Merge branch 'main' into pr-1074

README.md

@@ -16,10 +16,13 @@
 
 ⚡️ Delivers core agent functionality in just **~4,000** lines of code — **99% smaller** than Clawdbot's 430k+ lines.
 
-📏 Real-time line count: **3,897 lines** (run `bash core_agent_lines.sh` to verify anytime)
+📏 Real-time line count: **3,966 lines** (run `bash core_agent_lines.sh` to verify anytime)
 
 ## 📢 News
 
+- **2026-02-24** 🚀 Released **v0.1.4.post2** — a reliability-focused release with a redesigned heartbeat, prompt cache optimization, and hardened provider & channel stability. See [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4.post2) for details.
+- **2026-02-23** 🔧 Virtual tool-call heartbeat, prompt cache optimization, Slack mrkdwn fixes.
+- **2026-02-22** 🛡️ Slack thread isolation, Discord typing fix, agent reliability improvements.
 - **2026-02-21** 🎉 Released **v0.1.4.post1** — new providers, media support across channels, and major stability improvements. See [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4.post1) for details.
 - **2026-02-20** 🐦 Feishu now receives multimodal files from users. More reliable memory under the hood.
 - **2026-02-19** ✨ Slack now sends files, Discord splits long messages, and subagents work in CLI mode.

nanobot/__init__.py

@@ -2,5 +2,5 @@
 nanobot - A lightweight AI agent framework
 """
 
-__version__ = "0.1.4"
+__version__ = "0.1.4.post2"
 __logo__ = "🐈"

nanobot/agent/context.py

@@ -3,6 +3,8 @@
 import base64
 import mimetypes
 import platform
+import time
+from datetime import datetime
 from pathlib import Path
 from typing import Any
 
@@ -72,10 +74,6 @@ Skills with available="false" need dependencies installed first - you can try in
     
     def _get_identity(self) -> str:
         """Get the core identity section."""
-        from datetime import datetime
-        import time as _time
-        now = datetime.now().strftime("%Y-%m-%d %H:%M (%A)")
-        tz = _time.strftime("%Z") or "UTC"
         workspace_path = str(self.workspace.expanduser().resolve())
         system = platform.system()
         runtime = f"{'macOS' if system == 'Darwin' else system} {platform.machine()}, Python {platform.python_version()}"
@@ -84,9 +82,6 @@ Skills with available="false" need dependencies installed first - you can try in
 
 You are nanobot, a helpful AI assistant. 
 
-## Current Time
-{now} ({tz})
-
 ## Runtime
 {runtime}
 
@@ -109,6 +104,23 @@ Reply directly with text for conversations. Only use the 'message' tool to send
 - Remember important facts: write to {workspace_path}/memory/MEMORY.md
 - Recall past events: grep {workspace_path}/memory/HISTORY.md"""
 
+    @staticmethod
+    def _inject_runtime_context(
+        user_content: str | list[dict[str, Any]],
+        channel: str | None,
+        chat_id: str | None,
+    ) -> str | list[dict[str, Any]]:
+        """Append dynamic runtime context to the tail of the user message."""
+        now = datetime.now().strftime("%Y-%m-%d %H:%M (%A)")
+        tz = time.strftime("%Z") or "UTC"
+        lines = [f"Current Time: {now} ({tz})"]
+        if channel and chat_id:
+            lines += [f"Channel: {channel}", f"Chat ID: {chat_id}"]
+        block = "[Runtime Context]\n" + "\n".join(lines)
+        if isinstance(user_content, str):
+            return f"{user_content}\n\n{block}"
+        return [*user_content, {"type": "text", "text": block}]
+    
     def _load_bootstrap_files(self) -> str:
         """Load all bootstrap files from workspace."""
         parts = []
@@ -148,8 +160,6 @@ Reply directly with text for conversations. Only use the 'message' tool to send
 
         # System prompt
         system_prompt = self.build_system_prompt(skill_names)
-        if channel and chat_id:
-            system_prompt += f"\n\n## Current Session\nChannel: {channel}\nChat ID: {chat_id}"
         messages.append({"role": "system", "content": system_prompt})
 
