Files
optimclaw/providers.json
T
d73e35cfb0 feat: add AWS Bedrock LLM provider via native Converse API (#713)
* feat: add AWS Bedrock LLM provider via native Converse API

* fix: use JSON parsing for tool result error detection instead of brittle substring matching

* refactor: extract duplicated inference config builder into helper function

* fix: address review feedback — safe casts, input validation, and tests

- Safe u32→i32 cast for max_tokens using try_from with clamp
- Remove brittle string-based error detection fallback for tool results
- Validate BEDROCK_CROSS_REGION against allowed values (us/eu/apac/global)
- Validate message list is non-empty before Converse API call
- Log when using default us-east-1 region
- Update llm_backend doc comment to list all backends
- Add tests for build_inference_config and empty message handling

* fix: persist AWS_PROFILE for Bedrock named profile auth

The wizard collected the profile name but only printed a hint to set
it manually. Now it saves to settings and writes AWS_PROFILE to the
bootstrap .env, consistent with how BEDROCK_REGION and other Bedrock
settings are persisted.

* feat: gate AWS Bedrock behind optional `bedrock` feature flag

The AWS SDK dependencies (aws-config, aws-sdk-bedrockruntime,
aws-smithy-types) require cmake and a C compiler to build aws-lc-sys.
Gate them behind an opt-in `bedrock` feature flag so default builds
are unaffected.

Build with: cargo build --features bedrock
All config, settings, and wizard code stays unconditional (no AWS deps)
so users can configure Bedrock even without the feature compiled — they
get a clear error at startup directing them to rebuild.

* fix: address review feedback and adapt Bedrock provider to registry architecture (takeover #345)

- Resolve merge conflicts with main's registry-based provider system
- Add missing cache_creation_input_tokens/cache_read_input_tokens fields
- Add missing content_parts field in test ChatMessage
- Fix string literal type mismatches in wizard env_vars (.to_string())
- Remove non-functional bearer token auth (AWS_BEARER_TOKEN_BEDROCK) from
  wizard and documentation per reviewer feedback from @zmanian and @serrrfirat
- Remove stale BEDROCK_ACCESS_KEY proxy entry from provider table
- Update Bedrock provider to use is_bedrock string check (LlmBackend enum removed)
- Add bedrock_profile fallback from settings in config resolution

[skip-regression-check]

Co-Authored-By: cgorski <[email protected]>
Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: use main's Cargo.lock as base to preserve dependency versions

Regenerating Cargo.lock from scratch caused transitive dependency version
drift that broke the html_to_markdown fixture test in CI.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: bedrock config bugs — spurious warning, alias normalization, profile fallback

- Move is_bedrock check before unknown-backend warning to prevent
  spurious "unknown backend" log for bedrock users
- Normalize backend aliases ("aws", "aws_bedrock") to "bedrock" so
  the provider factory matches correctly
- Add settings.bedrock_profile fallback for AWS_PROFILE, consistent
  with region and cross_region resolution

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: address Copilot review feedback — bearer token cleanup, stop_sequences, model dedup

- Remove stale bearer token refs from setup README and CHANGELOG
- Remove dead bedrock_api_key secret injection mapping
- Pass stop_sequences through to Bedrock InferenceConfiguration
- Remove "API key" from wizard menu description (bearer token removed)
- Skip duplicate LLM_MODEL write for bedrock backend in wizard
- Fix cargo fmt formatting

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: address review feedback — async new(), remove LiteLLM entry, wizard fixes

- Remove dead LiteLLM-based bedrock entry from providers.json (native
  Converse API intercepts before registry lookup)
- Make BedrockProvider::new() async to avoid block_in_place panic in
  current_thread runtimes; propagate async to create_llm_provider,
  build_provider_chain, and init_llm
- Document CMake build prerequisite in docs/LLM_PROVIDERS.md
- Clear bedrock_profile when user selects "default credentials" in wizard
- Fix selected_model clearing to match established pattern (conditional
  on provider switch, not unconditional)
- Add regression tests for bedrock model preservation and profile clearing

Addresses review feedback from @zmanian on PR #713.
Streaming support tracked in #741.

