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When the active main model has native vision and the provider supports multimodal tool results (Anthropic, OpenAI Chat, Codex Responses, Gemini 3, OpenRouter, Nous), vision_analyze loads the image bytes and returns them to the model as a multimodal tool-result envelope. The model then sees the pixels directly on its next turn instead of receiving a lossy text description from an auxiliary LLM. Falls back to the legacy aux-LLM text path for non-vision models and unverified providers. Mirrors the architecture used in OpenCode, Claude Code, Codex CLI, and Cline. All four converge on the same pattern: tool results carry image content blocks for vision-capable provider/model combinations. Changes - tools/vision_tools.py: _vision_analyze_native fast path + provider capability table (_supports_media_in_tool_results). Schema description updated to reflect new behaviour. - agent/codex_responses_adapter.py: function_call_output.output now accepts the array form for multimodal tool results (was string-only). Preflight validates input_text/input_image parts. - agent/auxiliary_client.py: _RUNTIME_MAIN_PROVIDER/_MODEL globals so tools see the live CLI/gateway override, not the stale config.yaml default. set_runtime_main()/clear_runtime_main() helpers. - run_agent.py: AIAgent.run_conversation calls set_runtime_main at turn start so vision_analyze's fast-path check sees the actual runtime. - tests/conftest.py: clear runtime-main override between tests. Tests - tests/tools/test_vision_native_fast_path.py: provider capability table, envelope shape, fast-path gating (vision-capable model uses fast path; non-vision model falls through to aux). - tests/run_agent/test_codex_multimodal_tool_result.py: list tool content becomes function_call_output.output array; preflight preserves arrays and drops unknown part types. Live verified - Opus 4.6 + Sonnet 4.6 on OpenRouter: model calls vision_analyze on a typed filepath, gets pixels back, reads exact text from images that no aux description could capture (font color irony, multi-line fruit-count list, etc.). PR replaces the closed prior efforts (#16506 shipped the inbound user- attached path; this PR closes the gap for tool-discovered images).
207 lines
8.5 KiB
Python
207 lines
8.5 KiB
Python
"""Tests for the native-vision fast path inside vision_analyze.
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When the active main model supports native vision AND the provider supports
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image content inside tool-result messages, ``_handle_vision_analyze`` skips
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the auxiliary LLM and returns a multimodal envelope so the main model sees
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the pixels directly on its next turn.
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"""
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from __future__ import annotations
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import asyncio
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import base64
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import json
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from pathlib import Path
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from unittest.mock import patch
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import pytest
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from tools.vision_tools import (
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_build_native_vision_tool_result,
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_handle_vision_analyze,
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_supports_media_in_tool_results,
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_vision_analyze_native,
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)
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# Minimal valid 1x1 PNG bytes.
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_TINY_PNG = base64.b64decode(
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b"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII="
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)
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# ─── _supports_media_in_tool_results ─────────────────────────────────────────
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class TestSupportsMediaInToolResults:
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def test_anthropic_native_yes(self):
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assert _supports_media_in_tool_results("anthropic", "claude-opus-4-6") is True
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def test_openrouter_yes(self):
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assert _supports_media_in_tool_results("openrouter", "anthropic/claude-opus-4.6") is True
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def test_nous_yes(self):
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assert _supports_media_in_tool_results("nous", "anthropic/claude-sonnet-4.6") is True
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def test_openai_chat_yes(self):
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assert _supports_media_in_tool_results("openai", "gpt-5.4") is True
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def test_openai_codex_yes(self):
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assert _supports_media_in_tool_results("openai-codex", "gpt-5-codex") is True
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def test_gemini_3_yes(self):
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assert _supports_media_in_tool_results("google", "gemini-3-flash-preview") is True
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def test_gemini_2_no(self):
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assert _supports_media_in_tool_results("google", "gemini-2.5-pro") is False
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def test_unknown_provider_conservative_no(self):
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assert _supports_media_in_tool_results("brand-new-provider", "any-model") is False
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def test_empty_provider_no(self):
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assert _supports_media_in_tool_results("", "anything") is False
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assert _supports_media_in_tool_results(None, "anything") is False # type: ignore[arg-type]
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# ─── _build_native_vision_tool_result ────────────────────────────────────────
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class TestBuildNativeVisionToolResult:
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def test_envelope_shape(self):
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env = _build_native_vision_tool_result(
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image_url="/tmp/foo.png",
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question="what does it say?",
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image_data_url="data:image/png;base64,XYZ",
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image_size_bytes=1024,
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)
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assert env["_multimodal"] is True
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assert isinstance(env["content"], list)
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assert len(env["content"]) == 2
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assert env["content"][0]["type"] == "text"
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assert env["content"][1]["type"] == "image_url"
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assert env["content"][1]["image_url"]["url"] == "data:image/png;base64,XYZ"
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assert "what does it say?" in env["content"][0]["text"]
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assert "Image attached natively" in env["text_summary"]
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def test_no_question_omits_question_section(self):
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env = _build_native_vision_tool_result(
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image_url="/tmp/foo.png",
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question="",
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image_data_url="data:image/png;base64,XYZ",
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image_size_bytes=512,
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)
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text = env["content"][0]["text"]
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assert "Question:" not in text
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assert "Image loaded" in text
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# ─── _vision_analyze_native ──────────────────────────────────────────────────
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class TestVisionAnalyzeNative:
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def test_local_file_returns_multimodal_envelope(self, tmp_path):
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img = tmp_path / "test.png"
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img.write_bytes(_TINY_PNG)
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result = asyncio.get_event_loop().run_until_complete(
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_vision_analyze_native(str(img), "what is this?")
