auto-added claus
streamTextBuffer = "";
chatRunId = null;
chatStreamSegments = [];
+ if (streamMermaidTimerId != null) {
+ clearTimeout(streamMermaidTimerId);
+ streamMermaidTimerId = null;
+ }
return;
}
if (state === "error") {
@@ -3456,6 +3911,10 @@ ${autoLimit ? `auto-added claus
streamTextBuffer = "";
chatRunId = null;
chatStreamSegments = [];
+ if (streamMermaidTimerId != null) {
+ clearTimeout(streamMermaidTimerId);
+ streamMermaidTimerId = null;
+ }
statusBar.textContent = `${t("chat.error")}: ${String(payload.errorMessage || "chat error")}`;
}
},
diff --git a/interfaces/admin/static/theme-deepseek.css b/interfaces/admin/static/theme-deepseek.css
index ffbba424..9192979d 100644
--- a/interfaces/admin/static/theme-deepseek.css
+++ b/interfaces/admin/static/theme-deepseek.css
@@ -576,6 +576,190 @@ body.theme-ds-body .card {
border: 1px solid var(--ds-border, rgba(255, 255, 255, 0.08));
}
+.chat-msg__actions {
+ margin-top: 6px;
+ display: flex;
+ gap: 8px;
+ justify-content: flex-start;
+ opacity: 0;
+ pointer-events: none;
+ transition: opacity 120ms ease;
+}
+
+.chat-msg-col:hover .chat-msg__actions {
+ opacity: 1;
+ pointer-events: auto;
+}
+
+.chat-msg__action-btn {
+ border: 1px solid rgba(148, 163, 184, 0.25);
+ background: transparent;
+ color: rgba(203, 213, 225, 0.92);
+ border-radius: 999px;
+ font-size: 15px;
+ width: 32px;
+ height: 32px;
+ display: inline-flex;
+ align-items: center;
+ justify-content: center;
+ padding: 0;
+ cursor: pointer;
+}
+
+.chat-msg__action-btn:hover {
+ background: rgba(30, 41, 59, 0.45);
+}
+
+.chat-msg__action-btn--danger {
+ border-color: rgba(248, 113, 113, 0.45);
+ color: #fca5a5;
+}
+
+.chat-msg__md .mermaid {
+ display: block;
+ width: 100%;
+ overflow: auto;
+ padding: 8px;
+ border-radius: 10px;
+ border: 1px solid rgba(148, 163, 184, 0.35);
+ background: rgba(15, 23, 42, 0.35);
+}
+
+.chat-msg__md .mermaid svg {
+ display: block;
+ max-width: 100%;
+ height: auto;
+ margin: 0 auto;
+}
+
+.chat-img-lightbox {
+ position: fixed;
+ inset: 0;
+ z-index: 9999;
+ display: flex;
+ align-items: center;
+ justify-content: center;
+ padding: 18px;
+ background: rgba(0, 0, 0, 0.78);
+ backdrop-filter: blur(2px);
+}
+
+.chat-img-lightbox__inner {
+ position: relative;
+ width: min(96vw, 1400px);
+ max-height: 92vh;
+ display: flex;
+ align-items: center;
+ justify-content: center;
+ border-radius: 14px;
+ border: 1px solid rgba(148, 163, 184, 0.28);
+ background: rgba(2, 6, 23, 0.55);
+ overflow: hidden;
+}
+
+.chat-img-lightbox__close {
+ position: absolute;
+ top: 10px;
+ right: 10px;
+ width: 36px;
+ height: 36px;
+ border-radius: 10px;
+ border: 1px solid rgba(148, 163, 184, 0.35);
+ background: rgba(15, 23, 42, 0.85);
+ color: rgba(255, 255, 255, 0.9);
+ cursor: pointer;
+ font-size: 22px;
+ line-height: 32px;
+}
+
+.chat-img-lightbox__close:hover {
+ background: rgba(30, 41, 59, 0.9);
+}
+
+.chat-img-lightbox__img {
+ max-width: 96vw;
+ max-height: 92vh;
+ width: auto;
+ height: auto;
+ object-fit: contain;
+}
+
+.chat-mermaid-lightbox__svg {
+ width: min(96vw, 1400px);
+ max-height: 92vh;
+ overflow: auto;
+ padding: 14px;
+ cursor: grab;
+}
+
+.chat-mermaid-lightbox__svg--dragging {
+ cursor: grabbing;
+}
+
+.chat-mermaid-lightbox__viewport {
+ transform-origin: 0 0;
+}
+
+.chat-mermaid-lightbox__toolbar {
+ position: absolute;
+ left: 10px;
+ top: 10px;
+ display: flex;
+ gap: 8px;
+ align-items: center;
+ padding: 6px 8px;
+ border-radius: 12px;
+ border: 1px solid rgba(148, 163, 184, 0.35);
+ background: rgba(15, 23, 42, 0.85);
+ z-index: 2;
+}
+
+.chat-mermaid-lightbox__btn {
+ width: 40px;
+ height: 32px;
+ border-radius: 10px;
+ border: 1px solid rgba(148, 163, 184, 0.3);
+ background: rgba(2, 6, 23, 0.45);
+ color: rgba(255, 255, 255, 0.92);
+ cursor: pointer;
+ font-size: 16px;
+ line-height: 1;
+}
+
+.chat-mermaid-lightbox__btn:hover {
+ background: rgba(30, 41, 59, 0.75);
+}
+
+.chat-mermaid-lightbox__zoom {
+ color: rgba(226, 232, 240, 0.9);
+ font-size: 12px;
+ padding-left: 2px;
+}
+
+.chat-mermaid-lightbox__svg svg {
+ width: max(980px, 96vw);
+ max-width: 100%;
+ height: auto;
+}
+
+.chat-msg__md .mermaid .mermaid-fallback {
+ padding: 8px;
+ border-radius: 8px;
+ background: rgba(2, 6, 23, 0.55);
+}
+
+.chat-msg__md .mermaid .mermaid-fallback__err {
+ color: #fca5a5;
+ margin-bottom: 6px;
+ font-size: 12px;
+}
+
+.chat-msg__md .mermaid .mermaid-fallback pre {
+ margin: 0;
+ white-space: pre-wrap;
+ color: #e5e7eb;
+}
+
.chat-msg--tool {
align-self: flex-start;
font-family: ui-monospace, monospace;
diff --git a/platform/persistence/sqlite_store.py b/platform/persistence/sqlite_store.py
index eb1673ba..684160ad 100644
--- a/platform/persistence/sqlite_store.py
+++ b/platform/persistence/sqlite_store.py
@@ -1613,6 +1613,29 @@ class SqliteStore:
conn.execute("DELETE FROM chat_session WHERE id = ?", (str(session_id),))
return True
+ def delete_message(self, *, session_id: str, message_id: int) -> bool:
+ sid = str(session_id or "").strip()
+ mid = int(message_id or 0)
+ if not sid or mid <= 0:
+ return False
+ with self._connect() as conn:
+ cur = conn.execute(
+ "DELETE FROM chat_message WHERE session_id = ? AND id = ?",
+ (sid, mid),
+ )
+ if int(cur.rowcount or 0) <= 0:
+ return False
+ last_row = conn.execute(
+ "SELECT MAX(timestamp) AS ts FROM chat_message WHERE session_id = ?",
+ (sid,),
+ ).fetchone()
+ last_ts = str((last_row["ts"] if last_row else "") or "").strip() or None
+ conn.execute(
+ "UPDATE chat_session SET last_message_at = ? WHERE id = ?",
+ (last_ts, sid),
+ )
+ return True
+
def add_message(
self,
session_id: str,
diff --git a/runtime/chat/agent_messages.py b/runtime/chat/agent_messages.py
index e1469714..ee225cdf 100644
--- a/runtime/chat/agent_messages.py
+++ b/runtime/chat/agent_messages.py
@@ -14,6 +14,7 @@ import re
from typing import Any
from oclaw.platform.llm.chat_models import _normalize_image_b64_payload, gemini_openai_compat_client, ChatModel
+from oclaw.runtime.chat.media_redact import redact_embedded_image_blobs
from oclaw.runtime.chat.tool_runtime import tool_llm_message_max_chars, truncate_tool_result_for_llm_messages
from oclaw.prompts import render_prompt
from oclaw.platform.files.attachment_assets import attachment_id_to_data_url
@@ -196,8 +197,18 @@ def build_llm_messages(
model: ChatModel,
lang: str,
tool_context_truncate_enabled: bool = True,
+ active_turn_uuid: str | None = None,
) -> list[dict[str, Any]]:
- """把 DB 中的消息序列转换为 LLM messages。"""
+ """把 DB 中的消息序列转换为 LLM messages。
+
+ When ``active_turn_uuid`` matches a tool/user row ``turn_uuid``, that turn is treated as the
+ in-flight MCP turn: tool JSON is not stripped of nested image payloads here (see also
+ :func:`~oclaw.runtime.direct_loop._guard_tool_results_for_llm_context`). Omit or leave empty
+ to apply image-blob stripping for every tool row (safe default for callers without turn context).
