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fix(image-routing): expose attached image paths in native multimodal text part

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In native image mode (vision-capable models like gpt-4o, claude-sonnet-4),
build_native_content_parts() previously emitted only the user's caption
plus image_url parts. The local file path of each attached image never
appeared in the conversation text, so the model could see the pixels but
had no string handle for tools that take image_url: str (custom MCP
tools, vision_analyze on a re-look, attach-to-tracker workflows).

The text-mode path already injects an equivalent hint via
Runner._enrich_message_with_vision ("...vision_analyze using image_url:
<path>..."). This brings native mode to parity by appending one
"[Image attached at: <path>]" line per successfully attached image to
the user-text part of the multimodal turn. Skipped (unreadable) paths
are NOT advertised, so the model is never told a non-existent file is
attached.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
briandevans 2026-05-02 17:12:46 -07:00 • committed by Teknium
parent 1f27ca638f
commit 11b9b146f1
2 changed files with 79 additions and 15 deletions
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43
agent/image_routing.py
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@ -190,24 +190,30 @@ def build_native_content_parts(
"""Build an OpenAI-style ``content`` list for a user turn.
Shape:
[{"type": "text", "text": "..."},
[{"type": "text", "text": "...\\n\\n[Image attached at: /local/path]"},
{"type": "image_url", "image_url": {"url": "data:image/png;base64,..."}},
...]
The local path of each successfully attached image is appended to the
text part as ``[Image attached at: <path>]``. The model still sees the
pixels via the ``image_url`` part (full native vision); the path note
just gives it a string handle so MCP/skill tools that take an image
path or URL argument can be invoked on the same image without an
extra round-trip. This parallels the text-mode hint produced by
``Runner._enrich_message_with_vision`` (``vision_analyze using image_url:
<path>``) so behaviour is consistent across both image input modes.
Images are attached at their native size. If a provider rejects the
request because an image is too large (e.g. Anthropic's 5 MB per-image
ceiling), the agent's retry loop transparently shrinks and retries
once — see ``run_agent._try_shrink_image_parts_in_messages``.
Returns (content_parts, skipped_paths). Skipped paths are files that
couldn't be read from disk.
couldn't be read from disk and are NOT advertised in the path hints.
"""
parts: List[Dict[str, Any]] = []
skipped: List[str] = []
text = (user_text or "").strip()
if text:
parts.append({"type": "text", "text": text})
image_parts: List[Dict[str, Any]] = []
attached_paths: List[str] = []
for raw_path in image_paths:
p = Path(raw_path)
@ -218,15 +224,30 @@ def build_native_content_parts(
if not data_url:
skipped.append(str(raw_path))
continue
parts.append({
image_parts.append({
"type": "image_url",
"image_url": {"url": data_url},
})
attached_paths.append(str(raw_path))
# If the text was empty, add a neutral prompt so the turn isn't just images.
if not text and any(p.get("type") == "image_url" for p in parts):
parts.insert(0, {"type": "text", "text": "What do you see in this image?"})
text = (user_text or "").strip()
# If at least one image attached, build a single text part that combines
# the user's caption (or a neutral default) with one path hint per image.
if attached_paths:
base_text = text or "What do you see in this image?"
path_hints = "\n".join(
f"[Image attached at: {p}]" for p in attached_paths
)
combined_text = f"{base_text}\n\n{path_hints}"
parts: List[Dict[str, Any]] = [{"type": "text", "text": combined_text}]
parts.extend(image_parts)
return parts, skipped
# No images successfully attached — fall back to plain text-only behaviour.
parts = []
if text:
parts.append({"type": "text", "text": text})
return parts, skipped