feat: raise configurable chat tool call limit

.env.example

@@ -13,3 +13,4 @@ OCR_MODEL_DIR=/models/ocr
 MODEL_TIMEOUT_SECONDS=120
 MODEL_CONCURRENCY=2
 MODEL_RETRIES=2
+CHAT_MAX_TOOL_CALLS=32

backend/tests/test_chat_agent.py

@@ -218,8 +218,9 @@ def test_sse_persists_messages_and_tool_failure(session_factory, monkeypatch):
         def tool_call(self, messages, tools):
             calls.append(messages)
             if len(calls) == 1:
-                return {"role": "assistant", "content": None, "tool_calls": [{"id": "call1", "type": "function",
+                return {"role": "assistant", "content": None, "tool_calls": [
-                    "function": {"name": "list_courses", "arguments": "{}"}}]}
+                    {"id": f"call{index}", "type": "function",
+                     "function": {"name": "list_courses", "arguments": "{}"}} for index in range(9)]}
             return {"role": "assistant", "content": "已列出课程版本。", "tool_calls": []}
     monkeypatch.setattr(chat_api, "client_for_chat", lambda db: FakeClient())
     def override_db():
@@ -231,9 +232,10 @@ def test_sse_persists_messages_and_tool_failure(session_factory, monkeypatch):
         created = client.post("/api/conversations", json={"title": "测试对话"}).json()
         with client.stream("POST", f"/api/conversations/{created['id']}/messages", json={"content": "列出课程"}) as response:
             body = "".join(response.iter_text())
-        assert "event: tool" in body and "event: message" in body
+        assert body.count("event: tool") == 9 and "event: message" in body
         restored = client.get(f"/api/conversations/{created['id']}").json()
         assert [m["role"] for m in restored["messages"]] == ["user", "assistant"]
+        assert len(restored["messages"][1]["tool_calls"]) == 9
         assert restored["runs"][0]["status"] == "completed"
         monkeypatch.setattr(chat_api, "client_for_chat", lambda db: (_ for _ in ()).throw(ModelError("不支持工具调用")))
         with client.stream("POST", f"/api/conversations/{created['id']}/messages", json={"content": "再试"}) as response:
@@ -251,6 +253,35 @@ def test_sse_persists_messages_and_tool_failure(session_factory, monkeypatch):
         app.dependency_overrides.clear()
 
 
+def test_failed_tool_calls_count_toward_limit(monkeypatch):
+    class RepeatingClient:
+        def tool_call(self, messages, tools):
+            return {"role": "assistant", "content": None, "tool_calls": [
+                {"id": f"call{len(messages)}", "type": "function",
+                 "function": {"name": "unknown_tool", "arguments": "{}"}}]}
+
+    conversation = SimpleNamespace(id=1, course_version_id=None, batch_id=None, project_id=None, updated_at=None)
+    run = SimpleNamespace(id=1, status="running", error=None, finished_at=None)
+    class FakeSession:
+        def __enter__(self):
+            return self
+        def __exit__(self, *_args):
+            pass
+        def get(self, model, _id):
+            return conversation if model is Conversation else run
+        def scalars(self, _query):
+            return SimpleNamespace(all=lambda: [])
+        def commit(self):
+            pass
+
+    monkeypatch.setattr(chat_api, "client_for_chat", lambda db: RepeatingClient())
+    monkeypatch.setattr(chat_api, "get_settings", lambda: SimpleNamespace(chat_max_tool_calls=9))
+    body = "".join(chat_api._run_agent(FakeSession, 1, 1, "循环调用工具"))
+    assert body.count("event: tool") == 9
+    assert "本次消息工具调用超过上限 9 次" in body
+    assert run.status == "failed"
+
+
 def test_native_tool_calls_unsupported_endpoint():
     transport = httpx.MockTransport(lambda request: httpx.Response(400, json={"error": "unsupported"}))
     client = DeepSeekClient(api_key="test-key", transport=transport)

