* Studio: wire OpenAI Responses server-side context compaction
The OpenAI Responses API accepts a `context_management` field that
enables server-side compaction. When the rendered prompt crosses the
configured threshold, the API runs a server-side compaction step and
the request continues against the compacted prefix. No beta header
and no dated version pin are required, per the docs.
Changes:
- Add `compaction_threshold: Optional[int]` (ge=1_000, le=2_000_000)
to ChatCompletionRequest. Thread through `routes/inference.py` ->
`stream_chat_completion` -> `_stream_openai_responses`.
- In `_stream_openai_responses`, when threshold is set AND the base
URL points at cloud OpenAI (api.openai.com), attach
`context_management: [{type:"compaction", compact_threshold:N}]`
to the outbound body. Non-cloud bases (ollama, llama.cpp, "custom"
presets) silently drop the field so we don't 400 those servers.
- Add `test_openai_compaction.py` with 4 cases: cloud OpenAI sets
the field verbatim, low-threshold probe passes through (we don't
clamp on the OpenAI side because the API accepts whatever),
non-cloud base drops the field, omitted threshold leaves body
untouched.
Live verified against the real OpenAI API on gpt-5.5:
`context_management:[{type:"compaction", compact_threshold:200000}]`
returns 200 with no error.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: accept Azure OpenAI base URLs + raise compaction floor
Two reviewer follow-ups on the OpenAI compaction PR:
1. The `is_openai_cloud = "api.openai.com" in self.base_url` check
excluded Azure OpenAI Foundry, even though Azure exposes the
same /v1/responses extensions (context_management,
prompt_cache_retention, container shell). Users on Azure saw
their compaction toggle silently no-op. Broadened the check to
also match `*.openai.azure.com` and made it case-insensitive so
URLs copy-pasted from the Azure portal still resolve. Non-cloud
OpenAI-compatible servers (ollama / llama.cpp / vLLM / "custom"
preset) still fall outside the gate.
2. The schema floor on compaction_threshold was ge=1_000, which is
well below the upstream Responses API's effective minimum
(vercel/ai#12486, langchain-ai/langchain#35464 report
`compact_threshold is not enabled` 400s on Azure at 100k; cloud
uses 200k as the canonical example). Raised the floor to 10k
so obvious typos surface as a clean 422 from FastAPI rather than
an opaque upstream 400 the user has to debug from the SSE
stream.
Tests added: Azure base URL carries both context_management and
prompt_cache_retention; mixed-case Azure URLs match; schema rejects
9_999 and accepts 10_000.
* Address review: drop schema-level compaction floor (cross-provider regression)
Codex P2 follow-up on the previous floor bump: ge=10_000 was
enforced globally at the ChatCompletionRequest layer, but the field
is documented as a no-op on every non-cloud OpenAI base and every
non-OpenAI provider. With the global floor, an Anthropic / ollama
/ llama.cpp / custom request that happens to carry compaction_threshold
below 10k was rejected with 422 at request validation time instead
of being silently ignored as the description promised.
Reverted the schema floor to ge=1 (any positive int) and rewrote
the description to call out per-provider routing: OpenAI cloud's
effective floor is around 200k and surfaces upstream 400s below
that; _stream_anthropic clamps sub-50k values up. Per-provider
helpers stay the single source of truth on the floor.
Test updated to pin: zero is still rejected, but every positive
value (1, 5_000, 9_999, 10_000, 200_000) passes schema validation.
* Address CodeQL: hostname-anchored OpenAI cloud detection
CodeQL py/incomplete-url-substring-sanitization fired on
`".openai.azure.com" in _base`. An attacker who controls the
configured base_url could slip cloud-only request body fields
(prompt_cache_retention, context_management compaction, container
shell) to an arbitrary server with:
https://evil.com/api.openai.com/v1
https://api.openai.com.attacker.com/v1
https://attacker.com/.openai.azure.com/v1
https://my-resource.openai.azure.com.attacker.com/openai/v1
Replaced the substring check with a `_is_openai_family_cloud`
helper that runs urllib.parse.urlparse on the URL and matches the
lowercased hostname exactly (`api.openai.com`) or via `endswith`
on the leading-dot suffix (`.openai.azure.com`). Both halves are
host-anchored so path / fake-subdomain bypasses fail.