+
+ Only the **last** user message may expand attachments into native multimodal ``input_image``;
+ older user attachments are replayed as text metadata only.
+ """
out: list[dict[str, Any]] = [{"role": "system", "content": (system_prompt or "").strip()}]
thinking_mode_enabled = bool(getattr(model, "thinking_mode_enabled", False))
allow_signature_replay = _allow_reasoning_signature_replay(model)
@@ -239,6 +250,15 @@ def build_llm_messages(
seen_tool_ids.add(tcid)
tool_ids_after.append(set(seen_tool_ids))
tool_ids_after.reverse()
+
+ last_user_msg_idx = -1
+ for _ui, _um in enumerate(store_messages or []):
+ if str(getattr(_um, "role", "") or "") != "user":
+ continue
+ if str(getattr(_um, "event_type", "") or "").strip().lower() == "reasoning":
+ continue
+ last_user_msg_idx = _ui
+
def _attach_reasoning_content(row: dict[str, Any], m: Any) -> dict[str, Any]:
if not thinking_mode_enabled:
return row
@@ -291,34 +311,53 @@ def build_llm_messages(
if not isinstance(att, dict):
continue
att_type = att.get("type")
+ expand_user_image_for_model = bool(i == last_user_msg_idx)
if att_type in ("image", "input_image"):
- b64 = _normalize_image_b64_payload(att.get("image_base64") or att.get("data"))
- if not b64:
- continue
- content_list.append(
- {
- "type": "input_image",
- "image_base64": b64,
- "mime": att.get("mime") or "image/jpeg",
- }
- )
+ if expand_user_image_for_model:
+ b64 = _normalize_image_b64_payload(att.get("image_base64") or att.get("data"))
+ if not b64:
+ continue
+ content_list.append(
+ {
+ "type": "input_image",
+ "image_base64": b64,
+ "mime": att.get("mime") or "image/jpeg",
+ }
+ )
+ else:
+ name = str(att.get("name") or "image")
+ mime = str(att.get("mime") or "image/jpeg")
+ hs = "(historical attachment; pixels not replayed into model)"
+ hs_zh = "（历史附件；不向模型回放像素）"
+ hint = hs_zh if not str(lang or "").startswith("en") else hs
+ meta_line = f"- name={name} mime={mime} {hint}"
+ content_list.append(
+ {
+ "type": "text",
+ "text": render_prompt(
+ "tools/image_attachment_meta.md",
+ variables={"meta_line": meta_line},
+ strict=True,
+ ),
+ }
+ )
elif att_type == "image_ref":
- # Prefer actual image bytes so multi-agent/image specialist can truly "see" history images.
name = str(att.get("name") or "image")
mime = str(att.get("mime") or "image/jpeg")
aid = str(att.get("attachment_id") or "")
- data_url = attachment_id_to_data_url(aid, mime=mime) if aid else ""
- if data_url:
- if ";base64," in data_url:
- b64 = data_url.split(";base64,", 1)[1]
- content_list.append(
- {
- "type": "input_image",
- "image_base64": b64,
- "mime": mime,
- }
- )
- continue
+ if expand_user_image_for_model:
+ data_url = attachment_id_to_data_url(aid, mime=mime) if aid else ""
+ if data_url:
+ if ";base64," in data_url:
+ b64 = data_url.split(";base64,", 1)[1]
+ content_list.append(
+ {
+ "type": "input_image",
+ "image_base64": b64,
+ "mime": mime,
+ }
+ )
+ continue
w = att.get("width")
h = att.get("height")
sz = att.get("bytes")
@@ -423,7 +462,7 @@ def build_llm_messages(
aid = str(_fid or "").strip()
except Exception:
aid = ""
- if aid and mime.startswith("image/"):
+ if expand_user_image_for_model and aid and mime.startswith("image/"):
data_url = attachment_id_to_data_url(aid, mime=mime)
if data_url and ";base64," in data_url:
b64 = data_url.split(";base64,", 1)[1]
@@ -575,6 +614,15 @@ def build_llm_messages(
)
continue
raw_tc_content = getattr(m, "content", "") or ""
+ _tun = str(getattr(m, "turn_uuid", "") or "").strip()
+ _aus = str(active_turn_uuid or "").strip()
+ if (not _aus) or (_tun != _aus):
+ try:
+ _p = json.loads(raw_tc_content)
+ _p2 = redact_embedded_image_blobs(_p)
+ raw_tc_content = json.dumps(_p2, ensure_ascii=False, default=str)
+ except Exception:
+ pass
tool_content_out = raw_tc_content
cap = tool_llm_message_max_chars()
if str(tool_call_id) in historical_tool_ids:
diff --git a/runtime/chat/media_redact.py b/runtime/chat/media_redact.py
new file mode 100644
index 00000000..3fe4113b
--- /dev/null
+++ b/runtime/chat/media_redact.py
@@ -0,0 +1,198 @@
+"""Strip/ingest embedded binary payloads from tool/MCP-shaped JSON.
+
+Persistence is untouched; callers use copies when building model context."""
+
+from __future__ import annotations
+
+import base64
+from typing import Any
+from oclaw.platform.files.attachment_assets import AttachmentAssetStore
+
+_IMAGE_CONTENT_TYPES = frozenset({"image", "input_image"})
+_BASE64_PAYLOAD_KEYS = ("data", "image_base64", "base64", "content_base64", "body_base64")
+# Below this length we keep values (tiny icons / markers).
+_MIN_B64_CHARS = 200
+
+
+def redact_embedded_image_blobs(obj: Any) -> Any:
+ """Deep-copy-ish transform: replace large base64 payloads with metadata placeholders."""
+ if isinstance(obj, dict):
+ return _redact_dict(obj)
+ if isinstance(obj, list):
+ return [redact_embedded_image_blobs(x) for x in obj]
+ return obj
+
+
+def _looks_like_large_payload(s: str) -> bool:
+ t = str(s or "").strip()
+ if len(t) < _MIN_B64_CHARS:
+ return False
+ allowed = frozenset("ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=\n\r-_")
+ if not t[: min(512, len(t))]:
+ return False
+ noise = sum(1 for ch in t[: min(2000, len(t))] if ch not in allowed)
+ return noise <= max(2, len(t[: min(2000, len(t))]) // 200)
+
+
+def _redact_dict(d: dict[str, Any]) -> dict[str, Any]:
+ typ = str(d.get("type") or "").strip().lower()
+ payload_keys = [k for k in _BASE64_PAYLOAD_KEYS if isinstance(d.get(k), str) and _looks_like_large_payload(str(d.get(k) or ""))]
+ if payload_keys:
+ plen = max(len(str(d.get(k) or "")) for k in payload_keys)
+ dup: dict[str, Any] = {}
+ for k, v in d.items():
+ if k in payload_keys:
+ continue
+ if isinstance(v, dict):
+ dup[k] = _redact_dict(v)
+ elif isinstance(v, list):
+ dup[k] = [redact_embedded_image_blobs(x) for x in v]
+ else:
+ dup[k] = v
+ is_image = typ in _IMAGE_CONTENT_TYPES
+ dup["_image_payload_redacted" if is_image else "_binary_payload_redacted"] = True
+ dup["_redacted_payload_chars"] = int(plen)
+ dup["_redacted_payload_keys"] = list(payload_keys)
+ return dup
+
+ out: dict[str, Any] = {}
+ for k, v in d.items():
+ if isinstance(v, dict):
+ out[k] = _redact_dict(v)
+ elif isinstance(v, list):
+ out[k] = [redact_embedded_image_blobs(x) for x in v]
+ else:
+ out[k] = v
+ return out
+
+
+def ingest_embedded_image_blobs_as_refs(
+ obj: Any,
+ *,
+ root_dir: str | None = None,
+ filename_prefix: str = "tool-image",
+) -> tuple[Any, list[dict[str, Any]]]:
+ """Persist nested base64 blobs and replace them with attachment refs.
