mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-03 09:53:45 +00:00
feat(openapi): generate stainless config "more" programmatically (#4164)
Generate the Stainless client config directly from code so we can validate the config before we ever write the YAML. This change enforces allowed HTTP verbs/paths, detects duplicate routes across resources, and ensures README example endpoints exist and match the OpenAPI spec. The generator now fails fast when config entries drift, keeping the published config (hopefully) more current with the spec. I think more validation can be done but this is a good start.
This commit is contained in:
Ashwin Bharambe
GitHub
parent
5fe6098350
commit
7d3db6b22c
6 changed files with 990 additions and 193 deletions
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@ -11,6 +11,13 @@ This module provides functionality to generate OpenAPI specifications
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from FastAPI applications.
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"""
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from .main import generate_openapi_spec, main
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__all__ = ["generate_openapi_spec", "main"]
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def __getattr__(name: str):
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if name in {"generate_openapi_spec", "main"}:
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from .main import generate_openapi_spec as _gos
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from .main import main as _main
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return {"generate_openapi_spec": _gos, "main": _main}[name]
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raise AttributeError(name)
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7
scripts/openapi_generator/stainless_config/__init__.py
Normal file
7
scripts/openapi_generator/stainless_config/__init__.py
Normal file
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@ -0,0 +1,7 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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# Package marker for Stainless config generation.
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821
scripts/openapi_generator/stainless_config/generate_config.py
Normal file
821
scripts/openapi_generator/stainless_config/generate_config.py
Normal file
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@ -0,0 +1,821 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from __future__ import annotations
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from collections.abc import Iterator
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any
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import yaml
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HEADER = "# yaml-language-server: $schema=https://app.stainlessapi.com/config-internal.schema.json\n\n"
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SECTION_ORDER = [
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"organization",
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"security",
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"security_schemes",
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"targets",
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"client_settings",
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"environments",
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"pagination",
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"settings",
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"openapi",
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"readme",
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"resources",
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]
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ORGANIZATION = {
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"name": "llama-stack-client",
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"docs": "https://llama-stack.readthedocs.io/en/latest/",
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"contact": "llamastack@meta.com",
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}
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SECURITY = [{}, {"BearerAuth": []}]
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SECURITY_SCHEMES = {"BearerAuth": {"type": "http", "scheme": "bearer"}}
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TARGETS = {
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"node": {
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"package_name": "llama-stack-client",
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"production_repo": "llamastack/llama-stack-client-typescript",
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"publish": {"npm": False},
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},
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"python": {
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"package_name": "llama_stack_client",
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"production_repo": "llamastack/llama-stack-client-python",
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"options": {"use_uv": True},
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"publish": {"pypi": True},
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"project_name": "llama_stack_client",
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},
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"kotlin": {
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"reverse_domain": "com.llama_stack_client.api",
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"production_repo": None,
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"publish": {"maven": False},
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},
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"go": {
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"package_name": "llama-stack-client",
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"production_repo": "llamastack/llama-stack-client-go",
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"options": {"enable_v2": True, "back_compat_use_shared_package": False},
