diff --git a/.gitignore b/.gitignore index d7b930d..374875a 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +.worktrees/ .assets .env *.pyc @@ -19,4 +20,4 @@ __pycache__/ poetry.lock .pytest_cache/ botpy.log -tests/ + diff --git a/README.md b/README.md index 33cdeee..03f042a 100644 --- a/README.md +++ b/README.md @@ -12,11 +12,11 @@

-🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [OpenClaw](https://github.com/openclaw/openclaw) +🐈 **nanobot** is an **ultra-lightweight** personal AI assistant inspired by [OpenClaw](https://github.com/openclaw/openclaw). -⚑️ Delivers core agent functionality in just **~4,000** lines of code β€” **99% smaller** than Clawdbot's 430k+ lines. +⚑️ Delivers core agent functionality with **99% fewer lines of code** than OpenClaw. -πŸ“ Real-time line count: **3,935 lines** (run `bash core_agent_lines.sh` to verify anytime) +πŸ“ Real-time line count: run `bash core_agent_lines.sh` to verify anytime. ## πŸ“’ News @@ -293,12 +293,18 @@ If you prefer to configure manually, add the following to `~/.nanobot/config.jso "discord": { "enabled": true, "token": "YOUR_BOT_TOKEN", - "allowFrom": ["YOUR_USER_ID"] + "allowFrom": ["YOUR_USER_ID"], + "groupPolicy": "mention" } } } ``` +> `groupPolicy` controls how the bot responds in group channels: +> - `"mention"` (default) β€” Only respond when @mentioned +> - `"open"` β€” Respond to all messages +> DMs always respond when the sender is in `allowFrom`. + **5. Invite the bot** - OAuth2 β†’ URL Generator - Scopes: `bot` @@ -414,6 +420,10 @@ nanobot channels login nanobot gateway ``` +> WhatsApp bridge updates are not applied automatically for existing installations. +> If you upgrade nanobot and need the latest WhatsApp bridge, run: +> `rm -rf ~/.nanobot/bridge && nanobot channels login` +
@@ -658,12 +668,14 @@ Config file: `~/.nanobot/config.json` > - **Zhipu Coding Plan**: If you're on Zhipu's coding plan, set `"apiBase": "https://open.bigmodel.cn/api/coding/paas/v4"` in your zhipu provider config. > - **MiniMax (Mainland China)**: If your API key is from MiniMax's mainland China platform (minimaxi.com), set `"apiBase": "https://api.minimaxi.com/v1"` in your minimax provider config. > - **VolcEngine Coding Plan**: If you're on VolcEngine's coding plan, set `"apiBase": "https://ark.cn-beijing.volces.com/api/coding/v3"` in your volcengine provider config. +> - **Alibaba Cloud Coding Plan**: If you're on the Alibaba Cloud Coding Plan (BaiLian), set `"apiBase": "https://coding.dashscope.aliyuncs.com/v1"` in your dashscope provider config. | Provider | Purpose | Get API Key | |----------|---------|-------------| | `custom` | Any OpenAI-compatible endpoint (direct, no LiteLLM) | β€” | | `openrouter` | LLM (recommended, access to all models) | [openrouter.ai](https://openrouter.ai) | | `anthropic` | LLM (Claude direct) | [console.anthropic.com](https://console.anthropic.com) | +| `azure_openai` | LLM (Azure OpenAI) | [portal.azure.com](https://portal.azure.com) | | `openai` | LLM (GPT direct) | [platform.openai.com](https://platform.openai.com) | | `deepseek` | LLM (DeepSeek direct) | [platform.deepseek.com](https://platform.deepseek.com) | | `groq` | LLM + **Voice transcription** (Whisper) | [console.groq.com](https://console.groq.com) | @@ -884,6 +896,33 @@ MCP tools are automatically discovered and registered on startup. The LLM can us | `channels.*.allowFrom` | `[]` (allow all) | Whitelist of user IDs. Empty = allow everyone; non-empty = only listed users can interact. | +## Multiple Instances + +Run multiple nanobot instances simultaneously, each with its own workspace and configuration. + +```bash +# Instance A - Telegram bot +nanobot gateway -w ~/.nanobot/botA -p 18791 + +# Instance B - Discord bot +nanobot gateway -w ~/.nanobot/botB -p 18792 + +# Instance C - Using custom config file +nanobot gateway -w ~/.nanobot/botC -c ~/.nanobot/botC/config.json -p 18793 +``` + +| Option | Short | Description | +|--------|-------|-------------| +| `--workspace` | `-w` | Workspace directory (default: `~/.nanobot/workspace`) | +| `--config` | `-c` | Config file path (default: `~/.nanobot/config.json`) | +| `--port` | `-p` | Gateway port (default: `18790`) | + +Each instance has its own: +- Workspace directory (MEMORY.md, HEARTBEAT.md, session files) +- Cron jobs storage (`workspace/cron/jobs.json`) +- Configuration (if using `--config`) + + ## CLI Reference | Command | Description | diff --git a/bridge/src/whatsapp.ts b/bridge/src/whatsapp.ts index 069d72b..b91bacc 100644 --- a/bridge/src/whatsapp.ts +++ b/bridge/src/whatsapp.ts @@ -9,11 +9,17 @@ import makeWASocket, { useMultiFileAuthState, fetchLatestBaileysVersion, makeCacheableSignalKeyStore, + downloadMediaMessage, + extractMessageContent as baileysExtractMessageContent, } from '@whiskeysockets/baileys'; import { Boom } from '@hapi/boom'; import qrcode from 'qrcode-terminal'; import pino from 'pino'; +import { writeFile, mkdir } from 'fs/promises'; +import { join } from 'path'; +import { homedir } from 'os'; +import { randomBytes } from 'crypto'; const VERSION = '0.1.0'; @@ -24,6 +30,7 @@ export interface InboundMessage { content: string; timestamp: number; isGroup: boolean; + media?: string[]; } export interface WhatsAppClientOptions { @@ -110,14 +117,33 @@ export class WhatsAppClient { if (type !== 'notify') return; for (const msg of messages) { - // Skip own messages if (msg.key.fromMe) continue; - - // Skip status updates if (msg.key.remoteJid === 'status@broadcast') continue; - const content = this.extractMessageContent(msg); - if (!content) continue; + const unwrapped = baileysExtractMessageContent(msg.message); + if (!unwrapped) continue; + + const content = this.getTextContent(unwrapped); + let fallbackContent: string | null = null; + const mediaPaths: string[] = []; + + if (unwrapped.imageMessage) { + fallbackContent = '[Image]'; + const path = await this.downloadMedia(msg, unwrapped.imageMessage.mimetype ?? undefined); + if (path) mediaPaths.push(path); + } else if (unwrapped.documentMessage) { + fallbackContent = '[Document]'; + const path = await this.downloadMedia(msg, unwrapped.documentMessage.mimetype ?? undefined, + unwrapped.documentMessage.fileName ?? undefined); + if (path) mediaPaths.push(path); + } else if (unwrapped.videoMessage) { + fallbackContent = '[Video]'; + const path = await this.downloadMedia(msg, unwrapped.videoMessage.mimetype ?? undefined); + if (path) mediaPaths.push(path); + } + + const finalContent = content || (mediaPaths.length === 0 ? fallbackContent : '') || ''; + if (!finalContent && mediaPaths.length === 0) continue; const isGroup = msg.key.remoteJid?.endsWith('@g.us') || false; @@ -125,18 +151,45 @@ export class WhatsAppClient { id: msg.key.id || '', sender: msg.key.remoteJid || '', pn: msg.key.remoteJidAlt || '', - content, + content: finalContent, timestamp: msg.messageTimestamp as number, isGroup, + ...(mediaPaths.length > 0 ? { media: mediaPaths } : {}), }); } }); } - private extractMessageContent(msg: any): string | null { - const message = msg.message; - if (!message) return null; + private async downloadMedia(msg: any, mimetype?: string, fileName?: string): Promise { + try { + const mediaDir = join(homedir(), '.nanobot', 'media'); + await mkdir(mediaDir, { recursive: true }); + const buffer = await downloadMediaMessage(msg, 'buffer', {}) as Buffer; + + let outFilename: string; + if (fileName) { + // Documents have a filename β€” use it with a unique prefix to avoid collisions + const prefix = `wa_${Date.now()}_${randomBytes(4).toString('hex')}_`; + outFilename = prefix + fileName; + } else { + const mime = mimetype || 'application/octet-stream'; + // Derive extension from mimetype subtype (e.g. "image/png" β†’ ".png", "application/pdf" β†’ ".pdf") + const ext = '.' + (mime.split('/').pop()?.split(';')[0] || 'bin'); + outFilename = `wa_${Date.now()}_${randomBytes(4).toString('hex')}${ext}`; + } + + const filepath = join(mediaDir, outFilename); + await writeFile(filepath, buffer); + + return filepath; + } catch (err) { + console.error('Failed to download media:', err); + return null; + } + } + + private getTextContent(message: any): string | null { // Text message if (message.conversation) { return message.conversation; @@ -147,19 +200,19 @@ export class WhatsAppClient { return message.extendedTextMessage.text; } - // Image with caption - if (message.imageMessage?.caption) { - return `[Image] ${message.imageMessage.caption}`; + // Image with optional caption + if (message.imageMessage) { + return message.imageMessage.caption || ''; } - // Video with caption - if (message.videoMessage?.caption) { - return `[Video] ${message.videoMessage.caption}`; + // Video with optional caption + if (message.videoMessage) { + return message.videoMessage.caption || ''; } - // Document with caption - if (message.documentMessage?.caption) { - return `[Document] ${message.documentMessage.caption}`; + // Document with optional caption + if (message.documentMessage) { + return message.documentMessage.caption || ''; } // Voice/Audio message diff --git a/nanobot/agent/context.py b/nanobot/agent/context.py index df4825f..27511fa 100644 --- a/nanobot/agent/context.py +++ b/nanobot/agent/context.py @@ -10,6 +10,7 @@ from typing import Any from nanobot.agent.memory import MemoryStore from nanobot.agent.skills import SkillsLoader +from nanobot.utils.helpers import detect_image_mime class ContextBuilder: @@ -136,10 +137,14 @@ Reply directly with text for conversations. Only use the 'message' tool to send images = [] for path in media: p = Path(path) - mime, _ = mimetypes.guess_type(path) - if not p.is_file() or not mime or not mime.startswith("image/"): + if not p.is_file(): continue - b64 = base64.b64encode(p.read_bytes()).decode() + raw = p.read_bytes() + # Detect real MIME type from magic bytes; fallback to filename guess + mime = detect_image_mime(raw) or mimetypes.guess_type(path)[0] + if not mime or not mime.startswith("image/"): + continue + b64 = base64.b64encode(raw).decode() images.append({"type": "image_url", "image_url": {"url": f"data:{mime};base64,{b64}"}}) if not images: diff --git a/nanobot/agent/loop.py b/nanobot/agent/loop.py index 65a62e5..ca9a06e 100644 --- a/nanobot/agent/loop.py +++ b/nanobot/agent/loop.py @@ -202,9 +202,9 @@ class AgentLoop: if response.has_tool_calls: if on_progress: - clean = self._strip_think(response.content) - if clean: - await on_progress(clean) + thought = self._strip_think(response.content) + if thought: + await on_progress(thought) await on_progress(self._tool_hint(response.tool_calls), tool_hint=True) tool_call_dicts = [ diff --git a/nanobot/agent/memory.py b/nanobot/agent/memory.py index 93c1825..21fe77d 100644 --- a/nanobot/agent/memory.py +++ b/nanobot/agent/memory.py @@ -128,6 +128,13 @@ class MemoryStore: # Some providers return arguments as a JSON string instead of dict if isinstance(args, str): args = json.loads(args) + # Some providers return arguments as a list (handle edge case) + if isinstance(args, list): + if args and isinstance(args[0], dict): + args = args[0] + else: + logger.warning("Memory consolidation: unexpected arguments as empty or non-dict list") + return False if not isinstance(args, dict): logger.warning("Memory consolidation: unexpected arguments type {}", type(args).__name__) return False diff --git a/nanobot/agent/tools/base.py b/nanobot/agent/tools/base.py index 8dd82c7..06f5bdd 100644 --- a/nanobot/agent/tools/base.py +++ b/nanobot/agent/tools/base.py @@ -52,8 +52,79 @@ class Tool(ABC): """ pass + def cast_params(self, params: dict[str, Any]) -> dict[str, Any]: + """Apply safe schema-driven casts before validation.""" + schema = self.parameters or {} + if schema.get("type", "object") != "object": + return params + + return self._cast_object(params, schema) + + def _cast_object(self, obj: Any, schema: dict[str, Any]) -> dict[str, Any]: + """Cast an object (dict) according to schema.""" + if not isinstance(obj, dict): + return obj + + props = schema.get("properties", {}) + result = {} + + for key, value in obj.items(): + if key in props: + result[key] = self._cast_value(value, props[key]) + else: + result[key] = value + + return result + + def _cast_value(self, val: Any, schema: dict[str, Any]) -> Any: + """Cast a single value according to schema.""" + target_type = schema.get("type") + + if target_type == "boolean" and isinstance(val, bool): + return val + if target_type == "integer" and isinstance(val, int) and not isinstance(val, bool): + return val + if target_type in self._TYPE_MAP and target_type not in ("boolean", "integer", "array", "object"): + expected = self._TYPE_MAP[target_type] + if isinstance(val, expected): + return val + + if target_type == "integer" and isinstance(val, str): + try: + return int(val) + except ValueError: + return val + + if target_type == "number" and isinstance(val, str): + try: + return float(val) + except ValueError: + return val + + if target_type == "string": + return val if val is None else str(val) + + if target_type == "boolean" and isinstance(val, str): + val_lower = val.lower() + if val_lower in ("true", "1", "yes"): + return True + if val_lower in ("false", "0", "no"): + return False + return val + + if target_type == "array" and isinstance(val, list): + item_schema = schema.get("items") + return [self._cast_value(item, item_schema) for item in val] if item_schema else val + + if target_type == "object" and isinstance(val, dict): + return self._cast_object(val, schema) + + return val + def validate_params(self, params: dict[str, Any]) -> list[str]: """Validate tool parameters against JSON schema. Returns error list (empty if valid).""" + if not isinstance(params, dict): + return [f"parameters must be an object, got {type(params).__name__}"] schema = self.parameters or {} if schema.get("type", "object") != "object": raise ValueError(f"Schema must be object type, got {schema.get('type')!r}") @@ -61,7 +132,13 @@ class Tool(ABC): def _validate(self, val: Any, schema: dict[str, Any], path: str) -> list[str]: t, label = schema.get("type"), path or "parameter" - if t in self._TYPE_MAP and not isinstance(val, self._TYPE_MAP[t]): + if t == "integer" and (not isinstance(val, int) or isinstance(val, bool)): + return [f"{label} should be integer"] + if t == "number" and ( + not isinstance(val, self._TYPE_MAP[t]) or isinstance(val, bool) + ): + return [f"{label} should be number"] + if t in self._TYPE_MAP and t not in ("integer", "number") and not isinstance(val, self._TYPE_MAP[t]): return [f"{label} should be {t}"] errors = [] diff --git a/nanobot/agent/tools/cron.py b/nanobot/agent/tools/cron.py index 13b1e12..f8e737b 100644 --- a/nanobot/agent/tools/cron.py +++ b/nanobot/agent/tools/cron.py @@ -122,7 +122,10 @@ class CronTool(Tool): elif at: from datetime import datetime - dt = datetime.fromisoformat(at) + try: + dt = datetime.fromisoformat(at) + except ValueError: + return f"Error: invalid ISO datetime format '{at}'. Expected format: YYYY-MM-DDTHH:MM:SS" at_ms = int(dt.timestamp() * 1000) schedule = CronSchedule(kind="at", at_ms=at_ms) delete_after = True diff --git a/nanobot/agent/tools/filesystem.py b/nanobot/agent/tools/filesystem.py index bbdd49c..7b0b867 100644 --- a/nanobot/agent/tools/filesystem.py +++ b/nanobot/agent/tools/filesystem.py @@ -26,6 +26,8 @@ def _resolve_path( class ReadFileTool(Tool): """Tool to read file contents.""" + _MAX_CHARS = 128_000 # ~128 KB β€” prevents OOM from reading huge files into LLM context + def __init__(self, workspace: Path | None = None, allowed_dir: Path | None = None): self._workspace = workspace self._allowed_dir = allowed_dir @@ -54,7 +56,16 @@ class ReadFileTool(Tool): if not file_path.is_file(): return f"Error: Not a file: {path}" + size = file_path.stat().st_size + if size > self._MAX_CHARS * 4: # rough upper bound (UTF-8 chars ≀ 4 bytes) + return ( + f"Error: File too large ({size:,} bytes). " + f"Use exec tool with head/tail/grep to read portions." + ) + content = file_path.read_text(encoding="utf-8") + if len(content) > self._MAX_CHARS: + return content[: self._MAX_CHARS] + f"\n\n... (truncated β€” file is {len(content):,} chars, limit {self._MAX_CHARS:,})" return content except PermissionError as e: return f"Error: {e}" diff --git a/nanobot/agent/tools/mcp.py b/nanobot/agent/tools/mcp.py index 37464e1..2cbffd0 100644 --- a/nanobot/agent/tools/mcp.py +++ b/nanobot/agent/tools/mcp.py @@ -58,17 +58,48 @@ async def connect_mcp_servers( ) -> None: """Connect to configured MCP servers and register their tools.""" from mcp import ClientSession, StdioServerParameters + from mcp.client.sse import sse_client from mcp.client.stdio import stdio_client + from mcp.client.streamable_http import streamable_http_client for name, cfg in mcp_servers.items(): try: - if cfg.command: + transport_type = cfg.type + if not transport_type: + if cfg.command: + transport_type = "stdio" + elif cfg.url: + # Convention: URLs ending with /sse use SSE transport; others use streamableHttp + transport_type = ( + "sse" if cfg.url.rstrip("/").endswith("/sse") else "streamableHttp" + ) + else: + logger.warning("MCP server '{}': no command or url configured, skipping", name) + continue + + if transport_type == "stdio": params = StdioServerParameters( command=cfg.command, args=cfg.args, env=cfg.env or None ) read, write = await stack.enter_async_context(stdio_client(params)) - elif cfg.url: - from mcp.client.streamable_http import streamable_http_client + elif transport_type == "sse": + def httpx_client_factory( + headers: dict[str, str] | None = None, + timeout: httpx.Timeout | None = None, + auth: httpx.Auth | None = None, + ) -> httpx.AsyncClient: + merged_headers = {**(cfg.headers or {}), **(headers or {})} + return httpx.AsyncClient( + headers=merged_headers or None, + follow_redirects=True, + timeout=timeout, + auth=auth, + ) + + read, write = await stack.enter_async_context( + sse_client(cfg.url, httpx_client_factory=httpx_client_factory) + ) + elif transport_type == "streamableHttp": # Always provide an explicit httpx client so MCP HTTP transport does not # inherit httpx's default 5s timeout and preempt the higher-level tool timeout. http_client = await stack.enter_async_context( @@ -82,7 +113,7 @@ async def connect_mcp_servers( streamable_http_client(cfg.url, http_client=http_client) ) else: - logger.warning("MCP server '{}': no command or url configured, skipping", name) + logger.warning("MCP server '{}': unknown transport type '{}'", name, transport_type) continue session = await stack.enter_async_context(ClientSession(read, write)) diff --git a/nanobot/agent/tools/registry.py b/nanobot/agent/tools/registry.py index 5d36e52..896491f 100644 --- a/nanobot/agent/tools/registry.py +++ b/nanobot/agent/tools/registry.py @@ -44,6 +44,10 @@ class ToolRegistry: return f"Error: Tool '{name}' not found. Available: {', '.join(self.tool_names)}" try: + # Attempt to cast parameters to match schema types + params = tool.cast_params(params) + + # Validate parameters errors = tool.validate_params(params) if errors: return f"Error: Invalid parameters for tool '{name}': " + "; ".join(errors) + _HINT diff --git a/nanobot/channels/discord.py b/nanobot/channels/discord.py index 57e5922..0187c62 100644 --- a/nanobot/channels/discord.py +++ b/nanobot/channels/discord.py @@ -13,34 +13,13 @@ from nanobot.bus.events import OutboundMessage from nanobot.bus.queue import MessageBus from nanobot.channels.base import BaseChannel from nanobot.config.schema import DiscordConfig +from nanobot.utils.helpers import split_message DISCORD_API_BASE = "https://discord.com/api/v10" MAX_ATTACHMENT_BYTES = 20 * 1024 * 1024 # 20MB MAX_MESSAGE_LEN = 2000 # Discord message character limit -def _split_message(content: str, max_len: int = MAX_MESSAGE_LEN) -> list[str]: - """Split content into chunks within max_len, preferring line breaks.""" - if not content: - return [] - if len(content) <= max_len: - return [content] - chunks: list[str] = [] - while content: - if len(content) <= max_len: - chunks.append(content) - break - cut = content[:max_len] - pos = cut.rfind('\n') - if pos <= 0: - pos = cut.rfind(' ') - if pos <= 0: - pos = max_len - chunks.append(content[:pos]) - content = content[pos:].lstrip() - return chunks - - class DiscordChannel(BaseChannel): """Discord channel using Gateway websocket.""" @@ -54,6 +33,7 @@ class DiscordChannel(BaseChannel): self._heartbeat_task: asyncio.Task | None = None self._typing_tasks: dict[str, asyncio.Task] = {} self._http: httpx.AsyncClient | None = None + self._bot_user_id: str | None = None async def start(self) -> None: """Start the Discord gateway connection.""" @@ -95,7 +75,7 @@ class DiscordChannel(BaseChannel): self._http = None async def send(self, msg: OutboundMessage) -> None: - """Send a message through Discord REST API.""" + """Send a message through Discord REST API, including file attachments.""" if not self._http: logger.warning("Discord HTTP client not initialized") return @@ -104,15 +84,31 @@ class DiscordChannel(BaseChannel): headers = {"Authorization": f"Bot {self.config.token}"} try: - chunks = _split_message(msg.content or "") + sent_media = False + failed_media: list[str] = [] + + # Send file attachments first + for media_path in msg.media or []: + if await self._send_file(url, headers, media_path, reply_to=msg.reply_to): + sent_media = True + else: + failed_media.append(Path(media_path).name) + + # Send text content + chunks = split_message(msg.content or "", MAX_MESSAGE_LEN) + if not chunks and failed_media and not sent_media: + chunks = split_message( + "\n".join(f"[attachment: {name} - send failed]" for name in failed_media), + MAX_MESSAGE_LEN, + ) if not chunks: return for i, chunk in enumerate(chunks): payload: dict[str, Any] = {"content": chunk} - # Only set reply reference on the first chunk - if i == 0 and msg.reply_to: + # Let the first successful attachment carry the reply if present. + if i == 0 and msg.reply_to and not sent_media: payload["message_reference"] = {"message_id": msg.reply_to} payload["allowed_mentions"] = {"replied_user": False} @@ -143,6 +139,54 @@ class DiscordChannel(BaseChannel): await asyncio.sleep(1) return False + async def _send_file( + self, + url: str, + headers: dict[str, str], + file_path: