Merge branch 'main' into main

README.md

@@ -16,16 +16,24 @@
 
 ⚡️ Delivers core agent functionality in just **~4,000** lines of code — **99% smaller** than Clawdbot's 430k+ lines.
 
-📏 Real-time line count: **3,922 lines** (run `bash core_agent_lines.sh` to verify anytime)
+📏 Real-time line count: **3,935 lines** (run `bash core_agent_lines.sh` to verify anytime)
 
 ## 📢 News
 
+- **2026-02-28** 🚀 Released **v0.1.4.post3** — cleaner context, hardened session history, and smarter agent. Please see [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4.post3) for details.
+- **2026-02-27** 🧠 Experimental thinking mode support, DingTalk media messages, Feishu and QQ channel fixes.
+- **2026-02-26** 🛡️ Session poisoning fix, WhatsApp dedup, Windows path guard, Mistral compatibility.
+- **2026-02-25** 🧹 New Matrix channel, cleaner session context, auto workspace template sync.
 - **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.
+
+<details>
+<summary>Earlier news</summary>
+
 - **2026-02-18** ⚡️ nanobot now supports VolcEngine, MCP custom auth headers, and Anthropic prompt caching.
 - **2026-02-17** 🎉 Released **v0.1.4** — MCP support, progress streaming, new providers, and multiple channel improvements. Please see [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.4) for details.
 - **2026-02-16** 🦞 nanobot now integrates a [ClawHub](https://clawhub.ai) skill — search and install public agent skills.
@@ -34,10 +42,6 @@
 - **2026-02-13** 🎉 Released **v0.1.3.post7** — includes security hardening and multiple improvements. **Please upgrade to the latest version to address security issues**. See [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.3.post7) for more details.
 - **2026-02-12** 🧠 Redesigned memory system — Less code, more reliable. Join the [discussion](https://github.com/HKUDS/nanobot/discussions/566) about it!
 - **2026-02-11** ✨ Enhanced CLI experience and added MiniMax support!
-
-<details>
-<summary>Earlier news</summary>
-
 - **2026-02-10** 🎉 Released **v0.1.3.post6** with improvements! Check the updates [notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.3.post6) and our [roadmap](https://github.com/HKUDS/nanobot/discussions/431).
 - **2026-02-09** 💬 Added Slack, Email, and QQ support — nanobot now supports multiple chat platforms!
 - **2026-02-08** 🔧 Refactored Providers—adding a new LLM provider now takes just 2 simple steps! Check [here](#providers).

nanobot/__init__.py

@@ -2,5 +2,5 @@
 nanobot - A lightweight AI agent framework
 """
 
-__version__ = "0.1.4.post2"
+__version__ = "0.1.4.post3"
 __logo__ = "🐈"

nanobot/agent/context.py

@@ -150,6 +150,7 @@ Reply directly with text for conversations. Only use the 'message' tool to send
         content: str | None,
         tool_calls: list[dict[str, Any]] | None = None,
         reasoning_content: str | None = None,
+        thinking_blocks: list[dict] | None = None,
     ) -> list[dict[str, Any]]:
         """Add an assistant message to the message list."""
         msg: dict[str, Any] = {"role": "assistant", "content": content}
@@ -157,5 +158,7 @@ Reply directly with text for conversations. Only use the 'message' tool to send
             msg["tool_calls"] = tool_calls
         if reasoning_content is not None:
             msg["reasoning_content"] = reasoning_content
+        if thinking_blocks:
+            msg["thinking_blocks"] = thinking_blocks
         messages.append(msg)
         return messages