Test added: every attacker-controlled bypass shape above must NOT
carry context_management OR prompt_cache_retention on the wire.
Existing Azure and openai.com tests still pass.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address review: scope compaction_threshold description to OpenAI on this branch
Codex P2: the field description on this PR mentioned Anthropic
compaction behavior, but the Anthropic wiring lives on PR 5686
(separate branch). On feat/openai-compaction alone, _stream_anthropic
has no compaction_threshold parameter, so the field is silently
ignored for Anthropic requests and the doc claim was misleading.
Trimmed the description to OpenAI cloud + Azure Foundry only on
this branch. PR 5686 already re-adds the Anthropic clause via its
own change, so the rebase / merge order on main will land the
combined description naturally once both PRs ship.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
226 lines
8.1 KiB
Python
226 lines
8.1 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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"""Unit tests for OpenAI Responses API context_management wiring.
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OpenAI's Responses API supports server-side compaction via
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``context_management: [{type:"compaction", compact_threshold:N}]``.
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There is no beta header and no dated version pin; the threshold is
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silently accepted and the API runs the compaction step when the
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rendered prompt crosses it.
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These tests pin: the body shape when threshold is set on cloud OpenAI,
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the silent no-op when the base URL is non-cloud, and the
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omitted-threshold pass-through.
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"""
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import asyncio
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import json
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import httpx
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from core.inference import external_provider as ep_mod
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from core.inference.external_provider import ExternalProviderClient
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def _drive(coro):
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return asyncio.new_event_loop().run_until_complete(coro)
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def _capture(monkeypatch, *, base_url: str, threshold) -> dict:
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captured: dict = {}
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def handler(request: httpx.Request) -> httpx.Response:
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captured["body"] = json.loads(request.content.decode("utf-8"))
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# Send an empty Responses-shaped SSE stream so the helper exits
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# cleanly.
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return httpx.Response(
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200,
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content = (
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b"event: response.completed\n"
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b'data: {"type":"response.completed",'
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b'"response":{"output":[],"usage":{"input_tokens":0,'
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b'"output_tokens":0}}}\n\n'
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),
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headers = {"content-type": "text/event-stream"},
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)
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monkeypatch.setattr(
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ep_mod,
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"_http_client",
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httpx.AsyncClient(transport = httpx.MockTransport(handler)),
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)
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async def run():
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client = ExternalProviderClient(
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provider_type = "openai",
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base_url = base_url,
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api_key = "sk-test",
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)
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async for _ in client.stream_chat_completion(
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messages = [{"role": "user", "content": "hi"}],
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model = "gpt-5.5",
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temperature = 0.7,
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top_p = 0.95,
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max_tokens = 32,
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reasoning_effort = "medium",
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compaction_threshold = threshold,
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):
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pass
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await client.close()
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_drive(run())
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return captured
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# ── cloud OpenAI carries the compaction field verbatim ──────────────
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def test_cloud_openai_sets_compaction_block(monkeypatch):
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captured = _capture(
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monkeypatch,
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base_url = "https://api.openai.com/v1",
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threshold = 200_000,
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)
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assert captured["body"].get("context_management") == [
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{"type": "compaction", "compact_threshold": 200_000}
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]
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def test_cloud_openai_below_default_threshold_passes_through(monkeypatch):
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# Studio doesn't clamp the OpenAI side -- the API accepts whatever
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# the caller sends, so a small probe like 60k still goes through.
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captured = _capture(
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monkeypatch,
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base_url = "https://api.openai.com/v1",
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threshold = 60_000,
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)
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assert captured["body"]["context_management"] == [
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{"type": "compaction", "compact_threshold": 60_000}
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]
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# ── non-cloud bases drop the field ──────────────────────────────────
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def test_non_cloud_base_silently_drops_compaction(monkeypatch):
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# ollama / llama.cpp / "custom" presets collapse to provider="openai"
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# but don't implement context_management. Sending the field would
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# 400 those servers, so it must NOT appear on the wire.