str, + reply_to: str | None = None, + ) -> bool: + """Send a file attachment via Discord REST API using multipart/form-data.""" + path = Path(file_path) + if not path.is_file(): + logger.warning("Discord file not found, skipping: {}", file_path) + return False + + if path.stat().st_size > MAX_ATTACHMENT_BYTES: + logger.warning("Discord file too large (>20MB), skipping: {}", path.name) + return False + + payload_json: dict[str, Any] = {} + if reply_to: + payload_json["message_reference"] = {"message_id": reply_to} + payload_json["allowed_mentions"] = {"replied_user": False} + + for attempt in range(3): + try: + with open(path, "rb") as f: + files = {"files[0]": (path.name, f, "application/octet-stream")} + data: dict[str, Any] = {} + if payload_json: + data["payload_json"] = json.dumps(payload_json) + response = await self._http.post( + url, headers=headers, files=files, data=data + ) + if response.status_code == 429: + resp_data = response.json() + retry_after = float(resp_data.get("retry_after", 1.0)) + logger.warning("Discord rate limited, retrying in {}s", retry_after) + await asyncio.sleep(retry_after) + continue + response.raise_for_status() + logger.info("Discord file sent: {}", path.name) + return True + except Exception as e: + if attempt == 2: + logger.error("Error sending Discord file {}: {}", path.name, e) + else: + await asyncio.sleep(1) + return False + async def _gateway_loop(self) -> None: """Main gateway loop: identify, heartbeat, dispatch events.""" if not self._ws: @@ -170,6 +214,10 @@ class DiscordChannel(BaseChannel): await self._identify() elif op == 0 and event_type == "READY": logger.info("Discord gateway READY") + # Capture bot user ID for mention detection + user_data = payload.get("user") or {} + self._bot_user_id = user_data.get("id") + logger.info("Discord bot connected as user {}", self._bot_user_id) elif op == 0 and event_type == "MESSAGE_CREATE": await self._handle_message_create(payload) elif op == 7: @@ -226,6 +274,7 @@ class DiscordChannel(BaseChannel): sender_id = str(author.get("id", "")) channel_id = str(payload.get("channel_id", "")) content = payload.get("content") or "" + guild_id = payload.get("guild_id") if not sender_id or not channel_id: return @@ -233,6 +282,11 @@ class DiscordChannel(BaseChannel): if not self.is_allowed(sender_id): return + # Check group channel policy (DMs always respond if is_allowed passes) + if guild_id is not None: + if not self._should_respond_in_group(payload, content): + return + content_parts = [content] if content else [] media_paths: list[str] = [] media_dir = Path.home() / ".nanobot" / "media" @@ -269,11 +323,32 @@ class DiscordChannel(BaseChannel): media=media_paths, metadata={ "message_id": str(payload.get("id", "")), - "guild_id": payload.get("guild_id"), + "guild_id": guild_id, "reply_to": reply_to, }, ) + def _should_respond_in_group(self, payload: dict[str, Any], content: str) -> bool: + """Check if bot should respond in a group channel based on policy.""" + if self.config.group_policy == "open": + return True + + if self.config.group_policy == "mention": + # Check if bot was mentioned in the message + if self._bot_user_id: + # Check mentions array + mentions = payload.get("mentions") or [] + for mention in mentions: + if str(mention.get("id")) == self._bot_user_id: + return True + # Also check content for mention format <@USER_ID> + if f"<@{self._bot_user_id}>" in content or f"<@!{self._bot_user_id}>" in content: + return True + logger.debug("Discord message in {} ignored (bot not mentioned)", payload.get("channel_id")) + return False + + return True + async def _start_typing(self, channel_id: str) -> None: """Start periodic typing indicator for a channel.""" await self._stop_typing(channel_id) diff --git a/nanobot/channels/feishu.py b/nanobot/channels/feishu.py index 0a0a5e4..2dcf710 100644 --- a/nanobot/channels/feishu.py +++ b/nanobot/channels/feishu.py @@ -16,26 +16,9 @@ from nanobot.bus.queue import MessageBus from nanobot.channels.base import BaseChannel from nanobot.config.schema import FeishuConfig -try: - import lark_oapi as lark - from lark_oapi.api.im.v1 import ( - CreateFileRequest, - CreateFileRequestBody, - CreateImageRequest, - CreateImageRequestBody, - CreateMessageReactionRequest, - CreateMessageReactionRequestBody, - CreateMessageRequest, - CreateMessageRequestBody, - Emoji, - GetMessageResourceRequest, - P2ImMessageReceiveV1, - ) - FEISHU_AVAILABLE = True -except ImportError: - FEISHU_AVAILABLE = False - lark = None - Emoji = None +import importlib.util + +FEISHU_AVAILABLE = importlib.util.find_spec("lark_oapi") is not None # Message type display mapping MSG_TYPE_MAP = { @@ -261,15 +244,22 @@ class FeishuChannel(BaseChannel): name = "feishu" - def __init__(self, config: FeishuConfig, bus: MessageBus): + def __init__(self, config: FeishuConfig, bus: MessageBus, groq_api_key: str = ""): super().__init__(config, bus) self.config: FeishuConfig = config + self.groq_api_key = groq_api_key self._client: Any = None self._ws_client: Any = None self._ws_thread: threading.Thread | None = None self._processed_message_ids: OrderedDict[str, None] = OrderedDict() # Ordered dedup cache self._loop: asyncio.AbstractEventLoop | None = None + @staticmethod + def _register_optional_event(builder: Any, method_name: str, handler: Any) -> Any: + """Register an event handler only when the SDK supports it.""" + method = getattr(builder, method_name, None) + return method(handler) if callable(method) else builder + async def start(self) -> None: """Start the Feishu bot with WebSocket long connection.""" if not FEISHU_AVAILABLE: @@ -280,6 +270,7 @@ class FeishuChannel(BaseChannel): logger.error("Feishu app_id and app_secret not configured") return + import lark_oapi as lark self._running = True self._loop = asyncio.get_running_loop() @@ -289,14 +280,24 @@ class FeishuChannel(BaseChannel): .app_secret(self.config.app_secret) \ .log_level(lark.LogLevel.INFO) \ .build() - - # Create event handler (only register message receive, ignore other events) - event_handler = lark.EventDispatcherHandler.builder( + builder = lark.EventDispatcherHandler.builder( self.config.encrypt_key or "", self.config.verification_token or "", ).register_p2_im_message_receive_v1( self._on_message_sync - ).build() + ) + builder = self._register_optional_event( + builder, "register_p2_im_message_reaction_created_v1", self._on_reaction_created + ) + builder = self._register_optional_event( + builder, "register_p2_im_message_message_read_v1", self._on_message_read + ) + builder = self._register_optional_event( + builder, + "register_p2_im_chat_access_event_bot_p2p_chat_entered_v1", + self._on_bot_p2p_chat_entered, + ) + event_handler = builder.build() # Create WebSocket client for long connection self._ws_client = lark.ws.Client( @@ -306,16 +307,28 @@ class FeishuChannel(BaseChannel): log_level=lark.LogLevel.INFO ) - # Start WebSocket client in a separate thread with reconnect loop + # Start WebSocket client in a separate thread with reconnect loop. + # A dedicated event loop is created for this thread so that lark_oapi's + # module-level `loop = asyncio.get_event_loop()` picks up an idle loop + # instead of the already-running main asyncio loop, which would cause + # "This event loop is already running" errors. def run_ws(): - while self._running: - try: - self._ws_client.start() - except Exception as e: - logger.warning("Feishu WebSocket error: {}", e) - if self._running: - import time - time.sleep(5) + import time + import lark_oapi.ws.client as _lark_ws_client + ws_loop = asyncio.new_event_loop() + asyncio.set_event_loop(ws_loop) + # Patch the module-level loop used by lark's ws Client.start() + _lark_ws_client.loop = ws_loop + try: + while self._running: + try: + self._ws_client.start() + except Exception as e: + logger.warning("Feishu WebSocket error: {}", e) + if self._running: + time.sleep(5) + finally: + ws_loop.close() self._ws_thread = threading.Thread(target=run_ws, daemon=True) self._ws_thread.start() @@ -340,6 +353,7 @@ class FeishuChannel(BaseChannel): def _add_reaction_sync(self, message_id: str, emoji_type: str) -> None: """Sync helper for adding reaction (runs in thread pool).""" + from lark_oapi.api.im.v1 import CreateMessageReactionRequest, CreateMessageReactionRequestBody, Emoji try: request = CreateMessageReactionRequest.builder() \ .message_id(message_id) \ @@ -364,7 +378,7 @@ class FeishuChannel(BaseChannel): Common emoji types: THUMBSUP, OK, EYES, DONE, OnIt, HEART """ - if not self._client or not Emoji: + if not self._client: return loop = asyncio.get_running_loop() @@ -413,6 +427,34 @@ class FeishuChannel(BaseChannel): elements.extend(self._split_headings(remaining)) return elements or [{"tag": "markdown", "content": content}] + @staticmethod + def _split_elements_by_table_limit(elements: list[dict], max_tables: int = 1) -> list[list[dict]]: + """Split card elements into groups with at most *max_tables* table elements each. + + Feishu cards have a hard limit of one table per card (API error 11310). + When the rendered content contains multiple markdown tables each table is + placed in a separate card message so every table reaches the user. + """ + if not elements: + return [[]] + groups: list[list[dict]] = [] + current: list[dict] = [] + table_count = 0 + for el in elements: + if el.get("tag") == "table": + if table_count >= max_tables: + if current: + groups.append(current) + current = [] + table_count = 0 + current.append(el) + table_count += 1 + else: + current.append(el) + if current: + groups.append(current) + return groups or [[]] + def _split_headings(self, content: str) -> list[dict]: """Split content by headings, converting headings to div elements.""" protected = content @@ -447,8 +489,124 @@ class FeishuChannel(BaseChannel): return elements or [{"tag": "markdown", "content": content}] + # ── Smart format detection ────────────────────────────────────────── + # Patterns that indicate "complex" markdown needing card rendering + _COMPLEX_MD_RE = re.compile( + r"```" # fenced code block + r"|^\|.+\|.*\n\s*\|[-:\s|]+\|" # markdown table (header + separator) + r"|^#{1,6}\s+" # headings + , re.MULTILINE, + ) + + # Simple markdown patterns (bold, italic, strikethrough) + _SIMPLE_MD_RE = re.compile( + r"\*\*.+?\*\*" # **bold** + r"|__.+?__" # __bold__ + r"|(? str: + """Determine the optimal Feishu message format for *content*. + + Returns one of: + - ``"text"`` – plain text, short and no markdown + - ``"post"`` – rich text (links only, moderate length) + - ``"interactive"`` – card with full markdown rendering + """ + stripped = content.strip() + + # Complex markdown (code blocks, tables, headings) β†’ always card + if cls._COMPLEX_MD_RE.search(stripped): + return "interactive" + + # Long content β†’ card (better readability with card layout) + if len(stripped) > cls._POST_MAX_LEN: + return "interactive" + + # Has bold/italic/strikethrough β†’ card (post format can't render these) + if cls._SIMPLE_MD_RE.search(stripped): + return "interactive" + + # Has list items β†’ card (post format can't render list bullets well) + if cls._LIST_RE.search(stripped) or cls._OLIST_RE.search(stripped): + return "interactive" + + # Has links β†’ post format (supports tags) + if cls._MD_LINK_RE.search(stripped): + return "post" + + # Short plain text β†’ text format + if len(stripped) <= cls._TEXT_MAX_LEN: + return "text" + + # Medium plain text without any formatting β†’ post format + return "post" + + @classmethod + def _markdown_to_post(cls, content: str) -> str: + """Convert markdown content to Feishu post message JSON. + + Handles links ``[text](url)`` as ``a`` tags; everything else as ``text`` tags. + Each line becomes a paragraph (row) in the post body. + """ + lines = content.strip().split("\n") + paragraphs: list[list[dict]] = [] + + for line in lines: + elements: list[dict] = [] + last_end = 0 + + for m in cls._MD_LINK_RE.finditer(line): + # Text before this link + before = line[last_end:m.start()] + if before: + elements.append({"tag": "text", "text": before}) + elements.append({ + "tag": "a", + "text": m.group(1), + "href": m.group(2), + }) + last_end = m.end() + + # Remaining text after last link + remaining = line[last_end:] + if remaining: + elements.append({"tag": "text", "text": remaining}) + + # Empty line β†’ empty paragraph for spacing + if not elements: + elements.append({"tag": "text", "text": ""}) + + paragraphs.append(elements) + + post_body = { + "zh_cn": { + "content": paragraphs, + } + } + return json.dumps(post_body, ensure_ascii=False) + _IMAGE_EXTS = {".png", ".jpg", ".jpeg", ".gif", ".bmp", ".webp", ".ico", ".tiff", ".tif"} _AUDIO_EXTS = {".opus"} + _VIDEO_EXTS = {".mp4", ".mov", ".avi"} _FILE_TYPE_MAP = { ".opus": "opus", ".mp4": "mp4", ".pdf": "pdf", ".doc": "doc", ".docx": "doc", ".xls": "xls", ".xlsx": "xls", ".ppt": "ppt", ".pptx": "ppt", @@ -456,6 +614,7 @@ class FeishuChannel(BaseChannel): def _upload_image_sync(self, file_path: str) -> str | None: """Upload an image to Feishu and return the image_key.""" + from lark_oapi.api.im.v1 import CreateImageRequest, CreateImageRequestBody try: with open(file_path, "rb") as f: request = CreateImageRequest.builder() \ @@ -479,6 +638,7 @@ class FeishuChannel(BaseChannel): def _upload_file_sync(self, file_path: str) -> str | None: """Upload a file to Feishu and return the file_key.""" + from lark_oapi.api.im.v1 import CreateFileRequest, CreateFileRequestBody ext = os.path.splitext(file_path)[1].lower() file_type = self._FILE_TYPE_MAP.get(ext, "stream") file_name = os.path.basename(file_path) @@ -506,6 +666,7 @@ class FeishuChannel(BaseChannel): def _download_image_sync(self, message_id: str, image_key: str) -> tuple[bytes | None, str | None]: """Download an image from Feishu message by message_id and image_key.""" + from lark_oapi.api.im.v1 import GetMessageResourceRequest try: request = GetMessageResourceRequest.builder() \ .message_id(message_id) \ @@ -530,6 +691,13 @@ class FeishuChannel(BaseChannel): self, message_id: str, file_key: str, resource_type: str = "file" ) -> tuple[bytes | None, str | None]: """Download a file/audio/media from a Feishu message by message_id and file_key.""" + from lark_oapi.api.im.v1 import GetMessageResourceRequest + + # Feishu API only accepts 'image' or 'file' as type parameter + # Convert 'audio' to 'file' for API compatibility + if resource_type == "audio": + resource_type = "file" + try: request = ( GetMessageResourceRequest.builder() @@ -598,6 +766,7 @@ class FeishuChannel(BaseChannel): def _send_message_sync(self, receive_id_type: str, receive_id: str, msg_type: str, content: str) -> bool: """Send a single message (text/image/file/interactive) synchronously.""" + from lark_oapi.api.im.v1 import CreateMessageRequest, CreateMessageRequestBody try: request = CreateMessageRequest.builder() \ .receive_id_type(receive_id_type) \ @@ -646,23 +815,50 @@ class FeishuChannel(BaseChannel): else: key = await loop.run_in_executor(None, self._upload_file_sync, file_path) if key: - media_type = "audio" if ext in self._AUDIO_EXTS else "file" + # Use msg_type "media" for audio/video so users can play inline; + # "file" for everything else (documents, archives, etc.) + if ext in self._AUDIO_EXTS or ext in self._VIDEO_EXTS: + media_type = "media" + else: + media_type = "file" await loop.run_in_executor( None, self._send_message_sync, receive_id_type, msg.chat_id, media_type, json.dumps({"file_key": key}, ensure_ascii=False), ) if msg.content and msg.content.strip(): - card = {"config": {"wide_screen_mode": True}, "elements": self._build_card_elements(msg.content)} - await loop.run_in_executor( - None, self._send_message_sync, - receive_id_type, msg.chat_id, "interactive", json.dumps(card, ensure_ascii=False), - ) + fmt = self._detect_msg_format(msg.content) + + if fmt == "text": + # Short plain text – send as simple text message + text_body = json.dumps({"text": msg.content.strip()}, ensure_ascii=False) + await loop.run_in_executor( + None, self._send_message_sync, + receive_id_type, msg.chat_id, "text", text_body, + ) + + elif fmt == "post": + # Medium content with links – send as rich-text post + post_body = self._markdown_to_post(msg.content) + await loop.run_in_executor( + None, self._send_message_sync, + receive_id_type, msg.chat_id, "post", post_body, + ) + + else: + # Complex / long content – send as interactive card + elements = self._build_card_elements(msg.content) + for chunk in self._split_elements_by_table_limit(elements): + card = {"config": {"wide_screen_mode": True}, "elements": chunk} + await loop.run_in_executor( + None, self._send_message_sync, + receive_id_type, msg.chat_id, "interactive", json.dumps(card, ensure_ascii=False), + ) except Exception as e: logger.error("Error sending Feishu message: {}", e) - def _on_message_sync(self, data: "P2ImMessageReceiveV1") -> None: + def _on_message_sync(self, data: Any) -> None: """ Sync handler for incoming messages (called from WebSocket thread). Schedules async handling in the main event loop. @@ -670,7 +866,7 @@ class FeishuChannel(BaseChannel): if self._loop and self._loop.is_running(): asyncio.run_coroutine_threadsafe(self._on_message(data), self._loop) - async def _on_message(self, data: "P2ImMessageReceiveV1") -> None: + async def _on_message(self, data: Any) -> None: """Handle incoming message from Feishu.""" try: event = data.event @@ -730,6 +926,18 @@ class FeishuChannel(BaseChannel): file_path, content_text = await self._download_and_save_media(msg_type, content_json, message_id) if file_path: media_paths.append(file_path) + + # Transcribe audio using Groq Whisper + if msg_type == "audio" and file_path and self.groq_api_key: + try: + from nanobot.providers.transcription import GroqTranscriptionProvider + transcriber = GroqTranscriptionProvider(api_key=self.groq_api_key) + transcription = await transcriber.transcribe(file_path) + if transcription: + content_text = f"[transcription: {transcription}]" + except Exception as e: + logger.warning("Failed to transcribe audio: {}", e) + content_parts.append(content_text) elif msg_type in ("share_chat", "share_user", "interactive", "share_calendar_event", "system", "merge_forward"): @@ -762,3 +970,16 @@ class FeishuChannel(BaseChannel): except Exception as e: logger.error("Error processing Feishu message: {}", e) + + def _on_reaction_created(self, data: Any) -> None: + """Ignore reaction events so they do not generate SDK noise.""" + pass + + def _on_message_read(self, data: Any) -> None: + """Ignore read events so they do not generate SDK noise.""" + pass + + def _on_bot_p2p_chat_entered(self, data: Any) -> None: + """Ignore p2p-enter events when a user opens a bot chat.""" + logger.debug("Bot entered p2p chat (user opened chat window)") + pass diff --git a/nanobot/channels/manager.py b/nanobot/channels/manager.py index 7d7d110..51539dd 100644 --- a/nanobot/channels/manager.py +++ b/nanobot/channels/manager.py @@ -74,7 +74,8 @@ class ChannelManager: try: from nanobot.channels.feishu import FeishuChannel self.channels["feishu"] = FeishuChannel( - self.config.channels.feishu, self.bus + self.config.channels.feishu, self.bus, + groq_api_key=self.config.providers.groq.api_key, ) logger.info("Feishu channel enabled") except ImportError as e: diff --git a/nanobot/channels/qq.py b/nanobot/channels/qq.py index 7b171bc..6c58049 100644 --- a/nanobot/channels/qq.py +++ b/nanobot/channels/qq.py @@ -56,6 +56,7 @@ class QQChannel(BaseChannel): self.config: QQConfig = config self._client: "botpy.Client | None" = None self._processed_ids: deque = deque(maxlen=1000) + self._msg_seq: int = 1 # ζΆˆζ―εΊεˆ—ε·οΌŒιΏε…θ’« QQ API εŽ»ι‡ async def start(self) -> None: """Start the QQ bot.""" @@ -102,11 +103,13 @@ class QQChannel(BaseChannel): return try: msg_id = msg.metadata.get("message_id") + self._msg_seq += 1 # ι€’ε’žεΊεˆ—ε· await self._client.api.post_c2c_message( openid=msg.chat_id, msg_type=0, content=msg.content, msg_id=msg_id, + msg_seq=self._msg_seq, # ζ·»εŠ εΊεˆ—ε·ιΏε…εŽ»ι‡ ) except Exception as e: logger.error("Error sending QQ message: {}", e) @@ -133,3 +136,4 @@ class QQChannel(BaseChannel): ) except Exception: logger.exception("Error handling QQ message") + diff --git a/nanobot/channels/telegram.py b/nanobot/channels/telegram.py index 12b5440..2c92c2d 100644 --- a/nanobot/channels/telegram.py +++ b/nanobot/channels/telegram.py @@ -4,6 +4,8 @@ from __future__ import annotations import asyncio import re +import time +import unicodedata from loguru import logger from telegram import BotCommand, ReplyParameters, Update @@ -14,6 +16,50 @@ from nanobot.bus.events import OutboundMessage from nanobot.bus.queue import MessageBus from nanobot.channels.base import BaseChannel from nanobot.config.schema import TelegramConfig +from nanobot.utils.helpers import split_message + +TELEGRAM_MAX_MESSAGE_LEN = 4000 # Telegram message character limit + + +def _strip_md(s: str) -> str: + """Strip markdown inline formatting from text.""" + s = re.sub(r'\*\*(.+?)\*\*', r'\1', s) + s = re.sub(r'__(.+?)__', r'\1', s) + s = re.sub(r'~~(.+?)~~', r'\1', s) + s = re.sub(r'`([^`]+)`', r'\1', s) + return s.strip() + + +def _render_table_box(table_lines: list[str]) -> str: + """Convert markdown pipe-table to compact aligned text for 
 display."""
+
+    def dw(s: str) -> int:
+        return sum(2 if unicodedata.east_asian_width(c) in ('W', 'F') else 1 for c in s)
+
+    rows: list[list[str]] = []
+    has_sep = False
+    for line in table_lines:
+        cells = [_strip_md(c) for c in line.strip().strip('|').split('|')]
+        if all(re.match(r'^:?-+:?$', c) for c in cells if c):
+            has_sep = True
+            continue
+        rows.append(cells)
+    if not rows or not has_sep:
+        return '\n'.join(table_lines)
+
+    ncols = max(len(r) for r in rows)
+    for r in rows:
+        r.extend([''] * (ncols - len(r)))
+    widths = [max(dw(r[c]) for r in rows) for c in range(ncols)]
+
+    def dr(cells: list[str]) -> str:
+        return '  '.join(f'{c}{" " * (w - dw(c))}' for c, w in zip(cells, widths))
+
+    out = [dr(rows[0])]
+    out.append('  '.join('─' * w for w in widths))
+    for row in rows[1:]:
+        out.append(dr(row))
+    return '\n'.join(out)
 
