- Add `zeroclaw providers` CLI command that lists all 28 supported AI providers
- Each entry shows: config ID, display name, local/cloud tag, active marker, and aliases
- Also shows `custom:<URL>` and `anthropic-custom:<URL>` escape hatches at the bottom
Previously users had no way to discover available providers without reading source code. The
unknown-provider error message suggests `run zeroclaw onboard --interactive` but doesn't list
options. This command gives immediate visibility.
Integrate cloud endpoint behavior into existing ollama provider flow, avoid a separate standalone doc, and keep configuration minimal via api_url/api_key.
Also align reply_target and memory trait call sites needed for current baseline compatibility.
* fix(providers): add CN/global endpoint variants for Chinese vendors
* fix(onboard): deduplicate provider key-url match arms
* chore(i18n): normalize non-English literals to English
The existing Copilot provider passes a static Bearer token, but the
Copilot API requires short-lived session tokens obtained via GitHub's
OAuth device code flow, plus mandatory editor headers.
This replaces the stub with a dedicated CopilotProvider that:
- Runs the OAuth device code flow on first use (same client ID as VS Code)
- Exchanges the OAuth token for a Copilot API key via
api.github.com/copilot_internal/v2/token
- Sends required Editor-Version/Editor-Plugin-Version headers
- Caches tokens to disk (~/.config/zeroclaw/copilot/) with auto-refresh
- Uses Mutex to prevent concurrent refresh races / duplicate device prompts
- Writes token files with 0600 permissions (owner-only)
- Respects GitHub's polling interval and code expiry from device flow
- Sanitizes error messages to prevent token leakage
- Uses async filesystem I/O (tokio::fs) throughout
- Optionally accepts a pre-supplied GitHub token via config api_key
Fixes: 403 'Access to this endpoint is forbidden'
Fixes: 400 'missing Editor-Version header for IDE auth'
Add Astrai (https://as-trai.com) as a first-class OpenAI-compatible
provider. Astrai is an AI inference router with built-in cost
optimization, PII stripping, and compliance logging.
- Register ASTRAI_API_KEY env var in resolve_api_key
- Add "astrai" entry in provider factory → as-trai.com/v1
- Add factory_astrai unit test
- Add Astrai to compatible provider test list
- Update README provider count (22+ → 23+) and list
Co-authored-by: Maya Walcher <maya.walcher@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
fix(misc): complete parking_lot::Mutex migration (fixes#505)
- DiscordChannel: store actual channel_id in ChannelMessage.channel
instead of hardcoded "discord" string
- channels/mod.rs: use msg.channel instead of msg.sender for replies
- Migrate all std::sync::Mutex to parking_lot::Mutex:
* src/security/audit.rs
* src/memory/sqlite.rs
* src/memory/response_cache.rs
* src/memory/lucid.rs
* src/channels/email_channel.rs
* src/gateway/mod.rs
* src/observability/traits.rs
* src/providers/reliable.rs
* src/providers/router.rs
* src/agent/agent.rs
- Remove all .lock().unwrap() and .map_err(PoisonError) patterns
since parking_lot::Mutex never poisons
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add `lmstudio` / `lm-studio` as a built-in provider alias for local LM Studio instances
(`http://localhost:1234/v1`)
- Uses a dummy API key when none is provided, since LM Studio does not require authentication
- Users can connect to remote LM Studio instances via `custom:http://<ip>:1234/v1`
Add ProviderCapabilities struct to enable runtime detection of
provider-specific features, starting with native tool calling support.
This is a foundational change that enables future PRs to implement
intelligent tool calling mode selection (native vs prompt-guided).
Changes:
- Add ProviderCapabilities struct with native_tool_calling field
- Add capabilities() method to Provider trait with default impl
- Add unit tests for capabilities equality and defaults
Why:
- Current design cannot distinguish providers with native tool calling
- Needed to enable Gemini/Anthropic/OpenAI native function calling
- Fully backward compatible (all providers inherit default)
What did NOT change:
- No existing Provider methods modified
- No behavior changes for existing code
- Zero breaking changes
Testing:
- cargo test: all tests passed
- cargo fmt: pass
- cargo clippy: pass
- Remove unused import AsyncBufReadExt in compatible.rs
- Remove unused mut keywords from response and tx
- Remove unused variable 'name'
- Prefix unused parameters with _ in traits.rs
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- feat(streaming): add streaming support for LLM responses (fixes#211)
- security(deps): remove vulnerable xmas-elf dependency via embuild (fixes#399)
- fix: resolve merge conflicts and integrate chat_with_tools from main
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit fixes compilation errors when running tests by:
1. Adding `futures = "0.3"` dependency to Cargo.toml
2. Adding proper import `use futures_util::{stream, StreamExt};`
3. Replacing `futures::stream` with `stream` (using imported module)
The `futures_util` crate already had the `sink` feature but was missing
the stream-related types. Adding the full `futures` crate provides
the complete stream API needed for the streaming chat functionality.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implement Server-Sent Events (SSE) streaming for OpenAI-compatible providers:
- Add StreamChunk, StreamOptions, and StreamError types to traits module
- Add supports_streaming() and stream_chat_with_system() to Provider trait
- Implement SSE parser for OpenAI streaming responses (data: {...} format)
- Add streaming support to OpenAiCompatibleProvider
- Add streaming support to ReliableProvider with error propagation
- Add futures dependency for async stream support
Features:
- Token-by-token streaming for real-time feedback
- Token counting option (estimated ~4 chars per token)
- Graceful error handling and logging
- Channel-based stream bridging for async compatibility
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add chat_with_tools() to the Provider trait with a default fallback to
chat_with_history(). Implement native tool calling in OpenRouterProvider,
reusing existing NativeChatRequest/NativeChatResponse structs. Wire the
agent loop to use native tool calls when the provider supports them,
falling back to XML-based parsing otherwise.
