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chore: import upstream snapshot with attribution
2026-07-13 12:59:56 +08:00

584 lines
20 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""Tests for PDF / document attachment translation on external providers.
Studio adds a normalised `input_document` content part on
ChatCompletionRequest so the frontend needn't know the per-provider
attachment shape:
- Anthropic: `{type:"document", source:{type:"base64"|"url", ...}}`
- OpenAI Responses: `{type:"input_file", file_data|file_url, filename?}`
Pins the translation shape on both paths for base64 data URIs and remote
URLs (with optional filename), and confirms unknown / empty document
parts are dropped without breaking the request.
"""
import asyncio
import json
import httpx
from core.inference import external_provider as ep_mod
from core.inference.external_provider import ExternalProviderClient
def _drive(coro):
return asyncio.new_event_loop().run_until_complete(coro)
def _capture(monkeypatch, *, provider: str, base_url: str, messages) -> dict:
captured: dict = {}
def handler(request: httpx.Request) -> httpx.Response:
captured["body"] = json.loads(request.content.decode("utf-8"))
if provider == "anthropic":
body = b"event: message_stop\n" b'data: {"type": "message_stop"}\n\n'
else:
body = (
b"event: response.completed\n"
b'data: {"type":"response.completed",'
b'"response":{"output":[],"usage":{"input_tokens":0,'
b'"output_tokens":0}}}\n\n'
)
return httpx.Response(
200,
content = body,
headers = {"content-type": "text/event-stream"},
)
monkeypatch.setattr(
ep_mod,
"_http_client",
httpx.AsyncClient(transport = httpx.MockTransport(handler)),
)
async def run():
client = ExternalProviderClient(
provider_type = provider,
base_url = base_url,
api_key = "sk-test",
)
kwargs = {
"messages": messages,
"model": "claude-opus-4-7" if provider == "anthropic" else "gpt-5.5",
"temperature": 0.7,
"top_p": 0.95,
"max_tokens": 32,
}
if provider == "openai":
kwargs["reasoning_effort"] = "medium"
async for _ in client.stream_chat_completion(**kwargs):
pass
await client.close()
_drive(run())
return captured
_TINY_PDF_B64 = "JVBERi0xLjQKJcOkw7zDtsOfCjEgMCBvYmoKPDw+PgplbmRvYmoK"
_PDF_DATA_URI = f"data:application/pdf;base64,{_TINY_PDF_B64}"
# ── Anthropic translation ───────────────────────────────────────────
def _strip_cache(p: dict) -> dict:
# Strip the prompt-cache cache_control off the last user block so this
# test focuses on translation, not the caching layer.
return {k: v for k, v in p.items() if k != "cache_control"}
def test_anthropic_base64_pdf_becomes_document_block(monkeypatch):
captured = _capture(
monkeypatch,
provider = "anthropic",
base_url = "https://api.anthropic.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Summarise this paper."},
{
"type": "input_document",
"file_data": _PDF_DATA_URI,
"filename": "paper.pdf",
},
],
}
],
)
user_msg = captured["body"]["messages"][0]
parts = user_msg["content"]
types = [p.get("type") for p in parts]
assert "document" in types, parts
doc = _strip_cache(next(p for p in parts if p.get("type") == "document"))
# citations:{enabled:true} opts into Anthropic's citation pipeline;
# without it the citations_delta handler is a no-op.
assert doc == {
"type": "document",
"source": {
"type": "base64",
"media_type": "application/pdf",
"data": _TINY_PDF_B64,
},
"citations": {"enabled": True},
"title": "paper.pdf",
}
def test_anthropic_url_pdf_becomes_document_block(monkeypatch):
captured = _capture(
monkeypatch,
provider = "anthropic",
base_url = "https://api.anthropic.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Read this URL."},
{
"type": "input_document",
"file_url": "https://example.com/doc.pdf",
},
],
}
],
)
parts = captured["body"]["messages"][0]["content"]
doc = _strip_cache(next(p for p in parts if p.get("type") == "document"))
assert doc == {
"type": "document",
"source": {"type": "url", "url": "https://example.com/doc.pdf"},
"citations": {"enabled": True},
}
def test_anthropic_empty_document_part_is_dropped(monkeypatch):
captured = _capture(
monkeypatch,
provider = "anthropic",
base_url = "https://api.anthropic.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Hi."},
{"type": "input_document"}, # nothing usable
],
}
],
)
parts = captured["body"]["messages"][0]["content"]
types = [p.get("type") for p in parts]
assert "document" not in types, parts
def test_anthropic_empty_only_document_drops_whole_message(monkeypatch):
# If the only part is an unparseable input_document, the helper must not
# append an empty-content message (Anthropic 400s on "at least one block").
captured = _capture(
monkeypatch,
provider = "anthropic",
base_url = "https://api.anthropic.com/v1",
messages = [
{"role": "user", "content": [{"type": "input_document"}]},
{"role": "user", "content": "but THIS one is fine"},
],
)
msgs = captured["body"]["messages"]