+
+ Returns transformed object and newly created attachment refs.
+ """
+ store = AttachmentAssetStore(root_dir=root_dir) if root_dir else AttachmentAssetStore()
+ refs: list[dict[str, Any]] = []
+
+ def _ingest(node: Any, idx_seed: list[int]) -> Any:
+ if isinstance(node, list):
+ return [_ingest(x, idx_seed) for x in node]
+ if not isinstance(node, dict):
+ return node
+ typ = str(node.get("type") or "").strip().lower()
+ raw = _pick_base64_payload(node)
+ if raw:
+ blob = _decode_image_bytes(raw)
+ if blob:
+ idx_seed[0] += 1
+ mime = str(node.get("mime") or node.get("mime_type") or "image/png").strip() or "image/png"
+ ext = _filename_ext_for_mime(mime)
+ name = str(node.get("name") or f"{filename_prefix}-{idx_seed[0]}{ext}").strip()
+ meta = store.save_bytes(
+ blob,
+ filename=name,
+ mime=mime,
+ width=_safe_int(node.get("width")),
+ height=_safe_int(node.get("height")),
+ )
+ ref_type = _ref_type_for_mime(mime, typ)
+ ref = {
+ "type": ref_type,
+ "attachment_id": meta.attachment_id,
+ "name": meta.name,
+ "mime": meta.mime,
+ "bytes": meta.bytes,
+ "width": meta.width,
+ "height": meta.height,
+ }
+ refs.append(ref)
+ return ref
+ redacted = _redact_dict(node)
+ redacted["type"] = _ref_type_for_mime(
+ str(node.get("mime") or node.get("mime_type") or "application/octet-stream"),
+ typ,
+ )
+ redacted.setdefault("name", str(node.get("name") or "attachment"))
+ redacted.setdefault("mime", str(node.get("mime") or node.get("mime_type") or "application/octet-stream"))
+ return redacted
+ out: dict[str, Any] = {}
+ for k, v in node.items():
+ out[k] = _ingest(v, idx_seed)
+ return out
+
+ transformed = _ingest(obj, [0])
+ uniq: list[dict[str, Any]] = []
+ seen: set[str] = set()
+ for r in refs:
+ aid = str(r.get("attachment_id") or "").strip()
+ if not aid or aid in seen:
+ continue
+ seen.add(aid)
+ uniq.append(r)
+ return transformed, uniq
+
+
+def _decode_image_bytes(raw: Any) -> bytes:
+ s = str(raw or "").strip()
+ if not s:
+ return b""
+ if s.startswith("data:") and ";base64," in s:
+ s = s.split(";base64,", 1)[1]
+ try:
+ return base64.b64decode(s.encode("ascii"), validate=False)
+ except Exception:
+ return b""
+
+
+def _pick_base64_payload(node: dict[str, Any]) -> str:
+ for k in _BASE64_PAYLOAD_KEYS:
+ v = node.get(k)
+ if isinstance(v, str) and str(v).strip():
+ return v
+ return ""
+
+
+def _ref_type_for_mime(mime: str, typ: str = "") -> str:
+ m = str(mime or "").strip().lower()
+ t = str(typ or "").strip().lower()
+ if t in _IMAGE_CONTENT_TYPES or m.startswith("image/"):
+ return "image_ref"
+ if m.startswith("video/"):
+ return "video_ref"
+ if m.startswith("text/"):
+ return "text_ref"
+ return "binary_ref"
+
+
+def _filename_ext_for_mime(mime: str) -> str:
+ m = str(mime or "").strip().lower()
+ if m == "image/png":
+ return ".png"
+ if m in {"image/jpeg", "image/jpg"}:
+ return ".jpg"
+ if m == "image/webp":
+ return ".webp"
+ if m == "image/gif":
+ return ".gif"
+ if m == "video/mp4":
+ return ".mp4"
+ if m == "text/plain":
+ return ".txt"
+ return ".bin"
+
+
+def _safe_int(raw: Any) -> int | None:
+ try:
+ if raw is None:
+ return None
+ return int(raw)
+ except Exception:
+ return None
+
+
+__all__ = ["redact_embedded_image_blobs", "ingest_embedded_image_blobs_as_refs"]
diff --git a/runtime/chat/model_path_audit.py b/runtime/chat/model_path_audit.py
new file mode 100644
index 00000000..5ac400a5
--- /dev/null
+++ b/runtime/chat/model_path_audit.py
@@ -0,0 +1,87 @@
+from __future__ import annotations
+
+from typing import Any
+
+_MIN_B64_CHARS = 200
+
+
+def ensure_no_tool_or_embedded_image_payload(*, messages: list[dict[str, Any]], path: str) -> None:
+ """Guard non-turn model paths and degrade in place instead of raising.
+
+ - `role=tool` is downgraded to assistant text summary.
+ - Embedded image/base64 payloads are replaced with safe text placeholders.
+ """
+ for m in messages or []:
+ if not isinstance(m, dict):
+ continue
+ role = str(m.get("role") or "").strip().lower()
+ if role == "tool":
+ m["role"] = "assistant"
+ m["content"] = f"[model_path_audit:{path}] tool payload omitted"
+ continue
+ content = m.get("content")
+ if _contains_embedded_image_payload(content):
+ m["content"] = _sanitize_content(content, path=path)
+
+
+def _contains_embedded_image_payload(obj: Any) -> bool:
+ if isinstance(obj, str):
+ return _contains_large_base64_like_text(obj)
+ if isinstance(obj, list):
+ return any(_contains_embedded_image_payload(x) for x in obj)
+ if not isinstance(obj, dict):
+ return False
+ typ = str(obj.get("type") or "").strip().lower()
+ if typ in {"image", "input_image"}:
+ for k in ("data", "image_base64"):
+ v = obj.get(k)
+ if isinstance(v, str) and len(v.strip()) >= _MIN_B64_CHARS:
+ return True
+ for v in obj.values():
+ if _contains_embedded_image_payload(v):
+ return True
+ return False
+
+
+def _contains_large_base64_like_text(text: str) -> bool:
+ s = str(text or "").strip()
+ if len(s) < _MIN_B64_CHARS:
+ return False
+ if s.startswith("data:") and ";base64," in s:
+ s = s.split(";base64,", 1)[1]
+ head = s[: min(4096, len(s))]
+ if len(head) < _MIN_B64_CHARS:
+ return False
+ allowed = frozenset("ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=\n\r-_")
+ noise = sum(1 for ch in head if ch not in allowed)
+ # Similar heuristic to media redaction: mostly base64 alphabet over a long span.