[skip-regression-check]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: address remaining review comments — CLAUDE.md backends, wizard UX

- Add `bedrock` to CLAUDE.md inline backend list (#10)
- Skip full setup re-run when keeping existing Bedrock config (#11)
- Clear stale bedrock_profile on empty named-profile input (#12)
- Add regression test for empty profile clearing

Co-Authored-By: Claude Opus 4.6 <[email protected]>

---------

Co-authored-by: Chris Gorski <[email protected]>
Co-authored-by: cgorski <[email protected]>
Co-authored-by: Claude Opus 4.6 <[email protected]>
2026-03-09 07:10:25 +00:00

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[
{
"id": "openai",
"aliases": [
"open_ai"
],
"protocol": "open_ai_completions",
"api_key_env": "OPENAI_API_KEY",
"api_key_required": true,
"base_url_env": "OPENAI_BASE_URL",
"model_env": "OPENAI_MODEL",
"default_model": "gpt-4o",
"description": "OpenAI GPT models (direct API)",
"setup": {
"kind": "api_key",
"secret_name": "llm_openai_api_key",
"key_url": "https://platform.openai.com/api-keys",
"display_name": "OpenAI",
"can_list_models": true
}
},
{
"id": "anthropic",
"aliases": [
"claude"
],
"protocol": "anthropic",
"api_key_env": "ANTHROPIC_API_KEY",
"api_key_required": true,
"base_url_env": "ANTHROPIC_BASE_URL",
"model_env": "ANTHROPIC_MODEL",
"default_model": "claude-sonnet-4-20250514",
"description": "Anthropic Claude models (direct API)",
"setup": {
"kind": "api_key",
"secret_name": "llm_anthropic_api_key",
"key_url": "https://console.anthropic.com/settings/keys",
"display_name": "Anthropic",
"can_list_models": true
}
},
{
"id": "ollama",
"aliases": [],
"protocol": "ollama",
"default_base_url": "http://localhost:11434",
"base_url_env": "OLLAMA_BASE_URL",
"model_env": "OLLAMA_MODEL",
"default_model": "llama3",
"description": "Local Ollama instance (no API key needed)",
"setup": {
"kind": "ollama",
"display_name": "Ollama",
"can_list_models": true
}
},
{
"id": "openai_compatible",
"aliases": [
"openai-compatible",
"compatible"
],
"protocol": "open_ai_completions",
"base_url_env": "LLM_BASE_URL",
"base_url_required": true,
"api_key_env": "LLM_API_KEY",
"api_key_required": false,
"model_env": "LLM_MODEL",
"default_model": "default",
"extra_headers_env": "LLM_EXTRA_HEADERS",
"description": "Custom OpenAI-compatible endpoint (vLLM, LiteLLM, etc.)",
"setup": {
"kind": "open_ai_compatible",
"secret_name": "llm_compatible_api_key",
"display_name": "OpenAI-compatible",
"can_list_models": false
}
},
{
"id": "tinfoil",
"aliases": [],
"protocol": "open_ai_completions",
"default_base_url": "https://inference.tinfoil.sh/v1",
"api_key_env": "TINFOIL_API_KEY",
"api_key_required": true,
"model_env": "TINFOIL_MODEL",
"default_model": "kimi-k2-5",
"description": "Tinfoil private inference (hardware-attested TEE)",
"setup": {
"kind": "api_key",
"secret_name": "llm_tinfoil_api_key",
"key_url": "https://tinfoil.sh",
"display_name": "Tinfoil",
"can_list_models": false
}
},
{
"id": "openrouter",
"aliases": [
"open_router"
],
"protocol": "open_ai_completions",
"default_base_url": "https://openrouter.ai/api/v1",
"api_key_env": "OPENROUTER_API_KEY",
"api_key_required": true,
"model_env": "OPENROUTER_MODEL",
"default_model": "openai/gpt-4o",
"description": "OpenRouter multi-provider gateway (200+ models)",
"setup": {
"kind": "api_key",
