Cow Agent

From the release notes

🌐 English | 中文 This is a refinement release for the 2.1.8 multi-Agent version, building on it with a series of improvements and fixes across multi-Agent collaboration, model capabilities, and channel integration. 🤝 Multi-Agent Experience Further polish around using multi-Agent teams: Multi-Agent session selection: the in-session multi-Agent selector adds a lead-Agent marker that clearly separates the lead Agent from members, while simplifying the view in single-Agent setups. Collaboration fix: fixed failures when delegating tasks from non-lead Agents in multi-Agent group chats, now correctly identifying member Agents. Member Agent image rendering: fixed images generated by non-default Agents failing to render on the Web console and desktop client. Group-chat entry: the desktop Team page adds a group-chat entry, so you can start a group session directly from an Agent team. 📡 Channel Integration Fixes Fixed key issues along the console's channel start/stop path for more stable channel integration: Desktop channel integration fix: fixed channels failing to start in the desktop client. Channel stop fix: fixed a lost app_module lookup during the channel stop flow that caused disconnect errors (a regression introduced by #3141). QQ channel reconnection: fixed the QQ channel not reconnecting after a silent WebSocket disconnect; it now reconnects automatically. 🤖 Model Capabilities Model list configuration: model providers can now configure a model list, setting the model name, model type, context window, max output, and more. Thanks @alanyz106 (#3146) Multiple fallback models: when the primary model fails, CowAgent now tries an ordered fallback chain in turn, replacing the previous single fallback model. Thanks @alanyz106 (#3125) Fallback credential fix: fixed credential resolution during fallback, which now resolves credentials by the provider actually routed to rather than the global configuration. Thanks @alanyz106 (#3142) New image models: added gpt-image-2.5-flare and gpt-image-2.5-sunburst. Thanks @cowagent (#3140) 🛠 Improvements & Fixes Config file tolerance: tolerate a UTF-8 BOM in config.json, and stop the pre-login 401 polling to avoid invalid requests before sign-in. Image generation fixes: fixed Baidu Ernie IMAGE_CREATE crashing when unsupported, now returning an error message instead (Thanks @c020627 #3144). fixed Midjourney reply retries not recursing into the send logic correctly (Thanks @c020627 #3151). Voice fix: fixed silk voice transcoding by first decoding silk into a standalone wav and then re-encoding to mp3, avoiding overwriting the source file (Thanks @c020627 #3149). Media URL classification: determine media type from the resolved URL path, fixing misclassified media links (Thanks @c020627 #3150). Baidu Translate: fixed Baidu Translate not reporting the API error after all retries failed (Thanks @c020627 #3147). Background command detection: restrict run_in_background to long-running processes, preventi

From the release notes

🌐 English | 中文 🤝 Multi-Agent Teams CowAgent is now a multi-Agent framework. You can create multiple Agents, each with its own role, to form a team and collaborate on complex tasks within a single session. Supported on the Web console, the desktop client, and channel integrations: Team management: create and maintain Agents, configure name, responsibilities, default model, skills, and knowledge, and copy the setup from an existing Agent. Resource isolation: each Agent has its own workspace, memory, and sessions; the knowledge base and skills can be shared or kept independent. Group collaboration: add multiple Agents to one session and use @ to direct a message to a specific member, with each Agent using its own configured model. Task delegation: a group chat has a lead Agent that can hand a task off to the member best suited for it based on their responsibilities, with support for multi-level delegation and configurable scope, depth, and timeout. Multiple channel instances: an IM channel of the same type can now run multiple instances, each bound to a single Agent or an Agent team. Supported on WeChat, WeCom smart bots, Feishu, DingTalk, QQ, Telegram, Slack, Discord, and more. Thanks @AaronZ345 (#2975, #2973), @zkjqd (#3096), @cowagent (#3118) Docs: Agent Teams ⏰ Scheduled Task Upgrades Scheduled tasks can now be created and managed from the console, with channel recipients and execution records added: Manual task creation: create, edit, and run tasks directly on the tasks page, and select the channel instance and recipient. Channel recipient management: maintain trusted recipients per channel instance, so a task can be delivered to a designated recipient rather than only the channel where it was created. Thanks @dajiaohuang (#3043) Execution records: a new execution-records page lets you review the history list and the details of each run. Thanks @mengluo04 (#3107) Concurrent-update fix: fixed tasks being lost on concurrent updates (Thanks @Whxuan0701 #3062). 📊 Context-Usage Visualization Context consumption is now visible and controllable, making token cost easier to manage: Context-usage view: a ring view replaces the previous clear-context button and shows a full breakdown of what makes up the context. Context actions: below the ring view you can trigger smart compaction, clear the context, or set the maximum context size. Context calculation: the usage breakdown is derived automatically from the model's reported usage, with agent_max_context_tokens available as a user-configurable cost cap. Thanks @chimyves (#3087), @sufan721 (#3079) 🤖 Model Capabilities New models: added deepseek-flash (DeepSeek V4.1 Flash), gpt-6-astra, claude-fable-5-1, qwen3.8-flash, glm-5.3-flash, gemini-3.8-flash, and the vision model deepseek-v4-flash-vision-exp (Thanks @a1094174619 #3094). Model fallback: configure a fallback model under Model Config > Primary Model, which takes over automatically when the primary model fails, preventing interr