From a08aae93e6c8ac2b68a4a8d566899b95fd414844 Mon Sep 17 00:00:00 2001
From: hcanyz <hcanyz@163.com>
Date: Thu, 5 Mar 2026 11:33:20 +0800
Subject: [PATCH 01/15] fix: not imported when LiteLLMProvider is not used

LiteLLM:WARNING: get_model_cost_map.py:213 - LiteLLM: Failed to fetch remote model cost map from https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json: The read operation timed out. Falling back to local backup.
---
 nanobot/cli/commands.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/nanobot/cli/commands.py b/nanobot/cli/commands.py
index b75a2bc..2597928 100644
--- a/nanobot/cli/commands.py
+++ b/nanobot/cli/commands.py
@@ -200,8 +200,6 @@ 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
 
     model = config.agents.defaults.model
@@ -213,6 +211,7 @@ 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 +219,7 @@ def _make_provider(config: Config):
             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):

From 5cc3c032450f5a97c1ebf9bf153974ad00ddc725 Mon Sep 17 00:00:00 2001
From: Peixian Gong <peixiangong@microsoft.com>
Date: Thu, 5 Mar 2026 15:15:37 +0800
Subject: [PATCH 02/15] fix: merge tool_calls from multiple choices in LiteLLM
 response

GitHub Copilot's API returns tool_calls split across multiple choices:
- choices[0]: content only (tool_calls=null)
- choices[1]: tool_calls only (content=null)

The existing _parse_response only inspected choices[0], so tool_calls
were silently lost, causing the agent to never execute tools when using
github_copilot/ models.

This fix scans all choices and merges tool_calls + content, so
providers that return multi-choice responses work correctly.
Single-choice providers (OpenAI, Anthropic, etc.) are unaffected since
the loop over one choice is equivalent to the original code.
---
 nanobot/providers/litellm_provider.py | 44 +++++++++++++++++++--------
 1 file changed, 31 insertions(+), 13 deletions(-)

diff --git a/nanobot/providers/litellm_provider.py b/nanobot/providers/litellm_provider.py
index d8d8ace..a1819a2 100644
--- a/nanobot/providers/litellm_provider.py
+++ b/nanobot/providers/litellm_provider.py
@@ -8,6 +8,7 @@ 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
@@ -255,20 +256,37 @@ 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:
@@ -282,9 +300,9 @@ class LiteLLMProvider(LLMProvider):
         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,

From cf3e7e3f38325224dcb342af448ecd17c11d1d13 Mon Sep 17 00:00:00 2001
From: ouyangwulin <mr.artboy@gmail.com>
Date: Thu, 5 Mar 2026 16:54:15 +0800
Subject: [PATCH 03/15] feat: Add Alibaba Cloud Coding Plan API support

Add dashscope_coding_plan provider to registry with OpenAI-compatible
endpoint for BaiLian coding assistance.

- Supports API key detection by 'sk-sp-' prefix pattern
- Adds provider config schema entry for proper loading
- Updates documentation with configuration instructions
- Fixes duplicate MatrixConfig class issue in schema
- Follow existing nanobot provider patterns for consistency
---
 README.md                     |   1 +
 nanobot/config/schema.py      |  62 +++++++++++-----
 nanobot/providers/registry.py | 130 ++++++++++++++++------------------
 3 files changed, 109 insertions(+), 84 deletions(-)

diff --git a/README.md b/README.md
index 33cdeee..2977ccb 100644
--- a/README.md
+++ b/README.md
@@ -656,6 +656,7 @@ Config file: `~/.nanobot/config.json`
 > [!TIP]
 > - **Groq** provides free voice transcription via Whisper. If configured, Telegram voice messages will be automatically transcribed.
 > - **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.
+> - **Alibaba Cloud Coding Plan**: If you're on the Alibaba Cloud Coding Plan (BaiLian coding assistance), add configuration for `dashscope_coding_plan` provider with an API key starting with `sk-sp-` in your config. This provider uses OpenAI-compatible endpoint `https://coding.dashscope.aliyuncs.com/v1`.
 > - **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.
 
diff --git a/nanobot/config/schema.py b/nanobot/config/schema.py
index 61a7bd2..538fab8 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):
@@ -72,9 +76,13 @@ 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 +113,9 @@ 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 +193,32 @@ class QQConfig(Base):
     enabled: bool = False
     app_id: str = ""  # 机器人 ID (AppID) from q.qq.com
     secret: str = ""  # 机器人密钥 (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
+    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
+    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 +237,9 @@ 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
@@ -255,13 +272,20 @@ class ProvidersConfig(Base):
     groq: ProviderConfig = Field(default_factory=ProviderConfig)
     zhipu: ProviderConfig = Field(default_factory=ProviderConfig)
     dashscope: ProviderConfig = Field(default_factory=ProviderConfig)  # 阿里云通义千问
+    dashscope_coding_plan: ProviderConfig = Field(
+        default_factory=ProviderConfig
+    )  # 阿里云百炼Coding Plan
     vllm: ProviderConfig = Field(default_factory=ProviderConfig)
     gemini: ProviderConfig = Field(default_factory=ProviderConfig)
     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 (硅基流动) API gateway
-    volcengine: ProviderConfig = Field(default_factory=ProviderConfig)  # VolcEngine (火山引擎) API gateway
+    siliconflow: ProviderConfig = Field(
+        default_factory=ProviderConfig
+    )  # SiliconFlow (硅基流动) API gateway
+    volcengine: ProviderConfig = Field(
+        default_factory=ProviderConfig
+    )  # VolcEngine (火山引擎) API gateway
     openai_codex: ProviderConfig = Field(default_factory=ProviderConfig)  # OpenAI Codex (OAuth)
     github_copilot: ProviderConfig = Field(default_factory=ProviderConfig)  # Github Copilot (OAuth)
 