 
 def _markdown_to_telegram_html(text: str) -> str:
@@ -31,6 +77,27 @@ def _markdown_to_telegram_html(text: str) -> str:
 
     text = re.sub(r'```[\w]*\n?([\s\S]*?)```', save_code_block, text)
 
+    # 1.5. Convert markdown tables to box-drawing (reuse code_block placeholders)
+    lines = text.split('\n')
+    rebuilt: list[str] = []
+    li = 0
+    while li < len(lines):
+        if re.match(r'^\s*\|.+\|', lines[li]):
+            tbl: list[str] = []
+            while li < len(lines) and re.match(r'^\s*\|.+\|', lines[li]):
+                tbl.append(lines[li])
+                li += 1
+            box = _render_table_box(tbl)
+            if box != '\n'.join(tbl):
+                code_blocks.append(box)
+                rebuilt.append(f"\x00CB{len(code_blocks) - 1}\x00")
+            else:
+                rebuilt.extend(tbl)
+        else:
+            rebuilt.append(lines[li])
+            li += 1
+    text = '\n'.join(rebuilt)
+
     # 2. Extract and protect inline code
     inline_codes: list[str] = []
     def save_inline_code(m: re.Match) -> str:
@@ -79,26 +146,6 @@ def _markdown_to_telegram_html(text: str) -> str:
     return text
 
 
-def _split_message(content: str, max_len: int = 4000) -> list[str]:
-    """Split content into chunks within max_len, preferring line breaks."""
-    if len(content) <= max_len:
-        return [content]
-    chunks: list[str] = []
-    while content:
-        if len(content) <= max_len:
-            chunks.append(content)
-            break
-        cut = content[:max_len]
-        pos = cut.rfind('\n')
-        if pos == -1:
-            pos = cut.rfind(' ')
-        if pos == -1:
-            pos = max_len
-        chunks.append(content[:pos])
-        content = content[pos:].lstrip()
-    return chunks
-
-
 class TelegramChannel(BaseChannel):
     """
     Telegram channel using long polling.
@@ -154,6 +201,7 @@ class TelegramChannel(BaseChannel):
         # Add command handlers
         self._app.add_handler(CommandHandler("start", self._on_start))
         self._app.add_handler(CommandHandler("new", self._forward_command))
+        self._app.add_handler(CommandHandler("stop", self._forward_command))
         self._app.add_handler(CommandHandler("help", self._on_help))
 
         # Add message handler for text, photos, voice, documents
@@ -229,7 +277,9 @@ class TelegramChannel(BaseChannel):
             logger.warning("Telegram bot not running")
             return
 
-        self._stop_typing(msg.chat_id)
+        # Only stop typing indicator for final responses
+        if not msg.metadata.get("_progress", False):
+            self._stop_typing(msg.chat_id)
 
         try:
             chat_id = int(msg.chat_id)
@@ -273,25 +323,49 @@ class TelegramChannel(BaseChannel):
 