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},
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}
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CLIENT_SETTINGS = {
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"default_env_prefix": "LLAMA_STACK_CLIENT",
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"opts": {
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"api_key": {
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"type": "string",
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"read_env": "LLAMA_STACK_CLIENT_API_KEY",
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"auth": {"security_scheme": "BearerAuth"},
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"nullable": True,
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}
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},
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}
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ENVIRONMENTS = {"production": "http://any-hosted-llama-stack.com"}
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PAGINATION = [
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{
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"name": "datasets_iterrows",
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"type": "offset",
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"request": {
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"dataset_id": {"type": "string"},
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"start_index": {
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"type": "integer",
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"x-stainless-pagination-property": {"purpose": "offset_count_param"},
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},
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"limit": {"type": "integer"},
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},
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"response": {
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"data": {"type": "array", "items": {"type": "object"}},
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"next_index": {
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"type": "integer",
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"x-stainless-pagination-property": {"purpose": "offset_count_start_field"},
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},
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},
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},
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{
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"name": "openai_cursor_page",
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"type": "cursor",
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"request": {
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"limit": {"type": "integer"},
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"after": {
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"type": "string",
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"x-stainless-pagination-property": {"purpose": "next_cursor_param"},
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},
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},
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"response": {
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"data": {"type": "array", "items": {}},
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"has_more": {"type": "boolean"},
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"last_id": {
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"type": "string",
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"x-stainless-pagination-property": {"purpose": "next_cursor_field"},
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},
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},
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},
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]
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SETTINGS = {
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"license": "MIT",
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"unwrap_response_fields": ["data"],
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"file_header": "Copyright (c) Meta Platforms, Inc. and affiliates.\n"
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"All rights reserved.\n"
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"\n"
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"This source code is licensed under the terms described in the "
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"LICENSE file in\n"
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"the root directory of this source tree.\n",
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}
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OPENAPI = {
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"transformations": [
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{
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"command": "mergeObject",
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"reason": "Better return_type using enum",
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"args": {
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"target": ["$.components.schemas"],
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"object": {
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"ReturnType": {
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"additionalProperties": False,
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"properties": {
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"type": {
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"enum": [
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"string",
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"number",
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"boolean",
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"array",
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"object",
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"json",