nanobot/agent/loop.py

@@ -56,6 +56,7 @@ class AgentLoop:
         temperature: float = 0.1,
         max_tokens: int = 4096,
         memory_window: int = 100,
+        reasoning_effort: str | None = None,
         brave_api_key: str | None = None,
         exec_config: ExecToolConfig | None = None,
         cron_service: CronService | None = None,
@@ -74,6 +75,7 @@ class AgentLoop:
         self.temperature = temperature
         self.max_tokens = max_tokens
         self.memory_window = memory_window
+        self.reasoning_effort = reasoning_effort
         self.brave_api_key = brave_api_key
         self.exec_config = exec_config or ExecToolConfig()
         self.cron_service = cron_service
@@ -89,6 +91,7 @@ class AgentLoop:
             model=self.model,
             temperature=self.temperature,
             max_tokens=self.max_tokens,
+            reasoning_effort=reasoning_effort,
             brave_api_key=brave_api_key,
             exec_config=self.exec_config,
             restrict_to_workspace=restrict_to_workspace,
@@ -191,6 +194,7 @@ class AgentLoop:
                 model=self.model,
                 temperature=self.temperature,
                 max_tokens=self.max_tokens,
+                reasoning_effort=self.reasoning_effort,
             )
 
             if response.has_tool_calls:
@@ -214,6 +218,7 @@ class AgentLoop:
                 messages = self.context.add_assistant_message(
                     messages, response.content, tool_call_dicts,
                     reasoning_content=response.reasoning_content,
+                    thinking_blocks=response.thinking_blocks,
                 )
 
                 for tool_call in response.tool_calls:
@@ -234,6 +239,7 @@ class AgentLoop:
                     break
                 messages = self.context.add_assistant_message(
                     messages, clean, reasoning_content=response.reasoning_content,
+                    thinking_blocks=response.thinking_blocks,
                 )
                 final_content = clean
                 break
@@ -447,7 +453,7 @@ class AgentLoop:
         """Save new-turn messages into session, truncating large tool results."""
         from datetime import datetime
         for m in messages[skip:]:
-            entry = {k: v for k, v in m.items() if k != "reasoning_content"}
+            entry = dict(m)
             role, content = entry.get("role"), entry.get("content")
             if role == "assistant" and not content and not entry.get("tool_calls"):
                 continue  # skip empty assistant messages — they poison session context

nanobot/agent/subagent.py

@@ -29,6 +29,7 @@ class SubagentManager:
         model: str | None = None,
         temperature: float = 0.7,
         max_tokens: int = 4096,
+        reasoning_effort: str | None = None,
         brave_api_key: str | None = None,
         exec_config: "ExecToolConfig | None" = None,
         restrict_to_workspace: bool = False,
@@ -40,6 +41,7 @@ class SubagentManager:
         self.model = model or provider.get_default_model()
         self.temperature = temperature
         self.max_tokens = max_tokens
+        self.reasoning_effort = reasoning_effort
         self.brave_api_key = brave_api_key
         self.exec_config = exec_config or ExecToolConfig()
         self.restrict_to_workspace = restrict_to_workspace
@@ -104,9 +106,8 @@ class SubagentManager:
             ))
             tools.register(WebSearchTool(api_key=self.brave_api_key))
             tools.register(WebFetchTool())
-
+            
-            # Build messages with subagent-specific prompt
+            system_prompt = self._build_subagent_prompt()
-            system_prompt = self._build_subagent_prompt(task)
             messages: list[dict[str, Any]] = [
                 {"role": "system", "content": system_prompt},
                 {"role": "user", "content": task},
@@ -126,6 +127,7 @@ class SubagentManager:
                     model=self.model,
                     temperature=self.temperature,
                     max_tokens=self.max_tokens,
+                    reasoning_effort=self.reasoning_effort,
                 )
 
                 if response.has_tool_calls:
@@ -204,44 +206,29 @@ Summarize this naturally for the user. Keep it brief (1-2 sentences). Do not men
 
         await self.bus.publish_inbound(msg)
         logger.debug("Subagent [{}] announced result to {}:{}", task_id, origin['channel'], origin['chat_id'])
-
+    
-    def _build_subagent_prompt(self, task: str) -> str:
+    def _build_subagent_prompt(self) -> str:
         """Build a focused system prompt for the subagent."""
-        import time as _time
+        from nanobot.agent.context import ContextBuilder
-        from datetime import datetime
+        from nanobot.agent.skills import SkillsLoader
-        now = datetime.now().strftime("%Y-%m-%d %H:%M (%A)")
-        tz = _time.strftime("%Z") or "UTC"
 
