feat: add solve_task.py direct solver and fix MCP rate limit issues

- Add solve_task.py: fast direct solver (1 LLM call per task, no deepagents overhead)
- Add RetryOnRateLimitMiddleware: auto-retry on 429 from any tool
- Fix double MCP load: __init__.py cleared, pipeline reuses agent.py journal tools
- Fix proxy: add NO_PROXY for openrouter.ai, platform.brojs.ru, git.brojs.ru
- Add utility scripts: get_task_ids.py, read_tasks.py
- Update run_pipeline.py: TARGET_IDS support, unbuffered output

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

check_tasks.py

@@ -1,4 +1,6 @@
-import asyncio, json
+import asyncio, json, os
+# Обходим локальный прокси для всех наших сервисов (иначе SSL-ошибка)
+os.environ["NO_PROXY"] = "openrouter.ai,platform.brojs.ru,git.brojs.ru," + os.environ.get("NO_PROXY", "")
 from dotenv import load_dotenv
 load_dotenv()
 from src.agent.mcp_client import load_journal_toolsets, JOURNAL_PREFIX

get_task_ids.py

@@ -0,0 +1,24 @@
+import asyncio, json, os
+os.environ["NO_PROXY"] = "openrouter.ai,platform.brojs.ru,git.brojs.ru," + os.environ.get("NO_PROXY", "")
+from dotenv import load_dotenv
+load_dotenv()
+from src.agent.mcp_client import load_journal_toolsets, JOURNAL_PREFIX
+from src.agent.constants import COURSE_ID
+
+async def main():
+    j = load_journal_toolsets()
+    tool = next(t for t in j.tasks_submissions_tools if t.name == f"{JOURNAL_PREFIX}tasks_list")
+    raw = await tool.ainvoke({"courseId": COURSE_ID})
+    if isinstance(raw, list):
+        raw = next((x["text"] for x in raw if x.get("type") == "text"), str(raw))
+    data = json.loads(raw) if isinstance(raw, str) else raw
+    items = data.get("tasks", data) if isinstance(data, dict) else data
+    for item in items:
+        t = item.get("task", item) if isinstance(item, dict) else {}
+        tid = t.get("id", "")
+        status = item.get("status", "")
+        title = t.get("title", "")
+        if status == "todo":
+            print(f"TODO  {tid}  {title}")
+
+asyncio.run(main())

read_tasks.py

@@ -0,0 +1,25 @@
+import asyncio, json, os
+os.environ["NO_PROXY"] = "openrouter.ai,platform.brojs.ru,git.brojs.ru," + os.environ.get("NO_PROXY", "")
+from dotenv import load_dotenv
+load_dotenv()
+from src.agent.mcp_client import load_journal_toolsets, JOURNAL_PREFIX
+
+TASK_IDS = [
+    "6a1864fd",  # Планирующий агент
+    "6a186500",  # Структурированный вывод (Pydantic)
+    "6a1864f7",  # RAG-агент с ChromaDB
+    "6a1864fa",  # Самокорректирующийся агент
+]
+
+async def main():
+    j = load_journal_toolsets()
+    text_tool = next(t for t in j.tasks_submissions_tools if t.name == f"{JOURNAL_PREFIX}task_text")
+    for tid in TASK_IDS:
+        raw = await text_tool.ainvoke({"taskId": tid})
+        text = raw if isinstance(raw, str) else next((x["text"] for x in raw if x.get("type") == "text"), str(raw))
+        print(f"\n{'='*60}")
+        print(f"ЗАДАНИЕ {tid}")
+        print('='*60)
+        print(text)
+
+asyncio.run(main())

run_pipeline.py

@@ -1,28 +1,64 @@
 """Запуск пайплайна для выполнения заданий курса."""
 import asyncio
-import sys
 import os
+import traceback
 
 os.environ["PYTHONIOENCODING"] = "utf-8"
+# Обходим локальный прокси для OpenRouter (иначе SSL-ошибка)
+os.environ["NO_PROXY"] = "openrouter.ai,platform.brojs.ru,git.brojs.ru," + os.environ.get("NO_PROXY", "")
 
 from dotenv import load_dotenv
 load_dotenv()
 