         # History
@@ -157,6 +167,7 @@ Reply directly with text for conversations. Only use the 'message' tool to send
 
         # Current message (with optional image attachments)
         user_content = self._build_user_content(current_message, media)
+        user_content = self._inject_runtime_context(user_content, channel, chat_id)
         messages.append({"role": "user", "content": user_content})
 
         return messages

nanobot/agent/memory.py

@@ -125,6 +125,13 @@ class MemoryStore:
                 return False
 
             args = response.tool_calls[0].arguments
+            # Some providers return arguments as a JSON string instead of dict
+            if isinstance(args, str):
+                args = json.loads(args)
+            if not isinstance(args, dict):
+                logger.warning("Memory consolidation: unexpected arguments type {}", type(args).__name__)
+                return False
+
             if entry := args.get("history_entry"):
                 if not isinstance(entry, str):
                     entry = json.dumps(entry, ensure_ascii=False)

nanobot/agent/tools/mcp.py

@@ -69,20 +69,18 @@ async def connect_mcp_servers(
                 read, write = await stack.enter_async_context(stdio_client(params))
             elif cfg.url:
                 from mcp.client.streamable_http import streamable_http_client
-                if cfg.headers:
+                # Always provide an explicit httpx client so MCP HTTP transport does not
-                    http_client = await stack.enter_async_context(
+                # inherit httpx's default 5s timeout and preempt the higher-level tool timeout.
-                        httpx.AsyncClient(
+                http_client = await stack.enter_async_context(
-                            headers=cfg.headers,
+                    httpx.AsyncClient(
-                            follow_redirects=True
+                        headers=cfg.headers or None,
-                        )
+                        follow_redirects=True,
-                    )
+                        timeout=None,
-                    read, write, _ = await stack.enter_async_context(
-                        streamable_http_client(cfg.url, http_client=http_client)
-                    )
-                else:
-                    read, write, _ = await stack.enter_async_context(
-                        streamable_http_client(cfg.url)
                     )
+                )
+                read, write, _ = await stack.enter_async_context(
+                    streamable_http_client(cfg.url, http_client=http_client)
+                )
             else:
                 logger.warning("MCP server '{}': no command or url configured, skipping", name)
                 continue

nanobot/agent/tools/registry.py

@@ -36,19 +36,7 @@ class ToolRegistry:
         return [tool.to_schema() for tool in self._tools.values()]
     
     async def execute(self, name: str, params: dict[str, Any]) -> str:
-        """
+        """Execute a tool by name with given parameters."""
-        Execute a tool by name with given parameters.
-        
-        Args:
-            name: Tool name.
-            params: Tool parameters.
-        
-        Returns:
-            Tool execution result as string.
-        
-        Raises:
-            KeyError: If tool not found.
-        """
         _HINT = "\n\n[Analyze the error above and try a different approach.]"
 
         tool = self._tools.get(name)

nanobot/agent/tools/spawn.py

@@ -9,12 +9,7 @@ if TYPE_CHECKING:
 
 
 class SpawnTool(Tool):
-    """
+    """Tool to spawn a subagent for background task execution."""
-    Tool to spawn a subagent for background task execution.
-    
-    The subagent runs asynchronously and announces its result back
-    to the main agent when complete.
-    """
     
     def __init__(self, manager: "SubagentManager"):
         self._manager = manager

nanobot/agent/tools/web.py

@@ -58,12 +58,21 @@ class WebSearchTool(Tool):
     }
     
     def __init__(self, api_key: str | None = None, max_results: int = 5):
-        self.api_key = api_key or os.environ.get("BRAVE_API_KEY", "")
+        self._init_api_key = api_key
         self.max_results = max_results
 
+    @property
+    def api_key(self) -> str:
+        """Resolve API key at call time so env/config changes are picked up."""
+        return self._init_api_key or os.environ.get("BRAVE_API_KEY", "")
+
     async def execute(self, query: str, count: int | None = None, **kwargs: Any) -> str:
         if not self.api_key:
-            return "Error: BRAVE_API_KEY not configured"
+            return (
+                "Error: Brave Search API key not configured. "
+                "Set it in ~/.nanobot/config.json under tools.web.search.apiKey "
+                "(or export BRAVE_API_KEY), then restart the gateway."
+            )
         
         try:
             n = min(max(count or self.max_results, 1), 10)
@@ -71,7 +80,7 @@ class WebSearchTool(Tool):
                 r = await client.get(
                     "https://api.search.brave.com/res/v1/web/search",
                     params={"q": query, "count": n},
-                    headers={"Accept": "application/json", "X-Subscription-Token": self.api_key},
+                    headers={"Accept": "application/json", "X-Subscription-Token": api_key},
                     timeout=10.0
                 )
                 r.raise_for_status()

nanobot/channels/email.py

@@ -108,11 +108,6 @@ class EmailChannel(BaseChannel):
             logger.warning("Skip email send: consent_granted is false")
             return
 
