Add temporary AI commands and request transcripts

.gitignore

@@ -7,3 +7,4 @@ config.json
 .env
 workspace/.process-logs/
 workspace/.background-processes.json
+workspace/ai-transcript.jsonl*

app/ai/service.py

@@ -8,6 +8,7 @@ import logging
 from pathlib import Path
 import sys
 from typing import TYPE_CHECKING, Any, Awaitable, Callable
+from uuid import uuid4
 
 import httpx
 from openai import AsyncOpenAI
@@ -16,21 +17,24 @@ from app.ai.parser import AIInvocation
 from app.ai.prompts import PromptBook
 from app.ai.page_extract import PageExtractor
 from app.ai.processes import BackgroundProcessManager
+from app.ai.transcript import AITranscriptLogger
 from app.ai.tools import (
     FILE_TOOL_DISPATCH,
     FILE_TOOL_SCHEMAS,
     PAGE_EXTRACT_SCHEMA,
     PYTHON_EXEC_SCHEMA,
+    TEMPORARY_COMMAND_CREATE_SCHEMA,
     BACKGROUND_LIST_SCHEMA,
     BACKGROUND_START_SCHEMA,
     BACKGROUND_STOP_SCHEMA,
     WEB_SEARCH_SCHEMA,
 )
+from app.commands.temporary import TemporaryCommandStore
 from app.ai.web_search import BraveWebSearchClient, format_results
 from app.config import AIConfig, AIModelConfig, AIProviderConfig
 
 if TYPE_CHECKING:
-    from app.commands.core import CommandContext
+    from app.commands.core import CommandContext, CommandRegistry
 
 
 log = logging.getLogger(__name__)
@@ -69,7 +73,7 @@ class HistoryMessage:
 
 
 class AIService:
-    def __init__(self, config: AIConfig) -> None:
+    def __init__(self, config: AIConfig, command_registry: "CommandRegistry") -> None:
         self.config = config
         self.prompt_book = PromptBook(
             config.prompt.root,
@@ -80,10 +84,15 @@ class AIService:
         self.web_search = BraveWebSearchClient(config.web_search)
         self.page_extractor = PageExtractor(config.page_extract)
         self.processes = BackgroundProcessManager(config.workspace_dir)
+        self.temporary_commands = TemporaryCommandStore(command_registry)
+        self.transcript = AITranscriptLogger(config.workspace_dir)
 
     async def initialize(self) -> None:
         return None
 
+    def close(self) -> None:
+        self.transcript.close()
+
     @property
     def enabled(self) -> bool:
         return True
@@ -228,6 +237,7 @@ class AIService:
     async def _build_tool_list(self) -> list[dict]:
         tools = FILE_TOOL_SCHEMAS + [
             PYTHON_EXEC_SCHEMA,
+            TEMPORARY_COMMAND_CREATE_SCHEMA,
             BACKGROUND_START_SCHEMA,
             BACKGROUND_STOP_SCHEMA,
             BACKGROUND_LIST_SCHEMA,
@@ -363,10 +373,22 @@ class AIService:
             return f"Tool {name!r}: invalid JSON arguments: {exc}"
 
         try:
-            if name in {"python_exec", "background_start", "background_stop", "background_list"} and not ctx.is_owner:
+            if name in {
-                result = "Tool access denied: code execution and process control are owner-only"
+                "python_exec",
+                "temporary_command_create",
+                "background_start",
+                "background_stop",
+                "background_list",
+            } and not ctx.is_owner:
+                result = "Tool access denied: temporary commands, code execution, and process control are owner-only"
             elif name == "python_exec":
                 result = await self._execute_python_exec(arguments, ctx)
+            elif name == "temporary_command_create":
+                result = self.temporary_commands.create(
+                    str(arguments.get("name", "")),
+                    str(arguments.get("response", "")),
+                    str(arguments.get("description", "")) or None,
+                )
             elif name == "background_start":
                 result = await self.processes.start(
                     str(arguments.get("name", "")), arguments.get("command"), arguments.get("cwd")
@@ -414,6 +436,8 @@ class AIService:
         tools = await self._build_tool_list()
         allowed_roots = self._get_allowed_roots()
         max_rounds = self.config.tool_max_rounds
+        request_id = uuid4().hex
+        repeated_calls: dict[str, int] = {}
 
         for round_num in range(max_rounds + 1):
             kwargs: dict[str, Any] = {
@@ -423,12 +447,33 @@ class AIService:
             if tools:
                 kwargs["tools"] = tools
 
