fix(api_server): normalize array-based content parts in chat completions

Some OpenAI-compatible clients (Open WebUI, LobeChat, etc.) send
message content as an array of typed parts instead of a plain string:

    [{"type": "text", "text": "hello"}]

The agent pipeline expects strings, so these array payloads caused
silent failures or empty messages.

Add _normalize_chat_content() with defensive limits (recursion depth,
list size, output length) and apply it to both the Chat Completions
and Responses API endpoints. The Responses path had inline
normalization that only handled input_text/output_text — the shared
function also handles the standard 'text' type.

Salvaged from PR #7980 (ikelvingo) — only the content normalization;
the SSE and Weixin changes in that PR were regressions and are not
included.

Co-authored-by: ikelvingo <ikelvingo@users.noreply.github.com>

gateway/platforms/api_server.py

@@ -54,6 +54,66 @@ DEFAULT_PORT = 8642
 MAX_STORED_RESPONSES = 100
 MAX_REQUEST_BYTES = 1_000_000  # 1 MB default limit for POST bodies
 CHAT_COMPLETIONS_SSE_KEEPALIVE_SECONDS = 30.0
+MAX_NORMALIZED_TEXT_LENGTH = 65_536  # 64 KB cap for normalized content parts
+MAX_CONTENT_LIST_SIZE = 1_000  # Max items when content is an array
+
+
+def _normalize_chat_content(
+    content: Any, *, _max_depth: int = 10, _depth: int = 0,
+) -> str:
+    """Normalize OpenAI chat message content into a plain text string.
+
+    Some clients (Open WebUI, LobeChat, etc.) send content as an array of
+    typed parts instead of a plain string::
+
+        [{"type": "text", "text": "hello"}, {"type": "input_text", "text": "..."}]
+
+    This function flattens those into a single string so the agent pipeline
+    (which expects strings) doesn't choke.
+
+    Defensive limits prevent abuse: recursion depth, list size, and output
+    length are all bounded.
+    """
+    if _depth > _max_depth:
+        return ""
+    if content is None:
+        return ""
+    if isinstance(content, str):
+        return content[:MAX_NORMALIZED_TEXT_LENGTH] if len(content) > MAX_NORMALIZED_TEXT_LENGTH else content
+
+    if isinstance(content, list):
+        parts: List[str] = []
+        items = content[:MAX_CONTENT_LIST_SIZE] if len(content) > MAX_CONTENT_LIST_SIZE else content
+        for item in items:
+            if isinstance(item, str):
+                if item:
+                    parts.append(item[:MAX_NORMALIZED_TEXT_LENGTH])
+            elif isinstance(item, dict):
+                item_type = str(item.get("type") or "").strip().lower()
+                if item_type in {"text", "input_text", "output_text"}:
+                    text = item.get("text", "")
+                    if text:
+                        try:
+                            parts.append(str(text)[:MAX_NORMALIZED_TEXT_LENGTH])
+                        except Exception:
+                            pass
+                # Silently skip image_url / other non-text parts
+            elif isinstance(item, list):
+                nested = _normalize_chat_content(item, _max_depth=_max_depth, _depth=_depth + 1)
+                if nested:
+                    parts.append(nested)
+            # Check accumulated size
+            if sum(len(p) for p in parts) >= MAX_NORMALIZED_TEXT_LENGTH:
+                break
+        result = "\n".join(parts)
+        return result[:MAX_NORMALIZED_TEXT_LENGTH] if len(result) > MAX_NORMALIZED_TEXT_LENGTH else result
+
+    # Fallback for unexpected types (int, float, bool, etc.)
+    try:
+        result = str(content)
+        return result[:MAX_NORMALIZED_TEXT_LENGTH] if len(result) > MAX_NORMALIZED_TEXT_LENGTH else result
+    except Exception:
+        return ""
 
 
 def check_api_server_requirements() -> bool:
@@ -553,7 +613,7 @@ class APIServerAdapter(BasePlatformAdapter):
 
         for msg in messages:
             role = msg.get("role", "")
-            content = msg.get("content", "")
+            content = _normalize_chat_content(msg.get("content", ""))
             if role == "system":
                 # Accumulate system messages
                 if system_prompt is None:
@@ -926,18 +986,7 @@ class APIServerAdapter(BasePlatformAdapter):
                     input_messages.append({"role": "user", "content": item})
                 elif isinstance(item, dict):
                     role = item.get("role", "user")
-                    content = item.get("content", "")
-                    # Handle content that may be a list of content parts
-                    if isinstance(content, list):
-                        text_parts = []
-                        for part in content:
-                            if isinstance(part, dict) and part.get("type") == "input_text":
-                                text_parts.append(part.get("text", ""))
-                            elif isinstance(part, dict) and part.get("type") == "output_text":
-                                text_parts.append(part.get("text", ""))
-                            elif isinstance(part, str):
-                                text_parts.append(part)
-                        content = "\n".join(text_parts)
+                    content = _normalize_chat_content(item.get("content", ""))
                     input_messages.append({"role": role, "content": content})
         else:
             return web.json_response(_openai_error("'input' must be a string or array"), status=400)