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)
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assert isinstance(result, dict)
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assert result.get("_multimodal") is True
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parts = result["content"]
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assert any(p.get("type") == "image_url" for p in parts)
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assert any(p.get("type") == "text" for p in parts)
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url = next(p["image_url"]["url"] for p in parts if p.get("type") == "image_url")
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assert url.startswith("data:image/")
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def test_missing_file_returns_error_string(self, tmp_path):
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result = asyncio.get_event_loop().run_until_complete(
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_vision_analyze_native(str(tmp_path / "nope.png"), "?")
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)
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# tool_error returns a JSON string, not the multimodal envelope
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assert isinstance(result, str)
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parsed = json.loads(result)
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assert parsed.get("success") is False
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assert "Invalid image source" in parsed.get("error", "")
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def test_empty_image_url_returns_error(self):
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result = asyncio.get_event_loop().run_until_complete(
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_vision_analyze_native("", "?")
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)
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assert isinstance(result, str)
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parsed = json.loads(result)
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assert parsed.get("success") is False
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assert "image_url is required" in parsed.get("error", "")
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def test_file_url_scheme_resolves(self, tmp_path):
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img = tmp_path / "t.png"
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img.write_bytes(_TINY_PNG)
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result = asyncio.get_event_loop().run_until_complete(
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_vision_analyze_native(f"file://{img}", "?")
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)
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assert isinstance(result, dict)
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assert result.get("_multimodal") is True
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# ─── _handle_vision_analyze fast-path gating ─────────────────────────────────
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class TestHandleVisionAnalyzeFastPath:
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"""Verify the dispatcher chooses fast-path vs aux-LLM correctly."""
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def test_vision_capable_main_model_uses_fast_path(self, tmp_path, monkeypatch):
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"""Main model supports native vision → fast path returns multimodal."""
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img = tmp_path / "x.png"
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img.write_bytes(_TINY_PNG)
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# Set runtime override so the handler thinks we're on opus@openrouter
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from agent.auxiliary_client import set_runtime_main, clear_runtime_main
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set_runtime_main("openrouter", "anthropic/claude-opus-4.6")
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try:
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coro = _handle_vision_analyze({"image_url": str(img), "question": "?"})
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result = asyncio.get_event_loop().run_until_complete(coro)
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finally:
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clear_runtime_main()
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assert isinstance(result, dict), \
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f"Expected multimodal envelope, got {type(result).__name__}: {str(result)[:200]}"
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assert result.get("_multimodal") is True
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def test_non_vision_main_model_falls_through_to_aux(self, tmp_path, monkeypatch):
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"""Non-vision main model → fast path skipped, aux LLM path attempted."""
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img = tmp_path / "x.png"
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img.write_bytes(_TINY_PNG)
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async def _aux_sentinel(*args, **kwargs):
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return '{"sentinel": "aux-path"}'
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from agent.auxiliary_client import set_runtime_main, clear_runtime_main
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set_runtime_main("openrouter", "qwen/qwen3-coder")
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try:
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with patch("tools.vision_tools.vision_analyze_tool", side_effect=_aux_sentinel):
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coro = _handle_vision_analyze({"image_url": str(img), "question": "?"})
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result = asyncio.get_event_loop().run_until_complete(coro)
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finally:
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clear_runtime_main()
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assert not (isinstance(result, dict) and result.get("_multimodal") is True), \
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"Fast path fired for non-vision model; should have fallen through to aux LLM"
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def test_fast_path_disabled_for_unsupported_provider(self, tmp_path, monkeypatch):
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"""Even with vision-capable model, unknown provider → fall through."""
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img = tmp_path / "x.png"
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img.write_bytes(_TINY_PNG)
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async def _aux_sentinel(*args, **kwargs):
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return '{"sentinel": "aux-path"}'
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from agent.auxiliary_client import set_runtime_main, clear_runtime_main
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set_runtime_main("brand-new-provider", "anthropic/claude-opus-4.6")
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try:
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with patch("tools.vision_tools.vision_analyze_tool", side_effect=_aux_sentinel):
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coro = _handle_vision_analyze({"image_url": str(img), "question": "?"})
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result = asyncio.get_event_loop().run_until_complete(coro)
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finally:
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clear_runtime_main()
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assert not (isinstance(result, dict) and result.get("_multimodal") is True), \
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"Fast path fired for unknown provider; should have fallen through"
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