-        return f"""# Subagent
+        time_ctx = ContextBuilder._build_runtime_context(None, None)
+        parts = [f"""# Subagent
 
-## Current Time
+{time_ctx}
-{now} ({tz})
 
 You are a subagent spawned by the main agent to complete a specific task.
-
+Stay focused on the assigned task. Your final response will be reported back to the main agent.
-## Rules
-1. Stay focused - complete only the assigned task, nothing else
-2. Your final response will be reported back to the main agent
-3. Do not initiate conversations or take on side tasks
-4. Be concise but informative in your findings
-
-## What You Can Do
-- Read and write files in the workspace
-- Execute shell commands
-- Search the web and fetch web pages
-- Complete the task thoroughly
-
-## What You Cannot Do
-- Send messages directly to users (no message tool available)
-- Spawn other subagents
-- Access the main agent's conversation history
 
 ## Workspace
-Your workspace is at: {self.workspace}
+{self.workspace}"""]
-Skills are available at: {self.workspace}/skills/ (read SKILL.md files as needed)
 
-When you have completed the task, provide a clear summary of your findings or actions."""
+        skills_summary = SkillsLoader(self.workspace).build_skills_summary()
+        if skills_summary:
+            parts.append(f"## Skills\n\nRead SKILL.md with read_file to use a skill.\n\n{skills_summary}")
 
+        return "\n\n".join(parts)
+    
     async def cancel_by_session(self, session_key: str) -> int:
         """Cancel all subagents for the given session. Returns count cancelled."""
         tasks = [self._running_tasks[tid] for tid in self._session_tasks.get(session_key, [])

nanobot/channels/dingtalk.py

@@ -2,8 +2,12 @@
 
 import asyncio
 import json
+import mimetypes
+import os
 import time
+from pathlib import Path
 from typing import Any
+from urllib.parse import unquote, urlparse
 
 import httpx
 from loguru import logger
@@ -96,6 +100,9 @@ class DingTalkChannel(BaseChannel):
     """
 
     name = "dingtalk"
+    _IMAGE_EXTS = {".jpg", ".jpeg", ".png", ".gif", ".bmp", ".webp"}
+    _AUDIO_EXTS = {".amr", ".mp3", ".wav", ".ogg", ".m4a", ".aac"}
+    _VIDEO_EXTS = {".mp4", ".mov", ".avi", ".mkv", ".webm"}
 
     def __init__(self, config: DingTalkConfig, bus: MessageBus):
         super().__init__(config, bus)
@@ -191,40 +198,224 @@ class DingTalkChannel(BaseChannel):
             logger.error("Failed to get DingTalk access token: {}", e)
             return None
 
