AFI conformance test suite
Substrate-level gate: same @client fixture registered in both backends
emits equivalent schemas, therefore the codegen produces equivalent
TypeScript regardless of which backend the frontend is generated against.
Catches adapter symmetry problems (Pydantic→OpenAPI converter divergence,
metadata leakage, ordering non-determinism) without docker, browser, or
Playwright.
What ships:
backends/mizan-fastapi/src/mizan_fastapi/schema.py — build_schema():
- Builds OpenAPI 3.0 from registered Mizan functions, mirroring the
shape mizan-django's export emits.
- Drives FastAPI's native OpenAPI generation by registering a stub POST
endpoint per function with its Input/Output Pydantic models, then
appends x-mizan-functions and x-mizan-contexts extensions.
- Param-elevation logic mirrors mizan-django/src/mizan/export/__init__.py
exactly (sharedBy tracking, required iff every function in context has
the param).
- snake_to_camel and metadata field shapes match Django for byte-equality
on the AFI surface.
tests/afi/ — the conformance harness:
- fixture.py: 5 @client functions covering the protocol axes (plain,
context, mutation+affects). No channels/forms — those aren't AFI-common.
- django_app/: minimal Django project (settings, urls, AppConfig.ready
registers the fixture). manage.py adds tests/afi/ to sys.path so both
backends import the same fixture module.
- fastapi_app.py: thin make_app() that registers fixture and mounts router.
- schema_normalizer.py: drops backend-specific framing — Ninja-vs-FastAPI
envelope differences (info/servers/tags), Django-only function fields
(form metadata), x-mizan-channels. Plus afi_subset() and
function_io_schemas() helpers for narrower comparisons.
- test_codegen_parity.py: three gates
1. x-mizan-functions match across backends
2. x-mizan-contexts match across backends
3. Per-function Input/Output OpenAPI schemas match (what codegen feeds
to openapi-typescript for type generation)
The full normalized OpenAPI envelopes do diverge — FastAPI adds
HTTPValidationError, the two converters wrap things slightly differently
in non-AFI-essential ways. That's not in the test scope. The codegen
only consumes x-mizan-functions, x-mizan-contexts, and the per-function
type schemas; those are what the test gates.
Makefile: test-afi target added; rolls into the test aggregate.
Verified: 3/3 conformance tests pass. Other surfaces unaffected —
mizan-core 15/15, mizan-django 348 pass, mizan-fastapi 11/11.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
@@ -35,6 +35,7 @@ from .executor import (
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execute_function,
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)
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from .router import router, mizan_exception_handler, mizan_validation_handler
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from .schema import build_schema
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__all__ = [
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"router",
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@@ -42,6 +43,7 @@ __all__ = [
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"mizan_validation_handler",
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"execute_function",
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"compute_invalidation",
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"build_schema",
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"ErrorCode",
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"MizanError",
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"NotFound",
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209
backends/mizan-fastapi/src/mizan_fastapi/schema.py
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209
backends/mizan-fastapi/src/mizan_fastapi/schema.py
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@@ -0,0 +1,209 @@
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"""
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Mizan schema export for FastAPI backends.
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Builds an OpenAPI 3.0 document from the registered Mizan functions, mirroring
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the shape mizan-django emits via Django Ninja so the codegen consumes either
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backend identically.
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Usage:
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from mizan_fastapi.schema import build_schema
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schema = build_schema() # uses globally registered functions
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"""
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from __future__ import annotations
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import re
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from typing import Any
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from fastapi import FastAPI
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from fastapi.openapi.utils import get_openapi
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from pydantic import BaseModel, create_model
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from mizan_core.registry import get_all_functions, get_context_groups, get_function
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__all__ = ["build_schema", "snake_to_camel"]
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# Common user identity param names — mirrors mizan-django's _USER_SCOPED_PARAMS
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_USER_SCOPED_PARAMS = {"user_id", "user", "owner_id", "account_id"}
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def snake_to_camel(name: str) -> str:
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"""Convert snake_case or dotted.name to camelCase. Mirrors mizan-django."""
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components = re.split(r"[._]", name)
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return components[0] + "".join(c.title() for c in components[1:])
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def _has_input(input_cls: Any) -> bool:
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return (
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input_cls is not None
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and input_cls is not BaseModel
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and hasattr(input_cls, "model_fields")
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and bool(input_cls.model_fields)
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)
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def _annotation_to_jsonschema_type(annotation: Any) -> str:
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if annotation is int:
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return "integer"
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if annotation is float:
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return "number"
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if annotation is bool:
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return "boolean"
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return "string"
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def _function_metadata(name: str, fn_class: Any) -> dict[str, Any]:
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"""Build one entry of x-mizan-functions. Mirrors Django's shape exactly."""