-from langchain_core.messages import HumanMessage
+from src.agent.graph.pipeline import pipeline, TaskInfo, process_one_task, route, PipelineState
-from src.agent.graph.pipeline import pipeline
+
+# Целевые задания (None = все todo-задания автоматически)
+TARGET_IDS = [
+    "6a1864f78a94f887e50d46da",  # Экзамен: RAG-агент с ChromaDB и веб-поиском
+]
 
 
 async def main():
     print("=== Запуск пайплайна BroJS ===")
-    result = await pipeline.ainvoke(
+
-        {
+    if TARGET_IDS:
-            "tasks": [],
+        tasks = [TaskInfo(id=tid, title="", status="todo") for tid in TARGET_IDS]
+        print(f"Целевые задания: {TARGET_IDS}")
+        initial_state = {
+            "tasks": tasks,
             "current_index": 0,
             "results": [],
             "errors": [],
-        },
+        }
+        from langgraph.graph import StateGraph, START
+        builder = StateGraph(PipelineState)
+        builder.add_node("process_one_task", process_one_task)
+        builder.add_edge(START, "process_one_task")
+        builder.add_conditional_edges(
+            "process_one_task", route,
+            {"process_one_task": "process_one_task", "__end__": "__end__"}
+        )
+        targeted_pipeline = builder.compile()
+        try:
+            result = await targeted_pipeline.ainvoke(
+                initial_state,
+                {"configurable": {"thread_id": "pipeline-targeted"}},
+            )
+        except Exception as e:
+            print(f"КРИТИЧЕСКАЯ ОШИБКА: {e}")
+            traceback.print_exc()
+            return
+    else:
+        try:
+            result = await pipeline.ainvoke(
+                {"tasks": [], "current_index": 0, "results": [], "errors": []},
                 {"configurable": {"thread_id": "pipeline-main"}},
             )
+        except Exception as e:
+            print(f"КРИТИЧЕСКАЯ ОШИБКА: {e}")
+            traceback.print_exc()
+            return
+
     print("\n=== Результат пайплайна ===")
     for r in result.get("results", []):
         print(f"  Task {r['task_id'][:8]}: {r['status']} (mode={r['mode']}, retries={r['retries']})")