+    @staticmethod
+    def _is_http_url(value: str) -> bool:
+        return urlparse(value).scheme in ("http", "https")
+
+    def _guess_upload_type(self, media_ref: str) -> str:
+        ext = Path(urlparse(media_ref).path).suffix.lower()
+        if ext in self._IMAGE_EXTS: return "image"
+        if ext in self._AUDIO_EXTS: return "voice"
+        if ext in self._VIDEO_EXTS: return "video"
+        return "file"
+
+    def _guess_filename(self, media_ref: str, upload_type: str) -> str:
+        name = os.path.basename(urlparse(media_ref).path)
+        return name or {"image": "image.jpg", "voice": "audio.amr", "video": "video.mp4"}.get(upload_type, "file.bin")
+
+    async def _read_media_bytes(
+        self,
+        media_ref: str,
+    ) -> tuple[bytes | None, str | None, str | None]:
+        if not media_ref:
+            return None, None, None
+
+        if self._is_http_url(media_ref):
+            if not self._http:
+                return None, None, None
+            try:
+                resp = await self._http.get(media_ref, follow_redirects=True)
+                if resp.status_code >= 400:
+                    logger.warning(
+                        "DingTalk media download failed status={} ref={}",
+                        resp.status_code,
+                        media_ref,
+                    )
+                    return None, None, None
+                content_type = (resp.headers.get("content-type") or "").split(";")[0].strip()
+                filename = self._guess_filename(media_ref, self._guess_upload_type(media_ref))
+                return resp.content, filename, content_type or None
+            except Exception as e:
+                logger.error("DingTalk media download error ref={} err={}", media_ref, e)
+                return None, None, None
+
+        try:
+            if media_ref.startswith("file://"):
+                parsed = urlparse(media_ref)
+                local_path = Path(unquote(parsed.path))
+            else:
+                local_path = Path(os.path.expanduser(media_ref))
+            if not local_path.is_file():
+                logger.warning("DingTalk media file not found: {}", local_path)
+                return None, None, None
+            data = await asyncio.to_thread(local_path.read_bytes)
+            content_type = mimetypes.guess_type(local_path.name)[0]
+            return data, local_path.name, content_type
+        except Exception as e:
+            logger.error("DingTalk media read error ref={} err={}", media_ref, e)
+            return None, None, None
+
+    async def _upload_media(
+        self,
+        token: str,
+        data: bytes,
+        media_type: str,
+        filename: str,
+        content_type: str | None,
+    ) -> str | None:
+        if not self._http:
+            return None
+        url = f"https://oapi.dingtalk.com/media/upload?access_token={token}&type={media_type}"
+        mime = content_type or mimetypes.guess_type(filename)[0] or "application/octet-stream"
+        files = {"media": (filename, data, mime)}
+
+        try:
+            resp = await self._http.post(url, files=files)
+            text = resp.text
+            result = resp.json() if resp.headers.get("content-type", "").startswith("application/json") else {}
+            if resp.status_code >= 400:
+                logger.error("DingTalk media upload failed status={} type={} body={}", resp.status_code, media_type, text[:500])
+                return None
+            errcode = result.get("errcode", 0)
+            if errcode != 0:
+                logger.error("DingTalk media upload api error type={} errcode={} body={}", media_type, errcode, text[:500])
+                return None
+            sub = result.get("result") or {}
+            media_id = result.get("media_id") or result.get("mediaId") or sub.get("media_id") or sub.get("mediaId")
+            if not media_id:
+                logger.error("DingTalk media upload missing media_id body={}", text[:500])
+                return None
+            return str(media_id)
+        except Exception as e:
+            logger.error("DingTalk media upload error type={} err={}", media_type, e)
+            return None
+
+    async def _send_batch_message(
+        self,
+        token: str,
+        chat_id: str,
+        msg_key: str,
+        msg_param: dict[str, Any],
+    ) -> bool:
+        if not self._http:
+            logger.warning("DingTalk HTTP client not initialized, cannot send")
+            return False
+
+        url = "https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend"
+        headers = {"x-acs-dingtalk-access-token": token}
+        payload = {
+            "robotCode": self.config.client_id,
+            "userIds": [chat_id],
+            "msgKey": msg_key,
+            "msgParam": json.dumps(msg_param, ensure_ascii=False),
+        }
+
+        try:
+            resp = await self._http.post(url, json=payload, headers=headers)
+            body = resp.text
+            if resp.status_code != 200:
+                logger.error("DingTalk send failed msgKey={} status={} body={}", msg_key, resp.status_code, body[:500])
+                return False
+            try: result = resp.json()
+            except Exception: result = {}
+            errcode = result.get("errcode")
+            if errcode not in (None, 0):
+                logger.error("DingTalk send api error msgKey={} errcode={} body={}", msg_key, errcode, body[:500])
+                return False
+            logger.debug("DingTalk message sent to {} with msgKey={}", chat_id, msg_key)
+            return True
+        except Exception as e:
+            logger.error("Error sending DingTalk message msgKey={} err={}", msg_key, e)
+            return False
+
+    async def _send_markdown_text(self, token: str, chat_id: str, content: str) -> bool:
+        return await self._send_batch_message(
+            token,
+            chat_id,
+            "sampleMarkdown",
+            {"text": content, "title": "Nanobot Reply"},
+        )
+
+    async def _send_media_ref(self, token: str, chat_id: str, media_ref: str) -> bool:
+        media_ref = (media_ref or "").strip()
+        if not media_ref:
+            return True
+
+        upload_type = self._guess_upload_type(media_ref)
+        if upload_type == "image" and self._is_http_url(media_ref):
+            ok = await self._send_batch_message(
+                token,
+                chat_id,
+                "sampleImageMsg",
+                {"photoURL": media_ref},
+            )
+            if ok:
+                return True
+            logger.warning("DingTalk image url send failed, trying upload fallback: {}", media_ref)
+
+        data, filename, content_type = await self._read_media_bytes(media_ref)
+        if not data:
+            logger.error("DingTalk media read failed: {}", media_ref)
+            return False
+
+        filename = filename or self._guess_filename(media_ref, upload_type)
+        file_type = Path(filename).suffix.lower().lstrip(".")
+        if not file_type:
+            guessed = mimetypes.guess_extension(content_type or "")
+            file_type = (guessed or ".bin").lstrip(".")
+        if file_type == "jpeg":
+            file_type = "jpg"
+
+        media_id = await self._upload_media(
+            token=token,
+            data=data,
+            media_type=upload_type,
+            filename=filename,
+            content_type=content_type,
+        )
+        if not media_id:
+            return False
+
+        if upload_type == "image":
+            # Verified in production: sampleImageMsg accepts media_id in photoURL.
+            ok = await self._send_batch_message(
+                token,
+                chat_id,
+                "sampleImageMsg",
+                {"photoURL": media_id},
+            )
+            if ok:
+                return True
+            logger.warning("DingTalk image media_id send failed, falling back to file: {}", media_ref)
+
+        return await self._send_batch_message(
+            token,
+            chat_id,
+            "sampleFile",
+            {"mediaId": media_id, "fileName": filename, "fileType": file_type},
+        )
+
     async def send(self, msg: OutboundMessage) -> None:
         """Send a message through DingTalk."""
         token = await self._get_access_token()
         if not token:
             return
 
