deepcode+nanobot

Author: Zongwei9888

nanobot/COMMUNICATION.md

@@ -2,4 +2,4 @@ We provide QR codes for joining the HKUDS discussion groups on **WeChat** and **
 
 You can join by scanning the QR codes below:
 
-<img src="https://github.com/HKUDS/.github/blob/main/profile/QR.png" alt="WeChat QR Code" width="400"/>
+<img src="https://github.com/HKUDS/.github/blob/main/profile/QR.png" alt="WeChat QR Code" width="400"/>

nanobot/LICENSE

@@ -18,4 +18,4 @@ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+SOFTWARE.

nanobot/README.md

@@ -12,7 +12,7 @@
   </p>
 </div>
 
-🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [Clawdbot](https://github.com/openclaw/openclaw) 
+🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [Clawdbot](https://github.com/openclaw/openclaw)
 
 ⚡️ Delivers core agent functionality in just **~4,000** lines of code — **99% smaller** than Clawdbot's 430k+ lines.
 

nanobot/bridge/src/index.ts

@@ -1,14 +1,14 @@
 #!/usr/bin/env node
 /**
  * nanobot WhatsApp Bridge
- * 
+ *
  * This bridge connects WhatsApp Web to nanobot's Python backend
  * via WebSocket. It handles authentication, message forwarding,
  * and reconnection logic.
- * 
+ *
  * Usage:
  *   npm run build && npm start
- *   
+ *
  * Or with custom settings:
  *   BRIDGE_PORT=3001 AUTH_DIR=~/.nanobot/whatsapp npm start
  */

nanobot/nanobot/agent/__init__.py

@@ -1,7 +1,7 @@
 """Agent core module."""
 
-from nanobot.agent.loop import AgentLoop
 from nanobot.agent.context import ContextBuilder
+from nanobot.agent.loop import AgentLoop
 from nanobot.agent.memory import MemoryStore
 from nanobot.agent.skills import SkillsLoader
 

nanobot/nanobot/agent/context.py

@@ -13,51 +13,51 @@
 class ContextBuilder:
     """
     Builds the context (system prompt + messages) for the agent.
-    
+
     Assembles bootstrap files, memory, skills, and conversation history
     into a coherent prompt for the LLM.
     """
-    
+
     BOOTSTRAP_FILES = ["AGENTS.md", "SOUL.md", "USER.md", "TOOLS.md", "IDENTITY.md"]
-    
+
     def __init__(self, workspace: Path):
         self.workspace = workspace
         self.memory = MemoryStore(workspace)
         self.skills = SkillsLoader(workspace)
-    
+
     def build_system_prompt(self, skill_names: list[str] | None = None) -> str:
         """
         Build the system prompt from bootstrap files, memory, and skills.
-        
+
         Args:
             skill_names: Optional list of skills to include.
-        
+
         Returns:
             Complete system prompt.
         """
         parts = []
-        
+
         # Core identity
         parts.append(self._get_identity())
-        
+
         # Bootstrap files
         bootstrap = self._load_bootstrap_files()
         if bootstrap:
             parts.append(bootstrap)
-        
+
         # Memory context
         memory = self.memory.get_memory_context()
         if memory:
             parts.append(f"# Memory\n\n{memory}")
-        
+
         # Skills - progressive loading
         # 1. Always-loaded skills: include full content
         always_skills = self.skills.get_always_skills()
         if always_skills:
             always_content = self.skills.load_skills_for_context(always_skills)
             if always_content:
                 parts.append(f"# Active Skills\n\n{always_content}")
-        
+
         # 2. Available skills: only show summary (agent uses read_file to load)
         skills_summary = self.skills.build_skills_summary()
         if skills_summary:
@@ -67,17 +67,18 @@ def build_system_prompt(self, skill_names: list[str] | None = None) -> str:
 Skills with available="false" need dependencies installed first - you can try installing them with apt/brew.
 
 {skills_summary}""")
-        
+
         return "\n\n---\n\n".join(parts)
-    
+
     def _get_identity(self) -> str:
         """Get the core identity section."""
         from datetime import datetime
+
         now = datetime.now().strftime("%Y-%m-%d %H:%M (%A)")
         workspace_path = str(self.workspace.expanduser().resolve())
         system = platform.system()
         runtime = f"{'macOS' if system == 'Darwin' else system} {platform.machine()}, Python {platform.python_version()}"
-        
+
         return f"""# nanobot 🐈
 
 You are nanobot, a helpful AI assistant. You have access to tools that allow you to:
@@ -105,19 +106,19 @@ def _get_identity(self) -> str:
 
 Always be helpful, accurate, and concise. When using tools, explain what you're doing.
 When remembering something, write to {workspace_path}/memory/MEMORY.md"""
-    
+
     def _load_bootstrap_files(self) -> str:
         """Load all bootstrap files from workspace."""
         parts = []
-        
+
         for filename in self.BOOTSTRAP_FILES:
             file_path = self.workspace / filename
             if file_path.exists():
                 content = file_path.read_text(encoding="utf-8")
                 parts.append(f"## {filename}\n\n{content}")
-        
+
         return "\n\n".join(parts) if parts else ""
-    
+
     def build_messages(
         self,
         history: list[dict[str, Any]],
@@ -162,7 +163,7 @@ def _build_user_content(self, text: str, media: list[str] | None) -> str | list[
         """Build user message content with optional base64-encoded images."""
         if not media:
             return text
-        
+
         images = []
         for path in media:
             p = Path(path)
@@ -171,38 +172,31 @@ def _build_user_content(self, text: str, media: list[str] | None) -> str | list[
                 continue
             b64 = base64.b64encode(p.read_bytes()).decode()
             images.append({"type": "image_url", "image_url": {"url": f"data:{mime};base64,{b64}"}})
-        
+
         if not images:
             return text
         return images + [{"type": "text", "text": text}]
-    
+
     def add_tool_result(
-        self,
-        messages: list[dict[str, Any]],
-        tool_call_id: str,
-        tool_name: str,
-        result: str
+        self, messages: list[dict[str, Any]], tool_call_id: str, tool_name: str, result: str
     ) -> list[dict[str, Any]]:
         """
         Add a tool result to the message list.
-        
+
         Args:
             messages: Current message list.
             tool_call_id: ID of the tool call.
             tool_name: Name of the tool.
             result: Tool execution result.
-        
+
         Returns:
             Updated message list.
         """
-        messages.append({
-            "role": "tool",
-            "tool_call_id": tool_call_id,
-            "name": tool_name,
-            "content": result
-        })
+        messages.append(
+            {"role": "tool", "tool_call_id": tool_call_id, "name": tool_name, "content": result}
+        )
         return messages
-    
+
     def add_assistant_message(
         self,
         messages: list[dict[str, Any]],
@@ -212,24 +206,24 @@ def add_assistant_message(
     ) -> list[dict[str, Any]]:
         """
         Add an assistant message to the message list.
-        
+
         Args:
             messages: Current message list.
             content: Message content.
             tool_calls: Optional tool calls.
             reasoning_content: Thinking output (Kimi, DeepSeek-R1, etc.).
-        
+
         Returns:
             Updated message list.
         """
         msg: dict[str, Any] = {"role": "assistant", "content": content or ""}
-        
+
         if tool_calls:
             msg["tool_calls"] = tool_calls
-        
+
         # Thinking models reject history without this
         if reasoning_content:
             msg["reasoning_content"] = reasoning_content
-        
+
         messages.append(msg)
         return messages