solve_task.py

@@ -0,0 +1,360 @@
+"""
+Быстрый решатель заданий BroJS.
+Схема: читаем задание (MCP) → 1 LLM-вызов → пушим на Gitea → сабмитим (MCP).
+Автономный — не импортирует src.agent, нет двойной загрузки MCP.
+
+Использование:
+    python solve_task.py <full_task_id>
+"""
+import asyncio
+import base64
+import json
+import os
+import sys
+
+# Обходим локальный прокси
+os.environ["NO_PROXY"] = "openrouter.ai,platform.brojs.ru,git.brojs.ru," + os.environ.get("NO_PROXY", "")
+
+from dotenv import load_dotenv
+load_dotenv()
+
+import httpx
+from langchain_mcp_adapters.client import MultiServerMCPClient
+from langchain_openai import ChatOpenAI
+
+GITEA_BASE_URL = "https://git.brojs.ru"
+GITEA_OWNER    = os.getenv("GITEA_OWNER", "glevelll")
+GITEA_TOKEN    = os.getenv("GITEA_TOKEN", "")
+JOURNAL_TOKEN  = os.getenv("JOURNAL_TOKEN", "")
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
+
+MCP_URL = "https://platform.brojs.ru/jrnl-bh/api/mcp"
+
+# ---------------------------------------------------------------------------
+# LLM
+# ---------------------------------------------------------------------------
+
+llm = ChatOpenAI(
+    model="openai/gpt-oss-20b:free",
+    base_url="https://openrouter.ai/api/v1",
+    api_key=OPENAI_API_KEY,
+    temperature=0.0,
+    max_tokens=4096,
+)
+
+# ---------------------------------------------------------------------------
+# MCP — один клиент на весь запуск
+# ---------------------------------------------------------------------------
+
+_mcp_tools: dict = {}
+
+
+async def _load_mcp(retries=5, pause=30):
+    global _mcp_tools
+    if _mcp_tools:
+        return
+    config = {
+        "journal": {
+            "transport": "streamable_http",
+            "url": MCP_URL,
+            "headers": {"Authorization": f"Bearer {JOURNAL_TOKEN}"},
+        }
+    }
+    client = MultiServerMCPClient(config)
+    for attempt in range(1, retries + 1):
+        try:
+            tools = await client.get_tools(server_name="journal")
+            _mcp_tools = {t.name: t for t in tools}
+            print(f"  [mcp] Загружено {len(_mcp_tools)} инструментов")
+            return
+        except Exception as e:
+            if "429" in str(e) and attempt < retries:
+                print(f"  [mcp] 429 при загрузке, жду {pause}с...")
+                await asyncio.sleep(pause)
+            else:
+                raise
+
+
+async def mcp_call(name: str, args: dict, retries=5, pause=30):
+    await _load_mcp()
+    tool = _mcp_tools.get(name)
+    if not tool:
+        raise RuntimeError(f"MCP tool '{name}' not found. Available: {list(_mcp_tools.keys())}")
+    for attempt in range(1, retries + 1):
+        try:
+            result = await tool.ainvoke(args)
+            if isinstance(result, list):
+                return next((x["text"] for x in result if x.get("type") == "text"), str(result))
+            return str(result)
+        except Exception as e:
+            if "429" in str(e) and attempt < retries:
+                print(f"  [mcp] {name} → 429, жду {pause}с (попытка {attempt}/{retries})...")
+                await asyncio.sleep(pause)
+            else:
+                raise
+
+
+# ---------------------------------------------------------------------------
+# Gitea
+# ---------------------------------------------------------------------------
+
+def _gh():
+    return {"Authorization": f"token {GITEA_TOKEN}", "Content-Type": "application/json"}
+
+
+def gitea_create_repo(name: str) -> str:
+    with httpx.Client(timeout=30) as c:
+        r = c.post(f"{GITEA_BASE_URL}/api/v1/user/repos", headers=_gh(),
+                   json={"name": name, "private": False, "auto_init": False})
+        if r.status_code == 409:
+            return f"{GITEA_BASE_URL}/{GITEA_OWNER}/{name}"
+        r.raise_for_status()
+        return r.json().get("html_url", f"{GITEA_BASE_URL}/{GITEA_OWNER}/{name}")
+
+
+def gitea_write(repo: str, path: str, content: str, msg: str):
+    encoded = base64.b64encode(content.encode()).decode()
+    url = f"{GITEA_BASE_URL}/api/v1/repos/{GITEA_OWNER}/{repo}/contents/{path}"