-        # oToMessages/batchSend: sends to individual users (private chat)
+        if msg.content and msg.content.strip():
-        # https://open.dingtalk.com/document/orgapp/robot-batch-send-messages
+            await self._send_markdown_text(token, msg.chat_id, msg.content.strip())
-        url = "https://api.dingtalk.com/v1.0/robot/oToMessages/batchSend"
 
-        headers = {"x-acs-dingtalk-access-token": token}
+        for media_ref in msg.media or []:
-
+            ok = await self._send_media_ref(token, msg.chat_id, media_ref)
-        data = {
+            if ok:
-            "robotCode": self.config.client_id,
+                continue
-            "userIds": [msg.chat_id],  # chat_id is the user's staffId
+            logger.error("DingTalk media send failed for {}", media_ref)
-            "msgKey": "sampleMarkdown",
+            # Send visible fallback so failures are observable by the user.
-            "msgParam": json.dumps({
+            filename = self._guess_filename(media_ref, self._guess_upload_type(media_ref))
-                "text": msg.content,
+            await self._send_markdown_text(
-                "title": "Nanobot Reply",
+                token,
-            }, ensure_ascii=False),
+                msg.chat_id,
-        }
+                f"[Attachment send failed: {filename}]",
-
+            )
-        if not self._http:
-            logger.warning("DingTalk HTTP client not initialized, cannot send")
-            return
-
-        try:
-            resp = await self._http.post(url, json=data, headers=headers)
-            if resp.status_code != 200:
-                logger.error("DingTalk send failed: {}", resp.text)
-            else:
-                logger.debug("DingTalk message sent to {}", msg.chat_id)
-        except Exception as e:
-            logger.error("Error sending DingTalk message: {}", e)
 