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"union",
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"chat_completion_input",
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"completion_input",
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"agent_turn_input",
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]
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}
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},
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"required": ["type"],
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"type": "object",
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}
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},
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},
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},
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{
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"command": "replaceProperties",
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"reason": "Replace return type properties with better model (see above)",
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"args": {
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"filter": {
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"only": [
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"$.components.schemas.ScoringFn.properties.return_type",
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"$.components.schemas.RegisterScoringFunctionRequest.properties.return_type",
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]
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},
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"value": {"$ref": "#/components/schemas/ReturnType"},
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},
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},
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{
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"command": "oneOfToAnyOf",
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"reason": "Prism (mock server) doesn't like one of our "
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"requests as it technically matches multiple "
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"variants",
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},
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]
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}
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README = {
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"example_requests": {
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"default": {
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"type": "request",
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"endpoint": "post /v1/chat/completions",
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"params": {},
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},
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"headline": {"type": "request", "endpoint": "get /v1/models", "params": {}},
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"pagination": {
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"type": "request",
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"endpoint": "post /v1/chat/completions",
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"params": {},
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},
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}
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}
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ALL_RESOURCES = {
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"$shared": {
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"models": {
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"interleaved_content_item": "InterleavedContentItem",
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"interleaved_content": "InterleavedContent",
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"param_type": "ParamType",
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"safety_violation": "SafetyViolation",
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"sampling_params": "SamplingParams",
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"scoring_result": "ScoringResult",
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"system_message": "SystemMessage",
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}
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},
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"toolgroups": {
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"models": {
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"tool_group": "ToolGroup",
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"list_tool_groups_response": "ListToolGroupsResponse",
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},
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"methods": {
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"register": "post /v1/toolgroups",
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"get": "get /v1/toolgroups/{toolgroup_id}",
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"list": "get /v1/toolgroups",
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"unregister": "delete /v1/toolgroups/{toolgroup_id}",
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},
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},
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"tools": {
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"methods": {
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"get": "get /v1/tools/{tool_name}",
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"list": {"paginated": False, "endpoint": "get /v1/tools"},
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}
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},
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"tool_runtime": {
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"models": {
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"tool_def": "ToolDef",
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"tool_invocation_result": "ToolInvocationResult",
