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