feat: multimodal image clients, workspaces, Tushare skill, test fixes

- Replace monolithic image_message_client with HTTP/OCR/legacy modules; tighten OpenAI transport + tool schemas for multimodal downgrade to OCR specialist path.
- Add image/stock workspace prompts (META/SOUL/ROLE_SYSTEM); register experts; tweak specialist agent/direct loop/query_image_attachment.
- Add bundled runtime/skills/tushare-finance (references, api_client, SKILL metadata).
- Document OCR-related env vars; admin chat tweaks; README; weixin_install Ensure-OfficialPluginRuntimeDeps helper.
- Tests: multimodal downgrade + OCR coverage, strict tool pairing in attachment replay guard, workspace contract skips _internal/_system dirs, router/trace/prompt guards.

Co-authored-by: Cursor <cursoragent@cursor.com>

platform/llm/image_http_common.py

@@ -0,0 +1,148 @@
+"""Shared HTTP helpers for OCR and legacy image lanes (internal)."""
+
+from __future__ import annotations
+
+import base64
+import io
+import os
+import time
+from typing import Any
+
+import httpx
+from PIL import Image
+
+
+def join_url(base: str, path: str) -> str:
+    b = (base or "").rstrip("/")
+    p = (path or "").lstrip("/")
+    return f"{b}/{p}"
+
+
+def env_ocr_lane_api_key() -> str:
+    return (os.getenv("AIA_OCR_API_KEY") or "").strip()
+
+
+def env_ocr_lane_base_url() -> str:
+    return (os.getenv("AIA_OCR_BASE_URL") or "").strip()
+
+
+def env_ocr_lane_model() -> str:
+    return (os.getenv("AIA_OCR_MODEL") or "").strip()
+
+
+def env_ocr_lane_chat_endpoint() -> str:
+    raw = (os.getenv("AIA_OCR_CHAT_ENDPOINT") or "").strip()
+    return raw or "/chat/completions"
+
+
+def is_data_url(s: str) -> bool:
+    return s.startswith("data:") and ";base64," in s
+
+
+def compress_data_url_image(
+    data_url: str,
+    *,
+    max_side: int = 1600,
+    max_bytes: int = 2 * 1024 * 1024,
+    jpeg_quality: int = 82,
+) -> str:
+    if not is_data_url(data_url):
+        return data_url
+    try:
+        header, b64 = data_url.split(";base64,", 1)
+        mime = header.replace("data:", "", 1).strip() or "image/jpeg"
+        raw = base64.b64decode(b64.encode("ascii"))
+        if len(raw) <= max_bytes:
+            return data_url
+
+        with Image.open(io.BytesIO(raw)) as im:
+            im = im.convert("RGB")
+            w, h = im.size
+            longest = max(w, h)
+            if longest > max_side:
+                scale = max_side / float(longest)
+                nw, nh = max(1, int(w * scale)), max(1, int(h * scale))
+                im = im.resize((nw, nh), Image.Resampling.LANCZOS)
+
+            out = io.BytesIO()
+            im.save(out, format="JPEG", quality=max(30, min(95, int(jpeg_quality))), optimize=True)
+            blob = out.getvalue()
+            if not blob:
+                return data_url
+            b64_new = base64.b64encode(blob).decode("ascii")
+            return f"data:{'image/jpeg' if mime.startswith('image/') else mime};base64,{b64_new}"
+    except Exception:
+        return data_url
+
+
+def post_with_retry(
+    client: httpx.Client,
+    *,
+    url: str,
+    headers: dict[str, str],
+    payload: dict[str, Any],
+    retries: int = 3,
+    backoff_sec: float = 0.8,
+) -> httpx.Response:
+    last_exc: Exception | None = None
+    for attempt in range(1, max(1, retries) + 1):
+        try:
+            return client.post(url, headers=headers, json=payload)
+        except (httpx.ReadError, httpx.ConnectError, httpx.TimeoutException) as e:
+            last_exc = e
+            if attempt >= retries:
+                break
+            time.sleep(backoff_sec * (2 ** (attempt - 1)))
+    assert last_exc is not None
+    raise last_exc
+
+
+def extract_text_and_images(resp_json: dict[str, Any]) -> tuple[str, list[str]]:
+    text_parts: list[str] = []
+    images: list[str] = []
+    choices = resp_json.get("choices")
+    if isinstance(choices, list) and choices:
+        msg = choices[0].get("message") if isinstance(choices[0], dict) else None
+        if isinstance(msg, dict):
+            c = msg.get("content")
+            if isinstance(c, str):
+                text_parts.append(c)
+            elif isinstance(c, list):
+                for it in c:
+                    if not isinstance(it, dict):
+                        continue
+                    if isinstance(it.get("text"), str):
+                        text_parts.append(str(it.get("text")))
+                    elif isinstance(it.get("image"), str):
+                        images.append(str(it.get("image")))
+                    elif isinstance(it.get("image_url"), str):
+                        images.append(str(it.get("image_url")))
+                    elif isinstance(it.get("image_url"), dict) and isinstance(it["image_url"].get("url"), str):
+                        images.append(str(it["image_url"]["url"]))
+                    elif isinstance(it.get("b64_json"), str):
+                        images.append(f"data:image/png;base64,{it['b64_json']}")
+
+    if not images:
+        data = resp_json.get("data")
+        if isinstance(data, list):
+            for it in data:
+                if not isinstance(it, dict):
+                    continue
+                if isinstance(it.get("url"), str):
+                    images.append(str(it.get("url")))
+                if isinstance(it.get("b64_json"), str):
+                    images.append(f"data:image/png;base64,{it['b64_json']}")
+    return "\n".join([x for x in text_parts if x]).strip(), images
+
+
+__all__ = [
+    "compress_data_url_image",
+    "env_ocr_lane_api_key",
+    "env_ocr_lane_base_url",
+    "env_ocr_lane_chat_endpoint",
+    "env_ocr_lane_model",
+    "extract_text_and_images",
+    "is_data_url",
+    "join_url",
+    "post_with_retry",
+]