追踪 AI Agent、MCP、模型连接工具、智能体框架和自动化工作流。
## What's Changed * test: record what the Windows inode gates are hiding, and un-skip one by @yiliang114 in https://github.com/QwenLM/qwen-code/pull/11853 * fix(cua): preserve Linux observations and REPL diagnostics by @DragonnZhang in https://github.com/QwenL
## Highlights _See the complete change list below._ ## Breaking Changes - Removes configurable message-prefix filtering from channels, so eligible messages now follow normal sender, group, mention, and pairing policies without a prefix. ([#11571](https://githu
As local models become more capable, AI agents can handle more work directly on a PC while keeping sensitive information on the device. Portable Computer is a local version of the agent Perplexity Computer that plans and carries out multistep tasks. Accelerate
## Verify Docker Image Signature All LiteLLM Docker images are signed with [cosign](https://docs.sigstore.dev/cosign/overview/). Every release is signed with the same key introduced in [commit `0112e53`](https://github.com/BerriAI/litellm/commit/0112e53046018d
## What's changed - Fixed read-only git commands in Bash unexpectedly asking for permission after a session had been running for a while (regression in 2.1.269)
## What's changed - Added `claude plugin eval`: run a plugin's eval suite against Claude Code and get scored, reproducible results (JSON + HTML report); see `claude plugin eval --help` - Added `/output-style [name]` to list and switch output styles, including
Changes since langchain-core==1.6.2 release(core): 1.6.3 (#40407) feat(core): Allow model name and provider tracing metadata override based on gateway response (#40406) test(core): cover the deprecated `.text()` access path (#40243) docs(core): remove stale Ar
## Verify Docker Image Signature All LiteLLM Docker images are signed with [cosign](https://docs.sigstore.dev/cosign/overview/). Every release is signed with the same key introduced in [commit `0112e53`](https://github.com/BerriAI/litellm/commit/0112e53046018d
Changes since langchain-anthropic==1.7.1 release(anthropic): 1.7.2 (#40387) fix(anthropic): preserve invalid tool use blocks (#40372)
This blog post is the fourth and final installment of The Economics of Agent Optimization, which shares the strategies, capabilities, and proof points that can help you optimize agent costs and run AI as a managed investment system on Microsoft Foundry. The po
Meet the Data agent in ChatGPT Work. Connect company data, uncover insights, and build interactive dashboards with AI using natural language.
> [!WARNING] > **Self-hosted deployments using the bundled Weaviate must complete a manual, staged upgrade before starting 1.17.1.** The bundled Weaviate server moves from `1.27.0` to `1.39.2` — 12 minor versions — and skipping minors **is unsupported**. Pulli
## What's Changed ### Features - Add telemetry to track checkpoint runtime and CLI usage. ### Bug Fixes - Fix gateway errors reported inside an HTTP 200 response. - Keep deploy push on the AMP create source. - Report scrape failures instead of raising IndexErr
Changes since langchain-openai==1.6.1 release(openai): 1.6.2 (#40339) fix(openai): add GPT-6 Astra reasoning efforts (#40330) chore(deps): bump httpx2 from 2.10.0 to 2.12.0 in /libs/partners/openai (#40309)
Changes since langchain-openai==1.6.0 fix(openai): bump `max_completion_tokens` in cache breakpoint integration test (#40284) release(openai): 1.6.1 (#40268) chore(model-profiles): refresh model profile data (#40217) fix(openai): support Azure AD auth with Ope
## Highlight - **Realtime Voice Agent**: Introduced a realtime voice agent with DashScope backends and local transport support. - **A2A Protocol Support**: Added `A2AAgent` class to the agent module, enabling agent-to-agent communication. - **New Pipeline Modu
`pip install -U mcp`. Docs: https://py.sdk.modelcontextprotocol.io/ A few defaults changed in this release. If you run a server or client on 2.x, skim these first: ## Behaviour changes **HTTP client redirects are only followed within the endpoint's origin** (#
Maintenance release of the 1.x line. 2.x is the current line; 1.x docs are at https://py.sdk.modelcontextprotocol.io/v1/. A few defaults changed in this release. If you run a server or client on 1.x, skim these first: ## Behaviour changes **HTTP client redirec
Inside OpenAI, coding agents are reshaping AI research. Explore early data on agent usage, experiment velocity, task complexity, and research acceleration.
Changes since langchain-core==1.6.1 release(core): 1.6.2 (#40209) feat(openai): support async tools (#40208) chore(deps): bump mistune from 3.3.0 to 3.3.3 in /libs/core (#40150) chore(deps): bump tornado from 6.5.7 to 6.5.8 in /libs/core (#40113) fix(core): av
Enterprise work spans messages, decisions, projects, and obligations that change over time. An AI agent that starts without this context must reconstruct it...
## What's Changed ### Bug Fixes - Fix legacy platform tool alias discovery ### Documentation - Update snapshot and changelog for v1.15.19 ## Contributors @joaomdmoura, @vinibrsl
## What's Changed ### Features - Add Clipper integrations client - Add `now()` to the CEL expression environment - Record how a crew run ended for every user - Report machine size as a coarse band, not a core count - Add injectable client for CrewAI platform t
Changes since langchain==1.3.18 docs(langchain): runnable `langchain.mcp` examples (#39976) feat(langchain): `langchain.mcp` namespace, `MCPAdapter` (#39939) perf(anthropic,langchain): omit middleware trace inputs (#40098) fix(langchain): include model destina
Status: Resolved The issue causing elevated errors across ChatGPT and Codex has been resolved. Some Codex remote control users may need to pair their mobile device again following this incident. Affected components GPTs (Operational) Agent (Operational) CLI (O
Status: Resolved All impacted services have now fully recovered. Affected components GPTs (Operational) Agent (Operational) Connectors/Apps (Operational) Codex in ChatGPT Desktop (Operational) Sites (Operational) Image Generation (Operational) Deep Research (O
AI agents are learning to do more by working together. A lead agent can break a complex task into smaller jobs and assign those jobs to specialized subagents....
AI cost optimization goes beyond model selection. Discover how context engineering in Microsoft Foundry helps lower AI costs by improving knowledge retrieval, tool selection, memory, and agent performance at scale. The post The Economics of Agent Optimization:
## What's Changed * fix(kosong): omit empty anthropic-beta header when no beta features declared by @7Sageer in https://github.com/MoonshotAI/kimi-cli/pull/2580 * chore(release): bump kosong to 0.56.0 by @jackfish212 in https://github.com/MoonshotAI/kimi-cli/p
# Introducing Dify Agent *(Beta)*: A New Agent Experience in Dify > [!WARNING] > You should provide Dify Agent services ⚠️**only to trusted, non-malicious users**⚠️. As many of you know, the shell-based LLM agent paradigm has brought a major leap in agent capa