+    with httpx.Client(timeout=30) as c:
+        r = c.get(url, headers=_gh())
+        if r.status_code == 200:
+            sha = r.json().get("sha", "")
+            c.put(url, headers=_gh(), json={"message": msg, "content": encoded, "sha": sha}).raise_for_status()
+        else:
+            c.post(url, headers=_gh(), json={"message": msg, "content": encoded}).raise_for_status()
+
+
+# ---------------------------------------------------------------------------
+# LLM: генерация кода
+# ---------------------------------------------------------------------------
+
+_PROMPT = '''\
+Ты — Python-разработчик. Напиши решение для учебного задания по LLM/AI.
+Используй фреймворк deepagents (create_deep_agent) — это обязательное требование курса.
+
+## Задание
+{task_text}
+
+## ОБЯЗАТЕЛЬНЫЕ ТЕХНИЧЕСКИЕ ПАТТЕРНЫ
+
+### LLM — всегда OpenRouter:
+```python
+import os
+from langchain_openai import ChatOpenAI
+llm = ChatOpenAI(
+    model="openai/gpt-oss-20b:free",
+    base_url="https://openrouter.ai/api/v1",
+    api_key=os.getenv("OPENAI_API_KEY"),
+    temperature=0.0,
+)
+```
+
+### Базовый агент (deepagents) — ОБЯЗАТЕЛЬНАЯ основа:
+```python
+import asyncio, os
+from langchain_openai import ChatOpenAI
+from langchain_core.messages import HumanMessage
+from langchain.tools import tool
+from deepagents import create_deep_agent
+from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend
+
+llm = ChatOpenAI(model="openai/gpt-oss-20b:free", base_url="https://openrouter.ai/api/v1", api_key=os.getenv("OPENAI_API_KEY"))
+
+backend = CompositeBackend([
+    LocalShellBackend(workspace_dir="./workspace"),
+    FilesystemBackend(),
+])
+
+@tool
+def my_tool(query: str) -> str:
+    """Tool description."""
+    return f"result for {{query}}"
+
+agent = create_deep_agent(
+    model=llm,
+    tools=[my_tool],
+    backend=backend,
+    system_prompt="You are a helpful agent.",
+)
+
+async def main():
+    result = await agent.ainvoke(
+        {{"messages": [HumanMessage(content="Your task here")]}},
+        {{"configurable": {{"thread_id": "session-1"}}}},
+    )
+    print(result["messages"][-1].content)
+
+if __name__ == "__main__":
+    asyncio.run(main())
+```
+requirements.txt: deepagents, langchain-openai>=0.3.0, langchain>=1.2.10, langgraph>=0.2.0
+
+### RAG с Qdrant (для RAG-заданий):
+```python
+from langchain_openai import OpenAIEmbeddings
+from langchain_qdrant import QdrantVectorStore
+from qdrant_client import QdrantClient
+from qdrant_client.models import Distance, VectorParams
+from langchain_core.documents import Document
+
+embeddings = OpenAIEmbeddings(model="text-embedding-3-small", base_url="https://openrouter.ai/api/v1", api_key=os.getenv("OPENAI_API_KEY"))
+client = QdrantClient(":memory:")
+client.create_collection("knowledge", vectors_config=VectorParams(size=1536, distance=Distance.COSINE))
+vector_store = QdrantVectorStore(client=client, collection_name="knowledge", embedding=embeddings)
+
+@tool
+def search_knowledge(query: str) -> str:
+    """Search the knowledge base."""
+    docs = vector_store.similarity_search(query, k=3)
+    return "\\n".join(d.page_content for d in docs) if docs else "No results."
+
+@tool
+def add_to_knowledge(content: str, title: str = "doc") -> str:
+    """Add content to knowledge base."""
+    vector_store.add_documents([Document(page_content=content, metadata={{"title": title}})])
+    return f"Added: {{title}}"
+```
+requirements.txt добавить: langchain-qdrant, qdrant-client
+
+### Планирующий агент (для planning-заданий):
+```python
+from langgraph.graph import StateGraph, START, END
+from typing import TypedDict, Annotated
+from langgraph.graph.message import add_messages
+
+class PlanState(TypedDict):
+    messages: Annotated[list, add_messages]
+    plan: list[str]
+    current_step: int
+
+def planner_node(state):
+    # LLM создаёт план
+    ...
+
+def executor_node(state):
+    # LLM выполняет шаг плана
+    ...
+```
+
+### Самокорректирующийся агент:
+```python
+# Агент проверяет свой вывод и исправляет если нужно
+@tool