-        force_send = bool((msg.metadata or {}).get("force_send"))
-        if not self.config.auto_reply_enabled and not force_send:
-            logger.info("Skip automatic email reply: auto_reply_enabled is false")
-            return
-
         if not self.config.smtp_host:
             logger.warning("Email channel SMTP host not configured")
             return
@@ -122,6 +117,15 @@ class EmailChannel(BaseChannel):
             logger.warning("Email channel missing recipient address")
             return
 
+        # Determine if this is a reply (recipient has sent us an email before)
+        is_reply = to_addr in self._last_subject_by_chat
+        force_send = bool((msg.metadata or {}).get("force_send"))
+
+        # autoReplyEnabled only controls automatic replies, not proactive sends
+        if is_reply and not self.config.auto_reply_enabled and not force_send:
+            logger.info("Skip automatic email reply to {}: auto_reply_enabled is false", to_addr)
+            return
+
         base_subject = self._last_subject_by_chat.get(to_addr, "nanobot reply")
         subject = self._reply_subject(base_subject)
         if msg.metadata and isinstance(msg.metadata.get("subject"), str):

nanobot/channels/feishu.py

@@ -180,21 +180,25 @@ def _extract_element_content(element: dict) -> list[str]:
     return parts
 
 
-def _extract_post_text(content_json: dict) -> str:
+def _extract_post_content(content_json: dict) -> tuple[str, list[str]]:
-    """Extract plain text from Feishu post (rich text) message content.
+    """Extract text and image keys from Feishu post (rich text) message content.
     
     Supports two formats:
     1. Direct format: {"title": "...", "content": [...]}
     2. Localized format: {"zh_cn": {"title": "...", "content": [...]}}
+    
+    Returns:
+        (text, image_keys) - extracted text and list of image keys
     """
-    def extract_from_lang(lang_content: dict) -> str | None:
+    def extract_from_lang(lang_content: dict) -> tuple[str | None, list[str]]:
         if not isinstance(lang_content, dict):
-            return None
+            return None, []
         title = lang_content.get("title", "")
         content_blocks = lang_content.get("content", [])
         if not isinstance(content_blocks, list):
-            return None
+            return None, []
         text_parts = []
+        image_keys = []
         if title:
             text_parts.append(title)
         for block in content_blocks:
@@ -209,22 +213,36 @@ def _extract_post_text(content_json: dict) -> str:
                         text_parts.append(element.get("text", ""))
                     elif tag == "at":
                         text_parts.append(f"@{element.get('user_name', 'user')}")
-        return " ".join(text_parts).strip() if text_parts else None
+                    elif tag == "img":
+                        img_key = element.get("image_key")
+                        if img_key:
+                            image_keys.append(img_key)
+        text = " ".join(text_parts).strip() if text_parts else None
+        return text, image_keys
     
     # Try direct format first
     if "content" in content_json:
-        result = extract_from_lang(content_json)
+        text, images = extract_from_lang(content_json)
-        if result:
+        if text or images:
-            return result
+            return text or "", images
     
     # Try localized format
     for lang_key in ("zh_cn", "en_us", "ja_jp"):
         lang_content = content_json.get(lang_key)
-        result = extract_from_lang(lang_content)
+        text, images = extract_from_lang(lang_content)
-        if result:
+        if text or images:
-            return result
+            return text or "", images
     
-    return ""
+    return "", []
+
+
+def _extract_post_text(content_json: dict) -> str:
+    """Extract plain text from Feishu post (rich text) message content.
+    
+    Legacy wrapper for _extract_post_content, returns only text.
+    """
+    text, _ = _extract_post_content(content_json)
+    return text
 
 
 class FeishuChannel(BaseChannel):
@@ -691,9 +709,17 @@ class FeishuChannel(BaseChannel):
                     content_parts.append(text)
 
             elif msg_type == "post":
-                text = _extract_post_text(content_json)
+                text, image_keys = _extract_post_content(content_json)
                 if text:
                     content_parts.append(text)
+                # Download images embedded in post
+                for img_key in image_keys:
+                    file_path, content_text = await self._download_and_save_media(
+                        "image", {"image_key": img_key}, message_id
+                    )
+                    if file_path:
+                        media_paths.append(file_path)
+                    content_parts.append(content_text)
 
             elif msg_type in ("image", "audio", "file", "media"):
                 file_path, content_text = await self._download_and_save_media(msg_type, content_json, message_id)

nanobot/channels/slack.py

@@ -229,6 +229,11 @@ class SlackChannel(BaseChannel):
         return re.sub(rf"<@{re.escape(self._bot_user_id)}>\s*", "", text).strip()
 
