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- Switch all per-cell tests from @pytest.mark.parametrize("model", ...)
(3 sequential invocations) to a single test that fans out to all 3
Claude tiers via run_claude_models_parallel. Per-cell wall time is now
bounded by the slowest model rather than the sum.
- Add 5 new v0 feature dirs (5 providers each, 25 new test files):
web_search, pdf_input, prompt_caching_1h,
tool_use_streaming, thinking_with_tool_use
Manifest expanded to match.
- Add cross-process token-bucket rate limiter (rate_limiter.py + tests)
so xdist workers stay under per-provider req/s limits during full-grid
runs. New env knobs: LITELLM_COMPAT_RATE_{ANTHROPIC,AZURE,VERTEX_AI,
BEDROCK_CONVERSE,BEDROCK_INVOKE}.
- conftest.py: write per-worker shards under <artifact>.shards/, merge
in the controller; preserve the "don't write empty artifact" guard so
unit-test runs don't clobber a real compat-results.json.
- Vertex test_config.yaml: route project/location through env so the
cron VM can target a different GCP project than the upstream default.
- Add run_compat.sh wrapper for binary-searching ideal req/s per
provider against compat-rate-limit-summary.json output.
176 lines
6.2 KiB
Python
176 lines
6.2 KiB
Python
"""pdf_input x Anthropic.
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Drive the real `claude` CLI against a running LiteLLM proxy that routes
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to Anthropic, write a tiny valid PDF to disk, allow the built-in `Read`
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tool, and ask Claude to read the PDF and report what it contains.
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The Read tool inlines the PDF bytes as `document` content blocks on the
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next assistant turn, which is exactly the gateway path we want to
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exercise: it's distinct from image content blocks (which are tested in
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`vision/`) and uses a different transformation in LiteLLM's Anthropic
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provider. We assert the upstream produces a non-empty reply that
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references the contents of the PDF — proving the proxy preserved the
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document content block end-to-end.
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The (feature, provider) for this cell is inferred from the file path by
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`tests/claude_code/conftest.py`:
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tests/claude_code/pdf_input/test_anthropic.py
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^^^^^^^^^ ^^^^^^^^^
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feature_id provider
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"""
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from __future__ import annotations
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import os
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import pytest
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from tests.claude_code.cli_driver import (
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ClaudeCLIError,
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failure_diagnostic,
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run_claude_models_parallel,
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)
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PROXY_BASE_URL_ENV = "LITELLM_PROXY_BASE_URL"
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PROXY_API_KEY_ENV = "LITELLM_PROXY_API_KEY"
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ANTHROPIC_MODELS = [
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"claude-haiku-4-5",
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"claude-sonnet-4-6",
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"claude-opus-4-7",
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]
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# Smallest valid PDF that renders a single visible word ("PONG"). Built
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# inline rather than checked in as a binary fixture so the test stays
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# self-contained and the marker word is easy to grep for in CI logs.
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# The structure is a hand-crafted single-page PDF with one Helvetica
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# text show; offsets are computed at write time so the xref table
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# stays consistent regardless of platform line endings.
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PDF_MARKER = "PONG"
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def _build_minimal_pdf(marker: str) -> bytes:
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"""Return a single-page PDF whose only visible text is `marker`.
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We construct the PDF imperatively because `pypdf`/`reportlab` are
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not in the test deps and we want the cell to work in a clean
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environment. The xref offsets are recomputed for each `marker`
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length so the file stays well-formed.
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"""
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objects = [
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b"<< /Type /Catalog /Pages 2 0 R >>",
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b"<< /Type /Pages /Kids [3 0 R] /Count 1 >>",
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(
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b"<< /Type /Page /Parent 2 0 R /MediaBox [0 0 200 200] "
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b"/Contents 4 0 R /Resources << /Font << /F1 5 0 R >> >> >>"
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),
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# Page content stream: position the text and show the marker.