@@ -291,7 +315,9 @@ 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)
 
 
@@ -336,7 +362,9 @@ 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/registry.py b/nanobot/providers/registry.py
index df915b7..da04cd7 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" → model becomes "dashscope/{model}"
-    skip_prefixes: tuple[str, ...] = ()      # don't prefix if model already starts with these
+    litellm_prefix: str = ""  # "dashscope" → 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",
@@ -80,17 +79,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         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 → openrouter/claude-3
+        litellm_prefix="openrouter",  # claude-3 → openrouter/claude-3
         skip_prefixes=(),
         env_extras=(),
         is_gateway=True,
@@ -102,16 +99,15 @@ 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",            # → openai/{model}
+        litellm_prefix="openai",  # → openai/{model}
         skip_prefixes=(),
         env_extras=(),
         is_gateway=True,
@@ -119,10 +115,9 @@ 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 → claude-3 → openai/claude-3
+        strip_model_prefix=True,  # anthropic/claude-3 → claude-3 → openai/claude-3
         model_overrides=(),
     ),
-
     # SiliconFlow (硅基流动): OpenAI-compatible gateway, model names keep org prefix
     ProviderSpec(
         name="siliconflow",
@@ -140,7 +135,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-
     # VolcEngine (火山引擎): OpenAI-compatible gateway
     ProviderSpec(
         name="volcengine",
@@ -158,9 +152,7 @@ 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 +171,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         model_overrides=(),
         supports_prompt_caching=True,
     ),
-
     # OpenAI: LiteLLM recognizes "gpt-*" natively, no prefix needed.
     ProviderSpec(
         name="openai",
@@ -197,14 +188,13 @@ 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 +204,15 @@ 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 → github_copilot/model
+        litellm_prefix="github_copilot",  # github_copilot/model → github_copilot/model
         skip_prefixes=("github_copilot/",),
         env_extras=(),
         is_gateway=False,
@@ -233,17 +222,16 @@ 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 → deepseek/deepseek-chat
-        skip_prefixes=("deepseek/",),       # avoid double-prefix
+        litellm_prefix="deepseek",  # deepseek-chat → deepseek/deepseek-chat
+        skip_prefixes=("deepseek/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -253,15 +241,14 @@ 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 → gemini/gemini-pro
-        skip_prefixes=("gemini/",),         # avoid double-prefix
+        litellm_prefix="gemini",  # gemini-pro → gemini/gemini-pro
+        skip_prefixes=("gemini/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -271,7 +258,6 @@ 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 +266,9 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("zhipu", "glm", "zai"),
         env_key="ZAI_API_KEY",
         display_name="Zhipu AI",
-        litellm_prefix="zai",              # glm-4 → zai/glm-4
+        litellm_prefix="zai",  # glm-4 → 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 +277,13 @@ 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 → dashscope/qwen-max
+        litellm_prefix="dashscope",  # qwen-max → dashscope/qwen-max
         skip_prefixes=("dashscope/", "openrouter/"),
         env_extras=(),
         is_gateway=False,
@@ -311,7 +294,6 @@ 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 +302,17 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("moonshot", "kimi"),
         env_key="MOONSHOT_API_KEY",
         display_name="Moonshot",
-        litellm_prefix="moonshot",          # kimi-k2.5 → moonshot/kimi-k2.5
+        litellm_prefix="moonshot",  # kimi-k2.5 → 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 +320,7 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("minimax",),
         env_key="MINIMAX_API_KEY",
         display_name="MiniMax",
-        litellm_prefix="minimax",            # MiniMax-M2.1 → minimax/MiniMax-M2.1
+        litellm_prefix="minimax",  # MiniMax-M2.1 → minimax/MiniMax-M2.1
         skip_prefixes=("minimax/", "openrouter/"),
         env_extras=(),
         is_gateway=False,
@@ -354,9 +331,7 @@ 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 +339,38 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("vllm",),
         env_key="HOSTED_VLLM_API_KEY",
         display_name="vLLM/Local",
-        litellm_prefix="hosted_vllm",      # Llama-3-8B → hosted_vllm/Llama-3-8B
+        litellm_prefix="hosted_vllm",  # Llama-3-8B → 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=(),
+    ),
+    # === Coding Plan Gateway Providers =====================================
+    # Alibaba Cloud Coding Plan: OpenAI-compatible gateway for coding assistance.
+    # Uses special API key format starting with "sk-sp-" to distinguish it
+    # from regular dashscope keys. Uses the OpenAI-compatible endpoint.
+    ProviderSpec(
+        name="dashscope_coding_plan",
+        keywords=("dashscope-coding-plan", "coding-plan", "aliyun-coding", "bailian-coding"),
+        env_key="DASHSCOPE_CODING_PLAN_API_KEY",
+        display_name="Alibaba Cloud Coding Plan",
+        litellm_prefix="dashscope",  # → dashscope/{model}
+        skip_prefixes=("dashscope/", "openrouter/"),
+        env_extras=(),
+        is_gateway=True,
+        is_local=False,
+        detect_by_key_prefix="sk-sp-",  # coding plan API keys start with "sk-sp-"
+        detect_by_base_keyword="coding.dashscope",
+        default_api_base="https://coding.dashscope.aliyuncs.com/v1",
         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 — it rarely wins fallback.
     ProviderSpec(
@@ -385,8 +378,8 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("groq",),
         env_key="GROQ_API_KEY",
         display_name="Groq",
-        litellm_prefix="groq",              # llama3-8b-8192 → groq/llama3-8b-8192
-        skip_prefixes=("groq/",),           # avoid double-prefix
+        litellm_prefix="groq",  # llama3-8b-8192 → groq/llama3-8b-8192
+        skip_prefixes=("groq/",),  # avoid double-prefix
         env_extras=(),
         is_gateway=False,
         is_local=False,
@@ -403,6 +396,7 @@ 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 — those are matched by api_key/api_base instead."""
@@ -418,7 +412,9 @@ 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
 

