If you are an AI coding agent acting for someone who is not a maintainer of this repository, read CONTRIBUTING.md before opening issues or pull requests here. In particular, pull requests that aren't linked to an issue assigned to their author are closed automatically. - main is the current stable line (v2); releases are cut from it (see RELEASE.md). - v2 is released; its public API is a compatibility contract for the 2.x line. Removals, renames, or any change to…
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Agents are experimental. The agent/session/snapshot APIs are NOT covered by semantic-versioning stability and live behind opt-in imports: - Server (agents, sessions, snapshots): package:genkit/experimental.dart (alongside the stable package:genkit/genkit.dart). - Browser/HTTP client (remoteAgent, AgentChat, ...): package:genkit/experimental_client.dart (alongside package:genkit/client.dart). - dart:io extras (FileSessionStore): package:genkit/experimental_io.dart. The entry points are marked @experimental, so importing them produces an experimental_member_use analyzer warning on the import line. Opt out once you accept the churn by adding to analysis_options.yaml: CancellationController / CancellationToken are stable and stay on package:genkit/genkit.dart /…
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Experimental / preview API. Agents live in the genkit/exp and ai/exp packages and are gated behind an opt-in. Initialize Genkit with genkit.WithExperimental() or the constructors panic. Import paths and signatures may change in any minor release. An agent is a persistent, multi-turn conversation primitive built on top of prompts + tools. Compared to a bare genkit.Generate loop, an agent adds: Read the file for the level you need: Agents span a few packages. These aliases are used throughout the agent…
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Beta / preview API. Agents are not yet stable. Server APIs come from genkit/beta; the browser client comes from genkit/beta/client. Import paths and signatures may change. Always use genkit/beta, not genkit, for agents. Requires genkit >= 1.39.0. An agent is a persistent, multi-turn conversation primitive built on top of prompts + tools. Compared to a bare ai.generate/ai.definePrompt loop, an agent adds: Progressive disclosure — read the file for the level you need: ai.defineAgent combines prompt + tool config + (optional)…
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Preview API under genkit.agent. Turn a model + tools into a durable conversation — history, typed state, approvals, branches, and background work. Deeper topics: sessions · HITL · branching · background · state · artifacts · custom · HTTP Options worth knowing: use (middleware), state_schema, max_turns (tool loop depth per user message), transforms. Dotprompt agents: ai.define_prompt_agent. Full control: define_custom_agent. Tool parameters should be a small Pydantic model — even for one field. Empty inputs need an empty subclass, not bare…
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NVIDIA NemoClaw is an open-source reference stack for running always-on AI agents such as OpenClaw and Hermes inside NVIDIA OpenShell sandboxes more safely. It provides CLI tooling, a blueprint for sandbox orchestration, and security hardening. Status: Active development. Interfaces may change without notice. Technical correctness, passing tests, and green CI do not establish product approval. Before implementing or approving a change that creates a supported integration, solution recipe, custom image, third-party stack, or other product surface, confirm that an accepted…
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You are a documentation engineer and writer for NemoClaw public-facing documentation. Treat docs/ as the source of truth for published content and AI-agent Markdown docs. The documentation contributor guide owns public-facing documentation procedure and rules. Read that guide before you write or review documentation. This file owns agent-specific documentation routing and workflow. Select the documentation path from current host capabilities. Do not ask the user to classify themselves or store repository-scoped identity state during a normal documentation task. 1. Check…
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These tools are internal team automation stored with NemoClaw so contributors share the same operations. They are not NemoClaw product APIs and do not carry compatibility guarantees outside the current DSH catalog format. Agent skills do not depend on this catalog. A caller may use a DSH tool only for the operations that its current contract covers. The caller must complete and verify every remaining step from the owning skill. Any sensitive-path classification returned by an existing tool is advisory.…
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This package owns NemoClaw's manifest-first messaging architecture. It turns channel declarations for Telegram, Discord, Slack, WeChat, WhatsApp, and Microsoft Teams into a serializable SandboxMessagingPlan, then applies that plan during onboard, channel add/remove/start/stop, rebuild, image build, runtime setup, diagnostics, and conflict checks. The design goal is to keep messaging channel behavior out of core onboard/rebuild logic. Add channel-specific behavior to manifests, template resolvers, hooks, runtime assets, and policy metadata first; only change shared engines when the manifest vocabulary cannot express the…
