files |
Number of file parts accepted by form parsing | Does not cap total request bytes |
max_fields |
Number of non-file fields accepted by form parsing | Does not cap total request bytes |
max_part_size |
Size of non-file form parts | Does not limit uploaded file content |
| Whole-body limit | Total request body, including files and multipart overhead | Does not replace parser-specific count and field-size limits |
Use documented body-size controls at ingress and/or the application layer, such as Starlette’s RequestBodyLimitMiddleware, for a whole-body ceiling. Combine that with parser-specific field, file-count, and non-file-part limits: the controls address different resource risks. Choose values based on your service’s actual contract rather than assuming the downstream transcription API’s cap is an appropriate inbound limit.
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Establish tenant identity before parsing when possible
For tenant-aware failure attribution, authenticate the caller and resolve the tenant before reading or parsing the multipart body where the architecture permits. Attach an immutable tenant identifier and a request or correlation ID to request context so a parser exception can be associated with the caller even when form parsing never produces usable fields.
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Log enough to diagnose, not enough to expose the upload
Emit a structured event at the failure stage, with a bounded set of diagnostic fields. Useful fields include:
- Tenant identifier and request/correlation ID.
- Route and response status.
- Parser or framework error class, rather than an unbounded raw exception message.
- Request content type and byte count, when the count is reliably available.
- A stage label distinguishing multipart parsing from later transcription-provider work.
Redact or constrain untrusted values before logging them. Do not log raw multipart bodies, audio bytes, authorization headers, or client-provided filenames. A byte count may not be available or trustworthy on every failure path; omit it rather than presenting an estimate as an exact measurement.
Keep parser failures distinct from downstream transcription API failures. A malformed boundary or absent required part is an intake problem; a provider rejection after successful parsing is a different stage and should have a distinct event category. This makes tenant-level failure patterns meaningful without conflating client framing, local policy, and provider behavior.
Use a stable error taxonomy and test its boundaries
Map low-level parser and validation failures into a small, stable set of client-facing categories. Preserve the underlying error class in structured logs, but avoid exposing implementation details or sensitive request data in responses.
| Observed condition | Useful category | Diagnostic distinction |
|---|---|---|
| Malformed or missing multipart boundary; truncated framing | Malformed multipart request | Body framing or boundary could not be parsed |
| Request is not sent as multipart when multipart is required | Unsupported media type | Content type does not match the endpoint’s declared encoding |
| Required file part is absent, or field name is wrong | Missing or invalid required field | Multipart may parse, but it does not satisfy the endpoint contract |
| Configured body, file-count, field-count, or non-file-part limit is exceeded | Request limit exceeded | Identify which configured control rejected the request |
| Parsing succeeds but transcription provider rejects or fails | Downstream transcription failure | Failure occurred after intake parsing |
Test the taxonomy with malformed boundary, missing boundary, missing file part, wrong field name, wrong content type, truncated body, excess parts, and oversized body cases. For each case, verify the response category, status, tenant and request-ID attribution, and that no upload bytes or secrets appear in logs. These are proposed cases to exercise, not claims about results from a completed test run.
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