From 323e5f22cc1be888e2b6f291233d9a96a97edd6c Mon Sep 17 00:00:00 2001
From: suger-m <gau306323@gmail.com>
Date: Thu, 5 Mar 2026 11:14:04 +0800
Subject: [PATCH 04/15] refactor(channels): extract split_message utility to
 reduce code duplication

Extract the _split_message function from discord.py and telegram.py
into a shared utility function in utils/helpers.py.

Changes:
- Add split_message() to nanobot/utils/helpers.py with configurable max_len
- Update Discord channel to use shared utility (2000 char limit)
- Update Telegram channel to use shared utility (4000 char limit)
- Remove duplicate implementations from both channels

Benefits:
- Reduces code duplication
- Centralizes message splitting logic for easier maintenance
- Makes the function reusable for future channels

The function splits content into chunks within max_len, preferring
to break at newlines or spaces rather than mid-word.
---
 nanobot/channels/discord.py  | 25 ++-----------------------
 nanobot/channels/telegram.py | 25 ++++---------------------
 nanobot/utils/helpers.py     | 32 ++++++++++++++++++++++++++++++++
 3 files changed, 38 insertions(+), 44 deletions(-)

diff --git a/nanobot/channels/discord.py b/nanobot/channels/discord.py
index 57e5922..4368540 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."""
 
@@ -104,7 +83,7 @@ class DiscordChannel(BaseChannel):
         headers = {"Authorization": f"Bot {self.config.token}"}
 
         try:
-            chunks = _split_message(msg.content or "")
+            chunks = split_message(msg.content or "", MAX_MESSAGE_LEN)
             if not chunks:
                 return
 
diff --git a/nanobot/channels/telegram.py b/nanobot/channels/telegram.py
index c290535..2742181 100644
--- a/nanobot/channels/telegram.py
+++ b/nanobot/channels/telegram.py
@@ -14,6 +14,9 @@ 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 _markdown_to_telegram_html(text: str) -> str:
@@ -79,26 +82,6 @@ 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.
@@ -269,7 +252,7 @@ class TelegramChannel(BaseChannel):
 
         # Send text content
         if msg.content and msg.content != "[empty message]":
-            for chunk in _split_message(msg.content):
+            for chunk in split_message(msg.content, TELEGRAM_MAX_MESSAGE_LEN):
                 try:
                     html = _markdown_to_telegram_html(chunk)
                     await self._app.bot.send_message(
diff --git a/nanobot/utils/helpers.py b/nanobot/utils/helpers.py
index 3a8c802..8fd81f9 100644
--- a/nanobot/utils/helpers.py
+++ b/nanobot/utils/helpers.py
@@ -34,6 +34,38 @@ 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

From 6770a6e7e9dbebd5ca3ed490a5dd0b30b7c3d7a3 Mon Sep 17 00:00:00 2001
From: ouyangwulin <mr.artboy@gmail.com>
Date: Thu, 5 Mar 2026 17:34:36 +0800
Subject: [PATCH 05/15] supported aliyun coding plan.