         # Send text content
         if msg.content and msg.content != "[empty message]":
-            for chunk in _split_message(msg.content):
-                try:
-                    html = _markdown_to_telegram_html(chunk)
-                    await self._app.bot.send_message(
-                        chat_id=chat_id,
-                        text=html,
-                        parse_mode="HTML",
-                        reply_parameters=reply_params
-                    )
-                except Exception as e:
-                    logger.warning("HTML parse failed, falling back to plain text: {}", e)
-                    try:
-                        await self._app.bot.send_message(
-                            chat_id=chat_id,
-                            text=chunk,
-                            reply_parameters=reply_params
-                        )
-                    except Exception as e2:
-                        logger.error("Error sending Telegram message: {}", e2)
+            is_progress = msg.metadata.get("_progress", False)
+
+            for chunk in split_message(msg.content, TELEGRAM_MAX_MESSAGE_LEN):
+                # Final response: simulate streaming via draft, then persist
+                if not is_progress:
+                    await self._send_with_streaming(chat_id, chunk, reply_params)
+                else:
+                    await self._send_text(chat_id, chunk, reply_params)
+
+    async def _send_text(self, chat_id: int, text: str, reply_params=None) -> None:
+        """Send a plain text message with HTML fallback."""
+        try:
+            html = _markdown_to_telegram_html(text)
+            await self._app.bot.send_message(
+                chat_id=chat_id, text=html, parse_mode="HTML",
+                reply_parameters=reply_params,
+            )
+        except Exception as e:
+            logger.warning("HTML parse failed, falling back to plain text: {}", e)
+            try:
+                await self._app.bot.send_message(
+                    chat_id=chat_id, text=text, reply_parameters=reply_params,
+                )
+            except Exception as e2:
+                logger.error("Error sending Telegram message: {}", e2)
+
+    async def _send_with_streaming(self, chat_id: int, text: str, reply_params=None) -> None:
+        """Simulate streaming via send_message_draft, then persist with send_message."""
+        draft_id = int(time.time() * 1000) % (2**31)
+        try:
+            step = max(len(text) // 8, 40)
+            for i in range(step, len(text), step):
+                await self._app.bot.send_message_draft(
+                    chat_id=chat_id, draft_id=draft_id, text=text[:i],
+                )
+                await asyncio.sleep(0.04)
+            await self._app.bot.send_message_draft(
+                chat_id=chat_id, draft_id=draft_id, text=text,
+            )
+            await asyncio.sleep(0.15)
+        except Exception:
+            pass
+        await self._send_text(chat_id, text, reply_params)
 
     async def _on_start(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
         """Handle /start command."""
diff --git a/nanobot/channels/whatsapp.py b/nanobot/channels/whatsapp.py
index 0d1ec7e..1307716 100644
--- a/nanobot/channels/whatsapp.py
+++ b/nanobot/channels/whatsapp.py
@@ -2,6 +2,7 @@
 
 import asyncio
 import json
+import mimetypes
 from collections import OrderedDict
 
 from loguru import logger
@@ -128,10 +129,22 @@ class WhatsAppChannel(BaseChannel):
                 logger.info("Voice message received from {}, but direct download from bridge is not yet supported.", sender_id)
                 content = "[Voice Message: Transcription not available for WhatsApp yet]"
 
+            # Extract media paths (images/documents/videos downloaded by the bridge)
+            media_paths = data.get("media") or []
+
+            # Build content tags matching Telegram's pattern: [image: /path] or [file: /path]
+            if media_paths:
+                for p in media_paths:
+                    mime, _ = mimetypes.guess_type(p)
+                    media_type = "image" if mime and mime.startswith("image/") else "file"
+                    media_tag = f"[{media_type}: {p}]"
+                    content = f"{content}\n{media_tag}" if content else media_tag
+
             await self._handle_message(
                 sender_id=sender_id,
                 chat_id=sender,  # Use full LID for replies
                 content=content,
+                media=media_paths,
                 metadata={
                     "message_id": message_id,
                     "timestamp": data.get("timestamp"),
diff --git a/nanobot/cli/commands.py b/nanobot/cli/commands.py
index b75a2bc..ca5d8d7 100644
--- a/nanobot/cli/commands.py
+++ b/nanobot/cli/commands.py
@@ -7,6 +7,18 @@ import signal
 import sys
 from pathlib import Path
 
+# Force UTF-8 encoding for Windows console
+if sys.platform == "win32":
+    import locale
+    if sys.stdout.encoding != "utf-8":
+        os.environ["PYTHONIOENCODING"] = "utf-8"
+        # Re-open stdout/stderr with UTF-8 encoding
+        try:
+            sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+            sys.stderr.reconfigure(encoding="utf-8", errors="replace")
+        except Exception:
+            pass
+
 import typer
 from prompt_toolkit import PromptSession
 from prompt_toolkit.formatted_text import HTML
@@ -200,9 +212,8 @@ def onboard():
 
 def _make_provider(config: Config):
     """Create the appropriate LLM provider from config."""
-    from nanobot.providers.custom_provider import CustomProvider
-    from nanobot.providers.litellm_provider import LiteLLMProvider
     from nanobot.providers.openai_codex_provider import OpenAICodexProvider
+    from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
 
     model = config.agents.defaults.model
     provider_name = config.get_provider_name(model)
@@ -213,6 +224,7 @@ def _make_provider(config: Config):
         return OpenAICodexProvider(default_model=model)
 
     # Custom: direct OpenAI-compatible endpoint, bypasses LiteLLM
+    from nanobot.providers.custom_provider import CustomProvider
     if provider_name == "custom":
         return CustomProvider(
             api_key=p.api_key if p else "no-key",
@@ -220,6 +232,21 @@ def _make_provider(config: Config):
             default_model=model,
         )
 
+    # Azure OpenAI: direct Azure OpenAI endpoint with deployment name
+    if provider_name == "azure_openai":
+        if not p or not p.api_key or not p.api_base:
+            console.print("[red]Error: Azure OpenAI requires api_key and api_base.[/red]")
+            console.print("Set them in ~/.nanobot/config.json under providers.azure_openai section")
+            console.print("Use the model field to specify the deployment name.")
+            raise typer.Exit(1)
+        
+        return AzureOpenAIProvider(
+            api_key=p.api_key,
+            api_base=p.api_base,
+            default_model=model,
+        )
+
+    from nanobot.providers.litellm_provider import LiteLLMProvider
     from nanobot.providers.registry import find_by_name
     spec = find_by_name(provider_name)
     if not model.startswith("bedrock/") and not (p and p.api_key) and not (spec and spec.is_oauth):
@@ -244,13 +271,15 @@ def _make_provider(config: Config):
 @app.command()
 def gateway(
     port: int = typer.Option(18790, "--port", "-p", help="Gateway port"),
+    workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
+    config: str | None = typer.Option(None, "--config", "-c", help="Config file path"),
     verbose: bool = typer.Option(False, "--verbose", "-v", help="Verbose output"),
 ):
     """Start the nanobot gateway."""
     from nanobot.agent.loop import AgentLoop
     from nanobot.bus.queue import MessageBus
     from nanobot.channels.manager import ChannelManager
-    from nanobot.config.loader import get_data_dir, load_config
+    from nanobot.config.loader import load_config
     from nanobot.cron.service import CronService
     from nanobot.cron.types import CronJob
     from nanobot.heartbeat.service import HeartbeatService
@@ -260,16 +289,20 @@ def gateway(
         import logging
         logging.basicConfig(level=logging.DEBUG)
 
-    console.print(f"{__logo__} Starting nanobot gateway on port {port}...")
+    config_path = Path(config) if config else None
+    config = load_config(config_path)
+    if workspace:
+        config.agents.defaults.workspace = workspace
 
-    config = load_config()
+    console.print(f"{__logo__} Starting nanobot gateway on port {port}...")
     sync_workspace_templates(config.workspace_path)
     bus = MessageBus()
     provider = _make_provider(config)
     session_manager = SessionManager(config.workspace_path)
 
     # Create cron service first (callback set after agent creation)
-    cron_store_path = get_data_dir() / "cron" / "jobs.json"
+    # Use workspace path for per-instance cron store
+    cron_store_path = config.workspace_path / "cron" / "jobs.json"
     cron = CronService(cron_store_path)
 
     # Create agent with cron service
@@ -511,12 +544,21 @@ def agent(
         else:
             cli_channel, cli_chat_id = "cli", session_id
 
-        def _exit_on_sigint(signum, frame):
+        def _handle_signal(signum, frame):
+            sig_name = signal.Signals(signum).name
             _restore_terminal()
-            console.print("\nGoodbye!")
-            os._exit(0)
+            console.print(f"\nReceived {sig_name}, goodbye!")
+            sys.exit(0)
 
-        signal.signal(signal.SIGINT, _exit_on_sigint)
+        signal.signal(signal.SIGINT, _handle_signal)
+        signal.signal(signal.SIGTERM, _handle_signal)
+        # SIGHUP is not available on Windows
+        if hasattr(signal, 'SIGHUP'):
+            signal.signal(signal.SIGHUP, _handle_signal)
+        # Ignore SIGPIPE to prevent silent process termination when writing to closed pipes
+        # SIGPIPE is not available on Windows
+        if hasattr(signal, 'SIGPIPE'):
+            signal.signal(signal.SIGPIPE, signal.SIG_IGN)
 
         async def run_interactive():
             bus_task = asyncio.create_task(agent_loop.run())
diff --git a/nanobot/config/schema.py b/nanobot/config/schema.py
index 61a7bd2..803cb61 100644
--- a/nanobot/config/schema.py
+++ b/nanobot/config/schema.py
@@ -29,7 +29,9 @@ class TelegramConfig(Base):
     enabled: bool = False
     token: str = ""  # Bot token from @BotFather
     allow_from: list[str] = Field(default_factory=list)  # Allowed user IDs or usernames
-    proxy: str | None = None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
+    proxy: str | None = (
+        None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
+    )
     reply_to_message: bool = False  # If true, bot replies quote the original message
 
 
@@ -42,7 +44,9 @@ class FeishuConfig(Base):
     encrypt_key: str = ""  # Encrypt Key for event subscription (optional)
     verification_token: str = ""  # Verification Token for event subscription (optional)
     allow_from: list[str] = Field(default_factory=list)  # Allowed user open_ids
-    react_emoji: str = "THUMBSUP"  # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
+    react_emoji: str = (
+        "THUMBSUP"  # Emoji type for message reactions (e.g. THUMBSUP, OK, DONE, SMILE)
+    )
 
 
 class DingTalkConfig(Base):
@@ -62,6 +66,7 @@ class DiscordConfig(Base):
     allow_from: list[str] = Field(default_factory=list)  # Allowed user IDs
     gateway_url: str = "wss://gateway.discord.gg/?v=10&encoding=json"
     intents: int = 37377  # GUILDS + GUILD_MESSAGES + DIRECT_MESSAGES + MESSAGE_CONTENT
+    group_policy: Literal["mention", "open"] = "mention"
 
 
 class MatrixConfig(Base):
@@ -72,9 +77,13 @@ class MatrixConfig(Base):
     access_token: str = ""
     user_id: str = ""  # @bot:matrix.org
     device_id: str = ""
-    e2ee_enabled: bool = True # Enable Matrix E2EE support (encryption + encrypted room handling).
-    sync_stop_grace_seconds: int = 2 # Max seconds to wait for sync_forever to stop gracefully before cancellation fallback.
-    max_media_bytes: int = 20 * 1024 * 1024 # Max attachment size accepted for Matrix media handling (inbound + outbound).
+    e2ee_enabled: bool = True  # Enable Matrix E2EE support (encryption + encrypted room handling).
+    sync_stop_grace_seconds: int = (
+        2  # Max seconds to wait for sync_forever to stop gracefully before cancellation fallback.
+    )
+    max_media_bytes: int = (
+        20 * 1024 * 1024
+    )  # Max attachment size accepted for Matrix media handling (inbound + outbound).
     allow_from: list[str] = Field(default_factory=list)
     group_policy: Literal["open", "mention", "allowlist"] = "open"
     group_allow_from: list[str] = Field(default_factory=list)
@@ -105,7 +114,9 @@ class EmailConfig(Base):
     from_address: str = ""
 
     # Behavior
-    auto_reply_enabled: bool = True  # If false, inbound email is read but no automatic reply is sent
+    auto_reply_enabled: bool = (
+        True  # If false, inbound email is read but no automatic reply is sent
+    )
     poll_interval_seconds: int = 30
     mark_seen: bool = True
     max_body_chars: int = 12000
@@ -183,27 +194,17 @@ class QQConfig(Base):
     enabled: bool = False
     app_id: str = ""  # ζœΊε™¨δΊΊ ID (AppID) from q.qq.com
     secret: str = ""  # ζœΊε™¨δΊΊε―†ι’₯ (AppSecret) from q.qq.com
-    allow_from: list[str] = Field(default_factory=list)  # Allowed user openids (empty = public access)
+    allow_from: list[str] = Field(
+        default_factory=list
+    )  # Allowed user openids (empty = public access)
+
+
 
-class MatrixConfig(Base):
-    """Matrix (Element) channel configuration."""
-    enabled: bool = False
-    homeserver: str = "https://matrix.org"
-    access_token: str = ""
-    user_id: str = ""                       # e.g. @bot:matrix.org
-    device_id: str = ""
-    e2ee_enabled: bool = True               # end-to-end encryption support
-    sync_stop_grace_seconds: int = 2        # graceful sync_forever shutdown timeout
-    max_media_bytes: int = 20 * 1024 * 1024 # inbound + outbound attachment limit
-    allow_from: list[str] = Field(default_factory=list)
-    group_policy: Literal["open", "mention", "allowlist"] = "open"
-    group_allow_from: list[str] = Field(default_factory=list)
-    allow_room_mentions: bool = False
 
 class ChannelsConfig(Base):
     """Configuration for chat channels."""
 
-    send_progress: bool = True    # stream agent's text progress to the channel
+    send_progress: bool = True  # stream agent's text progress to the channel
     send_tool_hints: bool = False  # stream tool-call hints (e.g. read_file("…"))
     whatsapp: WhatsAppConfig = Field(default_factory=WhatsAppConfig)
     telegram: TelegramConfig = Field(default_factory=TelegramConfig)
@@ -222,7 +223,9 @@ class AgentDefaults(Base):
 
     workspace: str = "~/.nanobot/workspace"
     model: str = "anthropic/claude-opus-4-5"
-    provider: str = "auto"  # Provider name (e.g. "anthropic", "openrouter") or "auto" for auto-detection
+    provider: str = (
+        "auto"  # Provider name (e.g. "anthropic", "openrouter") or "auto" for auto-detection
+    )
     max_tokens: int = 8192
     temperature: float = 0.1
     max_tool_iterations: int = 40
@@ -248,6 +251,7 @@ class ProvidersConfig(Base):
     """Configuration for LLM providers."""
 
     custom: ProviderConfig = Field(default_factory=ProviderConfig)  # Any OpenAI-compatible endpoint
+    azure_openai: ProviderConfig = Field(default_factory=ProviderConfig)  # Azure OpenAI (model = deployment name)
     anthropic: ProviderConfig = Field(default_factory=ProviderConfig)
     openai: ProviderConfig = Field(default_factory=ProviderConfig)
     openrouter: ProviderConfig = Field(default_factory=ProviderConfig)
@@ -260,8 +264,8 @@ class ProvidersConfig(Base):
     moonshot: ProviderConfig = Field(default_factory=ProviderConfig)
     minimax: ProviderConfig = Field(default_factory=ProviderConfig)
     aihubmix: ProviderConfig = Field(default_factory=ProviderConfig)  # AiHubMix API gateway
-    siliconflow: ProviderConfig = Field(default_factory=ProviderConfig)  # SiliconFlow (η‘…εŸΊζ΅εŠ¨) API gateway
-    volcengine: ProviderConfig = Field(default_factory=ProviderConfig)  # VolcEngine (η«ε±±εΌ•ζ“Ž) API gateway
+    siliconflow: ProviderConfig = Field(default_factory=ProviderConfig)  # SiliconFlow (η‘…εŸΊζ΅εŠ¨)
+    volcengine: ProviderConfig = Field(default_factory=ProviderConfig)  # VolcEngine (η«ε±±εΌ•ζ“Ž)
     openai_codex: ProviderConfig = Field(default_factory=ProviderConfig)  # OpenAI Codex (OAuth)
     github_copilot: ProviderConfig = Field(default_factory=ProviderConfig)  # Github Copilot (OAuth)
 
@@ -291,7 +295,9 @@ class WebSearchConfig(Base):
 class WebToolsConfig(Base):
     """Web tools configuration."""
 