# Empty-content message skipped; only the second remains.
assert len(msgs) == 1, msgs
def test_anthropic_empty_data_uri_payload_is_dropped(monkeypatch):
# A `data:application/pdf;base64,` with empty/whitespace payload makes an
# empty `source.data` that Anthropic 400s on; filter it before the wire.
captured = _capture(
monkeypatch,
provider = "anthropic",
base_url = "https://api.anthropic.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "still here"},
{
"type": "input_document",
"file_data": "data:application/pdf;base64,",
"filename": "empty.pdf",
},
{
"type": "input_document",
"file_data": "data:application/pdf;base64, ",
"filename": "whitespace.pdf",
},
],
}
],
)
parts = captured["body"]["messages"][0]["content"]
assert all(p.get("type") != "document" for p in parts), parts
def test_anthropic_empty_data_uri_falls_back_to_file_url(monkeypatch):
# The empty-data-URI -> file_url fallback existed on OpenAI but not
# Anthropic, which discarded a valid file_url on the same part. Mirror
# OpenAI so a malformed inline payload + remote URL still attaches.
captured = _capture(
monkeypatch,
provider = "anthropic",
base_url = "https://api.anthropic.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Read this."},
{
"type": "input_document",
"file_data": "data:application/pdf;base64,",
"file_url": "https://example.com/doc.pdf",
"filename": "doc.pdf",
},
],
}
],
)
parts = captured["body"]["messages"][0]["content"]
doc = _strip_cache(next(p for p in parts if p.get("type") == "document"))
# base64 source MUST NOT reach the wire; URL source survives.
assert doc == {
"type": "document",
"source": {"type": "url", "url": "https://example.com/doc.pdf"},
"citations": {"enabled": True},
"title": "doc.pdf",
}
def test_anthropic_whitespace_only_data_uri_falls_back_to_file_url(monkeypatch):
captured = _capture(
monkeypatch,
provider = "anthropic",
base_url = "https://api.anthropic.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Read this."},
{
"type": "input_document",
"file_data": "data:application/pdf;base64, ",
"file_url": "https://example.com/doc.pdf",
},
],
}
],
)
parts = captured["body"]["messages"][0]["content"]
doc = _strip_cache(next(p for p in parts if p.get("type") == "document"))
assert doc == {
"type": "document",
"source": {"type": "url", "url": "https://example.com/doc.pdf"},
"citations": {"enabled": True},
}
# ── OpenAI Responses translation ────────────────────────────────────
def test_openai_base64_pdf_becomes_input_file(monkeypatch):
captured = _capture(
monkeypatch,
provider = "openai",
base_url = "https://api.openai.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Summarise this paper."},
{
"type": "input_document",
"file_data": _PDF_DATA_URI,
"filename": "paper.pdf",
},
],
}
],
)
user_msg = captured["body"]["input"][0]
parts = user_msg["content"]
fileblk = next(p for p in parts if p.get("type") == "input_file")
assert fileblk == {"type": "input_file", "file_data": _PDF_DATA_URI, "filename": "paper.pdf"}
def test_openai_url_pdf_becomes_input_file(monkeypatch):
captured = _capture(
monkeypatch,
provider = "openai",
base_url = "https://api.openai.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Read this URL."},
{
"type": "input_document",
"file_url": "https://example.com/doc.pdf",
},
],
}
],
)
parts = captured["body"]["input"][0]["content"]
fileblk = next(p for p in parts if p.get("type") == "input_file")
assert fileblk == {"type": "input_file", "file_url": "https://example.com/doc.pdf"}
def test_openai_empty_data_uri_falls_back_to_file_url(monkeypatch):
# An empty `data:application/pdf;base64,` payload was preferred over a valid
# `file_url` in the same part, sending `file_data=""` and 400ing. The
# translator must treat empty data URIs as missing and recover via file_url.
captured = _capture(
monkeypatch,
provider = "openai",
base_url = "https://api.openai.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Read this."},
{
"type": "input_document",
"file_data": "data:application/pdf;base64,",
"file_url": "https://example.com/doc.pdf",
"filename": "doc.pdf",
},
],
}
],
)
parts = captured["body"]["input"][0]["content"]
fileblk = next(p for p in parts if p.get("type") == "input_file")
# file_data MUST NOT reach the wire; file_url survives.
assert "file_data" not in fileblk, fileblk
assert fileblk["file_url"] == "https://example.com/doc.pdf"
assert fileblk["filename"] == "doc.pdf"
def test_openai_whitespace_only_data_uri_falls_back_to_file_url(monkeypatch):
captured = _capture(
monkeypatch,
provider = "openai",
base_url = "https://api.openai.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Read this."},
{
"type": "input_document",
"file_data": "data:application/pdf;base64, ",
"file_url": "https://example.com/doc.pdf",
},
],
}
],
)
parts = captured["body"]["input"][0]["content"]
fileblk = next(p for p in parts if p.get("type") == "input_file")
assert "file_data" not in fileblk, fileblk
assert fileblk["file_url"] == "https://example.com/doc.pdf"
def test_openai_empty_data_uri_without_fallback_is_dropped(monkeypatch):
