# 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"}]