Richard Tang
49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
"""Model capability checks for LLM providers.
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Vision support is sourced from the curated ``model_catalog.json``. Each model
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entry carries an optional ``supports_vision`` boolean; unknown models default
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to vision-capable so hosted frontier models work out of the box. To toggle
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support for a model, edit its catalog entry rather than this file.
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"""
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from framework.llm.model_catalog import model_supports_vision
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if TYPE_CHECKING:
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from framework.llm.provider import Tool
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def supports_image_tool_results(model: str) -> bool:
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"""Return whether *model* can receive image content in messages.
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Thin wrapper over :func:`model_supports_vision` so existing call sites
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keep working. Used to gate both user-message images and tool-result
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image blocks. Empty model strings are treated as capable so the default
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code path doesn't strip images before a provider is selected.
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"""
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if not model:
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return True
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return model_supports_vision(model)
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def filter_tools_for_model(tools: list[Tool], model: str) -> tuple[list[Tool], list[str]]:
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"""Drop image-producing tools for text-only models.
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Returns ``(filtered_tools, hidden_names)``. For vision-capable models
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(or when *model* is empty) the input list is returned unchanged and
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``hidden_names`` is empty. For text-only models any tool with
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``produces_image=True`` is removed so the LLM never sees it in its
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schema — avoids wasted calls and stale "screenshot failed" entries
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in agent memory.
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"""
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if not model or supports_image_tool_results(model):
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return list(tools), []
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hidden = [t.name for t in tools if t.produces_image]
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if not hidden:
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return list(tools), []
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kept = [t for t in tools if not t.produces_image]
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return kept, hidden
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