-    proxy: str | None = None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
+    proxy: str | None = (
+        None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"
+    )
     search: WebSearchConfig = Field(default_factory=WebSearchConfig)
 
 
@@ -305,12 +311,13 @@ class ExecToolConfig(Base):
 class MCPServerConfig(Base):
     """MCP server connection configuration (stdio or HTTP)."""
 
+    type: Literal["stdio", "sse", "streamableHttp"] | None = None  # auto-detected if omitted
     command: str = ""  # Stdio: command to run (e.g. "npx")
     args: list[str] = Field(default_factory=list)  # Stdio: command arguments
     env: dict[str, str] = Field(default_factory=dict)  # Stdio: extra env vars
-    url: str = ""  # HTTP: streamable HTTP endpoint URL
-    headers: dict[str, str] = Field(default_factory=dict)  # HTTP: Custom HTTP Headers
-    tool_timeout: int = 30  # Seconds before a tool call is cancelled
+    url: str = ""  # HTTP/SSE: endpoint URL
+    headers: dict[str, str] = Field(default_factory=dict)  # HTTP/SSE: custom headers
+    tool_timeout: int = 30  # seconds before a tool call is cancelled
 
 
 class ToolsConfig(Base):
@@ -336,7 +343,9 @@ class Config(BaseSettings):
         """Get expanded workspace path."""
         return Path(self.agents.defaults.workspace).expanduser()
 
-    def _match_provider(self, model: str | None = None) -> tuple["ProviderConfig | None", str | None]:
+    def _match_provider(
+        self, model: str | None = None
+    ) -> tuple["ProviderConfig | None", str | None]:
         """Match provider config and its registry name. Returns (config, spec_name)."""
         from nanobot.providers.registry import PROVIDERS
 
diff --git a/nanobot/providers/__init__.py b/nanobot/providers/__init__.py
index b2bb2b9..5bd06f9 100644
--- a/nanobot/providers/__init__.py
+++ b/nanobot/providers/__init__.py
@@ -3,5 +3,6 @@
 from nanobot.providers.base import LLMProvider, LLMResponse
 from nanobot.providers.litellm_provider import LiteLLMProvider
 from nanobot.providers.openai_codex_provider import OpenAICodexProvider
+from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
 
-__all__ = ["LLMProvider", "LLMResponse", "LiteLLMProvider", "OpenAICodexProvider"]
+__all__ = ["LLMProvider", "LLMResponse", "LiteLLMProvider", "OpenAICodexProvider", "AzureOpenAIProvider"]
diff --git a/nanobot/providers/azure_openai_provider.py b/nanobot/providers/azure_openai_provider.py
new file mode 100644
index 0000000..bd79b00
--- /dev/null
+++ b/nanobot/providers/azure_openai_provider.py
@@ -0,0 +1,210 @@
+"""Azure OpenAI provider implementation with API version 2024-10-21."""
+
+from __future__ import annotations
+
+import uuid
+from typing import Any
+from urllib.parse import urljoin
+
+import httpx
+import json_repair
+
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
+
+_AZURE_MSG_KEYS = frozenset({"role", "content", "tool_calls", "tool_call_id", "name"})
+
+
+class AzureOpenAIProvider(LLMProvider):
+    """
+    Azure OpenAI provider with API version 2024-10-21 compliance.
+    
+    Features:
+    - Hardcoded API version 2024-10-21
+    - Uses model field as Azure deployment name in URL path
+    - Uses api-key header instead of Authorization Bearer
+    - Uses max_completion_tokens instead of max_tokens
+    - Direct HTTP calls, bypasses LiteLLM
+    """
+
+    def __init__(
+        self,
+        api_key: str = "",
+        api_base: str = "",
+        default_model: str = "gpt-5.2-chat",
+    ):
+        super().__init__(api_key, api_base)
+        self.default_model = default_model
+        self.api_version = "2024-10-21"
+        
+        # Validate required parameters
+        if not api_key:
+            raise ValueError("Azure OpenAI api_key is required")
+        if not api_base:
+            raise ValueError("Azure OpenAI api_base is required")
+        
+        # Ensure api_base ends with /
+        if not api_base.endswith('/'):
+            api_base += '/'
+        self.api_base = api_base
+
+    def _build_chat_url(self, deployment_name: str) -> str:
+        """Build the Azure OpenAI chat completions URL."""
+        # Azure OpenAI URL format:
+        # https://{resource}.openai.azure.com/openai/deployments/{deployment}/chat/completions?api-version={version}
+        base_url = self.api_base
+        if not base_url.endswith('/'):
+            base_url += '/'
+        
+        url = urljoin(
+            base_url, 
+            f"openai/deployments/{deployment_name}/chat/completions"
+        )
+        return f"{url}?api-version={self.api_version}"
+
+    def _build_headers(self) -> dict[str, str]:
+        """Build headers for Azure OpenAI API with api-key header."""
+        return {
+            "Content-Type": "application/json",
+            "api-key": self.api_key,  # Azure OpenAI uses api-key header, not Authorization
+            "x-session-affinity": uuid.uuid4().hex,  # For cache locality
+        }
+
+    @staticmethod
+    def _supports_temperature(
+        deployment_name: str,
+        reasoning_effort: str | None = None,
+    ) -> bool:
+        """Return True when temperature is likely supported for this deployment."""
+        if reasoning_effort:
+            return False
+        name = deployment_name.lower()
+        return not any(token in name for token in ("gpt-5", "o1", "o3", "o4"))
+
+    def _prepare_request_payload(
+        self,
+        deployment_name: str,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        max_tokens: int = 4096,
+        temperature: float = 0.7,
+        reasoning_effort: str | None = None,
+    ) -> dict[str, Any]:
+        """Prepare the request payload with Azure OpenAI 2024-10-21 compliance."""
+        payload: dict[str, Any] = {
+            "messages": self._sanitize_request_messages(
+                self._sanitize_empty_content(messages),
+                _AZURE_MSG_KEYS,
+            ),
+            "max_completion_tokens": max(1, max_tokens),  # Azure API 2024-10-21 uses max_completion_tokens
+        }
+
+        if self._supports_temperature(deployment_name, reasoning_effort):
+            payload["temperature"] = temperature
+
+        if reasoning_effort:
+            payload["reasoning_effort"] = reasoning_effort
+
+        if tools:
+            payload["tools"] = tools
+            payload["tool_choice"] = "auto"
+
+        return payload
+
+    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,
+        reasoning_effort: str | None = None,
+    ) -> LLMResponse:
+        """
+        Send a chat completion request to Azure OpenAI.
+
+        Args:
+            messages: List of message dicts with 'role' and 'content'.
+            tools: Optional list of tool definitions in OpenAI format.
+            model: Model identifier (used as deployment name).
+            max_tokens: Maximum tokens in response (mapped to max_completion_tokens).
+            temperature: Sampling temperature.
+            reasoning_effort: Optional reasoning effort parameter.
+
+        Returns:
+            LLMResponse with content and/or tool calls.
+        """
+        deployment_name = model or self.default_model
+        url = self._build_chat_url(deployment_name)
+        headers = self._build_headers()
+        payload = self._prepare_request_payload(
+            deployment_name, messages, tools, max_tokens, temperature, reasoning_effort
+        )
+
+        try:
+            async with httpx.AsyncClient(timeout=60.0, verify=True) as client:
+                response = await client.post(url, headers=headers, json=payload)
+                if response.status_code != 200:
+                    return LLMResponse(
+                        content=f"Azure OpenAI API Error {response.status_code}: {response.text}",
+                        finish_reason="error",
+                    )
+                
+                response_data = response.json()
+                return self._parse_response(response_data)
+
+        except Exception as e:
+            return LLMResponse(
+                content=f"Error calling Azure OpenAI: {repr(e)}",
+                finish_reason="error",
+            )
+
+    def _parse_response(self, response: dict[str, Any]) -> LLMResponse:
+        """Parse Azure OpenAI response into our standard format."""
+        try:
+            choice = response["choices"][0]
+            message = choice["message"]
+
+            tool_calls = []
+            if message.get("tool_calls"):
+                for tc in message["tool_calls"]:
+                    # Parse arguments from JSON string if needed
+                    args = tc["function"]["arguments"]
+                    if isinstance(args, str):
+                        args = json_repair.loads(args)
+
+                    tool_calls.append(
+                        ToolCallRequest(
+                            id=tc["id"],
+                            name=tc["function"]["name"],
+                            arguments=args,
+                        )
+                    )
+
+            usage = {}
+            if response.get("usage"):
+                usage_data = response["usage"]
+                usage = {
+                    "prompt_tokens": usage_data.get("prompt_tokens", 0),
+                    "completion_tokens": usage_data.get("completion_tokens", 0),
+                    "total_tokens": usage_data.get("total_tokens", 0),
+                }
+
+            reasoning_content = message.get("reasoning_content") or None
+
+            return LLMResponse(
+                content=message.get("content"),
+                tool_calls=tool_calls,
+                finish_reason=choice.get("finish_reason", "stop"),
+                usage=usage,
+                reasoning_content=reasoning_content,
+            )
+
+        except (KeyError, IndexError) as e:
+            return LLMResponse(
+                content=f"Error parsing Azure OpenAI response: {str(e)}",
+                finish_reason="error",
+            )
+
+    def get_default_model(self) -> str:
+        """Get the default model (also used as default deployment name)."""
+        return self.default_model
\ No newline at end of file
diff --git a/nanobot/providers/base.py b/nanobot/providers/base.py
index 55bd805..0f73544 100644
--- a/nanobot/providers/base.py
+++ b/nanobot/providers/base.py
@@ -87,6 +87,20 @@ class LLMProvider(ABC):
             result.append(msg)
         return result
 
+    @staticmethod
+    def _sanitize_request_messages(
+        messages: list[dict[str, Any]],
+        allowed_keys: frozenset[str],
+    ) -> list[dict[str, Any]]:
+        """Keep only provider-safe message keys and normalize assistant content."""
+        sanitized = []
+        for msg in messages:
+            clean = {k: v for k, v in msg.items() if k in allowed_keys}
+            if clean.get("role") == "assistant" and "content" not in clean:
+                clean["content"] = None
+            sanitized.append(clean)
+        return sanitized
+
     @abstractmethod
     async def chat(
         self,
diff --git a/nanobot/providers/custom_provider.py b/nanobot/providers/custom_provider.py
index 56e6270..66df734 100644
--- a/nanobot/providers/custom_provider.py
+++ b/nanobot/providers/custom_provider.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import uuid
 from typing import Any
 
 import json_repair
@@ -15,7 +16,12 @@ class CustomProvider(LLMProvider):
     def __init__(self, api_key: str = "no-key", api_base: str = "http://localhost:8000/v1", default_model: str = "default"):
         super().__init__(api_key, api_base)
         self.default_model = default_model
-        self._client = AsyncOpenAI(api_key=api_key, base_url=api_base)
+        # Keep affinity stable for this provider instance to improve backend cache locality.
+        self._client = AsyncOpenAI(
+            api_key=api_key,
+            base_url=api_base,
+            default_headers={"x-session-affinity": uuid.uuid4().hex},
+        )
 
     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,
diff --git a/nanobot/providers/litellm_provider.py b/nanobot/providers/litellm_provider.py
index d8d8ace..cb67635 100644
--- a/nanobot/providers/litellm_provider.py
+++ b/nanobot/providers/litellm_provider.py
@@ -1,5 +1,6 @@
 """LiteLLM provider implementation for multi-provider support."""
 
+import hashlib
 import os
 import secrets
 import string
@@ -8,6 +9,7 @@ from typing import Any
 import json_repair
 import litellm
 from litellm import acompletion
+from loguru import logger
 
 from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
 from nanobot.providers.registry import find_by_model, find_gateway
@@ -165,17 +167,43 @@ class LiteLLMProvider(LLMProvider):
             return _ANTHROPIC_EXTRA_KEYS
         return frozenset()
 
+    @staticmethod
+    def _normalize_tool_call_id(tool_call_id: Any) -> Any:
+        """Normalize tool_call_id to a provider-safe 9-char alphanumeric form."""
+        if not isinstance(tool_call_id, str):
+            return tool_call_id
+        if len(tool_call_id) == 9 and tool_call_id.isalnum():
+            return tool_call_id
+        return hashlib.sha1(tool_call_id.encode()).hexdigest()[:9]
+
     @staticmethod
     def _sanitize_messages(messages: list[dict[str, Any]], extra_keys: frozenset[str] = frozenset()) -> list[dict[str, Any]]:
         """Strip non-standard keys and ensure assistant messages have a content key."""
         allowed = _ALLOWED_MSG_KEYS | extra_keys
-        sanitized = []
-        for msg in messages:
-            clean = {k: v for k, v in msg.items() if k in allowed}
-            # Strict providers require "content" even when assistant only has tool_calls
-            if clean.get("role") == "assistant" and "content" not in clean:
-                clean["content"] = None
-            sanitized.append(clean)
+        sanitized = LLMProvider._sanitize_request_messages(messages, allowed)
+        id_map: dict[str, str] = {}
+
+        def map_id(value: Any) -> Any:
+            if not isinstance(value, str):
+                return value
+            return id_map.setdefault(value, LiteLLMProvider._normalize_tool_call_id(value))
+
+        for clean in sanitized:
+            # Keep assistant tool_calls[].id and tool tool_call_id in sync after
+            # shortening, otherwise strict providers reject the broken linkage.
+            if isinstance(clean.get("tool_calls"), list):
+                normalized_tool_calls = []
+                for tc in clean["tool_calls"]:
+                    if not isinstance(tc, dict):
+                        normalized_tool_calls.append(tc)
+                        continue
+                    tc_clean = dict(tc)
+                    tc_clean["id"] = map_id(tc_clean.get("id"))
+                    normalized_tool_calls.append(tc_clean)
+                clean["tool_calls"] = normalized_tool_calls
+
+            if "tool_call_id" in clean and clean["tool_call_id"]:
+                clean["tool_call_id"] = map_id(clean["tool_call_id"])
         return sanitized
 
     async def chat(
@@ -255,20 +283,37 @@ class LiteLLMProvider(LLMProvider):
         """Parse LiteLLM response into our standard format."""
         choice = response.choices[0]
         message = choice.message
+        content = message.content
+        finish_reason = choice.finish_reason
+
+        # Some providers (e.g. GitHub Copilot) split content and tool_calls
+        # across multiple choices. Merge them so tool_calls are not lost.
+        raw_tool_calls = []
+        for ch in response.choices:
+            msg = ch.message
+            if hasattr(msg, "tool_calls") and msg.tool_calls:
+                raw_tool_calls.extend(msg.tool_calls)
+                if ch.finish_reason in ("tool_calls", "stop"):
+                    finish_reason = ch.finish_reason
+            if not content and msg.content:
+                content = msg.content
+
+        if len(response.choices) > 1:
+            logger.debug("LiteLLM response has {} choices, merged {} tool_calls",
+                         len(response.choices), len(raw_tool_calls))
 
         tool_calls = []
-        if hasattr(message, "tool_calls") and message.tool_calls:
-            for tc in message.tool_calls:
-                # Parse arguments from JSON string if needed
-                args = tc.function.arguments
-                if isinstance(args, str):
-                    args = json_repair.loads(args)
+        for tc in raw_tool_calls:
+            # Parse arguments from JSON string if needed
+            args = tc.function.arguments
+            if isinstance(args, str):
+                args = json_repair.loads(args)
 
-                tool_calls.append(ToolCallRequest(
-                    id=_short_tool_id(),
-                    name=tc.function.name,
-                    arguments=args,
-                ))
+            tool_calls.append(ToolCallRequest(
+                id=_short_tool_id(),
+                name=tc.function.name,
+                arguments=args,
+            ))
 
         usage = {}
         if hasattr(response, "usage") and response.usage:
@@ -280,11 +325,11 @@ 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,
+            content=content,
             tool_calls=tool_calls,
-            finish_reason=choice.finish_reason or "stop",
+            finish_reason=finish_reason or "stop",
             usage=usage,
             reasoning_content=reasoning_content,
             thinking_blocks=thinking_blocks,
diff --git a/nanobot/providers/openai_codex_provider.py b/nanobot/providers/openai_codex_provider.py
index b6afa65..d04e210 100644
--- a/nanobot/providers/openai_codex_provider.py
+++ b/nanobot/providers/openai_codex_provider.py
@@ -52,6 +52,9 @@ class OpenAICodexProvider(LLMProvider):
             "parallel_tool_calls": True,
         }
 