+            self.transcript.record(
+                "request",
+                request_id=request_id,
+                round=round_num,
+                model_alias=model.alias,
+                provider=model.provider.name,
+                payload=kwargs,
+            )
             try:
                 response = await client.chat.completions.create(**kwargs)
             except Exception as exc:
+                self.transcript.record(
+                    "request_error",
+                    request_id=request_id,
+                    round=round_num,
+                    error=str(exc),
+                )
                 log.exception("AI request failed for model %s", model.alias)
                 raise RuntimeError(f"AI request failed: {exc}") from exc
 
+            self.transcript.record(
+                "response",
+                request_id=request_id,
+                round=round_num,
+                payload=response,
+            )
+
             choice = response.choices[0]
             finish_reason = getattr(choice, "finish_reason", None)
 
@@ -466,9 +511,27 @@ class AIService:
             for tc in tool_calls:
                 tc_name = getattr(getattr(tc, "function", None), "name", "?")
                 await self._maybe_call_progress(progress, f"🛠 Calling tool: {tc_name}")
-                result_text = await self._execute_tool_call(
+                raw_arguments = getattr(getattr(tc, "function", None), "arguments", "{}") or "{}"
-                    tc, ctx, allowed_roots, progress
+                try:
-                )
+                    signature_arguments = json.dumps(json.loads(raw_arguments), sort_keys=True)
+                except (TypeError, json.JSONDecodeError):
+                    signature_arguments = str(raw_arguments)
+                signature = f"{tc_name}:{signature_arguments}"
+                repeated_calls[signature] = repeated_calls.get(signature, 0) + 1
+                if repeated_calls[signature] > 2:
+                    raise RuntimeError(
+                        f"Agentic loop repeated the identical {tc_name!r} tool call more than twice"
+                    )
+                if repeated_calls[signature] > 1:
+                    result_text = (
+                        f"The identical {tc_name!r} call has already been performed. "
+                        "Do not call it again; provide the final answer now."
+                    )
+                    await self._maybe_call_progress(progress, f"🛠 Suppressed duplicate tool call: {tc_name}")
+                else:
+                    result_text = await self._execute_tool_call(
+                        tc, ctx, allowed_roots, progress
+                    )
                 messages.append({
                     "role": "tool",
                     "tool_call_id": tc.id,

app/ai/tools.py

@@ -219,6 +219,27 @@ PYTHON_EXEC_SCHEMA: dict[str, Any] = {
     },
 }
 
+TEMPORARY_COMMAND_CREATE_SCHEMA: dict[str, Any] = {
+    "type": "function",
+    "function": {
+        "name": "temporary_command_create",
+        "description": (
+            "Create a simple owner-only Telegram command that replies with fixed text. "
+            "It exists only in memory and is removed when the bot restarts. Use this for "
+            "test or short-lived commands instead of writing a persistent command module."
+        ),
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "name": {"type": "string", "description": "Command name without the leading dot"},
+                "response": {"type": "string", "description": "Text returned when the command is used"},
+                "description": {"type": "string", "description": "Optional help text for the command"},
+            },
+            "required": ["name", "response"],
+        },
+    },
+}
+
 BACKGROUND_START_SCHEMA: dict[str, Any] = {
     "type": "function",
     "function": {

app/ai/transcript.py

@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+import json
+import logging
+import logging.handlers
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+
+log = logging.getLogger(__name__)
+
+
+def _json_value(value: Any) -> Any:
+    """Convert SDK objects to values suitable for a JSONL audit trail."""
+    if value is None or isinstance(value, (str, int, float, bool)):
+        return value
+    if isinstance(value, Path):
+        return str(value)
+    if isinstance(value, dict):
+        return {str(key): _json_value(item) for key, item in value.items()}
+    if isinstance(value, (list, tuple)):
+        return [_json_value(item) for item in value]
+    model_dump = getattr(value, "model_dump", None)
+    if callable(model_dump):
+        return _json_value(model_dump(exclude_none=True))
+    return str(value)
+
+
+class AITranscriptLogger:
+    """Writes complete provider requests and responses to a dedicated rotating JSONL file."""
+
+    def __init__(self, workspace_dir: Path) -> None:
+        self.path = workspace_dir / "ai-transcript.jsonl"
+        self._logger = logging.getLogger(f"{__name__}.{id(self)}")
+        self._logger.setLevel(logging.INFO)
+        self._logger.propagate = False
+        handler = logging.handlers.RotatingFileHandler(
+            self.path,
+            maxBytes=10 * 1024 * 1024,
+            backupCount=3,
+            encoding="utf-8",
+            delay=True,
+        )
+        handler.setFormatter(logging.Formatter("%(message)s"))
+        self._logger.addHandler(handler)
+
+    def record(self, event: str, **payload: Any) -> None:
+        entry = {
+            "timestamp": datetime.now(timezone.utc).isoformat(),
+            "event": event,
+            **payload,
+        }
+        try:
+            self.path.parent.mkdir(parents=True, exist_ok=True)
+            self._logger.info(json.dumps(_json_value(entry), ensure_ascii=False, separators=(",", ":")))
+        except OSError:
+            log.exception("Failed to write AI transcript to %s", self.path)
+
+    def close(self) -> None:
+        for handler in list(self._logger.handlers):
+            handler.close()
+            self._logger.removeHandler(handler)

app/commands/__init__.py

@@ -15,6 +15,7 @@ from app.commands.core import (
 )
 from app.commands.dispatcher import CommandDispatcher
 from app.commands.persistent import load_persistent_commands
+from app.commands.temporary import TemporaryCommandStore
 