"secret_name": "llm_openrouter_api_key",
"key_url": "https://openrouter.ai/settings/keys",
"display_name": "OpenRouter",
"can_list_models": false
}
},
{
"id": "groq",
"aliases": [],
"protocol": "open_ai_completions",
"default_base_url": "https://api.groq.com/openai/v1",
"api_key_env": "GROQ_API_KEY",
"api_key_required": true,
"model_env": "GROQ_MODEL",
"default_model": "llama-3.3-70b-versatile",
"description": "Groq LPU inference (ultra-fast)",
"setup": {
"kind": "api_key",
"secret_name": "llm_groq_api_key",
"key_url": "https://console.groq.com/keys",
"display_name": "Groq",
"can_list_models": true,
"models_filter": "chat"
}
},
{
"id": "nvidia",
"aliases": [
"nvidia_nim",
"nim"
],
"protocol": "open_ai_completions",
"default_base_url": "https://integrate.api.nvidia.com/v1",
"api_key_env": "NVIDIA_API_KEY",
"api_key_required": true,
"model_env": "NVIDIA_MODEL",
"default_model": "meta/llama-3.3-70b-instruct",
"description": "NVIDIA NIM API (high-performance inference)",
"setup": {
"kind": "api_key",
"secret_name": "llm_nvidia_api_key",
"key_url": "https://build.nvidia.com",
"display_name": "NVIDIA NIM",
"can_list_models": true
}
},
{
"id": "venice",
"aliases": [
"venice_ai",
"veniceai"
],
"protocol": "open_ai_completions",
"default_base_url": "https://api.venice.ai/api/v1",
"api_key_env": "VENICE_API_KEY",
"api_key_required": true,
"model_env": "VENICE_MODEL",
"default_model": "llama-3.3-70b",
"description": "Venice.ai privacy-focused inference",
"setup": {
"kind": "api_key",
"secret_name": "llm_venice_api_key",
"key_url": "https://venice.ai/settings/api",
"display_name": "Venice.ai",
"can_list_models": false
}
},
{
"id": "together",
"aliases": [
"together_ai",
"togetherai"
],
"protocol": "open_ai_completions",
"default_base_url": "https://api.together.xyz/v1",
"api_key_env": "TOGETHER_API_KEY",
"api_key_required": true,
"model_env": "TOGETHER_MODEL",
"default_model": "meta-llama/Llama-3-70b-chat-hf",
"description": "Together AI inference",
"setup": {
"kind": "api_key",
"secret_name": "llm_together_api_key",
"key_url": "https://api.together.ai/settings/api-keys",
"display_name": "Together AI",
"can_list_models": false
}
},
{
"id": "fireworks",
"aliases": [
"fireworks_ai"
],
"protocol": "open_ai_completions",
"default_base_url": "https://api.fireworks.ai/inference/v1",
"api_key_env": "FIREWORKS_API_KEY",
"api_key_required": true,
"model_env": "FIREWORKS_MODEL",
"default_model": "accounts/fireworks/models/llama-v3p1-70b-instruct",
"description": "Fireworks AI inference",
"setup": {
"kind": "api_key",
"secret_name": "llm_fireworks_api_key",
"key_url": "https://fireworks.ai/api-keys",
"display_name": "Fireworks AI",
"can_list_models": false
}
},
{
"id": "deepseek",
"aliases": [
"deep_seek"
],
"protocol": "open_ai_completions",
"default_base_url": "https://api.deepseek.com/v1",
"api_key_env": "DEEPSEEK_API_KEY",
"api_key_required": true,
"model_env": "DEEPSEEK_MODEL",
"default_model": "deepseek-chat",
"description": "DeepSeek inference API",
"setup": {
"kind": "api_key",
"secret_name": "llm_deepseek_api_key",
"key_url": "https://platform.deepseek.com/api_keys",
"display_name": "DeepSeek",
"can_list_models": false
}
},
{
"id": "cerebras",
"aliases": [],
"protocol": "open_ai_completions",
"default_base_url": "https://api.cerebras.ai/v1",
"api_key_env": "CEREBRAS_API_KEY",
"api_key_required": true,
"model_env": "CEREBRAS_MODEL",