+        if reasoning_effort:
+            body["reasoning"] = {"effort": reasoning_effort}
+
         if tools:
             body["tools"] = _convert_tools(tools)
 
diff --git a/nanobot/providers/registry.py b/nanobot/providers/registry.py
index df915b7..3ba1a0e 100644
--- a/nanobot/providers/registry.py
+++ b/nanobot/providers/registry.py
@@ -26,33 +26,33 @@ class ProviderSpec:
     """
 
     # identity
-    name: str                       # config field name, e.g. "dashscope"
-    keywords: tuple[str, ...]       # model-name keywords for matching (lowercase)
-    env_key: str                    # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
-    display_name: str = ""          # shown in `nanobot status`
+    name: str  # config field name, e.g. "dashscope"
+    keywords: tuple[str, ...]  # model-name keywords for matching (lowercase)
+    env_key: str  # LiteLLM env var, e.g. "DASHSCOPE_API_KEY"
+    display_name: str = ""  # shown in `nanobot status`
 
     # model prefixing
-    litellm_prefix: str = ""                 # "dashscope" β†’ model becomes "dashscope/{model}"
-    skip_prefixes: tuple[str, ...] = ()      # don't prefix if model already starts with these
+    litellm_prefix: str = ""  # "dashscope" β†’ model becomes "dashscope/{model}"
+    skip_prefixes: tuple[str, ...] = ()  # don't prefix if model already starts with these
 
     # extra env vars, e.g. (("ZHIPUAI_API_KEY", "{api_key}"),)
     env_extras: tuple[tuple[str, str], ...] = ()
 
     # gateway / local detection
-    is_gateway: bool = False                 # routes any model (OpenRouter, AiHubMix)
-    is_local: bool = False                   # local deployment (vLLM, Ollama)
-    detect_by_key_prefix: str = ""           # match api_key prefix, e.g. "sk-or-"
-    detect_by_base_keyword: str = ""         # match substring in api_base URL
-    default_api_base: str = ""               # fallback base URL
+    is_gateway: bool = False  # routes any model (OpenRouter, AiHubMix)
+    is_local: bool = False  # local deployment (vLLM, Ollama)
+    detect_by_key_prefix: str = ""  # match api_key prefix, e.g. "sk-or-"
+    detect_by_base_keyword: str = ""  # match substring in api_base URL
+    default_api_base: str = ""  # fallback base URL
 
     # gateway behavior
-    strip_model_prefix: bool = False         # strip "provider/" before re-prefixing
+    strip_model_prefix: bool = False  # strip "provider/" before re-prefixing
 
     # per-model param overrides, e.g. (("kimi-k2.5", {"temperature": 1.0}),)
     model_overrides: tuple[tuple[str, dict[str, Any]], ...] = ()
 
     # OAuth-based providers (e.g., OpenAI Codex) don't use API keys
-    is_oauth: bool = False                   # if True, uses OAuth flow instead of API key
+    is_oauth: bool = False  # if True, uses OAuth flow instead of API key
 
     # Direct providers bypass LiteLLM entirely (e.g., CustomProvider)
     is_direct: bool = False
@@ -70,7 +70,6 @@ class ProviderSpec:
 # ---------------------------------------------------------------------------
 
 PROVIDERS: tuple[ProviderSpec, ...] = (
-
     # === Custom (direct OpenAI-compatible endpoint, bypasses LiteLLM) ======
     ProviderSpec(
         name="custom",
@@ -81,16 +80,24 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         is_direct=True,
     ),
 
+    # === Azure OpenAI (direct API calls with API version 2024-10-21) =====
+    ProviderSpec(
+        name="azure_openai",
+        keywords=("azure", "azure-openai"),
+        env_key="",
+        display_name="Azure OpenAI",
+        litellm_prefix="",
+        is_direct=True,
+    ),
     # === Gateways (detected by api_key / api_base, not model name) =========
     # Gateways can route any model, so they win in fallback.
-
     # OpenRouter: global gateway, keys start with "sk-or-"
     ProviderSpec(
         name="openrouter",
         keywords=("openrouter",),
         env_key="OPENROUTER_API_KEY",
         display_name="OpenRouter",
-        litellm_prefix="openrouter",        # claude-3 β†’ openrouter/claude-3
+        litellm_prefix="openrouter",  # claude-3 β†’ openrouter/claude-3
         skip_prefixes=(),
         env_extras=(),
         is_gateway=True,
@@ -102,16 +109,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         model_overrides=(),
         supports_prompt_caching=True,
     ),
-
     # AiHubMix: global gateway, OpenAI-compatible interface.
     # strip_model_prefix=True: it doesn't understand "anthropic/claude-3",
     # so we strip to bare "claude-3" then re-prefix as "openai/claude-3".
     ProviderSpec(
         name="aihubmix",
         keywords=("aihubmix",),
-        env_key="OPENAI_API_KEY",           # OpenAI-compatible
+        env_key="OPENAI_API_KEY",  # OpenAI-compatible
         display_name="AiHubMix",
-        litellm_prefix="openai",            # β†’ openai/{model}
+        litellm_prefix="openai",  # β†’ openai/{model}
         skip_prefixes=(),
         env_extras=(),
         is_gateway=True,
@@ -119,10 +125,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         detect_by_key_prefix="",
         detect_by_base_keyword="aihubmix",
         default_api_base="https://aihubmix.com/v1",
-        strip_model_prefix=True,            # anthropic/claude-3 β†’ claude-3 β†’ openai/claude-3
+        strip_model_prefix=True,  # anthropic/claude-3 β†’ claude-3 β†’ openai/claude-3
         model_overrides=(),
     ),
-
     # SiliconFlow (η‘…εŸΊζ΅εŠ¨): OpenAI-compatible gateway, model names keep org prefix
     ProviderSpec(
         name="siliconflow",
@@ -140,7 +145,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # VolcEngine (η«ε±±εΌ•ζ“Ž): OpenAI-compatible gateway
     ProviderSpec(
         name="volcengine",
@@ -158,9 +162,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # === Standard providers (matched by model-name keywords) ===============
-
     # Anthropic: LiteLLM recognizes "claude-*" natively, no prefix needed.
     ProviderSpec(
         name="anthropic",
@@ -179,7 +181,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         model_overrides=(),
         supports_prompt_caching=True,
     ),
-
     # OpenAI: LiteLLM recognizes "gpt-*" natively, no prefix needed.
     ProviderSpec(
         name="openai",
@@ -197,14 +198,13 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # OpenAI Codex: uses OAuth, not API key.
     ProviderSpec(
         name="openai_codex",
         keywords=("openai-codex",),
-        env_key="",                         # OAuth-based, no API key
+        env_key="",  # OAuth-based, no API key
         display_name="OpenAI Codex",
-        litellm_prefix="",                  # Not routed through LiteLLM
+        litellm_prefix="",  # Not routed through LiteLLM
         skip_prefixes=(),
         env_extras=(),
         is_gateway=False,
@@ -214,16 +214,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         default_api_base="https://chatgpt.com/backend-api",
         strip_model_prefix=False,
         model_overrides=(),
-        is_oauth=True,                      # OAuth-based authentication
+        is_oauth=True,  # OAuth-based authentication
     ),
-
     # Github Copilot: uses OAuth, not API key.
     ProviderSpec(
         name="github_copilot",
         keywords=("github_copilot", "copilot"),
-        env_key="",                         # OAuth-based, no API key
+        env_key="",  # OAuth-based, no API key
         display_name="Github Copilot",
-        litellm_prefix="github_copilot",   # github_copilot/model β†’ github_copilot/model
+        litellm_prefix="github_copilot",  # github_copilot/model β†’ github_copilot/model
         skip_prefixes=("github_copilot/",),
         env_extras=(),
         is_gateway=False,
@@ -233,17 +232,16 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         default_api_base="",
         strip_model_prefix=False,
         model_overrides=(),
-        is_oauth=True,                      # OAuth-based authentication
+        is_oauth=True,  # OAuth-based authentication
     ),
-
     # DeepSeek: needs "deepseek/" prefix for LiteLLM routing.
     ProviderSpec(
         name="deepseek",
         keywords=("deepseek",),
         env_key="DEEPSEEK_API_KEY",
         display_name="DeepSeek",
-        litellm_prefix="deepseek",          # deepseek-chat β†’ deepseek/deepseek-chat
-        skip_prefixes=("deepseek/",),       # avoid double-prefix
+        litellm_prefix="deepseek",  # deepseek-chat β†’ deepseek/deepseek-chat
+        skip_prefixes=("deepseek/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -253,15 +251,14 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # Gemini: needs "gemini/" prefix for LiteLLM.
     ProviderSpec(
         name="gemini",
         keywords=("gemini",),
         env_key="GEMINI_API_KEY",
         display_name="Gemini",
-        litellm_prefix="gemini",            # gemini-pro β†’ gemini/gemini-pro
-        skip_prefixes=("gemini/",),         # avoid double-prefix
+        litellm_prefix="gemini",  # gemini-pro β†’ gemini/gemini-pro
+        skip_prefixes=("gemini/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -271,7 +268,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # Zhipu: LiteLLM uses "zai/" prefix.
     # Also mirrors key to ZHIPUAI_API_KEY (some LiteLLM paths check that).
     # skip_prefixes: don't add "zai/" when already routed via gateway.
@@ -280,11 +276,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("zhipu", "glm", "zai"),
         env_key="ZAI_API_KEY",
         display_name="Zhipu AI",
-        litellm_prefix="zai",              # glm-4 β†’ zai/glm-4
+        litellm_prefix="zai",  # glm-4 β†’ zai/glm-4
         skip_prefixes=("zhipu/", "zai/", "openrouter/", "hosted_vllm/"),
-        env_extras=(
-            ("ZHIPUAI_API_KEY", "{api_key}"),
-        ),
+        env_extras=(("ZHIPUAI_API_KEY", "{api_key}"),),
         is_gateway=False,
         is_local=False,
         detect_by_key_prefix="",
@@ -293,14 +287,13 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # DashScope: Qwen models, needs "dashscope/" prefix.
     ProviderSpec(
         name="dashscope",
         keywords=("qwen", "dashscope"),
         env_key="DASHSCOPE_API_KEY",
         display_name="DashScope",
-        litellm_prefix="dashscope",         # qwen-max β†’ dashscope/qwen-max
+        litellm_prefix="dashscope",  # qwen-max β†’ dashscope/qwen-max
         skip_prefixes=("dashscope/", "openrouter/"),
         env_extras=(),
         is_gateway=False,
@@ -311,7 +304,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # Moonshot: Kimi models, needs "moonshot/" prefix.
     # LiteLLM requires MOONSHOT_API_BASE env var to find the endpoint.
     # Kimi K2.5 API enforces temperature >= 1.0.
@@ -320,22 +312,17 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("moonshot", "kimi"),
         env_key="MOONSHOT_API_KEY",
         display_name="Moonshot",
-        litellm_prefix="moonshot",          # kimi-k2.5 β†’ moonshot/kimi-k2.5
+        litellm_prefix="moonshot",  # kimi-k2.5 β†’ moonshot/kimi-k2.5
         skip_prefixes=("moonshot/", "openrouter/"),
-        env_extras=(
-            ("MOONSHOT_API_BASE", "{api_base}"),
-        ),
+        env_extras=(("MOONSHOT_API_BASE", "{api_base}"),),
         is_gateway=False,
         is_local=False,
         detect_by_key_prefix="",
         detect_by_base_keyword="",
-        default_api_base="https://api.moonshot.ai/v1",   # intl; use api.moonshot.cn for China
+        default_api_base="https://api.moonshot.ai/v1",  # intl; use api.moonshot.cn for China
         strip_model_prefix=False,
-        model_overrides=(
-            ("kimi-k2.5", {"temperature": 1.0}),
-        ),
+        model_overrides=(("kimi-k2.5", {"temperature": 1.0}),),
     ),
-
     # MiniMax: needs "minimax/" prefix for LiteLLM routing.
     # Uses OpenAI-compatible API at api.minimax.io/v1.
     ProviderSpec(
@@ -343,7 +330,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("minimax",),
         env_key="MINIMAX_API_KEY",
         display_name="MiniMax",
-        litellm_prefix="minimax",            # MiniMax-M2.1 β†’ minimax/MiniMax-M2.1
+        litellm_prefix="minimax",  # MiniMax-M2.1 β†’ minimax/MiniMax-M2.1
         skip_prefixes=("minimax/", "openrouter/"),
         env_extras=(),
         is_gateway=False,
@@ -354,9 +341,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # === Local deployment (matched by config key, NOT by api_base) =========
-
     # vLLM / any OpenAI-compatible local server.
     # Detected when config key is "vllm" (provider_name="vllm").
     ProviderSpec(
@@ -364,20 +349,18 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("vllm",),
         env_key="HOSTED_VLLM_API_KEY",
         display_name="vLLM/Local",
-        litellm_prefix="hosted_vllm",      # Llama-3-8B β†’ hosted_vllm/Llama-3-8B
+        litellm_prefix="hosted_vllm",  # Llama-3-8B β†’ hosted_vllm/Llama-3-8B
         skip_prefixes=(),
         env_extras=(),
         is_gateway=False,
         is_local=True,
         detect_by_key_prefix="",
         detect_by_base_keyword="",
-        default_api_base="",                # user must provide in config
+        default_api_base="",  # user must provide in config
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # === Auxiliary (not a primary LLM provider) ============================
-
     # Groq: mainly used for Whisper voice transcription, also usable for LLM.
     # Needs "groq/" prefix for LiteLLM routing. Placed last β€” it rarely wins fallback.
     ProviderSpec(
@@ -385,8 +368,8 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("groq",),
         env_key="GROQ_API_KEY",
         display_name="Groq",
-        litellm_prefix="groq",              # llama3-8b-8192 β†’ groq/llama3-8b-8192
-        skip_prefixes=("groq/",),           # avoid double-prefix
+        litellm_prefix="groq",  # llama3-8b-8192 β†’ groq/llama3-8b-8192
+        skip_prefixes=("groq/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -403,6 +386,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
 # Lookup helpers
 # ---------------------------------------------------------------------------
 
+
 def find_by_model(model: str) -> ProviderSpec | None:
     """Match a standard provider by model-name keyword (case-insensitive).
     Skips gateways/local β€” those are matched by api_key/api_base instead."""
@@ -418,7 +402,9 @@ def find_by_model(model: str) -> ProviderSpec | None:
             return spec
 
     for spec in std_specs:
-        if any(kw in model_lower or kw.replace("-", "_") in model_normalized for kw in spec.keywords):
+        if any(
+            kw in model_lower or kw.replace("-", "_") in model_normalized for kw in spec.keywords
+        ):
             return spec
     return None
 
diff --git a/nanobot/utils/helpers.py b/nanobot/utils/helpers.py
index 3a8c802..c57c365 100644
--- a/nanobot/utils/helpers.py
+++ b/nanobot/utils/helpers.py
@@ -5,6 +5,19 @@ from datetime import datetime
 from pathlib import Path
 
 
+def detect_image_mime(data: bytes) -> str | None:
+    """Detect image MIME type from magic bytes, ignoring file extension."""
+    if data[:8] == b"\x89PNG\r\n\x1a\n":
+        return "image/png"
+    if data[:3] == b"\xff\xd8\xff":
+        return "image/jpeg"
+    if data[:6] in (b"GIF87a", b"GIF89a"):
+        return "image/gif"
+    if data[:4] == b"RIFF" and data[8:12] == b"WEBP":
+        return "image/webp"
+    return None
+
+
 def ensure_dir(path: Path) -> Path:
     """Ensure directory exists, return it."""
     path.mkdir(parents=True, exist_ok=True)
@@ -34,6 +47,38 @@ def safe_filename(name: str) -> str:
     return _UNSAFE_CHARS.sub("_", name).strip()
 