 __all__ = [
     "CheckResult",
@@ -33,4 +34,5 @@ __all__ = [
     "require_reply_check",
     "shared_access_check",
     "load_persistent_commands",
+    "TemporaryCommandStore",
 ]

app/commands/temporary.py

@@ -0,0 +1,47 @@
+from __future__ import annotations
+
+import re
+from dataclasses import dataclass, field
+
+from app.commands.core import CommandRegistry
+
+
+_COMMAND_NAME_RE = re.compile(r"[a-z][a-z0-9_-]{0,31}")
+
+
+@dataclass(slots=True)
+class TemporaryCommandStore:
+    """Registers simple commands that exist only for this bot process."""
+
+    registry: CommandRegistry
+    names: set[str] = field(default_factory=set)
+
+    def create(self, name: str, response: str, description: str | None = None) -> str:
+        normalized_name = name.strip().lower()
+        if not _COMMAND_NAME_RE.fullmatch(normalized_name):
+            raise ValueError(
+                "temporary_command_create: name must start with a letter and contain only "
+                "letters, digits, '-' or '_' (up to 32 characters)"
+            )
+        if self.registry.has_name(normalized_name):
+            raise ValueError(f"temporary_command_create: command .{normalized_name} already exists")
+
+        text = response.strip()
+        if not text:
+            raise ValueError("temporary_command_create: response must not be empty")
+        if len(text) > 3900:
+            raise ValueError("temporary_command_create: response must be at most 3900 characters")
+
+        command_description = (description or "Temporary AI-created command").strip()
+
+        async def handler(ctx: object) -> None:
+            await ctx.reply(text)  # type: ignore[attr-defined]
+
+        self.registry.command(
+            normalized_name,
+            command_description,
+            usage=f".{normalized_name}",
+            category="temporary",
+        )(handler)
+        self.names.add(normalized_name)
+        return f"Created temporary owner-only command .{normalized_name}; it will be removed on bot restart"

app/manager.py

@@ -41,7 +41,9 @@ class AccountManager:
             loaded = load_persistent_commands(self.config.ai.workspace_dir / "commands", self.command_registry)
             if loaded:
                 log.info("Loaded persistent commands: %s", ", ".join(loaded))
-        self.ai_service = AIService(self.config.ai) if self.config.ai is not None else None
+        self.ai_service = (
+            AIService(self.config.ai, self.command_registry) if self.config.ai is not None else None
+        )
         self.states = [AccountState(config=account) for account in self.config.accounts]
         self.github_webhook_server = GitHubWebhookServer(self, self.config.github_webhook)
 
@@ -162,3 +164,5 @@ class AccountManager:
         finally:
             await self.github_webhook_server.stop()
             await self.stop_all()
+            if self.ai_service is not None:
+                self.ai_service.close()

prompts/ai/parts/40_execution.md

@@ -1,6 +1,7 @@
 Инструменты выполнения доступны только владельцу аккаунта.
 
 - Для коротких вычислений и проверки кода используй `python_exec`; в `ctx` доступны `chat_id`, `message_id`, `message_text`, `args`, `from_user` и `replied_message`.
+- Для тестовой или краткоживущей команды используй `temporary_command_create`: она создаёт owner-only команду в памяти, которая отвечает заданным текстом, и исчезает после перезапуска. Не создавай для этого файлы.
 - Для долгоживущих задач (например, веб-сервера) используй `background_start` с argv-массивом без shell. Логи находятся в `workspace/.process-logs/`; для контроля используй `background_list` и `background_stop`.
 - Постоянные команды создавай как Python-модули в `workspace/commands/*.py`, импортируя `command_registry` и `CommandContext` из `app.commands`. После перезапуска они загружаются автоматически. По умолчанию команды owner-only; `.shared()` добавляй только по явной просьбе.
 - Перед изменением существующей команды прочитай файл и сохраняй совместимость с текущим API.