---
 nanobot/config/schema.py      | 34 ++++++++++++++++------------------
 nanobot/providers/registry.py |  6 +++---
 2 files changed, 19 insertions(+), 21 deletions(-)

diff --git a/nanobot/config/schema.py b/nanobot/config/schema.py
index 538fab8..15cf2b4 100644
--- a/nanobot/config/schema.py
+++ b/nanobot/config/schema.py
@@ -5,7 +5,7 @@ from typing import Literal
 
 from pydantic import BaseModel, ConfigDict, Field
 from pydantic.alias_generators import to_camel
-from pydantic_settings import BaseSettings
+from pydantic_settings import BaseSettings, SettingsConfigDict
 
 
 class Base(BaseModel):
@@ -198,23 +198,6 @@ class QQConfig(Base):
     )  # 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."""
 
@@ -339,6 +322,20 @@ class MCPServerConfig(Base):
     tool_timeout: int = 30  # Seconds before a tool call is cancelled
 
 
+class TTSConfig(Base):
+    """Text-to-Speech configuration."""
+
+    provider: str = "edge_tts"  # Default TTS provider
+    voice: str = "en-US-ChristopherNeural"  # Default voice
+    speed: float = 1.0  # Voice speed multiplier
+
+
+class AudioConfig(Base):
+    """Audio configuration."""
+
+    tts: TTSConfig = Field(default_factory=TTSConfig)
+
+
 class ToolsConfig(Base):
     """Tools configuration."""
 
@@ -356,6 +353,7 @@ class Config(BaseSettings):
     providers: ProvidersConfig = Field(default_factory=ProvidersConfig)
     gateway: GatewayConfig = Field(default_factory=GatewayConfig)
     tools: ToolsConfig = Field(default_factory=ToolsConfig)
+    audio: AudioConfig = Field(default_factory=AudioConfig)
 
     @property
     def workspace_path(self) -> Path:
diff --git a/nanobot/providers/registry.py b/nanobot/providers/registry.py
index da04cd7..3b6659e 100644
--- a/nanobot/providers/registry.py
+++ b/nanobot/providers/registry.py
@@ -359,15 +359,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("dashscope-coding-plan", "coding-plan", "aliyun-coding", "bailian-coding"),
         env_key="DASHSCOPE_CODING_PLAN_API_KEY",
         display_name="Alibaba Cloud Coding Plan",
-        litellm_prefix="dashscope",  # → dashscope/{model}
-        skip_prefixes=("dashscope/", "openrouter/"),
+        litellm_prefix="openai",  # → openai/{model} (uses OpenAI-compatible endpoint)
+        skip_prefixes=("openai/", "dashscope/", "openrouter/"),
         env_extras=(),
         is_gateway=True,
         is_local=False,
         detect_by_key_prefix="sk-sp-",  # coding plan API keys start with "sk-sp-"
         detect_by_base_keyword="coding.dashscope",
         default_api_base="https://coding.dashscope.aliyuncs.com/v1",
-        strip_model_prefix=False,
+        strip_model_prefix=True,  # Strip "dashscope_coding_plan/" prefix
         model_overrides=(),
     ),
     # === Auxiliary (not a primary LLM provider) ============================

From 46192fbd2abe922390be1961819a86dc75c74321 Mon Sep 17 00:00:00 2001
From: coldxiangyu <coldxiangyu@163.com>
Date: Thu, 5 Mar 2026 20:18:13 +0800
Subject: [PATCH 06/15] fix(context): detect image MIME type from magic bytes
 instead of file extension

Feishu downloads images with incorrect extensions (e.g. .jpg for PNG files).
mimetypes.guess_type() relies on the file extension, causing a MIME mismatch
that Anthropic rejects with 'image was specified using image/jpeg but appears
to be image/png'.

Fix: read the first bytes of the image data and detect the real MIME type via
magic bytes (PNG: 0x89PNG, JPEG: 0xFFD8FF, GIF: GIF87a/GIF89a, WEBP: RIFF+WEBP).
Fall back to mimetypes.guess_type() only when magic bytes are inconclusive.
---
 nanobot/agent/context.py | 23 ++++++++++++++++++++---
 1 file changed, 20 insertions(+), 3 deletions(-)

diff --git a/nanobot/agent/context.py b/nanobot/agent/context.py
index df4825f..7ead317 100644
--- a/nanobot/agent/context.py
+++ b/nanobot/agent/context.py
@@ -12,6 +12,19 @@ from nanobot.agent.memory import MemoryStore
 from nanobot.agent.skills import SkillsLoader
 
 
+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
+
+
 class ContextBuilder:
     """Builds the context (system prompt + messages) for the agent."""
 
@@ -136,10 +149,14 @@ 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:

From 5ced08b1f23f5ef275465fbe3140f64d42c95ced Mon Sep 17 00:00:00 2001
From: pikaqqqqqq <pikaqqqqqq@users.noreply.github.com>
Date: Fri, 6 Mar 2026 01:54:00 +0800
Subject: [PATCH 07/15] fix(feishu): use msg_type "media" for mp4 video files

Previously, mp4 video files were sent with msg_type "file", which meant
users had to download them to play. Feishu requires msg_type "media" for
audio and video files to enable inline playback in the chat.