"default_model": "llama-3.3-70b",
"description": "Cerebras wafer-scale inference",
"setup": {
"kind": "api_key",
"secret_name": "llm_cerebras_api_key",
"key_url": "https://cloud.cerebras.ai",
"display_name": "Cerebras",
"can_list_models": false
}
},
{
"id": "sambanova",
"aliases": [
"samba_nova"
],
"protocol": "open_ai_completions",
"default_base_url": "https://api.sambanova.ai/v1",
"api_key_env": "SAMBANOVA_API_KEY",
"api_key_required": true,
"model_env": "SAMBANOVA_MODEL",
"default_model": "Meta-Llama-3.1-70B-Instruct",
"description": "SambaNova Cloud inference",
"setup": {
"kind": "api_key",
"secret_name": "llm_sambanova_api_key",
"key_url": "https://cloud.sambanova.ai/apis",
"display_name": "SambaNova",
"can_list_models": false
}
},
{
"id": "gemini",
"aliases": [
"google_gemini",
"google"
],
"protocol": "open_ai_completions",
"default_base_url": "https://generativelanguage.googleapis.com/v1beta/openai",
"api_key_env": "GEMINI_API_KEY",
"api_key_required": true,
"model_env": "GEMINI_MODEL",
"default_model": "gemini-2.5-flash",
"description": "Google Gemini (via OpenAI-compatible endpoint)",
"setup": {
"kind": "api_key",
"secret_name": "llm_gemini_api_key",
"key_url": "https://aistudio.google.com/app/apikey",
"display_name": "Google Gemini",
"can_list_models": true
}
},
{
"id": "ionet",
"aliases": [
"io_net",
"io.net"
],
"protocol": "open_ai_completions",
"default_base_url": "https://api.intelligence.io.solutions/api/v1",
"api_key_env": "IONET_API_KEY",
"api_key_required": true,
"model_env": "IONET_MODEL",
"default_model": "deepseek-coder-v2-instruct",
"description": "io.net Intelligence API",
"setup": {
"kind": "api_key",
"secret_name": "llm_ionet_api_key",
"key_url": "https://cloud.io.net/intelligence",
"display_name": "io.net",
"can_list_models": true
}
},
{
"id": "mistral",
"aliases": [
"mistral_ai",
"mistralai"
],
"protocol": "open_ai_completions",
"default_base_url": "https://api.mistral.ai/v1",
"api_key_env": "MISTRAL_API_KEY",
"api_key_required": true,
"model_env": "MISTRAL_MODEL",
"default_model": "mistral-large-latest",
"description": "Mistral AI API",
"setup": {
"kind": "api_key",
"secret_name": "llm_mistral_api_key",
"key_url": "https://console.mistral.ai/api-keys",
"display_name": "Mistral",
"can_list_models": true
}
},
{
"id": "yandex",
"aliases": [
"yandex_ai_studio",
"yandexgpt",
"yandex_gpt"
],
"protocol": "open_ai_completions",
"default_base_url": "https://ai.api.cloud.yandex.net/v1",
"api_key_env": "YANDEX_API_KEY",
"api_key_required": true,
"model_env": "YANDEX_MODEL",
"extra_headers_env": "YANDEX_EXTRA_HEADERS",
"default_model": "yandexgpt-lite",
"description": "Yandex AI Studio (YandexGPT)",
"setup": {
"kind": "api_key",
"secret_name": "llm_yandex_api_key",
"key_url": "https://aistudio.yandex.ru/platform/folders/",
"display_name": "Yandex AI Studio",
"can_list_models": true
}
},
{
"id": "cloudflare",
"aliases": [
"cloudflare_ai",
"cf_ai"
],
"protocol": "open_ai_completions",
"api_key_env": "CLOUDFLARE_API_KEY",
"api_key_required": true,
"base_url_env": "CLOUDFLARE_BASE_URL",
"model_env": "CLOUDFLARE_MODEL",
"default_model": "@cf/meta/llama-3.3-70b-instruct-fp8-fast",
"description": "Cloudflare Workers AI",
"setup": {
"kind": "open_ai_compatible",
"secret_name": "llm_cloudflare_api_key",
"display_name": "Cloudflare Workers AI",
"can_list_models": false
}
}
]