+ return noise <= max(4, len(head) // 200)
+
+
+def _sanitize_content(content: Any, *, path: str) -> Any:
+ if isinstance(content, str):
+ if _contains_large_base64_like_text(content):
+ return f"[model_path_audit:{path}] base64 payload omitted"
+ return content
+ if isinstance(content, list):
+ out: list[Any] = []
+ for item in content:
+ if isinstance(item, dict):
+ typ = str(item.get("type") or "").strip().lower()
+ if typ in {"image", "input_image"}:
+ out.append({"type": "text", "text": f"[model_path_audit:{path}] image payload omitted"})
+ continue
+ out.append(_sanitize_content(item, path=path))
+ return out
+ if isinstance(content, dict):
+ out: dict[str, Any] = {}
+ for k, v in content.items():
+ if str(k) in {"data", "image_base64"} and isinstance(v, str) and _contains_large_base64_like_text(v):
+ out[k] = f"[model_path_audit:{path}] payload omitted"
+ continue
+ out[k] = _sanitize_content(v, path=path)
+ return out
+ return content
+
+
+__all__ = ["ensure_no_tool_or_embedded_image_payload"]
diff --git a/runtime/chat/tool_runtime.py b/runtime/chat/tool_runtime.py
index 1b34b92c..f2a36f38 100644
--- a/runtime/chat/tool_runtime.py
+++ b/runtime/chat/tool_runtime.py
@@ -21,6 +21,7 @@ from oclaw.platform.persistence.sqlite_store import SqliteStore
from oclaw.runtime.tools.base import ToolRegistry
from oclaw.platform.llm.chat_models import LLMToolCall
from oclaw.runtime.tools.tool_validation import validate_tool_arguments
+from oclaw.runtime.chat.media_redact import ingest_embedded_image_blobs_as_refs
from oclaw.runtime.tools.experts.workspace.workspace_base import (
workspace_path_access_scope,
workspace_write_namespace_scope,
@@ -58,13 +59,15 @@ def _attachments_from_tool_result(result: Any) -> list[dict[str, Any]]:
return []
out: list[dict[str, Any]] = []
aid = str(result.get("attachment_id") or "").strip()
+ root_mime = str(result.get("mime") or "").strip()
if aid:
+ ref_type = _ref_type_for_mime(root_mime)
out.append(
{
- "type": "image_ref",
+ "type": ref_type,
"attachment_id": aid,
"name": str(result.get("name") or "generated-image"),
- "mime": str(result.get("mime") or "image/png"),
+ "mime": root_mime or "application/octet-stream",
"bytes": result.get("bytes"),
"width": result.get("width"),
"height": result.get("height"),
@@ -91,12 +94,16 @@ def _attachments_from_tool_result(result: Any) -> list[dict[str, Any]]:
continue
r_aid = str(r.get("attachment_id") or "").strip()
if r_aid:
+ r_typ = str(r.get("type") or "").strip().lower()
+ r_mime = str(r.get("mime_type") or r.get("mime") or "").strip()
+ if r_typ not in {"image_ref", "video_ref", "text_ref", "binary_ref"}:
+ r_typ = _ref_type_for_mime(r_mime)
out.append(
{
- "type": "image_ref",
+ "type": r_typ,
"attachment_id": r_aid,
"name": str(r.get("name") or "generated-image"),
- "mime": str(r.get("mime") or "image/png"),
+ "mime": r_mime or "application/octet-stream",
"bytes": r.get("bytes"),
"width": r.get("width"),
"height": r.get("height"),
@@ -110,15 +117,18 @@ def _attachments_from_tool_result(result: Any) -> list[dict[str, Any]]:
if not isinstance(item, dict):
continue
typ = str(item.get("type") or "").strip().lower()
- if typ in {"image", "input_image"}:
- b64 = item.get("image_base64") or item.get("data")
- if isinstance(b64, str) and b64.strip():
+ if typ in {"image_ref", "video_ref", "text_ref", "binary_ref"}:
+ a_id = str(item.get("attachment_id") or "").strip()
+ if a_id:
out.append(
{
- "type": "image",
- "data": b64.strip(),
- "mime": str(item.get("mime_type") or item.get("mime") or "image/png"),
- "name": str(item.get("name") or "tool-image"),
+ "type": typ,
+ "attachment_id": a_id,
+ "mime": str(item.get("mime_type") or item.get("mime") or "application/octet-stream"),
+ "name": str(item.get("name") or "tool-attachment"),
+ "bytes": item.get("bytes"),
+ "width": item.get("width"),
+ "height": item.get("height"),
}
)
elif typ == "image_url":
@@ -132,7 +142,7 @@ def _attachments_from_tool_result(result: Any) -> list[dict[str, Any]]:
a.get("attachment_id")
or a.get("pointer_uri")
or a.get("url")
- or (f"b64:{a.get('mime')}:{len(str(a.get('data') or ''))}" if a.get("data") else "")
+ or ""
).strip()
if not k or k in seen:
continue
@@ -828,6 +838,10 @@ class ToolExecutor:
)
result, duration_ms = results_by_id[tc.id]
result = normalize_tool_result(result)
+ persisted_result, ingested_refs = ingest_embedded_image_blobs_as_refs(
+ result,
+ filename_prefix=f"{str(tc.name or 'tool')}-{str(tc.id or '')}",
+ )
logger.info(
"tool_runtime tool session=%s name=%s duration_ms=%d ok=%s",
ctx.session_id[:12],
@@ -840,7 +854,7 @@ class ToolExecutor:
session_id=ctx.session_id,
tool_name=tc.name,
args=tc.arguments,
- result=result,
+ result=persisted_result,
specialist=ctx.specialist,
duration_ms=duration_ms,
)
@@ -849,7 +863,7 @@ class ToolExecutor:
# until the turn finishes, so current-round model context remains lossless.
t_trunc = time.perf_counter()
observed_rows_this_call = int(_estimate_observed_rows(result))
- result_for_llm = dict(result or {})
+ result_for_llm = dict(persisted_result or {})
if tc.name in _SQL_REPLAY_COMPACT_TOOL_NAMES:
current = int(local_turn_tool_name_counts.get(tc.name, 0))
current_rows = int(local_turn_tool_observed_rows.get(tc.name, 0))
@@ -870,7 +884,7 @@ class ToolExecutor:
role="tool",
content=tool_content,
tool_calls={"tool_call_id": tc.id, "name": tc.name, "assistant_message_id": assistant_msg_id},
- attachments=_attachments_from_tool_result(result) or None,
+ attachments=(_merge_attachments(_attachments_from_tool_result(persisted_result), ingested_refs) or None),
turn_uuid=ctx.turn_uuid,
event_type="tool_result",
event_payload={"tool_name": tc.name, "observed_rows": int(observed_rows_this_call)},
@@ -971,3 +985,29 @@ __all__ = [
"truncate_tool_result_for_llm_messages",
"compact_turn_tool_messages_for_storage",
]
+
+
+def _merge_attachments(*parts: list[dict[str, Any]]) -> list[dict[str, Any]]:
+ out: list[dict[str, Any]] = []
+ seen: set[str] = set()
+ for part in parts:
+ for a in part or []:
+ if not isinstance(a, dict):
+ continue
+ k = str(a.get("attachment_id") or a.get("pointer_uri") or a.get("url") or "").strip()
+ if not k or k in seen:
+ continue
+ seen.add(k)
+ out.append(a)
+ return out
+
+
+def _ref_type_for_mime(mime: str) -> str:
+ m = str(mime or "").strip().lower()
+ if m.startswith("image/"):
+ return "image_ref"
+ if m.startswith("video/"):
+ return "video_ref"
+ if m.startswith("text/"):
+ return "text_ref"
+ return "binary_ref"
diff --git a/runtime/direct_loop.py b/runtime/direct_loop.py
index 4a96d67d..ed9a3be7 100644
--- a/runtime/direct_loop.py
+++ b/runtime/direct_loop.py
@@ -13,6 +13,7 @@ from types import SimpleNamespace
from typing import Any, Callable, Optional
from oclaw.runtime.chat.agent_messages import build_llm_messages
+from oclaw.runtime.chat.media_redact import redact_embedded_image_blobs
from oclaw.runtime.chat.tool_runtime import ToolExecutionConfig
from oclaw.runtime.chat.turn_types import TurnRunOutcome
from oclaw.runtime.skill_executor import SkillExecutionContext, SkillExecutor
@@ -269,6 +270,21 @@ def _json_dumps_safe(obj: Any) -> str:
return json.dumps({"ok": False, "error": "not_json_serializable"}, ensure_ascii=False)
+def _tool_message_with_content(m: Any, content: str, *, sid: str = "") -> SimpleNamespace:
+ return SimpleNamespace(
+ id=getattr(m, "id", 0),
+ session_id=str(getattr(m, "session_id", None) or sid or ""),
+ role="tool",
+ content=content,
+ tool_calls=getattr(m, "tool_calls", None),
+ timestamp=getattr(m, "timestamp", ""),
+ attachments=getattr(m, "attachments", None),
+ turn_uuid=getattr(m, "turn_uuid", None),
+ event_type=getattr(m, "event_type", None),
+ event_payload=getattr(m, "event_payload", None),
+ )
+
+
def _split_reasoning_and_body(text: str, *, explicit_reasoning: str | None = None) -> tuple[list[str], str]:
explicit = str(explicit_reasoning or "").strip()
raw = str(text or "")
@@ -317,6 +333,12 @@ def _guard_tool_results_for_llm_context(
out.append(m)
continue
raw = str(getattr(m, "content", "") or "")
+ try:
+ _parsed0 = json.loads(raw)
+ _parsed1 = redact_embedded_image_blobs(_parsed0)
+ raw = _json_dumps_safe(_parsed1)
+ except Exception:
+ pass
# Best-effort parse tool JSON for image-query specific guard and overflow metadata.
ok = None
error_code = ""
@@ -350,17 +372,7 @@ def _guard_tool_results_for_llm_context(
"图片分析结果在上下文回放中已截断，请缩小 query_image_attachment 的问题范围。"
)
guarded = _json_dumps_safe(guarded_obj)
- out.append(
- SimpleNamespace(
- id=getattr(m, "id", 0),
- session_id=getattr(m, "session_id", session_id),
- role="tool",
- content=guarded,
- tool_calls=getattr(m, "tool_calls", None),
- timestamp=getattr(m, "timestamp", ""),
- attachments=getattr(m, "attachments", None),
- )
- )
+ out.append(_tool_message_with_content(m, guarded, sid=session_id))
continue
# Guard video transcript replay similarly (usually long).
if str(obj.get("task") or "").strip().lower() == "transcript" and has_attachment_id and len(text) > video_cap:
@@ -371,20 +383,10 @@ def _guard_tool_results_for_llm_context(
guarded_obj["video_result_original_chars"] = len(text)
guarded_obj["video_result_replay_cap_chars"] = video_cap
guarded = _json_dumps_safe(guarded_obj)
- out.append(
- SimpleNamespace(
- id=getattr(m, "id", 0),
- session_id=getattr(m, "session_id", session_id),
- role="tool",
- content=guarded,
- tool_calls=getattr(m, "tool_calls", None),
- timestamp=getattr(m, "timestamp", ""),
- attachments=getattr(m, "attachments", None),
- )
- )
+ out.append(_tool_message_with_content(m, guarded, sid=session_id))
continue
if len(raw) <= cap:
- out.append(m)
+ out.append(_tool_message_with_content(m, raw, sid=session_id))
continue
preview = raw[: max(1, min(4000, cap - 400))] + "\n..."
guarded_obj = {
@@ -402,17 +404,7 @@ def _guard_tool_results_for_llm_context(
),
}
guarded = _json_dumps_safe(guarded_obj)
- out.append(
- SimpleNamespace(
- id=getattr(m, "id", 0),
- session_id=getattr(m, "session_id", session_id),
- role="tool",
- content=guarded,
- tool_calls=getattr(m, "tool_calls", None),
- timestamp=getattr(m, "timestamp", ""),
- attachments=getattr(m, "attachments", None),
- )
- )
+ out.append(_tool_message_with_content(m, guarded, sid=session_id))
if trace_id:
_emit_direct_loop_trace(
store=store,
@@ -631,6 +623,7 @@ def _build_model_context(
model=model,
lang=lang,
tool_context_truncate_enabled=tool_context_truncate_enabled,
+ active_turn_uuid=active_turn_uuid,
)
diff --git a/runtime/gateway.py b/runtime/gateway.py
index 20f55f75..0880a14c 100644
--- a/runtime/gateway.py
+++ b/runtime/gateway.py
@@ -35,6 +35,7 @@ from oclaw.runtime.router import decide_route
from oclaw.runtime.worker import ensure_worker_started
from oclaw.runtime.orchestration.trace import new_span_id, new_trace_id
from oclaw.runtime.chat.tool_runtime import compact_turn_tool_messages_for_storage
+from oclaw.runtime.chat.model_path_audit import ensure_no_tool_or_embedded_image_payload
_OC_STAGE_BY_EVENT: dict[str, str] = {
"gateway_received": "ingress",
@@ -203,11 +204,9 @@ class OclawGateway:
else "仅基于以下用户正文生成简短会话标题。请使用对话内容主体语言命名。"
"只返回标题文本，不要引号，不要markdown，最多18个字。"
)
- resp = model.chat(
- [{"role": "system", "content": sys}, {"role": "user", "content": body}],
- [],
- on_token=None,
- )
+ messages = [{"role": "system", "content": sys}, {"role": "user", "content": body}]
+ ensure_no_tool_or_embedded_image_payload(messages=messages, path="gateway.auto_title")
+ resp = model.chat(messages, [], on_token=None)
title = str(getattr(resp, "content", "") or "").strip().replace("\n", " ")
title = title.strip("\"'` ").strip()
if not title:
@@ -317,6 +316,7 @@ class OclawGateway:
),
},
]
+ ensure_no_tool_or_embedded_image_payload(messages=messages, path="gateway.manager_select")
resp = model.chat(messages, [], on_token=None)
obj = self._parse_json_object(str(getattr(resp, "content", "") or ""))
if not isinstance(obj, dict):
@@ -404,11 +404,9 @@ class OclawGateway:
f"专家结果:\n{str(specialist_reply or '').strip()}\n\n"
"要求：保持简洁、准确，不要暴露内部流程。"
)
- resp = model.chat(
- [{"role": "system", "content": manager_context}, {"role": "user", "content": user_text}],
- [],
- on_token=on_token,
- )
+ messages = [{"role": "system", "content": manager_context}, {"role": "user", "content": user_text}]
+ ensure_no_tool_or_embedded_image_payload(messages=messages, path="gateway.manager_finalize")
+ resp = model.chat(messages, [], on_token=on_token)
final_text = str(getattr(resp, "content", "") or "").strip()
return final_text or str(specialist_reply or "")
except Exception:
diff --git a/runtime/router.py b/runtime/router.py
index 96356785..228f5295 100644
--- a/runtime/router.py
+++ b/runtime/router.py
@@ -8,6 +8,7 @@ from typing import Any
from oclaw.runtime.types import StandardMessage
from oclaw.runtime.types import normalize_interaction_mode, normalize_requested_specialist
from oclaw.prompts.loader import render_runtime_prompt
+from oclaw.runtime.chat.model_path_audit import ensure_no_tool_or_embedded_image_payload
@dataclass(frozen=True)
@@ -86,6 +87,7 @@ def _decide_llm_json(msg: StandardMessage, *, model: Any | None) -> RouterDecisi
},
{"role": "user", "content": user_block},
]
+ ensure_no_tool_or_embedded_image_payload(messages=messages, path="router.llm_json")
resp = model.chat(messages, [], on_token=None)
raw = str(getattr(resp, "content", "") or "")
obj = _parse_router_json_object(raw)
diff --git a/runtime/skills/aiops-telecom/SKILL.md b/runtime/skills/aiops-telecom/SKILL.md
new file mode 100644
index 00000000..e661860b
--- /dev/null
+++ b/runtime/skills/aiops-telecom/SKILL.md
@@ -0,0 +1,144 @@
+# AIOps-电信数通智能运维技能包
+
+## 概述
+面向电信/数通网络的 AI 智能运维技能包。支持告警日志智能分析、配置错漏检查、故障模式学习与根因推荐。适用于华为、中兴、Cisco、Juniper 等主流数通设备。
+
+## 能力说明
+
+### 1. 告警日志智能分析
+
+#### 1.1 输入格式支持
+- Excel/CSV 格式的告警清单（如网管导出的告警报表）
+- 纯文本格式的 syslog/告警日志
+- 设备 CLI 输出的告警信息
+
+#### 1.2 分析维度
+
+| 维度 | 说明 |
+|------|------|