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},
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"methods": {
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"list_tools": {
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"paginated": False,
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"endpoint": "get /v1/tool-runtime/list-tools",
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},
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"invoke_tool": "post /v1/tool-runtime/invoke",
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},
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},
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"responses": {
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"models": {
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"response_object_stream": "OpenAIResponseObjectStream",
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"response_object": "OpenAIResponseObject",
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},
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"methods": {
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"create": {
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"type": "http",
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"streaming": {
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"stream_event_model": "responses.response_object_stream",
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"param_discriminator": "stream",
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},
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"endpoint": "post /v1/responses",
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},
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"retrieve": "get /v1/responses/{response_id}",
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"list": {"type": "http", "endpoint": "get /v1/responses"},
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"delete": {
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"type": "http",
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"endpoint": "delete /v1/responses/{response_id}",
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},
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},
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"subresources": {
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"input_items": {
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"methods": {
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"list": {
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"type": "http",
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"paginated": False,
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"endpoint": "get /v1/responses/{response_id}/input_items",
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}
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}
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}
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},
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},
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"prompts": {
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"models": {"prompt": "Prompt", "list_prompts_response": "ListPromptsResponse"},
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"methods": {
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"create": "post /v1/prompts",
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"list": {"paginated": False, "endpoint": "get /v1/prompts"},
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"retrieve": "get /v1/prompts/{prompt_id}",
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"update": "post /v1/prompts/{prompt_id}",
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"delete": "delete /v1/prompts/{prompt_id}",
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"set_default_version": "post /v1/prompts/{prompt_id}/set-default-version",
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},
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"subresources": {
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"versions": {
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"methods": {
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"list": {
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"paginated": False,
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"endpoint": "get /v1/prompts/{prompt_id}/versions",
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}
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}
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}
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},
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},
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"conversations": {
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"models": {"conversation_object": "Conversation"},
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"methods": {
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"create": {"type": "http", "endpoint": "post /v1/conversations"},
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"retrieve": "get /v1/conversations/{conversation_id}",
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"update": {
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"type": "http",
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"endpoint": "post /v1/conversations/{conversation_id}",
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},
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"delete": {
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"type": "http",
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"endpoint": "delete /v1/conversations/{conversation_id}",
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},
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},
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"subresources": {
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"items": {
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"methods": {
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"get": {
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"type": "http",