+def validate_output(output: str) -> str:
+    """Validate the output and return issues if any."""
+    issues = []
+    if len(output) < 10:
+        issues.append("Output too short")
+    return "OK" if not issues else f"Issues: {{', '.join(issues)}}"
+```
+
+### Структурированный вывод (Pydantic):
+```python
+from pydantic import BaseModel, Field
+from langchain_core.output_parsers import PydanticOutputParser
+
+class MyOutput(BaseModel):
+    field1: str = Field(description="...")
+    field2: int = Field(description="...")
+
+parser = PydanticOutputParser(pydantic_object=MyOutput)
+```
+
+## Требования
+- Полный рабочий код без заглушек (no pass, TODO, ...)
+- ОБЯЗАТЕЛЬНО использовать create_deep_agent из deepagents
+- requirements.txt: deepagents, langchain>=1.2.10, langchain-openai>=0.3.0, langgraph>=0.2.0 + нужные доп. зависимости
+
+## Ответ — ТОЛЬКО JSON без markdown:
+{{"main_py": "...", "requirements_txt": "...", "extra_files": {{}}}}
+
+extra_files — только если нужны доп. файлы, иначе пустой объект.
+'''
+
+
+async def generate(task_text: str, retries=5) -> dict:
+    prompt = _PROMPT.format(task_text=task_text)
+    for attempt in range(1, retries + 1):
+        try:
+            print(f"  [llm] Генерирую решение (попытка {attempt})...")
+            resp = await llm.ainvoke(prompt)
+            raw = resp.content.strip()
+            if raw.startswith("```"):
+                raw = raw.split("```")[1]
+                if raw.startswith("json"):
+                    raw = raw[4:]
+            return json.loads(raw.strip())
+        except json.JSONDecodeError as e:
+            print(f"  [llm] JSON parse error: {e}. Повтор...")
+            if attempt == retries:
+                raise
+        except Exception as e:
+            if "429" in str(e) and attempt < retries:
+                wait = 90 * attempt
+                print(f"  [llm] 429, жду {wait}с (попытка {attempt}/{retries})...")
+                await asyncio.sleep(wait)
+            else:
+                raise
+
+
+# ---------------------------------------------------------------------------
+# Основная логика
+# ---------------------------------------------------------------------------
+
+async def solve(task_id: str):
+    print(f"\n{'='*60}")
+    print(f"Задание: {task_id}")
+    print('='*60)
+
+    # 1. Читаем текст задания
+    print("[1/5] Читаем текст задания...")
+    task_text = await mcp_call("task_text", {"taskId": task_id})
+    print(f"  Получено {len(task_text)} символов")
+
+    # 2. Генерируем код
+    print("[2/5] Генерируем код (1 LLM-вызов)...")
+    solution = await generate(task_text)
+    main_py      = solution.get("main_py", "")
+    requirements = solution.get("requirements_txt", "")
+    extra        = solution.get("extra_files", {})
+    print(f"  main.py: {len(main_py)} символов, requirements.txt: {len(requirements)} символов")
+
+    # 3. Создаём репо
+    repo = f"task-{task_id}"
+    print(f"[3/5] Создаём репозиторий {repo}...")
+    repo_url = gitea_create_repo(repo)
+    print(f"  {repo_url}")
+
+    # 4. Пушим файлы
+    print("[4/5] Пушим файлы...")
+    gitea_write(repo, "main.py", main_py, "add main.py")
+    print("  main.py ✓")
+    gitea_write(repo, "requirements.txt", requirements, "add requirements.txt")
+    print("  requirements.txt ✓")
+    for fname, fcontent in extra.items():
+        gitea_write(repo, fname, fcontent, f"add {fname}")
+        print(f"  {fname} ✓")
+
+    # 5. Сабмитим
+    print("[5/5] Сабмитим...")
+    await mcp_call("task_update_answer", {
+        "taskId": task_id, "answerType": "link", "content": repo_url,
+    })
+    print("  task_update_answer ✓")
+    await asyncio.sleep(3)
+    await mcp_call("task_submit", {"taskId": task_id, "confirmSubmit": True})
+    print("  task_submit ✓")
+
+    print(f"\n✅ Готово! Репозиторий: {repo_url}")
+    return repo_url
+
+
+async def main():
+    if len(sys.argv) < 2:
+        print("Использование: python solve_task.py <task_id>")
+        sys.exit(1)
+    await solve(sys.argv[1])
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