+| **告警分级统计** | Critical / Major / Warning 级别分布及占比 |
+| **设备维度聚合** | 按设备（ME/NE）统计告警数量 Top N |
+| **告警类型归类** | 物理层/链路层/网络层/路由层/安全层分类 |
+| **时间维度分析** | 告警爆发时间窗口、频次趋势 |
+| **关联分析** | 同设备/同链路的多层告警关联，推测根因 |
+| **影响评估** | 评估受影响业务（L3VPN/Tunnel/Ethernet）范围 |
+
+#### 1.3 告警类型知识库
+
+##### 物理层告警
+| 告警名称 | 级别 | 含义 | 常见根因 | 推荐操作 |
+|----------|------|------|---------|---------|
+| Ethernet Physical LOS | Critical | 光口信号丢失 | 光纤断/松、光模块故障、对端设备断电 | 检查光纤链路、光功率、更换光模块 |
+| Ethernet Physical Laser Temperature | Major | 激光器温度越限 | 光模块老化、设备散热不良、环境温度过高 | 检查设备风扇/温度、更换光模块 |
+| Ethernet Physical Input Optical Power | Major | 接收光功率越限 | 光纤衰减过大、接口脏污、对端发光异常 | 清洁光纤接头、检查光功率预算 |
+| Ethernet Physical CRC Error | Major | CRC 误码越限 | 光纤质量差、接头污染、电磁干扰 | 清洁光纤、检查物理链路、更换尾纤 |
+| SmartGroup RX CRC Error | Major | 聚合口 CRC 误码 | 聚合成员链路质量问题 | 排查各成员链路、更换问题链路 |
+
+##### 路由/MPLS层告警
+| 告警名称 | 级别 | 含义 | 常见根因 | 推荐操作 |
+|----------|------|------|---------|---------|
+| OSPF Neighbor Down | Major | OSPF 邻居中断 | 物理链路故障、Hello 超时、配置不匹配 | 检查邻居间链路、验证 OSPF 配置参数 |
+| RSVP LSP BFD Session Down | Major | MPLS TE隧道 BFD 检测失败 | 隧道途经链路故障、节点故障 | 检查隧道路径、确认中间节点状态 |
+| BGP Peer Flap | Major | BGP 邻居震荡 | 链路不稳、Keepalive 超时、策略变更 | 检查 BGP 配置、链路稳定性 |
+
+##### 安全/控制面告警
+| 告警名称 | 级别 | 含义 | 常见根因 | 推荐操作 |
+|----------|------|------|---------|---------|
+| CPSBP 超阈值 | Warning | 控制面报文速率超阈值 | 攻击流量、广播风暴、配置过低 | 分析流量源、调整 CP 保护阈值 |
+| ARP IP冲突 | Warning | 检测到 IP 地址冲突 | 私接设备、IP 配置错误 | 定位冲突源、释放/更改 IP 地址 |
+
+### 2. 配置错漏检查
+
+#### 2.1 支持检查项
+
+| 检查类别 | 典型检查项 |
+|----------|-----------|
+| **接口配置** | VLAN 配置一致性、MTU 匹配、描述规范、端口模式(access/trunk) |
+| **路由协议** | OSPF area 一致性、BGP AS 号核对、Route-map 逻辑、邻居配置完整性 |
+| **MPLS/TE** | LSP 配置完整性、隧道保护策略、FRR 配置 |
+| **安全策略** | ACL 规则匹配、控制面保护(CoPP)、端口安全、MAC 漂移检测 |
+| **高可用** | VRRP/HSRP 配置一致性、BFD 联动、链路聚合(LACP)配置 |
+| **QoS** | 队列策略、带宽限制、优先级映射 |
+
+#### 2.2 分析模式
+- **配置比对**：新旧配置 diff，快速定位变更点
+- **合规检查**：基于标准模板检查配置是否符合规范
+- **逻辑验证**：检查配置逻辑矛盾（如 ACL 冗余/冲突、路由黑洞）
+
+### 3. 故障模式学习 (self-learning)
+
+系统会记录每次分析过程中的：
+- 告警 → 修复措施 对应关系
+- 配置错误 → 正确配置 修正方案
+- 经用户确认的根因分析结论
+
+这些 learnings 会存入 `.learnings/` 目录，在后续分析中自动参考，越用越准确。
+
+## 使用示例
+
+### 示例1：告警日志分析
+```
+用户: "分析这份告警日志"
+助手: 按以下格式输出分析报告：
+
+📊 告警概览
+- 总告警数：24条
+- Critical：2条 (8.3%) ⛔
+- Major：9条 (37.5%) ⚠️
+- Warning：13条 (54.2%) ⚡
+
+🔴 Critical 告警详情
+1. [SMD-LIIR-EN1-Z20HS] ETPI LOS → 物理光口信号丢失
+ → 该设备下联 SMD-SBRS-EN1-Z20HS，状态 Unack
+ → 建议：立即检查光纤/光模块
+
+🟠 Major 告警详情
+1. [BKL-UNB-AN1-ZM3SP] 光功率越限 → 接收光功率过低
+2. [MDN-PMKN-EN1-Z20HS] 激光器温度越限
+3. [PAD-KBU-AN1-ZM8S] CRC误码越限（物理口+聚合口）
+4. RSVP LSP BFD Session Down ×3条
+5. OSPF邻居中断 ×2条
+
+🔄 关联分析发现
+- PBR-RPKU 与 PBR-PYSK 之间：OSPF邻居中断 + CPSBP告警
+ → 推测该链路存在物理层问题
+- GRO 站点多条 RSVP LSP BFD Down
+ → 可能为 GRO 节点设备问题或出局光缆中断
+
+💡 根因推荐
+1. 优先处理 SMD-LIIR-EN1-Z20HS 的 LOS（Critical）
+2. 检查 PBR-RPKU ↔ PBR-PYSK 链路光功率和光模块
+3. 排查 GRO 站点汇聚设备状态
+```
+
+### 示例2：配置检查
+```
+用户: "帮我检查这两份配置文件"
+助手:
+🔍 配置检查报告
+1. OSPF 配置检查 ✅
+ - Area 一致性：匹配
+ - Hello/Dead 间隔：一致
+ - 网络类型：一致
+
+2. 接口配置检查 ⚠️
+ - [GE0/0/1] MTU 不匹配：本端 1500，对端 9000
+ - [GE0/0/2] 描述缺失
+
+3. BGP 配置检查 ❌
+ - AS 号不匹配：本端 AS65001，对端 AS65002
+```
+
+## 数据来源说明
+
+本技能的知识库基于以下标准构建：
+- 华为 NE40E/ME60 系列告警手册
+- 中兴 ZXR10 系列告警与配置规范
+- 3GPP 管理面标准（IRP/Solution）
+- ITU-T 光传输标准
+- RFC 相关协议标准
+
+## 局限性与注意事项
+- 本技能不直接连接设备执行命令，不做配置变更操作
+- 分析结果基于提供的日志/配置数据，用户需确认数据准确性
+- 推荐操作为参考建议，重大操作需人工复核
diff --git a/runtime/worker.py b/runtime/worker.py
index 3e060267..32709a72 100644
--- a/runtime/worker.py
+++ b/runtime/worker.py
@@ -11,6 +11,7 @@ from oclaw.runtime.agent_core_run import AgentCoreRunInput, run_agent_core
from oclaw.runtime.memory_stage import build_memory_context
from oclaw.runtime.relay_pointer import build_acp_relay_result, validate_relay_share_envelope
from oclaw.runtime.types import StandardMessage
+from oclaw.runtime.chat.model_path_audit import ensure_no_tool_or_embedded_image_payload
_LOCK = threading.Lock()
_THREAD: threading.Thread | None = None
@@ -120,11 +121,9 @@ def _maybe_generate_title_on_third_round(*, store: Any, msg: StandardMessage, mo
else "仅基于以下用户正文生成简短会话标题。请使用对话内容主体语言命名。"
"只返回标题文本，不要引号，不要markdown，最多18个字。"
)
- resp = model.chat(
- [{"role": "system", "content": sys}, {"role": "user", "content": body}],
- [],
- on_token=None,
- )
+ messages = [{"role": "system", "content": sys}, {"role": "user", "content": body}]
+ ensure_no_tool_or_embedded_image_payload(messages=messages, path="worker.auto_title")
+ resp = model.chat(messages, [], on_token=None)
title = str(getattr(resp, "content", "") or "").strip().replace("\n", " ")
title = title.strip("\"'` ").strip()
if not title:
diff --git a/tests/test_media_redact.py b/tests/test_media_redact.py
new file mode 100644
index 00000000..e8698ded
--- /dev/null
+++ b/tests/test_media_redact.py
@@ -0,0 +1,44 @@
+from __future__ import annotations
+
+import base64
+
+from oclaw.runtime.chat.media_redact import ingest_embedded_image_blobs_as_refs, redact_embedded_image_blobs
+
+
+def test_redact_nested_mcp_image_block() -> None:
+ big = "/9j/" + "a" * 800
+ obj = {
+ "ok": True,
+ "result": {"content": [{"type": "image", "mime": "image/jpeg", "data": big}]},
+ }
+ out = redact_embedded_image_blobs(obj)
+ assert out["result"]["content"][0].get("_image_payload_redacted") is True
+ assert "data" not in out["result"]["content"][0]
+ assert isinstance(out["result"]["content"][0].get("_redacted_payload_chars"), int)
+
+
+def test_redact_keeps_small_data_field() -> None:
+ obj = {"type": "image", "mime": "image/png", "data": "abc"}
+ assert redact_embedded_image_blobs(obj) == obj
+
+
+def test_ingest_embedded_image_blob_as_ref(tmp_path) -> None:
+ raw = base64.b64encode(b"png-bytes").decode("ascii")
+ obj = {"result": {"content": [{"type": "image", "mime": "image/png", "data": raw, "name": "x.png"}]}}