     async def _on_message(self, content: str, sender_id: str, sender_name: str) -> None:
         """Handle incoming message (called by NanobotDingTalkHandler).

nanobot/channels/feishu.py

@@ -326,13 +326,14 @@ class FeishuChannel(BaseChannel):
             await asyncio.sleep(1)
 
     async def stop(self) -> None:
-        """Stop the Feishu bot."""
+        """
+        Stop the Feishu bot.
+
+        Notice: lark.ws.Client does not expose stop method， simply exiting the program will close the client.
+
+        Reference: https://github.com/larksuite/oapi-sdk-python/blob/v2_main/lark_oapi/ws/client.py#L86
+        """
         self._running = False
-        if self._ws_client:
-            try:
-                self._ws_client.stop()
-            except Exception as e:
-                logger.warning("Error stopping WebSocket client: {}", e)
         logger.info("Feishu bot stopped")
 
     def _add_reaction_sync(self, message_id: str, emoji_type: str) -> None:

nanobot/channels/qq.py

@@ -31,7 +31,8 @@ def _make_bot_class(channel: "QQChannel") -> "type[botpy.Client]":
 
     class _Bot(botpy.Client):
         def __init__(self):
-            super().__init__(intents=intents)
+            # Disable botpy's file log — nanobot uses loguru; default "botpy.log" fails on read-only fs
+            super().__init__(intents=intents, ext_handlers=False)
 
         async def on_ready(self):
             logger.info("QQ bot ready: {}", self.robot.name)

nanobot/cli/commands.py

@@ -282,6 +282,7 @@ def gateway(
         max_tokens=config.agents.defaults.max_tokens,
         max_iterations=config.agents.defaults.max_tool_iterations,
         memory_window=config.agents.defaults.memory_window,
+        reasoning_effort=config.agents.defaults.reasoning_effort,
         brave_api_key=config.tools.web.search.api_key or None,
         exec_config=config.tools.exec,
         cron_service=cron,
@@ -441,6 +442,7 @@ def agent(
         max_tokens=config.agents.defaults.max_tokens,
         max_iterations=config.agents.defaults.max_tool_iterations,
         memory_window=config.agents.defaults.memory_window,
+        reasoning_effort=config.agents.defaults.reasoning_effort,
         brave_api_key=config.tools.web.search.api_key or None,
         exec_config=config.tools.exec,
         cron_service=cron,
@@ -934,6 +936,7 @@ def cron_run(
         max_tokens=config.agents.defaults.max_tokens,
         max_iterations=config.agents.defaults.max_tool_iterations,
         memory_window=config.agents.defaults.memory_window,
+        reasoning_effort=config.agents.defaults.reasoning_effort,
         brave_api_key=config.tools.web.search.api_key or None,
         exec_config=config.tools.exec,
         restrict_to_workspace=config.tools.restrict_to_workspace,

nanobot/config/schema.py

@@ -226,6 +226,7 @@ class AgentDefaults(Base):
     temperature: float = 0.1
     max_tool_iterations: int = 40
     memory_window: int = 100
+    reasoning_effort: str | None = None  # low / medium / high — enables LLM thinking mode
 
 
 class AgentsConfig(Base):

nanobot/providers/base.py

@@ -21,7 +21,8 @@ class LLMResponse:
     finish_reason: str = "stop"
     usage: dict[str, int] = field(default_factory=dict)
     reasoning_content: str | None = None  # Kimi, DeepSeek-R1 etc.
-
+    thinking_blocks: list[dict] | None = None  # Anthropic extended thinking
+    
     @property
     def has_tool_calls(self) -> bool:
         """Check if response contains tool calls."""
@@ -88,6 +89,7 @@ class LLMProvider(ABC):
         model: str | None = None,
         max_tokens: int = 4096,
         temperature: float = 0.7,
+        reasoning_effort: str | None = None,
     ) -> LLMResponse:
         """
         Send a chat completion request.