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# `BT ... ET` is a text object; `Tf` selects font, `Td` moves
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# the cursor, `Tj` paints a string.
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(
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b"<< /Length %d >>\nstream\nBT /F1 24 Tf 50 100 Td ("
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+ marker.encode("ascii")
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+ b") Tj ET\nendstream"
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),
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b"<< /Type /Font /Subtype /Type1 /BaseFont /Helvetica >>",
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]
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# Fix up the /Length on the content stream to match its body.
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body_open = objects[3].index(b"\nstream\n") + len(b"\nstream\n")
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body_close = objects[3].index(b"\nendstream")
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body_len = body_close - body_open
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objects[3] = (
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b"<< /Length "
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+ str(body_len).encode("ascii")
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+ b" >>\nstream\n"
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+ objects[3][body_open:body_close]
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+ b"\nendstream"
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)
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out = bytearray(b"%PDF-1.4\n")
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offsets = []
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for i, obj in enumerate(objects, start=1):
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offsets.append(len(out))
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out += f"{i} 0 obj\n".encode("ascii") + obj + b"\nendobj\n"
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xref_offset = len(out)
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out += b"xref\n0 %d\n" % (len(objects) + 1)
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out += b"0000000000 65535 f \n"
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for off in offsets:
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out += f"{off:010d} 00000 n \n".encode("ascii")
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out += (
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b"trailer\n<< /Size "
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+ str(len(objects) + 1).encode("ascii")
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+ b" /Root 1 0 R >>\nstartxref\n"
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+ str(xref_offset).encode("ascii")
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+ b"\n%%EOF\n"
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)
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return bytes(out)
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def test_pdf_input_anthropic(compat_result, tmp_path):
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"""Drive the `claude` CLI against the LiteLLM proxy with a PDF
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attached via the Read tool and assert the reply references it."""
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base_url = os.environ.get(PROXY_BASE_URL_ENV)
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api_key = os.environ.get(PROXY_API_KEY_ENV)
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if not base_url or not api_key:
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compat_result.set(
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{
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"status": "fail",
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"error": (
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f"missing required env: set {PROXY_BASE_URL_ENV} and "
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f"{PROXY_API_KEY_ENV} to point at a running LiteLLM proxy"
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),
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}
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)
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pytest.fail(
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f"{PROXY_BASE_URL_ENV} / {PROXY_API_KEY_ENV} not configured", pytrace=False
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)
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pdf_path = tmp_path / "marker.pdf"
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pdf_path.write_bytes(_build_minimal_pdf(PDF_MARKER))
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outcomes = run_claude_models_parallel(
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models=ANTHROPIC_MODELS,
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prompt=(
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f"Use the Read tool to read the file at {pdf_path}. "
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"Report the single word that appears in the document."
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),
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base_url=base_url,
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api_key=api_key,
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extra_args=["--allowed-tools", "Read"],
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)
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failures = []
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for model in ANTHROPIC_MODELS:
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outcome = outcomes[model]
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if isinstance(outcome, ClaudeCLIError):
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error = f"[{model}] {outcome}"
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compat_result.add({"status": "fail", "error": error})
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failures.append(error)
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continue
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if outcome.exit_code != 0:
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error = f"[{model}] claude CLI failed: {failure_diagnostic(outcome)}"
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compat_result.add({"status": "fail", "error": error})
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failures.append(error)
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continue
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# The strongest gateway-level signal we can assert without
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# parsing every event type: the model's final user-visible
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# reply names the marker word that only the PDF carries.
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# If the proxy dropped the `document` content block, the
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# model has no way to produce this token.
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if PDF_MARKER not in outcome.text.upper():
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error = (
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f"[{model}] reply did not reference the PDF marker {PDF_MARKER!r}; "
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f"got: {outcome.text.strip()!r}"
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)
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compat_result.add({"status": "fail", "error": error})
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failures.append(error)
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continue
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compat_result.add({"status": "pass"})
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if failures:
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pytest.fail("; ".join(failures), pytrace=False)
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