Changes:
- Add _VIDEO_EXTS constant for video file extensions (.mp4, .mov, .avi)
- Use msg_type "media" for both audio (_AUDIO_EXTS) and video (_VIDEO_EXTS)
- Keep msg_type "file" for documents and other file types

The upload_file API already uses file_type="mp4" for video files via the
existing _FILE_TYPE_MAP, so only the send msg_type needed fixing.
---
 nanobot/channels/feishu.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/nanobot/channels/feishu.py b/nanobot/channels/feishu.py
index e6f0049..3847ac1 100644
--- a/nanobot/channels/feishu.py
+++ b/nanobot/channels/feishu.py
@@ -474,6 +474,7 @@ class FeishuChannel(BaseChannel):
 
     _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",
@@ -682,7 +683,12 @@ 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),

From 9ab4155991627e45dd2c88b028d35c55b82ecce9 Mon Sep 17 00:00:00 2001
From: nanobot-contributor <noreply@github.com>
Date: Fri, 6 Mar 2026 09:57:03 +0800
Subject: [PATCH 08/15] fix(cli): add Windows compatibility for signal handlers
 (PR #1400)

SIGHUP and SIGPIPE are not available on Windows. Add hasattr() checks
before registering these signal handlers to prevent AttributeError on
Windows systems.

Fixes compatibility issue introduced in PR #1400.
---
 nanobot/cli/commands.py | 20 ++++++++++++++++++--
 1 file changed, 18 insertions(+), 2 deletions(-)

diff --git a/nanobot/cli/commands.py b/nanobot/cli/commands.py
index aca0778..eb3d833 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
@@ -525,9 +537,13 @@ def agent(
 
         signal.signal(signal.SIGINT, _handle_signal)
         signal.signal(signal.SIGTERM, _handle_signal)
-        signal.signal(signal.SIGHUP, _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
-        signal.signal(signal.SIGPIPE, signal.SIG_IGN)
+        # 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())

From c3526a7fdb2418d68c03d34db5ee43b624edbce9 Mon Sep 17 00:00:00 2001
From: PiKaqqqqqq <281705236@qq.com>
Date: Fri, 6 Mar 2026 10:11:53 +0800
Subject: [PATCH 09/15] fix(feishu): smart message format selection (fixes
 #1548)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Instead of always sending interactive cards, detect the optimal
message format based on content:
- text: short plain text (≤200 chars, no markdown)
- post: medium text with links (≤2000 chars)
- interactive: complex content (code, tables, headings, bold, lists)
---
 nanobot/channels/feishu.py | 143 +++++++++++++++++++++++++++++++++++--
 pr-description.md          |  47 ++++++++++++
 2 files changed, 186 insertions(+), 4 deletions(-)
 create mode 100644 pr-description.md

diff --git a/nanobot/channels/feishu.py b/nanobot/channels/feishu.py
index e6f0049..c405493 100644
--- a/nanobot/channels/feishu.py
+++ b/nanobot/channels/feishu.py
@@ -472,6 +472,121 @@ 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"|(?<!\*)\*(?!\*)(.+?)(?<!\*)\*(?!\*)"  # *italic* (single *)
+        r"|~~.+?~~"                   # ~~strikethrough~~
+        , re.DOTALL,
+    )
+
+    # Markdown link: [text](url)
+    _MD_LINK_RE = re.compile(r"\[([^\]]+)\]\((https?://[^\)]+)\)")
+
+    # Unordered list items
+    _LIST_RE = re.compile(r"^[\s]*[-*+]\s+", re.MULTILINE)
+
+    # Ordered list items
+    _OLIST_RE = re.compile(r"^[\s]*\d+\.\s+", re.MULTILINE)
+
+    # Max length for plain text format
+    _TEXT_MAX_LEN = 200
+
+    # Max length for post (rich text) format; beyond this, use card
+    _POST_MAX_LEN = 2000
+
+    @classmethod
+    def _detect_msg_format(cls, content: str) -> 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) → always card
+        if cls._COMPLEX_MD_RE.search(stripped):
+            return "interactive"
+
+        # Long content → card (better readability with card layout)
+        if len(stripped) > cls._POST_MAX_LEN:
+            return "interactive"
+
+        # Has bold/italic/strikethrough → card (post format can't render these)
+        if cls._SIMPLE_MD_RE.search(stripped):
+            return "interactive"
+
+        # Has list items → 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 → post format (supports <a> tags)
+        if cls._MD_LINK_RE.search(stripped):
+            return "post"
+
+        # Short plain text → text format
+        if len(stripped) <= cls._TEXT_MAX_LEN:
+            return "text"
+
+        # Medium plain text without any formatting → 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 → 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"}
     _FILE_TYPE_MAP = {
@@ -689,14 +804,34 @@ class FeishuChannel(BaseChannel):
                         )
 
             if msg.content and msg.content.strip():
-                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}
+                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, "interactive", json.dumps(card, ensure_ascii=False),
+                        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)
 