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captured = _capture(
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monkeypatch,
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base_url = "http://127.0.0.1:11434/v1",
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threshold = 200_000,
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)
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assert "context_management" not in captured["body"]
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# ── Azure OpenAI Foundry is treated as cloud ────────────────────────
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def test_azure_openai_base_url_carries_compaction_block(monkeypatch):
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# Azure OpenAI Foundry exposes the same /v1/responses extensions
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# (context_management, prompt_cache_retention, container shell)
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# under a *.openai.azure.com base URL. Treat it as cloud so the
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# compaction field actually reaches the API.
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captured = _capture(
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monkeypatch,
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base_url = "https://my-resource.openai.azure.com/openai/v1",
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threshold = 200_000,
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)
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assert captured["body"].get("context_management") == [
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{"type": "compaction", "compact_threshold": 200_000}
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]
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# Sibling Azure-cloud extension: prompt_cache_retention should also
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# be set so caching works the same way on Azure deployments.
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assert captured["body"].get("prompt_cache_retention") == "24h"
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def test_azure_openai_mixed_case_base_url_matches(monkeypatch):
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# The match is case-insensitive so URLs copy-pasted from the Azure
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# portal (which sometimes capitalise the resource name) still get
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# the cloud-only fields.
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captured = _capture(
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monkeypatch,
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base_url = "https://My-Resource.OpenAI.Azure.Com/openai/v1",
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threshold = 50_000,
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)
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assert captured["body"].get("context_management") == [
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{"type": "compaction", "compact_threshold": 50_000}
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]
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def test_cloud_gate_uses_hostname_not_substring(monkeypatch):
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# CodeQL py/incomplete-url-substring-sanitization: an attacker who
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# controls the configured base_url could embed `api.openai.com` or
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# `.openai.azure.com` as part of a path or a subdomain on an
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# arbitrary host to slip the cloud-only request body fields to a
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# server they control. The hostname-anchored helper must reject
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# both shapes.
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for evil in [
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"https://evil.com/api.openai.com/v1",
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"https://api.openai.com.attacker.com/v1",
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"https://attacker.com/.openai.azure.com/v1",
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"https://my-resource.openai.azure.com.attacker.com/openai/v1",
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]:
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captured = _capture(
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monkeypatch,
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base_url = evil,
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threshold = 200_000,
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)
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assert "context_management" not in captured["body"], evil
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assert "prompt_cache_retention" not in captured["body"], evil
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# ── omitted threshold leaves body untouched ─────────────────────────
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def test_omitted_threshold_no_body_field(monkeypatch):
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captured = _capture(
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monkeypatch,
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base_url = "https://api.openai.com/v1",
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threshold = None,
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)
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assert "context_management" not in captured["body"]
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# ── schema floor matches what the upstream API actually accepts ────
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def test_chat_completion_request_accepts_any_positive_compaction_threshold():
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# Codex follow-up: the field is documented as a no-op for non-cloud
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# OpenAI bases and every non-OpenAI provider, so a cross-provider
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# schema floor would 422 perfectly valid Anthropic / ollama /
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# llama.cpp requests that happen to carry the field. Keep schema
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# floor at ge=1 (any positive int) and rely on per-provider
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# helpers (_stream_openai_responses / _stream_anthropic) to
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# enforce or clamp the real floor.
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import pytest as _pytest
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from models.inference import ChatCompletionRequest
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# Non-positive values still rejected so blank-string posts don't
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# sneak through.
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with _pytest.raises(Exception):
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ChatCompletionRequest.model_validate(
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{
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"model": "default",
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"messages": [{"role": "user", "content": "hi"}],
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"compaction_threshold": 0,
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}
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)
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# Any positive int passes schema validation, including values that
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# would be no-ops on the OpenAI cloud path. This is intentional --
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# the OpenAI helper drops the field on non-cloud bases and
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# forwards-as-is on cloud bases; if the value is below the model's
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# effective floor, the upstream API surfaces the error.
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for v in (1, 5_000, 9_999, 10_000, 200_000):
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req = ChatCompletionRequest.model_validate(
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{
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"model": "default",
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"messages": [{"role": "user", "content": "hi"}],
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"compaction_threshold": v,
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}
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)
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assert req.compaction_threshold == v
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