     _TABLE_RE = re.compile(r"(?m)^\|.*\|$(?:\n\|[\s:|-]*\|$)(?:\n\|.*\|$)*")
+    _CODE_FENCE_RE = re.compile(r"```[\s\S]*?```")
+    _INLINE_CODE_RE = re.compile(r"`[^`]+`")
+    _LEFTOVER_BOLD_RE = re.compile(r"\*\*(.+?)\*\*")
+    _LEFTOVER_HEADER_RE = re.compile(r"^#{1,6}\s+(.+)$", re.MULTILINE)
+    _BARE_URL_RE = re.compile(r"(?<![|<])(https?://\S+)")
 
     @classmethod
     def _to_mrkdwn(cls, text: str) -> str:
@@ -236,7 +241,26 @@ class SlackChannel(BaseChannel):
         if not text:
             return ""
         text = cls._TABLE_RE.sub(cls._convert_table, text)
-        return slackify_markdown(text)
+        return cls._fixup_mrkdwn(slackify_markdown(text))
+
+    @classmethod
+    def _fixup_mrkdwn(cls, text: str) -> str:
+        """Fix markdown artifacts that slackify_markdown misses."""
+        code_blocks: list[str] = []
+
+        def _save_code(m: re.Match) -> str:
+            code_blocks.append(m.group(0))
+            return f"\x00CB{len(code_blocks) - 1}\x00"
+
+        text = cls._CODE_FENCE_RE.sub(_save_code, text)
+        text = cls._INLINE_CODE_RE.sub(_save_code, text)
+        text = cls._LEFTOVER_BOLD_RE.sub(r"*\1*", text)
+        text = cls._LEFTOVER_HEADER_RE.sub(r"*\1*", text)
+        text = cls._BARE_URL_RE.sub(lambda m: m.group(0).replace("&amp;", "&"), text)
+
+        for i, block in enumerate(code_blocks):
+            text = text.replace(f"\x00CB{i}\x00", block)
+        return text
 
     @staticmethod
     def _convert_table(match: re.Match) -> str:

nanobot/cli/commands.py

@@ -360,19 +360,19 @@ def gateway(
         return "cli", "direct"
 
     # Create heartbeat service
-    async def on_heartbeat(prompt: str) -> str:
+    async def on_heartbeat_execute(tasks: str) -> str:
-        """Execute heartbeat through the agent."""
+        """Phase 2: execute heartbeat tasks through the full agent loop."""
         channel, chat_id = _pick_heartbeat_target()
 
         async def _silent(*_args, **_kwargs):
             pass
 
         return await agent.process_direct(
-            prompt,
+            tasks,
             session_key="heartbeat",
             channel=channel,
             chat_id=chat_id,
-            on_progress=_silent,  # suppress: heartbeat should not push progress to external channels
+            on_progress=_silent,
         )
 
     async def on_heartbeat_notify(response: str) -> None:
@@ -383,12 +383,15 @@ def gateway(
             return  # No external channel available to deliver to
         await bus.publish_outbound(OutboundMessage(channel=channel, chat_id=chat_id, content=response))
 
+    hb_cfg = config.gateway.heartbeat
     heartbeat = HeartbeatService(
         workspace=config.workspace_path,
-        on_heartbeat=on_heartbeat,
+        provider=provider,
+        model=agent.model,
+        on_execute=on_heartbeat_execute,
         on_notify=on_heartbeat_notify,
-        interval_s=30 * 60,  # 30 minutes
+        interval_s=hb_cfg.interval_s,
-        enabled=True
+        enabled=hb_cfg.enabled,
     )
     
     if channels.enabled_channels:
@@ -400,7 +403,7 @@ def gateway(
     if cron_status["jobs"] > 0:
         console.print(f"[green]✓[/green] Cron: {cron_status['jobs']} scheduled jobs")
     
-    console.print(f"[green]✓[/green] Heartbeat: every 30m")
+    console.print(f"[green]✓[/green] Heartbeat: every {hb_cfg.interval_s}s")
     
     async def run():
         try:

nanobot/config/schema.py

@@ -228,11 +228,19 @@ class ProvidersConfig(Base):
     github_copilot: ProviderConfig = Field(default_factory=ProviderConfig)  # Github Copilot (OAuth)
 
 
+class HeartbeatConfig(Base):
+    """Heartbeat service configuration."""
+
+    enabled: bool = True
+    interval_s: int = 30 * 60  # 30 minutes
+
+
 class GatewayConfig(Base):
     """Gateway/server configuration."""
 
     host: str = "0.0.0.0"
     port: int = 18790
+    heartbeat: HeartbeatConfig = Field(default_factory=HeartbeatConfig)
 
 
 class WebSearchConfig(Base):

nanobot/heartbeat/service.py

@@ -1,61 +1,69 @@
 """Heartbeat service - periodic agent wake-up to check for tasks."""
 