 
+def split_message(content: str, max_len: int = 2000) -> list[str]:
+    """
+    Split content into chunks within max_len, preferring line breaks.
+
+    Args:
+        content: The text content to split.
+        max_len: Maximum length per chunk (default 2000 for Discord compatibility).
+
+    Returns:
+        List of message chunks, each within max_len.
+    """
+    if not content:
+        return []
+    if len(content) <= max_len:
+        return [content]
+    chunks: list[str] = []
+    while content:
+        if len(content) <= max_len:
+            chunks.append(content)
+            break
+        cut = content[:max_len]
+        # Try to break at newline first, then space, then hard break
+        pos = cut.rfind('\n')
+        if pos <= 0:
+            pos = cut.rfind(' ')
+        if pos <= 0:
+            pos = max_len
+        chunks.append(content[:pos])
+        content = content[pos:].lstrip()
+    return chunks
+
+
 def sync_workspace_templates(workspace: Path, silent: bool = False) -> list[str]:
     """Sync bundled templates to workspace. Only creates missing files."""
     from importlib.resources import files as pkg_files
diff --git a/pyproject.toml b/pyproject.toml
index 4199af1..41d0fbb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -30,7 +30,7 @@ dependencies = [
     "rich>=14.0.0,<15.0.0",
     "croniter>=6.0.0,<7.0.0",
     "dingtalk-stream>=0.24.0,<1.0.0",
-    "python-telegram-bot[socks]>=22.0,<23.0",
+    "python-telegram-bot[socks]>=22.6,<23.0",
     "lark-oapi>=1.5.0,<2.0.0",
     "socksio>=1.0.0,<2.0.0",
     "python-socketio>=5.16.0,<6.0.0",
@@ -42,6 +42,7 @@ dependencies = [
     "prompt-toolkit>=3.0.50,<4.0.0",
     "mcp>=1.26.0,<2.0.0",
     "json-repair>=0.57.0,<1.0.0",
+    "chardet>=3.0.2,<6.0.0",
     "openai>=2.8.0",
 ]
 
@@ -55,6 +56,9 @@ dev = [
     "pytest>=9.0.0,<10.0.0",
     "pytest-asyncio>=1.3.0,<2.0.0",
     "ruff>=0.1.0",
+    "matrix-nio[e2e]>=0.25.2",
+    "mistune>=3.0.0,<4.0.0",
+    "nh3>=0.2.17,<1.0.0",
 ]
 
 [project.scripts]
diff --git a/tests/test_azure_openai_provider.py b/tests/test_azure_openai_provider.py
new file mode 100644
index 0000000..77f36d4
--- /dev/null
+++ b/tests/test_azure_openai_provider.py
@@ -0,0 +1,399 @@
+"""Test Azure OpenAI provider implementation (updated for model-based deployment names)."""
+
+from unittest.mock import AsyncMock, Mock, patch
+
+import pytest
+
+from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
+from nanobot.providers.base import LLMResponse
+
+
+def test_azure_openai_provider_init():
+    """Test AzureOpenAIProvider initialization without deployment_name."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o-deployment",
+    )
+    
+    assert provider.api_key == "test-key"
+    assert provider.api_base == "https://test-resource.openai.azure.com/"
+    assert provider.default_model == "gpt-4o-deployment"
+    assert provider.api_version == "2024-10-21"
+
+
+def test_azure_openai_provider_init_validation():
+    """Test AzureOpenAIProvider initialization validation."""
+    # Missing api_key
+    with pytest.raises(ValueError, match="Azure OpenAI api_key is required"):
+        AzureOpenAIProvider(api_key="", api_base="https://test.com")
+    
+    # Missing api_base
+    with pytest.raises(ValueError, match="Azure OpenAI api_base is required"):
+        AzureOpenAIProvider(api_key="test", api_base="")
+
+
+def test_build_chat_url():
+    """Test Azure OpenAI URL building with different deployment names."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    # Test various deployment names
+    test_cases = [
+        ("gpt-4o-deployment", "https://test-resource.openai.azure.com/openai/deployments/gpt-4o-deployment/chat/completions?api-version=2024-10-21"),
+        ("gpt-35-turbo", "https://test-resource.openai.azure.com/openai/deployments/gpt-35-turbo/chat/completions?api-version=2024-10-21"),
+        ("custom-model", "https://test-resource.openai.azure.com/openai/deployments/custom-model/chat/completions?api-version=2024-10-21"),
+    ]
+    
+    for deployment_name, expected_url in test_cases:
+        url = provider._build_chat_url(deployment_name)
+        assert url == expected_url
+
+
+def test_build_chat_url_api_base_without_slash():
+    """Test URL building when api_base doesn't end with slash."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",  # No trailing slash
+        default_model="gpt-4o",
+    )
+    
+    url = provider._build_chat_url("test-deployment")
+    expected = "https://test-resource.openai.azure.com/openai/deployments/test-deployment/chat/completions?api-version=2024-10-21"
+    assert url == expected
+
+
+def test_build_headers():
+    """Test Azure OpenAI header building with api-key authentication."""
+    provider = AzureOpenAIProvider(
+        api_key="test-api-key-123",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    headers = provider._build_headers()
+    assert headers["Content-Type"] == "application/json"
+    assert headers["api-key"] == "test-api-key-123"  # Azure OpenAI specific header
+    assert "x-session-affinity" in headers
+
+
+def test_prepare_request_payload():
+    """Test request payload preparation with Azure OpenAI 2024-10-21 compliance."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    messages = [{"role": "user", "content": "Hello"}]
+    payload = provider._prepare_request_payload("gpt-4o", messages, max_tokens=1500, temperature=0.8)
+    
+    assert payload["messages"] == messages
+    assert payload["max_completion_tokens"] == 1500  # Azure API 2024-10-21 uses max_completion_tokens
+    assert payload["temperature"] == 0.8
+    assert "tools" not in payload
+    
+    # Test with tools
+    tools = [{"type": "function", "function": {"name": "get_weather", "parameters": {}}}]
+    payload_with_tools = provider._prepare_request_payload("gpt-4o", messages, tools=tools)
+    assert payload_with_tools["tools"] == tools
+    assert payload_with_tools["tool_choice"] == "auto"
+    
+    # Test with reasoning_effort
+    payload_with_reasoning = provider._prepare_request_payload(
+        "gpt-5-chat", messages, reasoning_effort="medium"
+    )
+    assert payload_with_reasoning["reasoning_effort"] == "medium"
+    assert "temperature" not in payload_with_reasoning
+
+
+def test_prepare_request_payload_sanitizes_messages():
+    """Test Azure payload strips non-standard message keys before sending."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+
+    messages = [
+        {
+            "role": "assistant",
+            "tool_calls": [{"id": "call_123", "type": "function", "function": {"name": "x"}}],
+            "reasoning_content": "hidden chain-of-thought",
+        },
+        {
+            "role": "tool",
+            "tool_call_id": "call_123",
+            "name": "x",
+            "content": "ok",
+            "extra_field": "should be removed",
+        },
+    ]
+
+    payload = provider._prepare_request_payload("gpt-4o", messages)
+
+    assert payload["messages"] == [
+        {
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "call_123", "type": "function", "function": {"name": "x"}}],
+        },
+        {
+            "role": "tool",
+            "tool_call_id": "call_123",
+            "name": "x",
+            "content": "ok",
+        },
+    ]
+
+
+@pytest.mark.asyncio
+async def test_chat_success():
+    """Test successful chat request using model as deployment name."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o-deployment",
+    )
+    
+    # Mock response data
+    mock_response_data = {
+        "choices": [{
+            "message": {
+                "content": "Hello! How can I help you today?",
+                "role": "assistant"
+            },
+            "finish_reason": "stop"
+        }],
+        "usage": {
+            "prompt_tokens": 12,
+            "completion_tokens": 18,
+            "total_tokens": 30
+        }
+    }
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_response = AsyncMock()
+        mock_response.status_code = 200
+        mock_response.json = Mock(return_value=mock_response_data)
+        
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(return_value=mock_response)
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        # Test with specific model (deployment name)
+        messages = [{"role": "user", "content": "Hello"}]
+        result = await provider.chat(messages, model="custom-deployment")
+        
+        assert isinstance(result, LLMResponse)
+        assert result.content == "Hello! How can I help you today?"
+        assert result.finish_reason == "stop"
+        assert result.usage["prompt_tokens"] == 12
+        assert result.usage["completion_tokens"] == 18
+        assert result.usage["total_tokens"] == 30
+        
+        # Verify URL was built with the provided model as deployment name
+        call_args = mock_context.post.call_args
+        expected_url = "https://test-resource.openai.azure.com/openai/deployments/custom-deployment/chat/completions?api-version=2024-10-21"
+        assert call_args[0][0] == expected_url
+
+
+@pytest.mark.asyncio
+async def test_chat_uses_default_model_when_no_model_provided():
+    """Test that chat uses default_model when no model is specified."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="default-deployment",
+    )
+    
+    mock_response_data = {
+        "choices": [{
+            "message": {"content": "Response", "role": "assistant"},
+            "finish_reason": "stop"
+        }],
+        "usage": {"prompt_tokens": 5, "completion_tokens": 5, "total_tokens": 10}
+    }
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_response = AsyncMock()
+        mock_response.status_code = 200
+        mock_response.json = Mock(return_value=mock_response_data)
+        
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(return_value=mock_response)
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        messages = [{"role": "user", "content": "Test"}]
+        await provider.chat(messages)  # No model specified
+        
+        # Verify URL was built with default model as deployment name
+        call_args = mock_context.post.call_args
+        expected_url = "https://test-resource.openai.azure.com/openai/deployments/default-deployment/chat/completions?api-version=2024-10-21"
+        assert call_args[0][0] == expected_url
+
+
+@pytest.mark.asyncio
+async def test_chat_with_tool_calls():
+    """Test chat request with tool calls in response."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    # Mock response with tool calls
+    mock_response_data = {
+        "choices": [{
+            "message": {
+                "content": None,
+                "role": "assistant",
+                "tool_calls": [{
+                    "id": "call_12345",
+                    "function": {
+                        "name": "get_weather",
+                        "arguments": '{"location": "San Francisco"}'
+                    }
+                }]
+            },
+            "finish_reason": "tool_calls"
+        }],
+        "usage": {
+            "prompt_tokens": 20,
+            "completion_tokens": 15,
+            "total_tokens": 35
+        }
+    }
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_response = AsyncMock()
+        mock_response.status_code = 200
+        mock_response.json = Mock(return_value=mock_response_data)
+        
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(return_value=mock_response)
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        messages = [{"role": "user", "content": "What's the weather?"}]
+        tools = [{"type": "function", "function": {"name": "get_weather", "parameters": {}}}]
+        result = await provider.chat(messages, tools=tools, model="weather-model")
+        
+        assert isinstance(result, LLMResponse)
+        assert result.content is None
+        assert result.finish_reason == "tool_calls"
+        assert len(result.tool_calls) == 1
+        assert result.tool_calls[0].name == "get_weather"
+        assert result.tool_calls[0].arguments == {"location": "San Francisco"}
+
+
+@pytest.mark.asyncio
+async def test_chat_api_error():
+    """Test chat request API error handling."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_response = AsyncMock()
+        mock_response.status_code = 401
+        mock_response.text = "Invalid authentication credentials"
+        
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(return_value=mock_response)
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        messages = [{"role": "user", "content": "Hello"}]
+        result = await provider.chat(messages)
+        
+        assert isinstance(result, LLMResponse)
+        assert "Azure OpenAI API Error 401" in result.content
+        assert "Invalid authentication credentials" in result.content
+        assert result.finish_reason == "error"
+
+
+@pytest.mark.asyncio
+async def test_chat_connection_error():
+    """Test chat request connection error handling."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    with patch("httpx.AsyncClient") as mock_client:
+        mock_context = AsyncMock()
+        mock_context.post = AsyncMock(side_effect=Exception("Connection failed"))
+        mock_client.return_value.__aenter__.return_value = mock_context
+        
+        messages = [{"role": "user", "content": "Hello"}]
+        result = await provider.chat(messages)
+        
+        assert isinstance(result, LLMResponse)
+        assert "Error calling Azure OpenAI: Exception('Connection failed')" in result.content
+        assert result.finish_reason == "error"
+
+
+def test_parse_response_malformed():
+    """Test response parsing with malformed data."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o",
+    )
+    
+    # Test with missing choices
+    malformed_response = {"usage": {"prompt_tokens": 10}}
+    result = provider._parse_response(malformed_response)
+    
+    assert isinstance(result, LLMResponse)
+    assert "Error parsing Azure OpenAI response" in result.content
+    assert result.finish_reason == "error"
+
+
+def test_get_default_model():
+    """Test get_default_model method."""
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="my-custom-deployment",
+    )
+    
+    assert provider.get_default_model() == "my-custom-deployment"
+
+
+if __name__ == "__main__":
+    # Run basic tests
+    print("Running basic Azure OpenAI provider tests...")
+    
+    # Test initialization
+    provider = AzureOpenAIProvider(
+        api_key="test-key",
+        api_base="https://test-resource.openai.azure.com",
+        default_model="gpt-4o-deployment",
+    )
+    print("βœ… Provider initialization successful")
+    
+    # Test URL building
+    url = provider._build_chat_url("my-deployment")
+    expected = "https://test-resource.openai.azure.com/openai/deployments/my-deployment/chat/completions?api-version=2024-10-21"
+    assert url == expected
+    print("βœ… URL building works correctly")
+    
+    # Test headers
+    headers = provider._build_headers()
+    assert headers["api-key"] == "test-key"
+    assert headers["Content-Type"] == "application/json"
+    print("βœ… Header building works correctly")
+    
+    # Test payload preparation
+    messages = [{"role": "user", "content": "Test"}]
+    payload = provider._prepare_request_payload("gpt-4o-deployment", messages, max_tokens=1000)
+    assert payload["max_completion_tokens"] == 1000  # Azure 2024-10-21 format
+    print("βœ… Payload preparation works correctly")
+    
+    print("βœ… All basic tests passed! Updated test file is working correctly.")
\ No newline at end of file
diff --git a/tests/test_context_prompt_cache.py b/tests/test_context_prompt_cache.py
index 9afcc7d..ce796e2 100644
--- a/tests/test_context_prompt_cache.py
+++ b/tests/test_context_prompt_cache.py
@@ -40,7 +40,7 @@ def test_system_prompt_stays_stable_when_clock_changes(tmp_path, monkeypatch) ->
 
 
 def test_runtime_context_is_separate_untrusted_user_message(tmp_path) -> None:
-    """Runtime metadata should be a separate user message before the actual user message."""
+    """Runtime metadata should be merged with the user message."""
     workspace = _make_workspace(tmp_path)
     builder = ContextBuilder(workspace)
 
@@ -54,13 +54,12 @@ def test_runtime_context_is_separate_untrusted_user_message(tmp_path) -> None:
     assert messages[0]["role"] == "system"
     assert "## Current Session" not in messages[0]["content"]
 