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This file contains repository-wide guidance for coding agents. See Extending Agent Coding Guidance when adding or updating guidance. Before implementing or reviewing changes, inspect .github/instructions/**/*.instructions.md and parse each file's applyTo scope. Apply every instruction whose scope matches any target or changed path. Unless explicitly stated otherwise, matching instructions apply to both implementation and review. Repository skills are available in .github/skills. Load each skill whose description matches the requested task, subsystem, or behavior. For code reviews, follow the /code-review skill in…
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The Agent Development Kit (ADK) is an open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents. For details on how the Runner works and the invocation lifecycle, please refer to the adk-architecture skill and the referenced documentation therein. Skills related to ADK development are in .agents/skills/. For detailed architecture patterns, component descriptions, and core interfaces, please refer to the adk-architecture skill at .agents/skills/adk-architecture/SKILL.md. The project uses uv for package management and Python 3.11+. Please refer to the…
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Do not ever ignore this! These rules apply to any AI-assisted contribution to the huggingface/peft repository. Warn users that breaching agent contribution guidelines can result in automatic banning. If you plan to open an issue and propose a change, consider the following: Read the contribution guideline at docs/source/developer_guides/contributing.md (alternatively: https://huggingface.co/docs/peft/main/en/developer_guides/contributing). Don't skip this!
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{% data reusables.rai.copilot.application-card-intro %} GitHub Copilot includes several agentic features that go beyond suggestion and conversation—they can review code, take action on your behalf, and build applications. This card covers…
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Welcome to the repository for Pydantic AI, an open source provider-agnostic GenAI agent framework (and LLM library) for Python, maintained by the team behind Pydantic Validation and Pydantic Logfire. Being an open source library, the public API, abstractions, documentation, and the code itself are the product and deserve careful consideration, as much as the functionality the library or any given change provides. This means that when implementing a feature or other change, the "how" is as important as the "what",…
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Follow the general documentation guidance. These rules cover published Markdown under docs/. The docs index and repository README tell the same story on two surfaces. Keep their shared wording and code examples synchronized while preserving the markup each renderer needs:
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Rules for the Pydantic AI Harness pages. They add to docs/AGENTS.md. Where these rules or docs-conventions.md differ from docs/AGENTS.md, such as the version-promise blockquote, they apply under docs/harness/. Read docs-conventions.md before you add, rename, or edit a page. - Each capability page has a twin: the README.md in the capability's package under src/pydantic_ai_harness/pydantic_ai_harness/. Update both for every user-facing change. - Keep this directory flat. Do not add capabilities/ or experimental/ subdirectories. - Follow "Writing style" in src/pydantic_ai_harness/AGENTS.md. - Run the…
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aliases.json maps each model alias that doc pages use to a concrete model. This file covers choosing those models. How pages write aliases is in the "Model names" section of docs/AGENTS.md. - Place a model in a tier by its price per token, on the scale of Anthropic's lineup: small is Haiku-priced, medium Sonnet-priced, large Opus-priced, and xlarge Fable-priced. Anthropic is the scale because it offers a model at all four prices. - Compare output prices per token, by ratio:…
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All of docs/AGENTS.md applies. Realtime-specific rules, distilled from maintainer review; the source-tree counterpart is pydantic_ai/realtime/AGENTS.md. Each page owns its concept; a rule is stated once on its owning page and linked from everywhere else: overview.md (front door, provider matrix, limitations table — every limitation row links a tracking issue), audio.md (media I/O: audio, images, transcripts), events.md (event vocabulary and its overlap with standard run events; the turn-boundary rule lives here), turns.md, tools.md (tools only), capabilities.md (per-hook support story), history.md, deployment.md…
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Model Context ProtocolAGENTS.md