+from __future__ import annotations
+
 import asyncio
 from pathlib import Path
-from typing import Any, Callable, Coroutine
+from typing import TYPE_CHECKING, Any, Callable, Coroutine
 
 from loguru import logger
 
-# Default interval: 30 minutes
+if TYPE_CHECKING:
-DEFAULT_HEARTBEAT_INTERVAL_S = 30 * 60
+    from nanobot.providers.base import LLMProvider
 
-# Token the agent replies with when there is nothing to report
+_HEARTBEAT_TOOL = [
-HEARTBEAT_OK_TOKEN = "HEARTBEAT_OK"
+    {
-
+        "type": "function",
-# The prompt sent to agent during heartbeat
+        "function": {
-HEARTBEAT_PROMPT = (
+            "name": "heartbeat",
-    "Read HEARTBEAT.md in your workspace and follow any instructions listed there. "
+            "description": "Report heartbeat decision after reviewing tasks.",
-    f"If nothing needs attention, reply with exactly: {HEARTBEAT_OK_TOKEN}"
+            "parameters": {
-)
+                "type": "object",
-
+                "properties": {
-
+                    "action": {
-def _is_heartbeat_empty(content: str | None) -> bool:
+                        "type": "string",
-    """Check if HEARTBEAT.md has no actionable content."""
+                        "enum": ["skip", "run"],
-    if not content:
+                        "description": "skip = nothing to do, run = has active tasks",
-        return True
+                    },
-    
+                    "tasks": {
-    # Lines to skip: empty, headers, HTML comments, empty checkboxes
+                        "type": "string",
-    skip_patterns = {"- [ ]", "* [ ]", "- [x]", "* [x]"}
+                        "description": "Natural-language summary of active tasks (required for run)",
-    
+                    },
-    for line in content.split("\n"):
+                },
-        line = line.strip()
+                "required": ["action"],
-        if not line or line.startswith("#") or line.startswith("<!--") or line in skip_patterns:
+            },
-            continue
+        },
-        return False  # Found actionable content
+    }
-    
+]
-    return True
 
 
 class HeartbeatService:
     """
     Periodic heartbeat service that wakes the agent to check for tasks.
 
-    The agent reads HEARTBEAT.md from the workspace and executes any tasks
+    Phase 1 (decision): reads HEARTBEAT.md and asks the LLM — via a virtual
-    listed there. If it has something to report, the response is forwarded
+    tool call — whether there are active tasks.  This avoids free-text parsing
-    to the user via on_notify. If nothing needs attention, the agent replies
+    and the unreliable HEARTBEAT_OK token.
-    HEARTBEAT_OK and the response is silently dropped.
+
+    Phase 2 (execution): only triggered when Phase 1 returns ``run``.  The
+    ``on_execute`` callback runs the task through the full agent loop and
+    returns the result to deliver.
     """
 
     def __init__(
         self,
         workspace: Path,
-        on_heartbeat: Callable[[str], Coroutine[Any, Any, str]] | None = None,
+        provider: LLMProvider,
+        model: str,
+        on_execute: Callable[[str], Coroutine[Any, Any, str]] | None = None,
         on_notify: Callable[[str], Coroutine[Any, Any, None]] | None = None,
-        interval_s: int = DEFAULT_HEARTBEAT_INTERVAL_S,
+        interval_s: int = 30 * 60,
         enabled: bool = True,
     ):
         self.workspace = workspace
-        self.on_heartbeat = on_heartbeat
+        self.provider = provider
+        self.model = model
+        self.on_execute = on_execute
         self.on_notify = on_notify
         self.interval_s = interval_s
         self.enabled = enabled
@@ -67,7 +75,6 @@ class HeartbeatService:
         return self.workspace / "HEARTBEAT.md"
 
     def _read_heartbeat_file(self) -> str | None:
-        """Read HEARTBEAT.md content."""
         if self.heartbeat_file.exists():
             try:
                 return self.heartbeat_file.read_text(encoding="utf-8")
@@ -75,6 +82,29 @@ class HeartbeatService:
                 return None
         return None
 