src/agent/__init__.py

@@ -1,3 +1,2 @@
-from src.agent.agent import agent, homework_direct_agent, rework_agent
+# Намеренно пустой — предотвращает двойную загрузку MCP при импорте подмодулей.
-
+# Импортируй напрямую: from src.agent.agent import agent
-__all__ = ["agent", "homework_direct_agent", "rework_agent"]

src/agent/agent.py

@@ -12,7 +12,7 @@ from src.agent.constants import (
 from src.agent.gitea_tools import GITEA_TOOLS
 from src.agent.llm import llm
 from src.agent.mcp_client import load_journal_toolsets
-from src.agent.middlewares import SanitizeToolCallsMiddleware, ValidateJournalWorkflowMiddleware
+from src.agent.middlewares import RetryOnRateLimitMiddleware, SanitizeToolCallsMiddleware, ValidateJournalWorkflowMiddleware
 from src.agent.prompts import (
     homework_doing_instructions,
     main_agent_instructions,
@@ -129,6 +129,7 @@ homework_direct_agent = create_deep_agent(
     system_prompt=homework_doing_instructions,
     backend=_composite_backend,
     middleware=[
+        RetryOnRateLimitMiddleware(),
         SanitizeToolCallsMiddleware(known_tools=_subagent_tool_names["homework_doing"]),
         ValidateJournalWorkflowMiddleware(),
     ],
@@ -144,6 +145,7 @@ rework_agent = create_deep_agent(
     system_prompt=rework_instructions,
     backend=_composite_backend,
     middleware=[
+        RetryOnRateLimitMiddleware(),
         SanitizeToolCallsMiddleware(known_tools=_subagent_tool_names["homework_doing"]),
         ValidateJournalWorkflowMiddleware(),
     ],

src/agent/graph/pipeline.py

@@ -10,10 +10,10 @@ from typing import TypedDict
 from langchain_core.messages import HumanMessage
 from langgraph.graph import START, StateGraph
 
-from src.agent.agent import homework_direct_agent, rework_agent
+from src.agent.agent import homework_direct_agent, journal as _journal_toolsets, rework_agent
 from src.agent.constants import COURSE_ID, GITEA_OWNER
 from src.agent.gitea_tools import _get as gitea_get
-from src.agent.mcp_client import JOURNAL_PREFIX, load_journal_toolsets
+from src.agent.mcp_client import JOURNAL_PREFIX
 
 # ---------------------------------------------------------------------------
 # Типы состояния
@@ -36,11 +36,8 @@ class PipelineState(TypedDict):
 # Вспомогательные функции
 # ---------------------------------------------------------------------------
 
-_journal = load_journal_toolsets()
-
-
 def _get_journal_tool(suffix: str):
-    all_tools = _journal.courses_lessons_tools + _journal.tasks_submissions_tools
+    all_tools = _journal_toolsets.courses_lessons_tools + _journal_toolsets.tasks_submissions_tools
     target = f"{JOURNAL_PREFIX}{suffix}"
     for t in all_tools:
         if t.name == target:
@@ -116,13 +113,13 @@ async def _force_submit(task_id: str) -> bool:
         print(f"[pipeline] force_submit: инструменты не найдены")
         return False
     try:
-        await update_tool.ainvoke({
+        await _mcp_invoke(update_tool, {
             "taskId":     task_id,
             "answerType": "link",
             "content":    repo_url,
             "commit":     {"repoUrl": repo_url, "branch": "main"},
         })
-        await submit_tool.ainvoke({"taskId": task_id, "confirmSubmit": True})
+        await _mcp_invoke(submit_tool, {"taskId": task_id, "confirmSubmit": True})
         print(f"[pipeline] Задание {task_id[:8]} — сабмит выполнен пайплайном ✓")
         return True
     except Exception as e:
@@ -137,12 +134,25 @@ async def _is_submitted(task_id: str) -> bool:
     return status in ("ready_for_review", "done")
 
 
+async def _mcp_invoke(tool, args: dict, retries: int = 5, pause: int = 30):
+    """Вызывает MCP-инструмент с retry при 429."""
+    for attempt in range(1, retries + 1):
+        try:
+            return await tool.ainvoke(args)
+        except Exception as e:
+            if "429" in str(e) and attempt < retries:
+                print(f"[pipeline] MCP 429, жду {pause}с (попытка {attempt}/{retries})...")
+                await asyncio.sleep(pause)
+            else:
+                raise
+
+
 async def _task_text(task_id: str) -> str:
     tool = _get_journal_tool("task_text")
     if not tool:
         return ""
     try:
-        return _parse_text(await tool.ainvoke({"taskId": task_id}))
+        return _parse_text(await _mcp_invoke(tool, {"taskId": task_id}))
     except Exception:
         return ""
 