+ out, refs = ingest_embedded_image_blobs_as_refs(obj, root_dir=str(tmp_path), filename_prefix="unit")
+ block = out["result"]["content"][0]
+ assert block["type"] == "image_ref"
+ assert str(block.get("attachment_id") or "")
+ assert "data" not in block
+ assert refs and refs[0]["attachment_id"] == block["attachment_id"]
+
+
+def test_ingest_embedded_binary_blob_as_binary_ref(tmp_path) -> None:
+ raw = base64.b64encode(b"%PDF-1.4-fake").decode("ascii")
+ obj = {"result": {"content": [{"type": "file", "mime": "application/pdf", "base64": raw, "name": "a.pdf"}]}}
+ out, refs = ingest_embedded_image_blobs_as_refs(obj, root_dir=str(tmp_path), filename_prefix="unit")
+ block = out["result"]["content"][0]
+ assert block["type"] == "binary_ref"
+ assert str(block.get("attachment_id") or "")
+ assert "base64" not in block
+ assert refs and refs[0]["attachment_id"] == block["attachment_id"]
diff --git a/tests/test_model_path_audit.py b/tests/test_model_path_audit.py
new file mode 100644
index 00000000..91cca02d
--- /dev/null
+++ b/tests/test_model_path_audit.py
@@ -0,0 +1,46 @@
+from __future__ import annotations
+
+from oclaw.runtime.chat.model_path_audit import ensure_no_tool_or_embedded_image_payload
+
+
+def test_audit_accepts_plain_system_user_messages() -> None:
+ ensure_no_tool_or_embedded_image_payload(
+ path="unit.ok",
+ messages=[
+ {"role": "system", "content": "sys"},
+ {"role": "user", "content": "hello"},
+ ],
+ )
+
+
+def test_audit_degrades_tool_role() -> None:
+ msgs = [
+ {"role": "assistant", "content": "a"},
+ {"role": "tool", "content": '{"ok":true}'},
+ ]
+ ensure_no_tool_or_embedded_image_payload(path="unit.tool", messages=msgs)
+ assert msgs[1]["role"] == "assistant"
+ assert "omitted" in str(msgs[1]["content"] or "")
+
+
+def test_audit_degrades_embedded_image_payload() -> None:
+ msgs = [
+ {
+ "role": "user",
+ "content": [
+ {"type": "text", "text": "x"},
+ {"type": "input_image", "image_base64": "a" * 600, "mime": "image/png"},
+ ],
+ }
+ ]
+ ensure_no_tool_or_embedded_image_payload(path="unit.image", messages=msgs)
+ c = msgs[0]["content"]
+ assert isinstance(c, list)
+ assert any(isinstance(x, dict) and str(x.get("type") or "") == "text" and "omitted" in str(x.get("text") or "") for x in c)
+
+
+def test_audit_degrades_large_base64_like_plain_text() -> None:
+ payload = "A" * 700
+ msgs = [{"role": "user", "content": payload}]
+ ensure_no_tool_or_embedded_image_payload(path="unit.b64_text", messages=msgs)
+ assert "omitted" in str(msgs[0]["content"] or "")
diff --git a/tests/test_oclaw_tool_result_guard.py b/tests/test_oclaw_tool_result_guard.py
index adcee740..88a46a92 100644
--- a/tests/test_oclaw_tool_result_guard.py
+++ b/tests/test_oclaw_tool_result_guard.py
@@ -1,5 +1,6 @@
from __future__ import annotations
+import json
from pathlib import Path
from oclaw.runtime.direct_loop import _OCLAW_TOOL_RESULT_HARD_CAP_CHARS, _build_model_context
@@ -78,3 +79,42 @@ def test_oclaw_tool_result_context_guard_skips_active_turn_tool_messages(tmp_pat
raw = str(tool_msgs[-1].get("content") or "")
assert "_tool_result_guarded" not in raw
+
+def test_guard_redacts_mcp_nested_image_for_non_active_turn(tmp_path: Path) -> None:
+ store = SqliteStore(str(tmp_path / "ops.sqlite"))
+ sess = store.create_session("t")
+ past_turn = "turn-old"
+ blob = "/9j/" + "a" * 1200
+ body = {"ok": True, "result": {"content": [{"type": "image", "mime": "image/jpeg", "data": blob}]}}
+ store.add_message(
+ session_id=sess.id,
+ role="assistant",
+ content="",
+ tool_calls=[{"id": "c_hist", "name": "mcp", "arguments": {}}],
+ turn_uuid=past_turn,
+ )
+ store.add_message(
+ session_id=sess.id,
+ role="tool",
+ content=json.dumps(body, ensure_ascii=False),
+ tool_calls={"tool_call_id": "c_hist", "name": "mcp", "assistant_message_id": 1},
+ turn_uuid=past_turn,
+ )
+ msgs = _build_model_context(
+ store=store,
+ session_id=sess.id,
+ max_messages=50,
+ system_prompt="sys",
+ model=RuleBasedChatModel(),
+ lang="zh",
+ memory_context=None,
+ trace_id="t1",
+ parent_span_id=None,
+ active_turn_uuid="different-active-turn",
+ )
+ tm = next(m for m in msgs if m.get("role") == "tool")
+ inner = json.loads(str(tm.get("content") or ""))
+ block = inner["result"]["content"][0]
+ assert block.get("_image_payload_redacted") is True
+ assert "data" not in block
+
diff --git a/tests/test_tool_loop_guard.py b/tests/test_tool_loop_guard.py
index cc2e66d1..042f50f8 100644
--- a/tests/test_tool_loop_guard.py
+++ b/tests/test_tool_loop_guard.py
@@ -1,5 +1,6 @@
from __future__ import annotations
+import base64
import json
from pathlib import Path
@@ -89,6 +90,94 @@ def test_repeated_tool_results_are_compacted_in_history(tmp_path: Path) -> None:
assert "audit_note" in payloads[2]
+def test_tool_result_image_blob_persisted_as_attachment_ref(tmp_path: Path) -> None:
+ store = SqliteStore(str(tmp_path / "img.sqlite"))
+ sess = store.create_session("t")
+
+ def _handler(_args):
+ raw = base64.b64encode(b"\x89PNGtest-image").decode("ascii")
+ return {
+ "ok": True,
+ "result": {"content": [{"type": "image", "mime": "image/png", "data": raw, "name": "mcp.png"}]},
+ }
+
+ reg = ToolRegistry(
+ [
+ ToolSpec(
+ name="mcp_image_tool",
+ description="returns image payload",
+ parameters={"type": "object", "properties": {}},
+ handler=_handler,
+ read_only=True,
+ )
+ ]
+ )
+ tool_uses = [LLMToolCall(id="c1", name="mcp_image_tool", arguments={})]
+ ToolExecutor().execute_tool_uses(
+ ctx=ToolExecutionContext(store=store, tools=reg, session_id=sess.id, turn_uuid="turn-img"),
+ assistant_msg_id=1,
+ tool_uses=tool_uses,
+ )
+ rows = store.get_messages(session_id=sess.id, limit=20)
+ tool_rows = [m for m in rows if str(getattr(m, "role", "") or "") == "tool"]