+    async def _decide(self, content: str) -> tuple[str, str]:
+        """Phase 1: ask LLM to decide skip/run via virtual tool call.
+
+        Returns (action, tasks) where action is 'skip' or 'run'.
+        """
+        response = await self.provider.chat(
+            messages=[
+                {"role": "system", "content": "You are a heartbeat agent. Call the heartbeat tool to report your decision."},
+                {"role": "user", "content": (
+                    "Review the following HEARTBEAT.md and decide whether there are active tasks.\n\n"
+                    f"{content}"
+                )},
+            ],
+            tools=_HEARTBEAT_TOOL,
+            model=self.model,
+        )
+
+        if not response.has_tool_calls:
+            return "skip", ""
+
+        args = response.tool_calls[0].arguments
+        return args.get("action", "skip"), args.get("tasks", "")
+
     async def start(self) -> None:
         """Start the heartbeat service."""
         if not self.enabled:
@@ -110,28 +140,34 @@ class HeartbeatService:
     async def _tick(self) -> None:
         """Execute a single heartbeat tick."""
         content = self._read_heartbeat_file()
-        
+        if not content:
-        # Skip if HEARTBEAT.md is empty or doesn't exist
+            logger.debug("Heartbeat: HEARTBEAT.md missing or empty")
-        if _is_heartbeat_empty(content):
-            logger.debug("Heartbeat: no tasks (HEARTBEAT.md empty)")
             return
 
         logger.info("Heartbeat: checking for tasks...")
 
-        if self.on_heartbeat:
+        try:
-            try:
+            action, tasks = await self._decide(content)
-                response = await self.on_heartbeat(HEARTBEAT_PROMPT)
+
-                if HEARTBEAT_OK_TOKEN in response.upper():
+            if action != "run":
-                    logger.info("Heartbeat: OK (nothing to report)")
+                logger.info("Heartbeat: OK (nothing to report)")
-                else:
+                return
+
+            logger.info("Heartbeat: tasks found, executing...")
+            if self.on_execute:
+                response = await self.on_execute(tasks)
+                if response and self.on_notify:
                     logger.info("Heartbeat: completed, delivering response")
-                    if self.on_notify:
+                    await self.on_notify(response)
-                        await self.on_notify(response)
+        except Exception:
-            except Exception:
+            logger.exception("Heartbeat execution failed")
-                logger.exception("Heartbeat execution failed")
 
     async def trigger_now(self) -> str | None:
         """Manually trigger a heartbeat."""
-        if self.on_heartbeat:
+        content = self._read_heartbeat_file()
-            return await self.on_heartbeat(HEARTBEAT_PROMPT)
+        if not content:
-        return None
+            return None
+        action, tasks = await self._decide(content)
+        if action != "run" or not self.on_execute:
+            return None
+        return await self.on_execute(tasks)

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "nanobot-ai"
-version = "0.1.4.post1"
+version = "0.1.4.post2"
 description = "A lightweight personal AI assistant framework"
 requires-python = ">=3.11"
 license = {text = "MIT"}

tests/test_context_prompt_cache.py

@@ -0,0 +1,63 @@
+"""Tests for cache-friendly prompt construction."""
+
+from __future__ import annotations
+
+from datetime import datetime as real_datetime
+from pathlib import Path
+import datetime as datetime_module
+
+from nanobot.agent.context import ContextBuilder
+
+
+class _FakeDatetime(real_datetime):
+    current = real_datetime(2026, 2, 24, 13, 59)
+
+    @classmethod
+    def now(cls, tz=None):  # type: ignore[override]
+        return cls.current
+
+
+def _make_workspace(tmp_path: Path) -> Path:
+    workspace = tmp_path / "workspace"
+    workspace.mkdir(parents=True)
+    return workspace
+
+
+def test_system_prompt_stays_stable_when_clock_changes(tmp_path, monkeypatch) -> None:
+    """System prompt should not change just because wall clock minute changes."""
+    monkeypatch.setattr(datetime_module, "datetime", _FakeDatetime)
+
+    workspace = _make_workspace(tmp_path)
+    builder = ContextBuilder(workspace)
+
+    _FakeDatetime.current = real_datetime(2026, 2, 24, 13, 59)
+    prompt1 = builder.build_system_prompt()
+
+    _FakeDatetime.current = real_datetime(2026, 2, 24, 14, 0)
+    prompt2 = builder.build_system_prompt()
+
+    assert prompt1 == prompt2
+
+
+def test_runtime_context_is_appended_to_current_user_message(tmp_path) -> None:
+    """Dynamic runtime details should be added at the tail user message, not system."""
+    workspace = _make_workspace(tmp_path)
+    builder = ContextBuilder(workspace)
+
+    messages = builder.build_messages(
+        history=[],
+        current_message="Return exactly: OK",
+        channel="cli",
+        chat_id="direct",
+    )
+
+    assert messages[0]["role"] == "system"
+    assert "## Current Session" not in messages[0]["content"]
+
+    assert messages[-1]["role"] == "user"
+    user_content = messages[-1]["content"]
+    assert isinstance(user_content, str)
+    assert "Return exactly: OK" in user_content
+    assert "Current Time:" in user_content
+    assert "Channel: cli" in user_content
+    assert "Chat ID: direct" in user_content