diff --git a/pr-description.md b/pr-description.md
new file mode 100644
index 0000000..dacab5c
--- /dev/null
+++ b/pr-description.md
@@ -0,0 +1,47 @@
+## fix(feishu): smart message format selection (fixes #1548)
+
+### Problem
+
+Currently, the Feishu channel sends **all** messages as interactive cards (`msg_type: "interactive"`). This is overkill for short, simple replies like "OK" or "收到" — they look heavy and unnatural compared to normal chat messages.
+
+### Solution
+
+Implement smart message format selection that picks the most appropriate Feishu message type based on content analysis:
+
+| Content Type | Format | `msg_type` |
+|---|---|---|
+| Short plain text (≤ 200 chars, no markdown) | Text | `text` |
+| Medium text with links (≤ 2000 chars, no complex formatting) | Rich Text Post | `post` |
+| Long text, code blocks, tables, headings, bold/italic, lists | Interactive Card | `interactive` |
+
+### How it works
+
+1. **`_detect_msg_format(content)`** — Analyzes the message content and returns the optimal format:
+   - Checks for complex markdown (code blocks, tables, headings) → `interactive`
+   - Checks for simple markdown (bold, italic, lists) → `interactive`  
+   - Checks for links → `post` (Feishu post format supports `<a>` tags natively)
+   - Short plain text → `text`
+   - Medium plain text → `post`
+
+2. **`_markdown_to_post(content)`** — Converts markdown links `[text](url)` to Feishu post format with proper `a` tags. Each line becomes a paragraph in the post body.
+
+3. **Modified `send()` method** — Uses `_detect_msg_format()` to choose the right format, then dispatches to the appropriate sending logic.
+
+### Design decisions
+
+- **Post format for links only**: Feishu's post format (`[[{"tag":"text",...}]]`) doesn't support bold/italic rendering, so we only use it for messages containing links (where the `a` tag adds real value). Messages with bold/italic/lists still use cards which render markdown properly.
+- **Conservative thresholds**: 200 chars for text, 2000 chars for post — these keep the UX natural without being too aggressive.
+- **Backward compatible**: The card rendering path is completely unchanged. Only the routing logic is new.
+
+### Testing
+
+Format detection tested against 13 cases covering all content types:
+- ✅ Plain text → `text`
+- ✅ Links → `post`  
+- ✅ Bold/italic/code/tables/headings/lists → `interactive`
+- ✅ Long content → `interactive`
+- ✅ Post format generates valid Feishu post JSON with proper `a` tags
+
+### Changes
+
+- `nanobot/channels/feishu.py`: Added `_detect_msg_format()`, `_markdown_to_post()`, and updated `send()` method

From 6fb4204ac6a5109a4ff068a17975615498c40c05 Mon Sep 17 00:00:00 2001
From: nanobot-contributor <noreply@github.com>
Date: Fri, 6 Mar 2026 11:47:00 +0800
Subject: [PATCH 10/15] fix(memory): handle list type tool call arguments

Some LLM providers return tool_calls[0].arguments as a list instead of
dict or str. Add handling to extract the first dict element from the list.

Fixes /new command warning: 'unexpected arguments type list'
---
 nanobot/agent/memory.py                  |  7 +++
 tests/test_memory_consolidation_types.py | 75 ++++++++++++++++++++++++
 2 files changed, 82 insertions(+)

diff --git a/nanobot/agent/memory.py b/nanobot/agent/memory.py
index 93c1825..80fba5e 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 type list with non-dict content")
+                    return False
             if not isinstance(args, dict):
                 logger.warning("Memory consolidation: unexpected arguments type {}", type(args).__name__)
                 return False
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

From fc0b38c3047c20241c94b38f1be6138191da41f6 Mon Sep 17 00:00:00 2001
From: Re-bin <xubinrencs@gmail.com>
Date: Fri, 6 Mar 2026 05:27:39 +0000
Subject: [PATCH 11/15] fix(memory): improve warning message for empty/non-dict
 list arguments

---
 nanobot/agent/memory.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nanobot/agent/memory.py b/nanobot/agent/memory.py
index 80fba5e..21fe77d 100644
--- a/nanobot/agent/memory.py
+++ b/nanobot/agent/memory.py
@@ -133,7 +133,7 @@ class MemoryStore:
                 if args and isinstance(args[0], dict):
                     args = args[0]
                 else:
-                    logger.warning("Memory consolidation: unexpected arguments type list with non-dict content")
+                    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__)

From ba63f6f62d9b2181b56863d8efe32215fe8f6321 Mon Sep 17 00:00:00 2001
From: Re-bin <xubinrencs@gmail.com>
Date: Fri, 6 Mar 2026 06:09:46 +0000
Subject: [PATCH 12/15] chore: remove pr-description.md from repo