backend/wisegrade/chat_api.py

@@ -10,6 +10,7 @@ from sqlalchemy.orm import Session, sessionmaker
 
 from .actions import action_dict, confirm, prepare, require_scope
 from .agent_tools import execute, tool_specs
+from .config import get_settings
 from .db import get_db
 from .llm import ModelError
 from .models import AgentRun, ChatMessage, Conversation, PendingAction, Project, ScoringBatch, now
@@ -113,7 +114,10 @@ def _run_agent(factory, conversation_id, run_id, user_text):
                 "project_id": conversation.project_id}, ensure_ascii=False)}]
             messages.extend({"role": m.role, "content": m.content[:4000]} for m in history)
             yield _event("run", {"id": run.id, "status": "running"})
-            for round_number in range(4):
+            max_tool_calls = get_settings().chat_max_tool_calls
+            attempted_calls = 0
+            # One extra model response lets the agent answer after its last allowed tool call.
+            for _ in range(max_tool_calls + 1):
                 reply = client.tool_call(messages, tool_specs())
                 calls = reply.get("tool_calls") or []
                 if not calls:
@@ -121,16 +125,17 @@ def _run_agent(factory, conversation_id, run_id, user_text):
                     if not isinstance(content, str) or not content.strip():
                         raise ModelError("对话模型未返回文字或工具调用")
                     db.add(ChatMessage(conversation_id=conversation_id, role="assistant", content=content,
-                                       citations=citations[:20], tool_calls=used[:8]))
+                                       citations=citations[:20], tool_calls=used))
                     run.status, run.finished_at = "completed", now()
                     conversation.updated_at = now()
                     db.commit()
                     completed = True
-                    yield _event("message", {"content": content, "citations": citations[:20], "tool_calls": used[:8]})
+                    yield _event("message", {"content": content, "citations": citations[:20], "tool_calls": used})
                     yield _event("done", {"run_id": run.id})
                     return
-                if len(calls) + len(used) > 8:
+                if attempted_calls + len(calls) > max_tool_calls:
-                    raise ModelError("单轮工具调用超过上限 8 次")
+                    raise ModelError(f"本次消息工具调用超过上限 {max_tool_calls} 次")
+                attempted_calls += len(calls)
                 messages.append({"role": "assistant", "content": reply.get("content"), "tool_calls": calls})
                 for call in calls:
                     name = call.get("function", {}).get("name", "")
@@ -155,7 +160,7 @@ def _run_agent(factory, conversation_id, run_id, user_text):
                         messages.append({"role": "tool", "tool_call_id": call_id,
                                          "content": json.dumps({"error": error[:500]}, ensure_ascii=False)})
                         yield _event("tool", {"name": name, "status": "failed", "error": error[:500]})
-            raise ModelError("模型工具调用轮数超过上限 4 次")
+            raise ModelError(f"本次消息模型调用超过上限 {max_tool_calls + 1} 轮")
         except Exception as exc:
             run.status, run.error, run.finished_at = "failed", str(exc)[:500], now()
             db.commit()

backend/wisegrade/config.py

@@ -1,6 +1,7 @@
 from functools import lru_cache
 from pathlib import Path
 
+from pydantic import Field
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
 
@@ -23,6 +24,7 @@ class Settings(BaseSettings):
     model_timeout_seconds: int = 120
     model_concurrency: int = 2
     model_retries: int = 2
+    chat_max_tool_calls: int = Field(default=32, ge=1, le=64)
 
 
 @lru_cache

docs/CHAT_AGENT.md

@@ -26,7 +26,7 @@
 
 对话使用模型设置页的 OpenAI 兼容 `/chat/completions` 地址、模型和后端 API Key。适配层按 [DeepSeek 原生工具调用文档](https://api-docs.deepseek.com/guides/tool_calls) 发送 `tools`，在每轮前用不含学生资料的 `wisegrade_ping` 最小探针验证端点会返回 `tool_calls`。当前 `deepseek-flash` 端点支持自动工具选择，但拒绝强制 `tool_choice="required"`，因此探针采用 `auto` 并检查返回结构。模型不支持时会显示明确配置错误，不会伪装工具已执行。既有评分 `json_call` 保持原有 JSON 行为。
 
-工具输入由 Pydantic 校验，后端再校验课程、批次和项目关系。每轮最多 8 次工具调用、4 轮模型调用；工具输出和会话上下文限量。工具没有任意 SQL、任意文件路径、HTTP 请求、代码执行或确认能力。检索片段只作为数据，不作为工具指令。模型只收到当前问题所需的规则摘要、检索片段或紧凑统计；API Key 不写入日志或会话表。
+工具输入由 Pydantic 校验，后端再校验课程、批次和项目关系。每条教师消息默认最多调用工具 32 次，成功与失败的尝试均计数；模型最多请求 33 轮，以便用完工具次数后还能生成回答。可在 `.env` 中通过 `CHAT_MAX_TOOL_CALLS` 调整工具上限（1–64），修改后重新创建 API 容器。工具输出和会话上下文限量。工具没有任意 SQL、任意文件路径、HTTP 请求、代码执行或确认能力。检索片段只作为数据，不作为工具指令。模型只收到当前问题所需的规则摘要、检索片段或紧凑统计；API Key 不写入日志或会话表。
 
 ## API 与故障恢复