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"endpoint": "get /v1/conversations/{conversation_id}/items/{item_id}",
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},
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"list": {
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"type": "http",
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"endpoint": "get /v1/conversations/{conversation_id}/items",
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},
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"create": {
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"type": "http",
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"endpoint": "post /v1/conversations/{conversation_id}/items",
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},
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"delete": {
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"type": "http",
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"endpoint": "delete /v1/conversations/{conversation_id}/items/{item_id}",
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},
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}
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}
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},
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},
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"inspect": {
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"models": {
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"healthInfo": "HealthInfo",
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"providerInfo": "ProviderInfo",
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"routeInfo": "RouteInfo",
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"versionInfo": "VersionInfo",
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},
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"methods": {"health": "get /v1/health", "version": "get /v1/version"},
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},
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"embeddings": {
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"models": {"create_embeddings_response": "OpenAIEmbeddingsResponse"},
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"methods": {"create": "post /v1/embeddings"},
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},
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"chat": {
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"models": {"chat_completion_chunk": "OpenAIChatCompletionChunk"},
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"subresources": {
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"completions": {
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"methods": {
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"create": {
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"type": "http",
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"streaming": {
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"stream_event_model": "chat.chat_completion_chunk",
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"param_discriminator": "stream",
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},
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"endpoint": "post /v1/chat/completions",
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},
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"list": {
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"type": "http",
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"paginated": False,
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"endpoint": "get /v1/chat/completions",
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},
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"retrieve": {
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"type": "http",
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"endpoint": "get /v1/chat/completions/{completion_id}",
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},
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}
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}
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},
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},
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"completions": {
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"methods": {
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"create": {
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"type": "http",
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"streaming": {"param_discriminator": "stream"},
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"endpoint": "post /v1/completions",
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}
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}
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},
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"vector_io": {
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"models": {"queryChunksResponse": "QueryChunksResponse"},
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"methods": {
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"insert": "post /v1/vector-io/insert",
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"query": "post /v1/vector-io/query",
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},
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},
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"vector_stores": {
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"models": {
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"vector_store": "VectorStoreObject",
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"list_vector_stores_response": "VectorStoreListResponse",
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"vector_store_delete_response": "VectorStoreDeleteResponse",
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"vector_store_search_response": "VectorStoreSearchResponsePage",
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},
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"methods": {
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"create": "post /v1/vector_stores",