tests/test_email_channel.py

@@ -169,7 +169,8 @@ async def test_send_uses_smtp_and_reply_subject(monkeypatch) -> None:
 
 
 @pytest.mark.asyncio
-async def test_send_skips_when_auto_reply_disabled(monkeypatch) -> None:
+async def test_send_skips_reply_when_auto_reply_disabled(monkeypatch) -> None:
+    """When auto_reply_enabled=False, replies should be skipped but proactive sends allowed."""
     class FakeSMTP:
         def __init__(self, _host: str, _port: int, timeout: int = 30) -> None:
             self.sent_messages: list[EmailMessage] = []
@@ -201,6 +202,11 @@ async def test_send_skips_when_auto_reply_disabled(monkeypatch) -> None:
     cfg = _make_config()
     cfg.auto_reply_enabled = False
     channel = EmailChannel(cfg, MessageBus())
+
+    # Mark alice as someone who sent us an email (making this a "reply")
+    channel._last_subject_by_chat["alice@example.com"] = "Previous email"
+
+    # Reply should be skipped (auto_reply_enabled=False)
     await channel.send(
         OutboundMessage(
             channel="email",
@@ -210,6 +216,7 @@ async def test_send_skips_when_auto_reply_disabled(monkeypatch) -> None:
     )
     assert fake_instances == []
 
+    # Reply with force_send=True should be sent
     await channel.send(
         OutboundMessage(
             channel="email",
@@ -222,6 +229,56 @@ async def test_send_skips_when_auto_reply_disabled(monkeypatch) -> None:
     assert len(fake_instances[0].sent_messages) == 1
 
 
+@pytest.mark.asyncio
+async def test_send_proactive_email_when_auto_reply_disabled(monkeypatch) -> None:
+    """Proactive emails (not replies) should be sent even when auto_reply_enabled=False."""
+    class FakeSMTP:
+        def __init__(self, _host: str, _port: int, timeout: int = 30) -> None:
+            self.sent_messages: list[EmailMessage] = []
+
+        def __enter__(self):
+            return self
+
+        def __exit__(self, exc_type, exc, tb):
+            return False
+
+        def starttls(self, context=None):
+            return None
+
+        def login(self, _user: str, _pw: str):
+            return None
+
+        def send_message(self, msg: EmailMessage):
+            self.sent_messages.append(msg)
+
+    fake_instances: list[FakeSMTP] = []
+
+    def _smtp_factory(host: str, port: int, timeout: int = 30):
+        instance = FakeSMTP(host, port, timeout=timeout)
+        fake_instances.append(instance)
+        return instance
+
+    monkeypatch.setattr("nanobot.channels.email.smtplib.SMTP", _smtp_factory)
+
+    cfg = _make_config()
+    cfg.auto_reply_enabled = False
+    channel = EmailChannel(cfg, MessageBus())
+
+    # bob@example.com has never sent us an email (proactive send)
+    # This should be sent even with auto_reply_enabled=False
+    await channel.send(
+        OutboundMessage(
+            channel="email",
+            chat_id="bob@example.com",
+            content="Hello, this is a proactive email.",
+        )
+    )
+    assert len(fake_instances) == 1
+    assert len(fake_instances[0].sent_messages) == 1
+    sent = fake_instances[0].sent_messages[0]
+    assert sent["To"] == "bob@example.com"
+
+
 @pytest.mark.asyncio
 async def test_send_skips_when_consent_not_granted(monkeypatch) -> None:
     class FakeSMTP:

tests/test_memory_consolidation_types.py

@@ -0,0 +1,147 @@
+"""Test MemoryStore.consolidate() handles non-string tool call arguments.
+
+Regression test for https://github.com/HKUDS/nanobot/issues/1042
+When memory consolidation receives dict values instead of strings from the LLM
+tool call response, it should serialize them to JSON instead of raising TypeError.
+"""
+
+import json
+from pathlib import Path
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from nanobot.agent.memory import MemoryStore
+from nanobot.providers.base import LLMResponse, ToolCallRequest
+
+
+def _make_session(message_count: int = 30, memory_window: int = 50):
+    """Create a mock session with messages."""
+    session = MagicMock()
+    session.messages = [
+        {"role": "user", "content": f"msg{i}", "timestamp": "2026-01-01 00:00"}
+        for i in range(message_count)
+    ]
+    session.last_consolidated = 0
+    return session
+
+
+def _make_tool_response(history_entry, memory_update):
+    """Create an LLMResponse with a save_memory tool call."""
+    return LLMResponse(
+        content=None,
+        tool_calls=[
+            ToolCallRequest(
+                id="call_1",
+                name="save_memory",
+                arguments={
+                    "history_entry": history_entry,
+                    "memory_update": memory_update,
+                },
+            )
+        ],
+    )
+
+
+class TestMemoryConsolidationTypeHandling:
+    """Test that consolidation handles various argument types correctly."""
+
+    @pytest.mark.asyncio
+    async def test_string_arguments_work(self, tmp_path: Path) -> None:
+        """Normal case: LLM returns string arguments."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+        provider.chat = AsyncMock(
+            return_value=_make_tool_response(
+                history_entry="[2026-01-01] User discussed testing.",
+                memory_update="# Memory\nUser likes testing.",
+            )
+        )
+        session = _make_session(message_count=60)
+
+        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+
+        assert result is True
+        assert store.history_file.exists()
+        assert "[2026-01-01] User discussed testing." in store.history_file.read_text()
+        assert "User likes testing." in store.memory_file.read_text()
+
+    @pytest.mark.asyncio
+    async def test_dict_arguments_serialized_to_json(self, tmp_path: Path) -> None:
+        """Issue #1042: LLM returns dict instead of string — must not raise TypeError."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+        provider.chat = AsyncMock(
+            return_value=_make_tool_response(
+                history_entry={"timestamp": "2026-01-01", "summary": "User discussed testing."},
+                memory_update={"facts": ["User likes testing"], "topics": ["testing"]},
+            )
+        )
+        session = _make_session(message_count=60)
+
+        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+
+        assert result is True
+        assert store.history_file.exists()
+        history_content = store.history_file.read_text()
+        parsed = json.loads(history_content.strip())
+        assert parsed["summary"] == "User discussed testing."
+
+        memory_content = store.memory_file.read_text()
+        parsed_mem = json.loads(memory_content)
+        assert "User likes testing" in parsed_mem["facts"]
+
+    @pytest.mark.asyncio
+    async def test_string_arguments_as_raw_json(self, tmp_path: Path) -> None:
+        """Some providers return arguments as a JSON string instead of parsed dict."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+
+        # Simulate arguments being a JSON string (not yet parsed)
+        response = LLMResponse(
+            content=None,
+            tool_calls=[
+                ToolCallRequest(
+                    id="call_1",
+                    name="save_memory",
+                    arguments=json.dumps({
+                        "history_entry": "[2026-01-01] User discussed testing.",
+                        "memory_update": "# Memory\nUser likes testing.",
+                    }),
+                )
+            ],
+        )
+        provider.chat = AsyncMock(return_value=response)
+        session = _make_session(message_count=60)
+
+        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+
+        assert result is True
+        assert "User discussed testing." in store.history_file.read_text()
+
+    @pytest.mark.asyncio
+    async def test_no_tool_call_returns_false(self, tmp_path: Path) -> None:
+        """When LLM doesn't use the save_memory tool, return False."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+        provider.chat = AsyncMock(
+            return_value=LLMResponse(content="I summarized the conversation.", tool_calls=[])
+        )
+        session = _make_session(message_count=60)
+
+        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+
+        assert result is False
+        assert not store.history_file.exists()
+
+    @pytest.mark.asyncio
+    async def test_skips_when_few_messages(self, tmp_path: Path) -> None:
+        """Consolidation should be a no-op when messages < keep_count."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+        session = _make_session(message_count=10)
+
+        result = await store.consolidate(session, provider, "test-model", memory_window=50)
+
+        assert result is True
+        provider.chat.assert_not_called()