+ assert len(tool_rows) == 1
+ payload = json.loads(str(getattr(tool_rows[0], "content", "") or "{}"))
+ blk = (((payload.get("result") or {}).get("content") or [{}])[0]) if isinstance(payload, dict) else {}
+ assert isinstance(blk, dict)
+ assert str(blk.get("type") or "") == "image_ref"
+ assert str(blk.get("attachment_id") or "")
+ assert "data" not in blk
+ atts = json.loads(str(getattr(tool_rows[0], "attachments", "") or "[]"))
+ assert isinstance(atts, list) and atts
+ assert str((atts[0] or {}).get("type") or "") == "image_ref"
+ assert str((atts[0] or {}).get("attachment_id") or "")
+ logs = store.get_tool_logs(sess.id, limit=10)
+ assert logs and isinstance(logs[0], dict)
+ body = logs[0].get("result") or {}
+ blk2 = (((body.get("result") or {}).get("content") or [{}])[0]) if isinstance(body, dict) else {}
+ assert isinstance(blk2, dict)
+ assert str(blk2.get("type") or "") == "image_ref"
+ assert "data" not in blk2
+
+
+def test_tool_result_non_image_base64_persisted_as_binary_ref(tmp_path: Path) -> None:
+ store = SqliteStore(str(tmp_path / "bin.sqlite"))
+ sess = store.create_session("t")
+
+ def _handler(_args):
+ raw = base64.b64encode(b"PK\x03\x04fake-zip-bytes").decode("ascii")
+ return {"ok": True, "result": {"content": [{"type": "file", "mime": "application/zip", "base64": raw, "name": "a.zip"}]}}
+
+ reg = ToolRegistry(
+ [
+ ToolSpec(
+ name="mcp_file_tool",
+ description="returns file payload",
+ parameters={"type": "object", "properties": {}},
+ handler=_handler,
+ read_only=True,
+ )
+ ]
+ )
+ ToolExecutor().execute_tool_uses(
+ ctx=ToolExecutionContext(store=store, tools=reg, session_id=sess.id, turn_uuid="turn-bin"),
+ assistant_msg_id=1,
+ tool_uses=[LLMToolCall(id="c1", name="mcp_file_tool", arguments={})],
+ )
+ rows = store.get_messages(session_id=sess.id, limit=20)
+ tool_rows = [m for m in rows if str(getattr(m, "role", "") or "") == "tool"]
+ assert len(tool_rows) == 1
+ payload = json.loads(str(getattr(tool_rows[0], "content", "") or "{}"))
+ blk = (((payload.get("result") or {}).get("content") or [{}])[0]) if isinstance(payload, dict) else {}
+ assert isinstance(blk, dict)
+ assert str(blk.get("type") or "") == "binary_ref"
+ assert str(blk.get("attachment_id") or "")
+ assert "base64" not in blk
+ atts = json.loads(str(getattr(tool_rows[0], "attachments", "") or "[]"))
+ assert isinstance(atts, list) and atts
+ assert str((atts[0] or {}).get("type") or "") == "binary_ref"
+
+
def test_repeated_non_sql_tools_are_not_compacted(tmp_path: Path) -> None:
store = SqliteStore(str(tmp_path / "g3.sqlite"))
sess = store.create_session("t")
@@ -429,6 +518,11 @@ def test_tool_result_image_payload_persisted_as_attachments(tmp_path: Path) -> N
tool_rows = [m for m in rows if str(getattr(m, "role", "") or "") == "tool"]
assert len(tool_rows) == 1
attachments = json.loads(str(getattr(tool_rows[0], "attachments", "") or "[]"))
- assert any(str(a.get("type") or "") == "image" and str(a.get("data") or "") == "YWJj" for a in attachments)
+ assert any(str(a.get("type") or "") == "image_ref" and str(a.get("attachment_id") or "") for a in attachments)
assert any(str(a.get("type") or "") == "image_url" and str(a.get("url") or "").endswith("/a.png") for a in attachments)
+ body = json.loads(str(getattr(tool_rows[0], "content", "") or "{}"))
+ content_items = ((body.get("result") or {}).get("content") or []) if isinstance(body, dict) else []
+ image_block = next((x for x in content_items if isinstance(x, dict) and str(x.get("type") or "") == "image_ref"), {})
+ assert str(image_block.get("attachment_id") or "")
+ assert "data" not in image_block
diff --git a/tests/test_tool_pairing_messages.py b/tests/test_tool_pairing_messages.py
index f83b693c..6c9f0cd1 100644
--- a/tests/test_tool_pairing_messages.py
+++ b/tests/test_tool_pairing_messages.py
@@ -138,7 +138,13 @@ def test_signature_metadata_not_replayed_by_default_for_non_whitelist_model() ->
ensure_ascii=False,
),
event_type="tool_call",
- )
+ ),
+ _Msg(
+ "tool",
+ json.dumps({"ok": True}),
+ tool_calls=json.dumps({"tool_call_id": "call_1", "name": "t"}, ensure_ascii=False),
+ event_type="tool_result",
+ ),
]
msgs = build_llm_messages(store_messages=rows, system_prompt="s", model=model, lang="zh")
assistant = [m for m in msgs if m.get("role") == "assistant"][0]
@@ -158,7 +164,13 @@ def test_signature_metadata_can_be_forced_on_via_env(monkeypatch) -> None:
ensure_ascii=False,
),
event_type="tool_call",
- )
+ ),
+ _Msg(
+ "tool",
+ json.dumps({"ok": True}),
+ tool_calls=json.dumps({"tool_call_id": "call_1", "name": "t"}, ensure_ascii=False),
+ event_type="tool_result",
+ ),
]
msgs = build_llm_messages(store_messages=rows, system_prompt="s", model=model, lang="zh")
assistant = [m for m in msgs if m.get("role") == "assistant"][0]
diff --git a/tests/test_tool_runtime_attachments.py b/tests/test_tool_runtime_attachments.py
new file mode 100644
index 00000000..140c0a33
--- /dev/null
+++ b/tests/test_tool_runtime_attachments.py
@@ -0,0 +1,30 @@
+from __future__ import annotations
+
+from oclaw.runtime.chat.tool_runtime import _attachments_from_tool_result
+
+
+def test_attachments_from_tool_result_preserves_non_image_ref_types() -> None:
+ result = {
+ "attachments": [
+ {
+ "type": "text_ref",
+ "attachment_id": "att-text-1",
+ "mime": "text/plain",
+ "name": "a.txt",
+ "bytes": 12,
+ },
+ {
+ "attachment_id": "att-video-1",
+ "mime": "video/mp4",
+ "name": "a.mp4",
+ "bytes": 1024,
+ },
+ ]
+ }
+
+ out = _attachments_from_tool_result(result)
+ by_id = {str(x.get("attachment_id")): x for x in out}
+
+ assert by_id["att-text-1"]["type"] == "text_ref"
+ assert by_id["att-video-1"]["type"] == "video_ref"
+