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"list": "get /v1/vector_stores",
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"retrieve": "get /v1/vector_stores/{vector_store_id}",
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"update": "post /v1/vector_stores/{vector_store_id}",
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"delete": "delete /v1/vector_stores/{vector_store_id}",
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"search": "post /v1/vector_stores/{vector_store_id}/search",
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},
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"subresources": {
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"files": {
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"models": {"vector_store_file": "VectorStoreFileObject"},
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"methods": {
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"list": "get /v1/vector_stores/{vector_store_id}/files",
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"retrieve": "get /v1/vector_stores/{vector_store_id}/files/{file_id}",
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"update": "post /v1/vector_stores/{vector_store_id}/files/{file_id}",
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"delete": "delete /v1/vector_stores/{vector_store_id}/files/{file_id}",
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"create": "post /v1/vector_stores/{vector_store_id}/files",
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"content": "get /v1/vector_stores/{vector_store_id}/files/{file_id}/content",
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},
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},
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"file_batches": {
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"models": {
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"vector_store_file_batches": "VectorStoreFileBatchObject",
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"list_vector_store_files_in_batch_response": "VectorStoreFilesListInBatchResponse",
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},
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"methods": {
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"create": "post /v1/vector_stores/{vector_store_id}/file_batches",
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"retrieve": "get /v1/vector_stores/{vector_store_id}/file_batches/{batch_id}",
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"list_files": "get /v1/vector_stores/{vector_store_id}/file_batches/{batch_id}/files",
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"cancel": "post /v1/vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel",
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},
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},
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},
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},
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"models": {
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"models": {
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"model": "OpenAIModel",
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"list_models_response": "OpenAIListModelsResponse",
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},
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"methods": {
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"list": {"paginated": False, "endpoint": "get /v1/models"},
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"retrieve": "get /v1/models/{model_id}",
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"register": "post /v1/models",
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"unregister": "delete /v1/models/{model_id}",
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},
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"subresources": {"openai": {"methods": {"list": {"paginated": False, "endpoint": "get /v1/models"}}}},
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},
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"providers": {
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"models": {"list_providers_response": "ListProvidersResponse"},
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"methods": {
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"list": {"paginated": False, "endpoint": "get /v1/providers"},
|
||||
"retrieve": "get /v1/providers/{provider_id}",
|
||||
},
|
||||
},
|
||||
"routes": {
|
||||
"models": {"list_routes_response": "ListRoutesResponse"},
|
||||
"methods": {"list": {"paginated": False, "endpoint": "get /v1/inspect/routes"}},
|
||||
},
|
||||
"moderations": {
|
||||
"models": {"create_response": "ModerationObject"},
|
||||
"methods": {"create": "post /v1/moderations"},
|
||||
},
|
||||
"safety": {
|
||||
"models": {"run_shield_response": "RunShieldResponse"},
|
||||
"methods": {"run_shield": "post /v1/safety/run-shield"},
|
||||
},
|
||||
"shields": {
|
||||
"models": {"shield": "Shield", "list_shields_response": "ListShieldsResponse"},
|
||||
"methods": {
|
||||
"retrieve": "get /v1/shields/{identifier}",
|
||||
"list": {"paginated": False, "endpoint": "get /v1/shields"},
|
||||
"register": "post /v1/shields",
|
||||
"delete": "delete /v1/shields/{identifier}",
|
||||
},
|
||||
},
|
||||
"scoring": {
|
||||
"methods": {
|
||||
"score": "post /v1/scoring/score",
|
||||
"score_batch": "post /v1/scoring/score-batch",
|
||||
}
|
||||
},
|
||||
"scoring_functions": {
|
||||
"models": {
|
||||
"scoring_fn": "ScoringFn",
|
||||
"scoring_fn_params": "ScoringFnParams",
|
||||
"list_scoring_functions_response": "ListScoringFunctionsResponse",
|
||||
},
|
||||
"methods": {
|
||||
"retrieve": "get /v1/scoring-functions/{scoring_fn_id}",
|
||||
"list": {"paginated": False, "endpoint": "get /v1/scoring-functions"},
|
||||
"register": "post /v1/scoring-functions",
|
||||
"unregister": "delete /v1/scoring-functions/{scoring_fn_id}",
|
||||
},
|
||||
},
|
||||
"files": {
|
||||
"models": {
|
||||
"file": "OpenAIFileObject",
|
||||
"list_files_response": "ListOpenAIFileResponse",
|
||||
"delete_file_response": "OpenAIFileDeleteResponse",