Changes are purely additive to traits.rs and openrouter.rs. The only
deletions (36 lines) are within run_tool_call_loop() in loop_.rs where
the LLM call section was replaced with a branching if/else for native
vs XML tool calling.
Includes 5 new tests covering:
- chat_with_tools error path (missing API key)
- NativeChatResponse deserialization (tool calls only, mixed)
- parse_native_response conversion to ChatResponse
- tools_to_openai_format schema validation
- fix onboard command ownership handling before spawn_blocking
- restore memory helper imports in wizard to resolve build regression
- centralize Anthropic OAuth beta header in apply_auth for all request paths
- correct OpenRouter Anthropic Sonnet 4.5 model ID format
- add regression tests for auth headers and curated model IDs
- Fixes the environment variable name from `NVIDIA_NIM_API_KEY` to `NVIDIA_API_KEY` to match NVIDIA's official documentation
- Adds model suggestions for NVIDIA NIM provider in the onboarding wizard
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add Alibaba Qwen as an OpenAI-compatible provider via DashScope API
- Support three regional endpoints: China (Beijing), Singapore, and US (Virginia)
- All regions share a single `DASHSCOPE_API_KEY` environment variable
| Config Value | Region | Base URL |
|---|---|---|
| `qwen` / `dashscope` | China (Beijing) | `dashscope.aliyuncs.com/compatible-mode/v1` |
| `qwen-intl` / `dashscope-intl` | Singapore | `dashscope-intl.aliyuncs.com/compatible-mode/v1` |
| `qwen-us` / `dashscope-us` | US (Virginia) | `dashscope-us.aliyuncs.com/compatible-mode/v1` |
* feat: add ZeroClaw firmware for ESP32 and Nucleo
* Introduced new firmware for ZeroClaw on ESP32 and Nucleo-F401RE, enabling JSON-over-serial communication for GPIO control.
* Added `zeroclaw-esp32` with support for commands like `gpio_read` and `gpio_write`, along with capabilities reporting.
* Implemented `zeroclaw-nucleo` firmware with similar functionality for STM32, ensuring compatibility with existing ZeroClaw protocols.
* Updated `.gitignore` to include new firmware targets and added necessary dependencies in `Cargo.toml` for both platforms.
* Created README files for both firmware projects detailing setup, build, and usage instructions.
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: enhance hardware peripheral support and documentation
- Added `Peripheral` trait implementation in `src/peripherals/` to manage hardware boards (STM32, RPi GPIO).
- Updated `AGENTS.md` to include new extension points for peripherals and their configuration.
- Introduced comprehensive documentation for adding boards and tools, including a quick start guide and supported boards.
- Enhanced `Cargo.toml` to include optional dependencies for PDF extraction and peripheral support.
- Created new datasheets for Arduino Uno, ESP32, and Nucleo-F401RE, detailing pin aliases and GPIO usage.
- Implemented new tools for hardware memory reading and board information retrieval in the agent loop.
This update significantly improves the integration and usability of hardware peripherals within the ZeroClaw framework.
* feat: add ZeroClaw firmware for ESP32 and Nucleo
* Introduced new firmware for ZeroClaw on ESP32 and Nucleo-F401RE, enabling JSON-over-serial communication for GPIO control.
* Added `zeroclaw-esp32` with support for commands like `gpio_read` and `gpio_write`, along with capabilities reporting.
* Implemented `zeroclaw-nucleo` firmware with similar functionality for STM32, ensuring compatibility with existing ZeroClaw protocols.
* Updated `.gitignore` to include new firmware targets and added necessary dependencies in `Cargo.toml` for both platforms.
* Created README files for both firmware projects detailing setup, build, and usage instructions.
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: enhance hardware peripheral support and documentation
- Added `Peripheral` trait implementation in `src/peripherals/` to manage hardware boards (STM32, RPi GPIO).
- Updated `AGENTS.md` to include new extension points for peripherals and their configuration.
- Introduced comprehensive documentation for adding boards and tools, including a quick start guide and supported boards.
- Enhanced `Cargo.toml` to include optional dependencies for PDF extraction and peripheral support.
- Created new datasheets for Arduino Uno, ESP32, and Nucleo-F401RE, detailing pin aliases and GPIO usage.
- Implemented new tools for hardware memory reading and board information retrieval in the agent loop.
This update significantly improves the integration and usability of hardware peripherals within the ZeroClaw framework.
* feat: Introduce hardware auto-discovery and expanded configuration options for agents, hardware, and security.
* chore: update dependencies and improve probe-rs integration
- Updated `Cargo.lock` to remove specific version constraints for several dependencies, including `zerocopy`, `syn`, and `strsim`, allowing for more flexibility in version resolution.
- Upgraded `bincode` and `bitfield` to their latest versions, enhancing serialization and memory management capabilities.
- Updated `Cargo.toml` to reflect the new version of `probe-rs` from `0.24` to `0.30`, improving hardware probing functionality.
- Refactored code in `src/hardware` and `src/tools` to utilize the new `SessionConfig` for session management in `probe-rs`, ensuring better compatibility and performance.
- Cleaned up documentation in `docs/datasheets/nucleo-f401re.md` by removing unnecessary lines.
* fix: apply cargo fmt
* docs: add hardware architecture diagram.
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
