feat: cap telemetry bodies at a configurable length

Chat rows stored full message and response text with no upper bound, so
downstream contracts and tenders lived in llm_calls indefinitely. Add
_cap_text/_cap_messages in the single telemetry exit (_record), applied
after digest_messages and before json.dumps, plus to response/thinking.

Capping is per text, not over the serialized JSON: cutting the whole
string would emit invalid JSON into an unvalidated TEXT column. The cap
builds new dicts and never mutates in place — digest_messages passes
non-list content straight through as the same object, so an in-place cut
would silently poison the caller's messages and the cache key.

text_cap is required on TelemetryEmitter (internal class, three known
construction sites) and defaults to None on the three public clients, so
the default behaviour stays byte-for-byte identical. Settings wiring
lands separately.

src/polygateway/middleware/telemetry.py

@@ -55,6 +55,44 @@ def _canonical_meta_json(meta: Mapping[str, Any]) -> str:
     return json.dumps(dict(meta), sort_keys=True, ensure_ascii=False, allow_nan=False)
 
 
+def _cap_text(text: str, cap: int | None) -> str:
+    """超出 cap 时头部硬切并附省略标记 `…(略 N 字)`;cap 为 None 原样返回。"""
+    if cap is None or len(text) <= cap:
+        return text
+    return f"{text[:cap]}…(略 {len(text) - cap} 字)"
+
+
+def _cap_part(part: Any, cap: int) -> Any:
+    """多模态 part 的文本截断;非 `type == "text"` 的 part 原样返回同一对象。"""
+    if isinstance(part, dict) and part.get("type") == "text" and isinstance(part.get("text"), str):
+        return {**part, "text": _cap_text(part["text"], cap)}
+    return part
+
+
+def _cap_messages(messages: list[dict[str, Any]], cap: int | None) -> list[dict[str, Any]]:
+    """对每条消息的文本 content 与多模态 part 中 type == "text" 的 text 逐条施加 cap。
+
+    非字符串 content 原样放行(外部输入形状不可控,遥测路径不得因此抛错)。
+
+    **只产出新对象,严禁就地修改**: `digest_messages` 对 content 非 list 的消息是
+    原样透传**同一个 dict 对象**(`cache.py:43`),多模态里非 image_url 的 part 同理。
+    就地改它会一并污染调用方持有的 messages、后续重试尝试的请求体与缓存写入的 key,
+    且全程无任何报错。
+    """
+    if cap is None:
+        return messages
+    capped: list[dict[str, Any]] = []
+    for msg in messages:
+        content = msg.get("content")
+        if isinstance(content, str):
+            capped.append({**msg, "content": _cap_text(content, cap)})
+        elif isinstance(content, list):
+            capped.append({**msg, "content": [_cap_part(part, cap) for part in content]})
+        else:
+            capped.append(msg)
+    return capped
+
+
 @dataclass(frozen=True)
 class _AttemptUsage:
     """一次尝试的用量视图;默认值即"失败尝试"档(无用量可言,记 0 并标 unavailable)。
@@ -96,9 +134,20 @@ class _AttemptUsage:
 class TelemetryEmitter:
     """从请求与结果组装 24 字段并写入 recorder;一切写失败降级 warning。"""
 
-    def __init__(self, recorder: TelemetryRecorder, *, pricing: PricingTable | None = None) -> None:
+    def __init__(
+        self,
+        recorder: TelemetryRecorder,
+        *,
+        pricing: PricingTable | None = None,
+        text_cap: int | None,
+    ) -> None:
+        """`text_cap` 无默认值是有意的: 它是关键行为参数,漏传即静默改变落库正文。
+
+        本类是库内部类,唯一构造者是三个公共 Client,必填能保证没有一处漏传。
+        """
         self._recorder = recorder
         self._pricing = pricing
+        self._text_cap = text_cap
 
     async def emit_attempt(
         self,
@@ -241,8 +290,12 @@ class TelemetryEmitter:
                 )
             else:
                 cost = None
-            # messages 落库前多模态摘要,与缓存 key 共用同一函数(VT R12)
-            messages_json = json.dumps(digest_messages(request.messages), ensure_ascii=False)
+            # messages 落库前多模态摘要,与缓存 key 共用同一函数(VT R12);
+            # 截断只发生在摘要之后、序列化之前的遥测分支,缓存路径不经过它(issue #12)
+            messages_json = json.dumps(
+                _cap_messages(digest_messages(request.messages), self._text_cap),
+                ensure_ascii=False,
+            )
             await self._recorder.record_llm_call(
                 call_id=call_id,
                 parent_call_id=request.parent_call_id,
@@ -251,8 +304,8 @@ class TelemetryEmitter:
                 provider=provider,
                 source_name=source_name,
                 messages=messages_json,
-                response=response_text,
-                thinking=thinking,
+                response=_cap_text(response_text, self._text_cap),
+                thinking=_cap_text(thinking, self._text_cap),
                 prompt_tokens=prompt_tokens,
                 completion_tokens=completion_tokens,
                 usage_source=usage_source,