-    assert messages[-2]["role"] == "user"
-    runtime_content = messages[-2]["content"]
-    assert isinstance(runtime_content, str)
-    assert ContextBuilder._RUNTIME_CONTEXT_TAG in runtime_content
-    assert "Current Time:" in runtime_content
-    assert "Channel: cli" in runtime_content
-    assert "Chat ID: direct" in runtime_content
-
+    # Runtime context is now merged with user message into a single message
     assert messages[-1]["role"] == "user"
-    assert messages[-1]["content"] == "Return exactly: OK"
+    user_content = messages[-1]["content"]
+    assert isinstance(user_content, str)
+    assert ContextBuilder._RUNTIME_CONTEXT_TAG in user_content
+    assert "Current Time:" in user_content
+    assert "Channel: cli" in user_content
+    assert "Chat ID: direct" in user_content
+    assert "Return exactly: OK" in user_content
diff --git a/tests/test_cron_commands.py b/tests/test_cron_commands.py
deleted file mode 100644
index bce1ef5..0000000
--- a/tests/test_cron_commands.py
+++ /dev/null
@@ -1,29 +0,0 @@
-from typer.testing import CliRunner
-
-from nanobot.cli.commands import app
-
-runner = CliRunner()
-
-
-def test_cron_add_rejects_invalid_timezone(monkeypatch, tmp_path) -> None:
-    monkeypatch.setattr("nanobot.config.loader.get_data_dir", lambda: tmp_path)
-
-    result = runner.invoke(
-        app,
-        [
-            "cron",
-            "add",
-            "--name",
-            "demo",
-            "--message",
-            "hello",
-            "--cron",
-            "0 9 * * *",
-            "--tz",
-            "America/Vancovuer",
-        ],
-    )
-
-    assert result.exit_code == 1
-    assert "Error: unknown timezone 'America/Vancovuer'" in result.stdout
-    assert not (tmp_path / "cron" / "jobs.json").exists()
diff --git a/tests/test_cron_service.py b/tests/test_cron_service.py
index 2a36f4c..9631da5 100644
--- a/tests/test_cron_service.py
+++ b/tests/test_cron_service.py
@@ -48,6 +48,8 @@ async def test_running_service_honors_external_disable(tmp_path) -> None:
     )
     await service.start()
     try:
+        # Wait slightly to ensure file mtime is definitively different
+        await asyncio.sleep(0.05)
         external = CronService(store_path)
         updated = external.enable_job(job.id, enabled=False)
         assert updated is not None
diff --git a/tests/test_feishu_post_content.py b/tests/test_feishu_post_content.py
index bf1ea82..7b1cb9d 100644
--- a/tests/test_feishu_post_content.py
+++ b/tests/test_feishu_post_content.py
@@ -1,4 +1,4 @@
-from nanobot.channels.feishu import _extract_post_content
+from nanobot.channels.feishu import FeishuChannel, _extract_post_content
 
 
 def test_extract_post_content_supports_post_wrapper_shape() -> None:
@@ -38,3 +38,28 @@ def test_extract_post_content_keeps_direct_shape_behavior() -> None:
 
     assert text == "Daily report"
     assert image_keys == ["img_a", "img_b"]
+
+
+def test_register_optional_event_keeps_builder_when_method_missing() -> None:
+    class Builder:
+        pass
+
+    builder = Builder()
+    same = FeishuChannel._register_optional_event(builder, "missing", object())
+    assert same is builder
+
+
+def test_register_optional_event_calls_supported_method() -> None:
+    called = []
+
+    class Builder:
+        def register_event(self, handler):
+            called.append(handler)
+            return self
+
+    builder = Builder()
+    handler = object()
+    same = FeishuChannel._register_optional_event(builder, "register_event", handler)
+
+    assert same is builder
+    assert called == [handler]
diff --git a/tests/test_feishu_table_split.py b/tests/test_feishu_table_split.py
new file mode 100644
index 0000000..af8fa16
--- /dev/null
+++ b/tests/test_feishu_table_split.py
@@ -0,0 +1,104 @@
+"""Tests for FeishuChannel._split_elements_by_table_limit.
+
+Feishu cards reject messages that contain more than one table element
+(API error 11310: card table number over limit).  The helper splits a flat
+list of card elements into groups so that each group contains at most one
+table, allowing nanobot to send multiple cards instead of failing.
+"""
+
+from nanobot.channels.feishu import FeishuChannel
+
+
+def _md(text: str) -> dict:
+    return {"tag": "markdown", "content": text}
+
+
+def _table() -> dict:
+    return {
+        "tag": "table",
+        "columns": [{"tag": "column", "name": "c0", "display_name": "A", "width": "auto"}],
+        "rows": [{"c0": "v"}],
+        "page_size": 2,
+    }
+
+
+split = FeishuChannel._split_elements_by_table_limit
+
+
+def test_empty_list_returns_single_empty_group() -> None:
+    assert split([]) == [[]]
+
+
+def test_no_tables_returns_single_group() -> None:
+    els = [_md("hello"), _md("world")]
+    result = split(els)
+    assert result == [els]
+
+
+def test_single_table_stays_in_one_group() -> None:
+    els = [_md("intro"), _table(), _md("outro")]
+    result = split(els)
+    assert len(result) == 1
+    assert result[0] == els
+
+
+def test_two_tables_split_into_two_groups() -> None:
+    # Use different row values so the two tables are not equal
+    t1 = {
+        "tag": "table",
+        "columns": [{"tag": "column", "name": "c0", "display_name": "A", "width": "auto"}],
+        "rows": [{"c0": "table-one"}],
+        "page_size": 2,
+    }
+    t2 = {
+        "tag": "table",
+        "columns": [{"tag": "column", "name": "c0", "display_name": "B", "width": "auto"}],
+        "rows": [{"c0": "table-two"}],
+        "page_size": 2,
+    }
+    els = [_md("before"), t1, _md("between"), t2, _md("after")]
+    result = split(els)
+    assert len(result) == 2
+    # First group: text before table-1 + table-1
+    assert t1 in result[0]
+    assert t2 not in result[0]
+    # Second group: text between tables + table-2 + text after
+    assert t2 in result[1]
+    assert t1 not in result[1]
+
+
+def test_three_tables_split_into_three_groups() -> None:
+    tables = [
+        {"tag": "table", "columns": [], "rows": [{"c0": f"t{i}"}], "page_size": 1}
+        for i in range(3)
+    ]
+    els = tables[:]
+    result = split(els)
+    assert len(result) == 3
+    for i, group in enumerate(result):
+        assert tables[i] in group
+
+
+def test_leading_markdown_stays_with_first_table() -> None:
+    intro = _md("intro")
+    t = _table()
+    result = split([intro, t])
+    assert len(result) == 1
+    assert result[0] == [intro, t]
+
+
+def test_trailing_markdown_after_second_table() -> None:
+    t1, t2 = _table(), _table()
+    tail = _md("end")
+    result = split([t1, t2, tail])
+    assert len(result) == 2
+    assert result[1] == [t2, tail]
+
+
+def test_non_table_elements_before_first_table_kept_in_first_group() -> None:
+    head = _md("head")
+    t1, t2 = _table(), _table()
+    result = split([head, t1, t2])
+    # head + t1 in group 0; t2 in group 1
+    assert result[0] == [head, t1]
+    assert result[1] == [t2]
diff --git a/tests/test_matrix_channel.py b/tests/test_matrix_channel.py
index c6714c2..c25b95a 100644
--- a/tests/test_matrix_channel.py
+++ b/tests/test_matrix_channel.py
@@ -159,6 +159,7 @@ class _FakeAsyncClient:
 
 
 def _make_config(**kwargs) -> MatrixConfig:
+    kwargs.setdefault("allow_from", ["*"])
     return MatrixConfig(
         enabled=True,
         homeserver="https://matrix.org",
@@ -274,7 +275,7 @@ async def test_stop_stops_sync_forever_before_close(monkeypatch) -> None:
 
 
 @pytest.mark.asyncio
-async def test_room_invite_joins_when_allow_list_is_empty() -> None:
+async def test_room_invite_ignores_when_allow_list_is_empty() -> None:
     channel = MatrixChannel(_make_config(allow_from=[]), MessageBus())
     client = _FakeAsyncClient("", "", "", None)
     channel.client = client
@@ -284,9 +285,22 @@ async def test_room_invite_joins_when_allow_list_is_empty() -> None:
 
     await channel._on_room_invite(room, event)
 
-    assert client.join_calls == ["!room:matrix.org"]
+    assert client.join_calls == []
 
 
+@pytest.mark.asyncio
+async def test_room_invite_joins_when_sender_allowed() -> None:
+    channel = MatrixChannel(_make_config(allow_from=["@alice:matrix.org"]), MessageBus())
+    client = _FakeAsyncClient("", "", "", None)
+    channel.client = client
+
+    room = SimpleNamespace(room_id="!room:matrix.org")
+    event = SimpleNamespace(sender="@alice:matrix.org")
+
+    await channel._on_room_invite(room, event)
+
+    assert client.join_calls == ["!room:matrix.org"]
+
 @pytest.mark.asyncio
 async def test_room_invite_respects_allow_list_when_configured() -> None:
     channel = MatrixChannel(_make_config(allow_from=["@bob:matrix.org"]), MessageBus())
@@ -1163,6 +1177,8 @@ async def test_send_progress_keeps_typing_keepalive_running() -> None:
     assert "!room:matrix.org" in channel._typing_tasks
     assert client.typing_calls[-1] == ("!room:matrix.org", True, TYPING_NOTICE_TIMEOUT_MS)
 
+    await channel.stop()
+
 
 @pytest.mark.asyncio
 async def test_send_clears_typing_when_send_fails() -> None:
diff --git a/tests/test_memory_consolidation_types.py b/tests/test_memory_consolidation_types.py
index 375c802..ff15584 100644
--- a/tests/test_memory_consolidation_types.py
+++ b/tests/test_memory_consolidation_types.py
@@ -145,3 +145,78 @@ class TestMemoryConsolidationTypeHandling:
 
         assert result is True
         provider.chat.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_list_arguments_extracts_first_dict(self, tmp_path: Path) -> None:
+        """Some providers return arguments as a list - extract first element if it's a dict."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+
+        # Simulate arguments being a list containing a dict
+        response = LLMResponse(
+            content=None,
+            tool_calls=[
+                ToolCallRequest(
+                    id="call_1",
+                    name="save_memory",
+                    arguments=[{
+                        "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()
+        assert "User likes testing." in store.memory_file.read_text()
+
+    @pytest.mark.asyncio
+    async def test_list_arguments_empty_list_returns_false(self, tmp_path: Path) -> None:
+        """Empty list arguments should return False."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+
+        response = LLMResponse(
+            content=None,
+            tool_calls=[
+                ToolCallRequest(
+                    id="call_1",
+                    name="save_memory",
+                    arguments=[],
+                )
+            ],
+        )
+        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 False
+
+    @pytest.mark.asyncio
+    async def test_list_arguments_non_dict_content_returns_false(self, tmp_path: Path) -> None:
+        """List with non-dict content should return False."""
+        store = MemoryStore(tmp_path)
+        provider = AsyncMock()
+
+        response = LLMResponse(
+            content=None,
+            tool_calls=[
+                ToolCallRequest(
+                    id="call_1",
+                    name="save_memory",
+                    arguments=["string", "content"],
+                )
+            ],
+        )
+        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 False
diff --git a/tests/test_message_tool_suppress.py b/tests/test_message_tool_suppress.py
index 26b8a16..f5e65c9 100644
--- a/tests/test_message_tool_suppress.py
+++ b/tests/test_message_tool_suppress.py
@@ -86,6 +86,36 @@ class TestMessageToolSuppressLogic:
         assert result is not None
         assert "Hello" in result.content
 
+    @pytest.mark.asyncio
+    async def test_progress_hides_internal_reasoning(self, tmp_path: Path) -> None:
+        loop = _make_loop(tmp_path)
+        tool_call = ToolCallRequest(id="call1", name="read_file", arguments={"path": "foo.txt"})
+        calls = iter([
+            LLMResponse(
+                content="Visiblehidden",
+                tool_calls=[tool_call],
+                reasoning_content="secret reasoning",
+                thinking_blocks=[{"signature": "sig", "thought": "secret thought"}],
+            ),
+            LLMResponse(content="Done", tool_calls=[]),
+        ])
+        loop.provider.chat = AsyncMock(side_effect=lambda *a, **kw: next(calls))
+        loop.tools.get_definitions = MagicMock(return_value=[])
+        loop.tools.execute = AsyncMock(return_value="ok")
+
+        progress: list[tuple[str, bool]] = []
+
+        async def on_progress(content: str, *, tool_hint: bool = False) -> None:
+            progress.append((content, tool_hint))
+
+        final_content, _, _ = await loop._run_agent_loop([], on_progress=on_progress)
+
+        assert final_content == "Done"
+        assert progress == [
+            ("Visible", False),
+            ('read_file("foo.txt")', True),
+        ]
+
 
 class TestMessageToolTurnTracking:
 
diff --git a/tests/test_tool_validation.py b/tests/test_tool_validation.py
index cb50fb0..c2b4b6a 100644
--- a/tests/test_tool_validation.py
+++ b/tests/test_tool_validation.py
@@ -106,3 +106,234 @@ def test_exec_extract_absolute_paths_captures_posix_absolute_paths() -> None:
     paths = ExecTool._extract_absolute_paths(cmd)
     assert "/tmp/data.txt" in paths
     assert "/tmp/out.txt" in paths
+
+
+# --- cast_params tests ---
+
+
+class CastTestTool(Tool):
+    """Minimal tool for testing cast_params."""
+
+    def __init__(self, schema: dict[str, Any]) -> None:
+        self._schema = schema
+
+    @property
+    def name(self) -> str:
+        return "cast_test"
+
+    @property
+    def description(self) -> str:
+        return "test tool for casting"
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return self._schema
+
+    async def execute(self, **kwargs: Any) -> str:
+        return "ok"
+
+
+def test_cast_params_string_to_int() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"count": {"type": "integer"}},
+        }
+    )
+    result = tool.cast_params({"count": "42"})
+    assert result["count"] == 42
+    assert isinstance(result["count"], int)
+
+
+def test_cast_params_string_to_number() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"rate": {"type": "number"}},
+        }
+    )
+    result = tool.cast_params({"rate": "3.14"})
+    assert result["rate"] == 3.14
+    assert isinstance(result["rate"], float)
+
+
+def test_cast_params_string_to_bool() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"enabled": {"type": "boolean"}},
+        }
+    )
+    assert tool.cast_params({"enabled": "true"})["enabled"] is True
+    assert tool.cast_params({"enabled": "false"})["enabled"] is False
+    assert tool.cast_params({"enabled": "1"})["enabled"] is True
+
+
+def test_cast_params_array_items() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {
+                "nums": {"type": "array", "items": {"type": "integer"}},
+            },
+        }
+    )
+    result = tool.cast_params({"nums": ["1", "2", "3"]})
+    assert result["nums"] == [1, 2, 3]
+
+
+def test_cast_params_nested_object() -> None:
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {
+                "config": {
+                    "type": "object",
+                    "properties": {
+                        "port": {"type": "integer"},
+                        "debug": {"type": "boolean"},
+                    },
+                },
+            },
+        }
+    )
+    result = tool.cast_params({"config": {"port": "8080", "debug": "true"}})
+    assert result["config"]["port"] == 8080
+    assert result["config"]["debug"] is True
+
+
+def test_cast_params_bool_not_cast_to_int() -> None:
+    """Booleans should not be silently cast to integers."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"count": {"type": "integer"}},
+        }
+    )
+    result = tool.cast_params({"count": True})
+    assert result["count"] is True
+    errors = tool.validate_params(result)
+    assert any("count should be integer" in e for e in errors)
+
+
+def test_cast_params_preserves_empty_string() -> None:
+    """Empty strings should be preserved for string type."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"name": {"type": "string"}},
+        }
+    )
+    result = tool.cast_params({"name": ""})
+    assert result["name"] == ""
+
+
+def test_cast_params_bool_string_false() -> None:
+    """Test that 'false', '0', 'no' strings convert to False."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"flag": {"type": "boolean"}},
+        }
+    )
+    assert tool.cast_params({"flag": "false"})["flag"] is False
+    assert tool.cast_params({"flag": "False"})["flag"] is False
+    assert tool.cast_params({"flag": "0"})["flag"] is False
+    assert tool.cast_params({"flag": "no"})["flag"] is False
+    assert tool.cast_params({"flag": "NO"})["flag"] is False
+
+
+def test_cast_params_bool_string_invalid() -> None:
+    """Invalid boolean strings should not be cast."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"flag": {"type": "boolean"}},
+        }
+    )
+    # Invalid strings should be preserved (validation will catch them)
+    result = tool.cast_params({"flag": "random"})
+    assert result["flag"] == "random"
+    result = tool.cast_params({"flag": "maybe"})
+    assert result["flag"] == "maybe"
+
+
+def test_cast_params_invalid_string_to_int() -> None:
+    """Invalid strings should not be cast to integer."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"count": {"type": "integer"}},
+        }
+    )
+    result = tool.cast_params({"count": "abc"})
+    assert result["count"] == "abc"  # Original value preserved
+    result = tool.cast_params({"count": "12.5.7"})
+    assert result["count"] == "12.5.7"
+
+
+def test_cast_params_invalid_string_to_number() -> None:
+    """Invalid strings should not be cast to number."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"rate": {"type": "number"}},
+        }
+    )
+    result = tool.cast_params({"rate": "not_a_number"})
+    assert result["rate"] == "not_a_number"
+
+
+def test_validate_params_bool_not_accepted_as_number() -> None:
+    """Booleans should not pass number validation."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"rate": {"type": "number"}},
+        }
+    )
+    errors = tool.validate_params({"rate": False})
+    assert any("rate should be number" in e for e in errors)
+
+
+def test_cast_params_none_values() -> None:
+    """Test None handling for different types."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {
+                "name": {"type": "string"},
+                "count": {"type": "integer"},
+                "items": {"type": "array"},
+                "config": {"type": "object"},
+            },
+        }
+    )
+    result = tool.cast_params(
+        {
+            "name": None,
+            "count": None,
+            "items": None,
+            "config": None,
+        }
+    )
+    # None should be preserved for all types
+    assert result["name"] is None
+    assert result["count"] is None
+    assert result["items"] is None
+    assert result["config"] is None
+
+
+def test_cast_params_single_value_not_auto_wrapped_to_array() -> None:
+    """Single values should NOT be automatically wrapped into arrays."""
+    tool = CastTestTool(
+        {
+            "type": "object",
+            "properties": {"items": {"type": "array"}},
+        }
+    )
+    # Non-array values should be preserved (validation will catch them)
+    result = tool.cast_params({"items": 5})
+    assert result["items"] == 5  # Not wrapped to [5]
+    result = tool.cast_params({"items": "text"})
+    assert result["items"] == "text"  # Not wrapped to ["text"]