---
 pr-description.md | 47 -----------------------------------------------
 1 file changed, 47 deletions(-)
 delete mode 100644 pr-description.md

diff --git a/pr-description.md b/pr-description.md
deleted file mode 100644
index dacab5c..0000000
--- a/pr-description.md
+++ /dev/null
@@ -1,47 +0,0 @@
-## fix(feishu): smart message format selection (fixes #1548)
-
-### Problem
-
-Currently, the Feishu channel sends **all** messages as interactive cards (`msg_type: "interactive"`). This is overkill for short, simple replies like "OK" or "收到" — they look heavy and unnatural compared to normal chat messages.
-
-### Solution
-
-Implement smart message format selection that picks the most appropriate Feishu message type based on content analysis:
-
-| Content Type | Format | `msg_type` |
-|---|---|---|
-| Short plain text (≤ 200 chars, no markdown) | Text | `text` |
-| Medium text with links (≤ 2000 chars, no complex formatting) | Rich Text Post | `post` |
-| Long text, code blocks, tables, headings, bold/italic, lists | Interactive Card | `interactive` |
-
-### How it works
-
-1. **`_detect_msg_format(content)`** — Analyzes the message content and returns the optimal format:
-   - Checks for complex markdown (code blocks, tables, headings) → `interactive`
-   - Checks for simple markdown (bold, italic, lists) → `interactive`  
-   - Checks for links → `post` (Feishu post format supports `<a>` tags natively)
-   - Short plain text → `text`
-   - Medium plain text → `post`
-
-2. **`_markdown_to_post(content)`** — Converts markdown links `[text](url)` to Feishu post format with proper `a` tags. Each line becomes a paragraph in the post body.
-
-3. **Modified `send()` method** — Uses `_detect_msg_format()` to choose the right format, then dispatches to the appropriate sending logic.
-
-### Design decisions
-
-- **Post format for links only**: Feishu's post format (`[[{"tag":"text",...}]]`) doesn't support bold/italic rendering, so we only use it for messages containing links (where the `a` tag adds real value). Messages with bold/italic/lists still use cards which render markdown properly.
-- **Conservative thresholds**: 200 chars for text, 2000 chars for post — these keep the UX natural without being too aggressive.
-- **Backward compatible**: The card rendering path is completely unchanged. Only the routing logic is new.
-
-### Testing
-
-Format detection tested against 13 cases covering all content types:
-- ✅ Plain text → `text`
-- ✅ Links → `post`  
-- ✅ Bold/italic/code/tables/headings/lists → `interactive`
-- ✅ Long content → `interactive`
-- ✅ Post format generates valid Feishu post JSON with proper `a` tags
-
-### Changes
-
-- `nanobot/channels/feishu.py`: Added `_detect_msg_format()`, `_markdown_to_post()`, and updated `send()` method

From 3a01fe536a37c8424fc196b1b0aad3535a50af93 Mon Sep 17 00:00:00 2001
From: Re-bin <xubinrencs@gmail.com>
Date: Fri, 6 Mar 2026 06:49:09 +0000
Subject: [PATCH 13/15] refactor: move detect_image_mime to utils/helpers for
 reuse

---
 nanobot/agent/context.py | 16 ++--------------
 nanobot/utils/helpers.py | 13 +++++++++++++
 2 files changed, 15 insertions(+), 14 deletions(-)

diff --git a/nanobot/agent/context.py b/nanobot/agent/context.py
index 7ead317..27511fa 100644
--- a/nanobot/agent/context.py
+++ b/nanobot/agent/context.py
@@ -10,19 +10,7 @@ from typing import Any
 
 from nanobot.agent.memory import MemoryStore
 from nanobot.agent.skills import SkillsLoader
-
-
-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
+from nanobot.utils.helpers import detect_image_mime
 
 
 class ContextBuilder:
@@ -153,7 +141,7 @@ Reply directly with text for conversations. Only use the 'message' tool to send
                 continue
             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]
+            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()
diff --git a/nanobot/utils/helpers.py b/nanobot/utils/helpers.py
index 3a8c802..b543174 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)

From b817463939c9529ab119fec1c7be89dd2da68606 Mon Sep 17 00:00:00 2001
From: Re-bin <xubinrencs@gmail.com>
Date: Fri, 6 Mar 2026 07:13:04 +0000
Subject: [PATCH 14/15] chore: simplify Alibaba Coding Plan to apiBase hint,
 remove dedicated provider

---
 README.md                     |  2 +-
 nanobot/config/schema.py      | 28 +++-------------------------
 nanobot/providers/registry.py | 20 --------------------
 3 files changed, 4 insertions(+), 46 deletions(-)

diff --git a/README.md b/README.md
index 627bb37..0c49608 100644
--- a/README.md
+++ b/README.md
@@ -662,9 +662,9 @@ Config file: `~/.nanobot/config.json`
 > [!TIP]
 > - **Groq** provides free voice transcription via Whisper. If configured, Telegram voice messages will be automatically transcribed.
 > - **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.
-> - **Alibaba Cloud Coding Plan**: If you're on the Alibaba Cloud Coding Plan (BaiLian coding assistance), add configuration for `dashscope_coding_plan` provider with an API key starting with `sk-sp-` in your config. This provider uses OpenAI-compatible endpoint `https://coding.dashscope.aliyuncs.com/v1`.
 > - **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 |
 |----------|---------|-------------|
diff --git a/nanobot/config/schema.py b/nanobot/config/schema.py
index e80c8d0..2073eeb 100644
--- a/nanobot/config/schema.py
+++ b/nanobot/config/schema.py
@@ -5,7 +5,7 @@ from typing import Literal
 