|
||||
},
|
||||
"methods": {
|
||||
"create": "post /v1/files",
|
||||
"list": "get /v1/files",
|
||||
"retrieve": "get /v1/files/{file_id}",
|
||||
"delete": "delete /v1/files/{file_id}",
|
||||
"content": "get /v1/files/{file_id}/content",
|
||||
},
|
||||
},
|
||||
"batches": {
|
||||
"methods": {
|
||||
"create": "post /v1/batches",
|
||||
"list": "get /v1/batches",
|
||||
"retrieve": "get /v1/batches/{batch_id}",
|
||||
"cancel": "post /v1/batches/{batch_id}/cancel",
|
||||
}
|
||||
},
|
||||
"alpha": {
|
||||
"subresources": {
|
||||
"inference": {"methods": {"rerank": "post /v1alpha/inference/rerank"}},
|
||||
"post_training": {
|
||||
"models": {
|
||||
"algorithm_config": "AlgorithmConfig",
|
||||
"post_training_job": "PostTrainingJob",
|
||||
"list_post_training_jobs_response": "ListPostTrainingJobsResponse",
|
||||
},
|
||||
"methods": {
|
||||
"preference_optimize": "post /v1alpha/post-training/preference-optimize",
|
||||
"supervised_fine_tune": "post /v1alpha/post-training/supervised-fine-tune",
|
||||
},
|
||||
"subresources": {
|
||||
"job": {
|
||||
"methods": {
|
||||
"artifacts": "get /v1alpha/post-training/job/artifacts",
|
||||
"cancel": "post /v1alpha/post-training/job/cancel",
|
||||
"status": "get /v1alpha/post-training/job/status",
|
||||
"list": {
|
||||
"paginated": False,
|
||||
"endpoint": "get /v1alpha/post-training/jobs",
|
||||
},
|
||||
}
|
||||
}
|
||||
},
|
||||
},
|
||||
"benchmarks": {
|
||||
"models": {
|
||||
"benchmark": "Benchmark",
|
||||
"list_benchmarks_response": "ListBenchmarksResponse",
|
||||
},
|
||||
"methods": {
|
||||
"retrieve": "get /v1alpha/eval/benchmarks/{benchmark_id}",
|
||||
"list": {
|
||||
"paginated": False,
|
||||
"endpoint": "get /v1alpha/eval/benchmarks",
|
||||
},
|
||||
"register": "post /v1alpha/eval/benchmarks",
|
||||
"unregister": "delete /v1alpha/eval/benchmarks/{benchmark_id}",
|
||||
},
|
||||
},
|
||||
"eval": {
|
||||
"models": {
|
||||
"evaluate_response": "EvaluateResponse",
|
||||
"benchmark_config": "BenchmarkConfig",
|
||||
"job": "Job",
|
||||
},
|
||||
"methods": {
|
||||
"evaluate_rows": "post /v1alpha/eval/benchmarks/{benchmark_id}/evaluations",
|
||||
"run_eval": "post /v1alpha/eval/benchmarks/{benchmark_id}/jobs",
|
||||
"evaluate_rows_alpha": "post /v1alpha/eval/benchmarks/{benchmark_id}/evaluations",
|
||||
"run_eval_alpha": "post /v1alpha/eval/benchmarks/{benchmark_id}/jobs",
|
||||
},
|
||||
"subresources": {
|
||||
"jobs": {
|
||||
"methods": {
|
||||
"cancel": "delete /v1alpha/eval/benchmarks/{benchmark_id}/jobs/{job_id}",
|
||||
"status": "get /v1alpha/eval/benchmarks/{benchmark_id}/jobs/{job_id}",
|
||||
"retrieve": "get /v1alpha/eval/benchmarks/{benchmark_id}/jobs/{job_id}/result",
|
||||
}
|
||||
}
|
||||
},
|
||||
},
|
||||
}
|
||||
},
|
||||
"beta": {
|
||||
"subresources": {
|
||||
"datasets": {
|
||||
"models": {"list_datasets_response": "ListDatasetsResponse"},
|
||||
"methods": {
|
||||
"register": "post /v1beta/datasets",
|
||||
"retrieve": "get /v1beta/datasets/{dataset_id}",
|
||||
"list": {"paginated": False, "endpoint": "get /v1beta/datasets"},
|
||||
"unregister": "delete /v1beta/datasets/{dataset_id}",
|
||||
"iterrows": "get /v1beta/datasetio/iterrows/{dataset_id}",
|
||||
"appendrows": "post /v1beta/datasetio/append-rows/{dataset_id}",
|
||||
},
|
||||
}
|
||||
}
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
HTTP_METHODS = {"get", "post", "put", "patch", "delete", "options", "head"}
|
||||
|
||||
|
||||
@dataclass
|
||||
class Endpoint:
|
||||
method: str
|
||||
path: str
|
||||
extra: dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
@classmethod
|
||||
def from_config(cls, value: Any) -> Endpoint:
|
||||
if isinstance(value, str):
|
||||
method, _, path = value.partition(" ")
|
||||
return cls._from_parts(method, path)
|
||||
if isinstance(value, dict) and "endpoint" in value:
|
||||
method, _, path = value["endpoint"].partition(" ")
|
||||
extra = {k: v for k, v in value.items() if k != "endpoint"}
|
||||
endpoint = cls._from_parts(method, path)
|
||||
endpoint.extra.update(extra)
|
||||
return endpoint
|
||||
raise ValueError(f"Unsupported endpoint value: {value!r}")
|
||||
|
||||
@classmethod
|
||||
def _from_parts(cls, method: str, path: str) -> Endpoint:
|
||||
method = method.strip().lower()
|
||||
path = path.strip()
|
||||
if method not in HTTP_METHODS:
|
||||
raise ValueError(f"Unsupported HTTP method for Stainless config: {method!r}")
|
||||
if not path.startswith("/"):
|
||||
raise ValueError(f"Endpoint path must start with '/': {path!r}")
|
||||
return cls(method=method, path=path)
|
||||
|
||||
def to_config(self) -> Any:
|
||||
if not self.extra:
|
||||
return f"{self.method} {self.path}"
|
||||
data = dict(self.extra)
|
||||
data["endpoint"] = f"{self.method} {self.path}"
|
||||
return data
|
||||
|
||||
def route_key(self) -> str:
|
||||
return f"{self.method} {self.path}"
|
||||
|
||||
|
||||
@dataclass
|
||||
class Resource:
|
||||
models: dict[str, str] | None = None
|
||||
methods: dict[str, Endpoint] = field(default_factory=dict)
|
||||
subresources: dict[str, Resource] = field(default_factory=dict)
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, data: dict[str, Any]) -> Resource:
|
||||
models = data.get("models")
|
||||
methods = {name: Endpoint.from_config(value) for name, value in data.get("methods", {}).items()}
|
||||
subresources = {name: cls.from_dict(value) for name, value in data.get("subresources", {}).items()}
|
||||
return cls(models=models, methods=methods, subresources=subresources)
|
||||
|
||||
def to_config(self) -> dict[str, Any]:
|
||||
result: dict[str, Any] = {}
|
||||
if self.models:
|
||||
result["models"] = self.models
|
||||
if self.methods:
|
||||
result["methods"] = {name: endpoint.to_config() for name, endpoint in self.methods.items()}
|
||||
if self.subresources:
|
||||
result["subresources"] = {name: resource.to_config() for name, resource in self.subresources.items()}
|
||||
return result
|
||||
|
||||
def collect_endpoint_paths(self) -> set[str]:
|
||||
paths = {endpoint.route_key() for endpoint in self.methods.values()}
|
||||