@@ -152,7 +162,7 @@ async def _task_json(task_id: str) -> dict:
     if not tool:
         return {}
     try:
-        raw = _parse_text(await tool.ainvoke({"taskId": task_id}))
+        raw = _parse_text(await _mcp_invoke(tool, {"taskId": task_id}))
         return json.loads(raw)
     except Exception:
         return {}
@@ -276,6 +286,10 @@ async def process_one_task(state: PipelineState) -> dict:
     results  = list(state.get("results", []))
     errors   = list(state.get("errors", []))
 
+    # Пауза перед стартом — даём BroJS MCP сбросить rate limit после загрузки инструментов
+    print(f"[pipeline] Задание {task_id[:8]} — пауза 10с перед стартом...")
+    await asyncio.sleep(10)
+
     repo_url  = await _existing_repo_url(task_id)
     is_rework = repo_url is not None
 
@@ -348,8 +362,16 @@ async def process_one_task(state: PipelineState) -> dict:
             "retries":      retries,
         })
 
-    except Exception as e:
+    except BaseException as e:
-        print(f"[pipeline] Задание {task_id[:8]} — ОШИБКА: {e}")
+        import traceback
+        # Разворачиваем ExceptionGroup (Python 3.11+) чтобы увидеть реальные ошибки
+        if isinstance(e, ExceptionGroup):
+            for i, sub in enumerate(e.exceptions):
+                print(f"[pipeline] Задание {task_id[:8]} — под-ошибка {i+1}: {type(sub).__name__}: {sub}")
+                traceback.print_exception(type(sub), sub, sub.__traceback__)
+        else:
+            print(f"[pipeline] Задание {task_id[:8]} — ОШИБКА: {type(e).__name__}: {e}")
+            traceback.print_exc()
         errors.append(f"Задание {task_id} ({'rework' if is_rework else 'new'}): {e}")
 
     # Пауза между заданиями чтобы не перегружать rate limit

src/agent/middlewares/__init__.py

@@ -1,4 +1,5 @@
 from src.agent.middlewares.sanitize_tool_calls import SanitizeToolCallsMiddleware
 from src.agent.middlewares.validate_journal_workflow import ValidateJournalWorkflowMiddleware
+from src.agent.middlewares.retry_on_rate_limit import RetryOnRateLimitMiddleware
 
-__all__ = ["SanitizeToolCallsMiddleware", "ValidateJournalWorkflowMiddleware"]
+__all__ = ["SanitizeToolCallsMiddleware", "ValidateJournalWorkflowMiddleware", "RetryOnRateLimitMiddleware"]

src/agent/middlewares/retry_on_rate_limit.py

@@ -0,0 +1,46 @@
+"""Middleware: повторяет вызов инструмента при 429 Rate Limit."""
+from __future__ import annotations
+
+import asyncio
+from typing import Any
+
+from langchain.agents.middleware import AgentMiddleware, AgentState
+from langchain_core.messages import ToolMessage
+
+
+_PAUSE = 30   # секунд ожидания при 429
+_TRIES = 5    # максимум попыток
+
+
+def _is_429(exc: Exception) -> bool:
+    msg = str(exc)
+    return "429" in msg or "rate" in msg.lower()
+
+
+class RetryOnRateLimitMiddleware(AgentMiddleware[AgentState[Any], Any]):
+    """Перехватывает 429 от любого инструмента и повторяет с паузой."""
+
+    def wrap_tool_call(self, request, handler):
+        for attempt in range(1, _TRIES + 1):
+            try:
+                return handler(request)
+            except Exception as e:
+                if _is_429(e) and attempt < _TRIES:
+                    name = request.tool_call.get("name", "")
+                    print(f"[retry-mw] {name} → 429, жду {_PAUSE}с (попытка {attempt}/{_TRIES})...")
+                    import time
+                    time.sleep(_PAUSE)
+                else:
+                    raise
+
+    async def awrap_tool_call(self, request, handler):
+        for attempt in range(1, _TRIES + 1):
+            try:
+                return await handler(request)
+            except Exception as e:
+                if _is_429(e) and attempt < _TRIES:
+                    name = request.tool_call.get("name", "")
+                    print(f"[retry-mw] {name} → 429, жду {_PAUSE}с (попытка {attempt}/{_TRIES})...")
+                    await asyncio.sleep(_PAUSE)
+                else:
+                    raise