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camel = snake_to_camel(name)
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meta = getattr(fn_class, "_meta", {})
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input_cls = getattr(fn_class, "Input", None)
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has_input = _has_input(input_cls)
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entry: dict[str, Any] = {
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"name": name,
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"camelName": camel,
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"hasInput": has_input,
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"inputType": f"{camel}Input" if has_input else None,
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"outputType": f"{camel}Output",
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"transport": "websocket" if meta.get("websocket") else "http",
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"isContext": meta.get("context", False),
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# Form metadata — always emitted so the schema shape matches Django's,
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# even for FastAPI projects that don't use forms (these stay False/None).
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"isForm": meta.get("form", False),
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"formName": meta.get("form_name"),
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"formRole": meta.get("form_role"),
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}
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if meta.get("affects"):
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entry["affects"] = meta["affects"]
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return entry
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def _context_metadata(context_groups: dict[str, list[str]]) -> dict[str, Any]:
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"""Build x-mizan-contexts. Mirrors Django's param-elevation logic."""
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out: dict[str, Any] = {}
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for ctx_name, fn_names in context_groups.items():
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param_info: dict[str, dict[str, Any]] = {}
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for fn_name in fn_names:
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fn_cls = get_function(fn_name)
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if fn_cls is None:
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continue
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input_cls = getattr(fn_cls, "Input", None)
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if not _has_input(input_cls):
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continue
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for field_name, field_info in input_cls.model_fields.items():
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if field_name not in param_info:
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param_info[field_name] = {
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"type": _annotation_to_jsonschema_type(field_info.annotation),
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"sharedBy": [],
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}
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param_info[field_name]["sharedBy"].append(fn_name)
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# A param is required iff every function in the context declares it.
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for p_meta in param_info.values():
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p_meta["required"] = len(p_meta["sharedBy"]) == len(fn_names)
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out[ctx_name] = {
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"functions": list(fn_names),
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"params": param_info,
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}
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return out
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def build_schema() -> dict[str, Any]:
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"""
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Build an OpenAPI 3.0 schema for all registered Mizan functions.
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Drives FastAPI's native OpenAPI generation by registering a stub endpoint
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per function with the function's Input/Output Pydantic models, then
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appends the protocol's `x-mizan-functions` and `x-mizan-contexts`
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extensions.
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Returns a dict in the same shape mizan-django's schema export emits, so
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the same codegen pipeline consumes either.
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"""
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functions = get_all_functions()
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context_groups = get_context_groups()
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schema_app = FastAPI(
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title="mizan Server Functions",
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version="1.0.0",
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description="Auto-generated schema for mizan server functions",
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)
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# Per-function endpoints + renamed Pydantic models so component names are
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# camelCase + "Input"/"Output" rather than the user's original class names.
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schema_classes: dict[str, type[BaseModel]] = {}
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function_metadata: list[dict[str, Any]] = []
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for name, fn_class in functions.items():
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camel = snake_to_camel(name)
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input_cls = getattr(fn_class, "Input", None)
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output_cls = getattr(fn_class, "Output", None) or BaseModel
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has_input = _has_input(input_cls)
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input_type_name = f"{camel}Input" if has_input else None
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output_type_name = f"{camel}Output"
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if has_input:
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schema_classes[input_type_name] = create_model(
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input_type_name, __base__=input_cls,
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)
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schema_classes[output_type_name] = create_model(
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output_type_name, __base__=output_cls,
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)
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# Stub endpoint — only exists so FastAPI walks Pydantic types into
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# components.schemas. Never invoked. Annotations are set explicitly
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# rather than via closures so forward-ref resolution doesn't trip on
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# locally-bound type names.
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if has_input:
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async def stub(payload):
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return None
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stub.__annotations__ = {"payload": schema_classes[input_type_name]}
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else:
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async def stub():
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return None
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schema_app.post(
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f"/mizan/{name}",
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response_model=schema_classes[output_type_name],
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operation_id=camel,
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summary=fn_class.__doc__ or f"Call {name}",
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)(stub)
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function_metadata.append(_function_metadata(name, fn_class))
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schema = get_openapi(
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title=schema_app.title,
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version=schema_app.version,
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description=schema_app.description,
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routes=schema_app.routes,
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)
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schema["x-mizan-functions"] = function_metadata
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if context_groups:
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schema["x-mizan-contexts"] = _context_metadata(context_groups)
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# Attach x-mizan operation metadata, mirroring Django.
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paths = schema.get("paths", {})
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for fn_meta in function_metadata:
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op = paths.get(f"/mizan/{fn_meta['name']}", {}).get("post")
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if op is not None:
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op["x-mizan"] = {
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"transport": fn_meta["transport"],
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"isContext": fn_meta["isContext"],
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}
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return schema
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