for subresource in self.subresources.values():
|
||||
paths.update(subresource.collect_endpoint_paths())
|
||||
return paths
|
||||
|
||||
def iter_endpoints(self, prefix: str) -> Iterator[tuple[str, str]]:
|
||||
for method_name, endpoint in self.methods.items():
|
||||
label = f"{prefix}.{method_name}" if prefix else method_name
|
||||
yield endpoint.route_key(), label
|
||||
for sub_name, subresource in self.subresources.items():
|
||||
sub_prefix = f"{prefix}.{sub_name}" if prefix else sub_name
|
||||
yield from subresource.iter_endpoints(sub_prefix)
|
||||
|
||||
|
||||
_RESOURCES = {name: Resource.from_dict(data) for name, data in ALL_RESOURCES.items()}
|
||||
|
||||
|
||||
def _load_openapi_paths(openapi_path: Path) -> set[str]:
|
||||
spec = yaml.safe_load(openapi_path.read_text()) or {}
|
||||
paths: set[str] = set()
|
||||
for path, path_item in (spec.get("paths") or {}).items():
|
||||
if not isinstance(path_item, dict):
|
||||
continue
|
||||
for method, operation in path_item.items():
|
||||
if not isinstance(operation, dict):
|
||||
continue
|
||||
paths.add(f"{str(method).lower()} {path}")
|
||||
return paths
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class StainlessConfig:
|
||||
organization: dict[str, Any]
|
||||
security: list[Any]
|
||||
security_schemes: dict[str, Any]
|
||||
targets: dict[str, Any]
|
||||
client_settings: dict[str, Any]
|
||||
environments: dict[str, Any]
|
||||
pagination: list[dict[str, Any]]
|
||||
settings: dict[str, Any]
|
||||
openapi: dict[str, Any]
|
||||
readme: dict[str, Any]
|
||||
resources: dict[str, Resource]
|
||||
|
||||
@classmethod
|
||||
def make(cls) -> StainlessConfig:
|
||||
return cls(
|
||||
organization=ORGANIZATION,
|
||||
security=SECURITY,
|
||||
security_schemes=SECURITY_SCHEMES,
|
||||
targets=TARGETS,
|
||||
client_settings=CLIENT_SETTINGS,
|
||||
environments=ENVIRONMENTS,
|
||||
pagination=PAGINATION,
|
||||
settings=SETTINGS,
|
||||
openapi=OPENAPI,
|
||||
readme=README,
|
||||
resources=dict(_RESOURCES),
|
||||
)
|
||||
|
||||
def referenced_paths(self) -> set[str]:
|
||||
paths: set[str] = set()
|
||||
for resource in self.resources.values():
|
||||
paths.update(resource.collect_endpoint_paths())
|
||||
paths.update(self.readme_endpoint_paths())
|
||||
return paths
|
||||
|
||||
def readme_endpoint_paths(self) -> set[str]:
|
||||
example_requests = self.readme.get("example_requests", {}) if self.readme else {}
|
||||
paths: set[str] = set()
|
||||
for entry in example_requests.values():
|
||||
endpoint = entry.get("endpoint") if isinstance(entry, dict) else None
|
||||
if isinstance(endpoint, str):
|
||||
method, _, route = endpoint.partition(" ")
|
||||
method = method.strip().lower()
|
||||
route = route.strip()
|
||||
if method and route:
|
||||
paths.add(f"{method} {route}")
|
||||
return paths
|
||||
|
||||
def endpoint_map(self) -> dict[str, list[str]]:
|
||||
mapping: dict[str, list[str]] = {}
|
||||
for resource_name, resource in self.resources.items():
|
||||
for route, label in resource.iter_endpoints(resource_name):
|
||||
mapping.setdefault(route, []).append(label)
|
||||
return mapping
|
||||
|
||||
def validate_unique_endpoints(self) -> None:
|
||||
duplicates: dict[str, list[str]] = {}
|
||||
for route, labels in self.endpoint_map().items():
|
||||
top_levels = {label.split(".", 1)[0] for label in labels}
|
||||
if len(top_levels) > 1:
|
||||
duplicates[route] = labels
|
||||
if duplicates:
|
||||
formatted = "\n".join(
|
||||
f" - {route} defined in: {', '.join(sorted(labels))}" for route, labels in sorted(duplicates.items())
|
||||
)
|
||||
raise ValueError("Duplicate endpoints found across resources:\n" + formatted)
|
||||
|
||||
def validate_readme_endpoints(self) -> None:
|
||||
resource_paths: set[str] = set()
|
||||
for resource in self.resources.values():
|
||||
resource_paths.update(resource.collect_endpoint_paths())
|
||||
missing = sorted(path for path in self.readme_endpoint_paths() if path not in resource_paths)
|
||||
if missing:
|
||||
formatted = "\n".join(f" - {path}" for path in missing)
|
||||
raise ValueError("README example endpoints are not present in Stainless resources:\n" + formatted)
|
||||
|
||||
def to_dict(self) -> dict[str, Any]:
|
||||
cfg: dict[str, Any] = {}
|
||||
for section in SECTION_ORDER:
|
||||
if section == "resources":
|
||||
cfg[section] = {name: resource.to_config() for name, resource in self.resources.items()}
|
||||
continue
|
||||
cfg[section] = getattr(self, section)
|
||||
return cfg
|
||||
|
||||
def validate_against_openapi(self, openapi_path: Path) -> None:
|
||||
if not openapi_path.exists():
|
||||
raise FileNotFoundError(f"OpenAPI spec not found at {openapi_path}")
|
||||
spec_paths = _load_openapi_paths(openapi_path)
|
||||
config_paths = self.referenced_paths()
|
||||
missing = sorted(path for path in config_paths if path not in spec_paths)
|
||||
if missing:
|
||||
formatted = "\n".join(f" - {path}" for path in missing)
|
||||
raise ValueError("Stainless config references missing endpoints:\n" + formatted)
|
||||
|
||||
def validate(self, openapi_path: Path | None = None) -> None:
|
||||
self.validate_unique_endpoints()
|
||||
self.validate_readme_endpoints()
|
||||
if openapi_path is not None:
|
||||
self.validate_against_openapi(openapi_path)
|
||||
|
||||
|
||||
def build_config() -> dict[str, Any]:
|
||||
return StainlessConfig.make().to_dict()
|
||||
|
||||
|
||||
def write_config(repo_root: Path, openapi_path: Path | None = None) -> Path:
|
||||
stainless_config = StainlessConfig.make()
|
||||
spec_path = (openapi_path or (repo_root / "client-sdks" / "stainless" / "openapi.yml")).resolve()
|
||||
stainless_config.validate(spec_path)
|
||||
yaml_text = yaml.safe_dump(stainless_config.to_dict(), sort_keys=False)
|
||||
output = repo_root / "client-sdks" / "stainless" / "config.yml"
|
||||
output.write_text(HEADER + yaml_text)
|
||||
return output
|
||||
|
||||
|
||||
def main() -> None:
|
||||
repo_root = Path(__file__).resolve().parents[3]
|
||||
output = write_config(repo_root)
|
||||
print(f"Wrote Stainless config: {output}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
Add table
Add a link
Reference in a new issue