# Only signal is an empty data URI (no file_url): skip the whole part
# rather than send `file_data=""`.
captured = _capture(
monkeypatch,
provider = "openai",
base_url = "https://api.openai.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Hi."},
{
"type": "input_document",
"file_data": "data:application/pdf;base64,",
"filename": "empty.pdf",
},
],
}
],
)
parts = captured["body"]["input"][0]["content"]
types = [p.get("type") for p in parts]
assert "input_file" not in types, parts
def test_openai_empty_document_part_is_dropped(monkeypatch):
captured = _capture(
monkeypatch,
provider = "openai",
base_url = "https://api.openai.com/v1",
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": "Hi."},
{"type": "input_document"},
],
}
],
)
parts = captured["body"]["input"][0]["content"]
types = [p.get("type") for p in parts]
assert "input_file" not in types, parts
# ── Pydantic schema + builder pass-through ──────────────────────────
# The tests above call the client with hand-built dicts, bypassing the schema
# and _build_external_messages. The tests below parse an input_document part
# through the real schema + builder and assert it survives to the client dict.
def test_chat_message_accepts_input_document_part():
from models.inference import ChatMessage
msg = ChatMessage.model_validate(
{
"role": "user",
"content": [
{"type": "text", "text": "look"},
{
"type": "input_document",
"file_data": _PDF_DATA_URI,
"filename": "paper.pdf",
"media_type": "application/pdf",
},
],
}
)
assert isinstance(msg.content, list)
assert msg.content[1].type == "input_document"
assert msg.content[1].file_data == _PDF_DATA_URI
assert msg.content[1].filename == "paper.pdf"
assert msg.content[1].media_type == "application/pdf"
def test_build_external_messages_passes_input_document_for_anthropic_and_openai():
# Both providers' stream helpers translate input_document (Anthropic ->
# {type:"document"}, OpenAI Responses -> {type:"input_file"}), so the
# part round-trips through the builder unchanged on those routes.
from models.inference import ChatMessage
from routes.inference import _build_external_messages
msgs = [
ChatMessage.model_validate(
{
"role": "user",
"content": [
{"type": "text", "text": "summarise"},
{
"type": "input_document",
"file_url": "https://example.com/doc.pdf",
"filename": "doc.pdf",
},
],
}
)
]
for provider in ("anthropic", "openai"):
out = _build_external_messages(msgs, supports_vision = True, provider_type = provider)
assert len(out) == 1, (provider, out)
parts = out[0]["content"]
assert parts[0] == {"type": "text", "text": "summarise"}, provider
assert parts[1] == {
"type": "input_document",
"file_url": "https://example.com/doc.pdf",
"filename": "doc.pdf",
}, provider
def test_build_external_messages_strips_input_document_for_unmapped_providers():
# Codex P1 follow-up: gemini / mistral / kimi / openrouter / deepseek
# / custom use generic /chat/completions passthrough that forwards
# `messages` verbatim, so an `input_document` part fails the upstream
# validator. The builder must strip it for any provider whose stream
# helper doesn't translate it.
from models.inference import ChatMessage
from routes.inference import _build_external_messages
msgs = [
ChatMessage.model_validate(
{
"role": "user",
"content": [
{"type": "text", "text": "summarise"},
{
"type": "input_document",
"file_url": "https://example.com/doc.pdf",
"filename": "doc.pdf",
},
],
}
)
]
for provider in ("gemini", "mistral", "kimi", "openrouter", "deepseek", "qwen"):
out = _build_external_messages(msgs, supports_vision = True, provider_type = provider)
assert len(out) == 1, (provider, out)
parts = out[0]["content"]
types = [p.get("type") for p in parts if isinstance(p, dict)]
assert "input_document" not in types, (provider, parts)
# Text part survives.
assert {"type": "text", "text": "summarise"} in parts, (provider, parts)
def test_build_external_messages_strips_input_document_when_provider_type_unknown():
# Defensive: legacy callers without provider_type must not leak the
# part to an unknown destination.
from models.inference import ChatMessage
from routes.inference import _build_external_messages
msgs = [
ChatMessage.model_validate(
{
"role": "user",
"content": [
{"type": "text", "text": "summarise"},
{
"type": "input_document",
"file_data": _PDF_DATA_URI,
},
],
}
)
]
out = _build_external_messages(msgs, supports_vision = True)
parts = out[0]["content"]
types = [p.get("type") for p in parts if isinstance(p, dict)]
assert "input_document" not in types, parts
def test_build_external_messages_drops_input_document_for_non_vision_provider():
from models.inference import ChatMessage
from routes.inference import _build_external_messages
msgs = [
ChatMessage.model_validate(
{
"role": "user",
"content": [
{"type": "text", "text": "summarise"},
{
"type": "input_document",
"file_data": _PDF_DATA_URI,
},
],
}
)
]
out = _build_external_messages(msgs, supports_vision = False)
assert out == [{"role": "user", "content": "summarise"}]