tests/test_ai_tool_loop.py

@@ -0,0 +1,92 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+from tempfile import TemporaryDirectory
+from types import SimpleNamespace
+import unittest
+
+from app.ai.service import AIService
+from app.commands import CommandRegistry
+from app.config import AIConfig, AIModelConfig, AIPromptConfig, AIProviderConfig
+
+
+def _tool_response(call_id: str) -> SimpleNamespace:
+    call = SimpleNamespace(
+        id=call_id,
+        function=SimpleNamespace(
+            name="temporary_command_create",
+            arguments=json.dumps({"name": "test", "response": "ok"}),
+        ),
+    )
+    return SimpleNamespace(
+        choices=[
+            SimpleNamespace(
+                finish_reason="tool_calls",
+                message=SimpleNamespace(content=None, tool_calls=[call]),
+            )
+        ]
+    )
+
+
+class _FakeCompletions:
+    def __init__(self, responses: list[SimpleNamespace]) -> None:
+        self.responses = responses
+        self.requests: list[dict] = []
+
+    async def create(self, **kwargs: object) -> SimpleNamespace:
+        self.requests.append(dict(kwargs))
+        return self.responses.pop(0)
+
+
+class AIToolLoopTests(unittest.IsolatedAsyncioTestCase):
+    async def test_suppresses_duplicate_tool_call_and_returns_final_answer(self) -> None:
+        with TemporaryDirectory() as temp_dir:
+            root = Path(temp_dir)
+            config = AIConfig(
+                default_model="test",
+                context_messages=0,
+                prompt=AIPromptConfig(root=root),
+                providers={"provider": AIProviderConfig("provider", "key", "https://example.test")},
+                models={"test": AIModelConfig("test", "provider", "model")},
+                workspace_dir=root / "workspace",
+            )
+            registry = CommandRegistry()
+            service = AIService(config, registry)
+            completions = _FakeCompletions(
+                [
+                    _tool_response("one"),
+                    _tool_response("two"),
+                    SimpleNamespace(
+                        choices=[
+                            SimpleNamespace(
+                                finish_reason="stop",
+                                message=SimpleNamespace(content="Created .test", tool_calls=[]),
+                            )
+                        ]
+                    ),
+                ]
+            )
+            service._clients["provider"] = SimpleNamespace(
+                chat=SimpleNamespace(completions=completions)
+            )
+            ctx = SimpleNamespace(
+                is_owner=True,
+                actor=None,
+                message=SimpleNamespace(chat=SimpleNamespace(id=1), id=1, text=".ai test"),
+                args="test",
+                replied_message=None,
+                replied_user=None,
+            )
+
+            response = await service.generate(ctx, SimpleNamespace(context_messages=0, model_flags=[], prompt="create test"))
+            service.close()
+
+        self.assertEqual(response.text, "Created .test")
+        self.assertIsNotNone(registry.resolve("test"))
+        self.assertEqual(len(completions.requests), 3)
+        self.assertIn("already been performed", completions.requests[2]["messages"][-1]["content"])
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_ai_transcript.py

@@ -0,0 +1,22 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+from tempfile import TemporaryDirectory
+import unittest
+
+from app.ai.transcript import AITranscriptLogger
+
+
+class AITranscriptLoggerTests(unittest.TestCase):
+    def test_writes_jsonl_events(self) -> None:
+        with TemporaryDirectory() as temp_dir:
+            logger = AITranscriptLogger(Path(temp_dir))
+            logger.record("request", payload={"model": "test", "messages": []})
+            logger.record("response", payload={"choices": [{"message": {"content": "ok"}}]})
+
+            events = [json.loads(line) for line in logger.path.read_text(encoding="utf-8").splitlines()]
+            logger.close()
+
+        self.assertEqual([event["event"] for event in events], ["request", "response"])
+        self.assertEqual(events[1]["payload"]["choices"][0]["message"]["content"], "ok")

tests/test_temporary_commands.py

@@ -0,0 +1,31 @@
+from __future__ import annotations
+
+import unittest
+from types import SimpleNamespace
+from unittest.mock import AsyncMock
+
+from app.commands import CommandRegistry, TemporaryCommandStore
+
+
+class TemporaryCommandStoreTests(unittest.IsolatedAsyncioTestCase):
+    async def test_created_command_is_owner_only_and_replies_from_memory(self) -> None:
+        registry = CommandRegistry()
+        store = TemporaryCommandStore(registry)
+
+        message = store.create("test-command", "Temporary response", "Test command")
+        command = registry.resolve("test-command")
+
+        self.assertIn(".test-command", message)
+        self.assertIsNotNone(command)
+        self.assertFalse(command.is_shared)
+        ctx = SimpleNamespace(reply=AsyncMock())
+        await command.handler(ctx)
+        ctx.reply.assert_awaited_once_with("Temporary response")
+
+    def test_rejects_existing_command_name(self) -> None:
+        registry = CommandRegistry()
+        store = TemporaryCommandStore(registry)
+        store.create("test", "First")
+
+        with self.assertRaisesRegex(ValueError, "already exists"):
+            store.create("test", "Second")