nanobot/providers/custom_provider.py

@@ -18,13 +18,16 @@ class CustomProvider(LLMProvider):
         self._client = AsyncOpenAI(api_key=api_key, base_url=api_base)
 
     async def chat(self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
-                   model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7) -> LLMResponse:
+                   model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7,
+                   reasoning_effort: str | None = None) -> LLMResponse:
         kwargs: dict[str, Any] = {
             "model": model or self.default_model,
             "messages": self._sanitize_empty_content(messages),
             "max_tokens": max(1, max_tokens),
             "temperature": temperature,
         }
+        if reasoning_effort:
+            kwargs["reasoning_effort"] = reasoning_effort
         if tools:
             kwargs.update(tools=tools, tool_choice="auto")
         try:

nanobot/providers/litellm_provider.py

@@ -14,7 +14,7 @@ from nanobot.providers.registry import find_by_model, find_gateway
 
 # Standard OpenAI chat-completion message keys plus reasoning_content for
 # thinking-enabled models (Kimi k2.5, DeepSeek-R1, etc.).
-_ALLOWED_MSG_KEYS = frozenset({"role", "content", "tool_calls", "tool_call_id", "name", "reasoning_content"})
+_ALLOWED_MSG_KEYS = frozenset({"role", "content", "tool_calls", "tool_call_id", "name", "reasoning_content", "thinking_blocks"})
 _ALNUM = string.ascii_letters + string.digits
 
 def _short_tool_id() -> str:
@@ -176,6 +176,7 @@ class LiteLLMProvider(LLMProvider):
         model: str | None = None,
         max_tokens: int = 4096,
         temperature: float = 0.7,
+        reasoning_effort: str | None = None,
     ) -> LLMResponse:
         """
         Send a chat completion request via LiteLLM.
@@ -221,7 +222,11 @@ class LiteLLMProvider(LLMProvider):
         # Pass extra headers (e.g. APP-Code for AiHubMix)
         if self.extra_headers:
             kwargs["extra_headers"] = self.extra_headers
-
+        
+        if reasoning_effort:
+            kwargs["reasoning_effort"] = reasoning_effort
+            kwargs["drop_params"] = True
+        
         if tools:
             kwargs["tools"] = tools
             kwargs["tool_choice"] = "auto"
@@ -264,13 +269,15 @@ class LiteLLMProvider(LLMProvider):
             }
 
         reasoning_content = getattr(message, "reasoning_content", None) or None
-
+        thinking_blocks = getattr(message, "thinking_blocks", None) or None
+        
         return LLMResponse(
             content=message.content,
             tool_calls=tool_calls,
             finish_reason=choice.finish_reason or "stop",
             usage=usage,
             reasoning_content=reasoning_content,
+            thinking_blocks=thinking_blocks,
         )
 
     def get_default_model(self) -> str:

nanobot/providers/openai_codex_provider.py

@@ -31,6 +31,7 @@ class OpenAICodexProvider(LLMProvider):
         model: str | None = None,
         max_tokens: int = 4096,
         temperature: float = 0.7,
+        reasoning_effort: str | None = None,
     ) -> LLMResponse:
         model = model or self.default_model
         system_prompt, input_items = _convert_messages(messages)

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "nanobot-ai"
-version = "0.1.4.post2"
+version = "0.1.4.post3"
 description = "A lightweight personal AI assistant framework"
 requires-python = ">=3.11"
 license = {text = "MIT"}