 from pydantic import BaseModel, ConfigDict, Field
 from pydantic.alias_generators import to_camel
-from pydantic_settings import BaseSettings, SettingsConfigDict
+from pydantic_settings import BaseSettings
 
 
 class Base(BaseModel):
@@ -258,20 +258,13 @@ class ProvidersConfig(Base):
     groq: ProviderConfig = Field(default_factory=ProviderConfig)
     zhipu: ProviderConfig = Field(default_factory=ProviderConfig)
     dashscope: ProviderConfig = Field(default_factory=ProviderConfig)  # 阿里云通义千问
-    dashscope_coding_plan: ProviderConfig = Field(
-        default_factory=ProviderConfig
-    )  # 阿里云百炼Coding Plan
     vllm: ProviderConfig = Field(default_factory=ProviderConfig)
     gemini: ProviderConfig = Field(default_factory=ProviderConfig)
     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 (硅基流动) API gateway
-    volcengine: ProviderConfig = Field(
-        default_factory=ProviderConfig
-    )  # VolcEngine (火山引擎) API gateway
+    siliconflow: ProviderConfig = Field(default_factory=ProviderConfig)  # SiliconFlow (硅基流动)
+    volcengine: ProviderConfig = Field(default_factory=ProviderConfig)  # VolcEngine (火山引擎)
     openai_codex: ProviderConfig = Field(default_factory=ProviderConfig)  # OpenAI Codex (OAuth)
     github_copilot: ProviderConfig = Field(default_factory=ProviderConfig)  # Github Copilot (OAuth)
 
@@ -326,20 +319,6 @@ class MCPServerConfig(Base):
     tool_timeout: int = 30  # seconds before a tool call is cancelled
 
 
-class TTSConfig(Base):
-    """Text-to-Speech configuration."""
-
-    provider: str = "edge_tts"  # Default TTS provider
-    voice: str = "en-US-ChristopherNeural"  # Default voice
-    speed: float = 1.0  # Voice speed multiplier
-
-
-class AudioConfig(Base):
-    """Audio configuration."""
-
-    tts: TTSConfig = Field(default_factory=TTSConfig)
-
-
 class ToolsConfig(Base):
     """Tools configuration."""
 
@@ -357,7 +336,6 @@ class Config(BaseSettings):
     providers: ProvidersConfig = Field(default_factory=ProvidersConfig)
     gateway: GatewayConfig = Field(default_factory=GatewayConfig)
     tools: ToolsConfig = Field(default_factory=ToolsConfig)
-    audio: AudioConfig = Field(default_factory=AudioConfig)
 
     @property
     def workspace_path(self) -> Path:
diff --git a/nanobot/providers/registry.py b/nanobot/providers/registry.py
index 3b6659e..59ba31a 100644
--- a/nanobot/providers/registry.py
+++ b/nanobot/providers/registry.py
@@ -350,26 +350,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         strip_model_prefix=False,
         model_overrides=(),
     ),
-    # === Coding Plan Gateway Providers =====================================
-    # Alibaba Cloud Coding Plan: OpenAI-compatible gateway for coding assistance.
-    # Uses special API key format starting with "sk-sp-" to distinguish it
-    # from regular dashscope keys. Uses the OpenAI-compatible endpoint.
-    ProviderSpec(
-        name="dashscope_coding_plan",
-        keywords=("dashscope-coding-plan", "coding-plan", "aliyun-coding", "bailian-coding"),
-        env_key="DASHSCOPE_CODING_PLAN_API_KEY",
-        display_name="Alibaba Cloud Coding Plan",
-        litellm_prefix="openai",  # → openai/{model} (uses OpenAI-compatible endpoint)
-        skip_prefixes=("openai/", "dashscope/", "openrouter/"),
-        env_extras=(),
-        is_gateway=True,
-        is_local=False,
-        detect_by_key_prefix="sk-sp-",  # coding plan API keys start with "sk-sp-"
-        detect_by_base_keyword="coding.dashscope",
-        default_api_base="https://coding.dashscope.aliyuncs.com/v1",
-        strip_model_prefix=True,  # Strip "dashscope_coding_plan/" prefix
-        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 — it rarely wins fallback.

From dcebb94b014cd80dd93e80acad0664cf708ae767 Mon Sep 17 00:00:00 2001
From: Re-bin <xubinrencs@gmail.com>
Date: Fri, 6 Mar 2026 07:16:20 +0000
Subject: [PATCH 15/15] style: remove trailing whitespace

---
 nanobot/providers/litellm_provider.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nanobot/providers/litellm_provider.py b/nanobot/providers/litellm_provider.py
index a1819a2..620424e 100644
--- a/nanobot/providers/litellm_provider.py
+++ b/nanobot/providers/litellm_provider.py
@@ -298,7 +298,7 @@ class LiteLLMProvider(LLMProvider):
 
         reasoning_content = getattr(message, "reasoning_content", None) or None
         thinking_blocks = getattr(message, "thinking_blocks", None) or None
-        
+
         return LLMResponse(
             content=content,
             tool_calls=tool_calls,