Add Venice.ai provider by adrienlo · Pull Request #451 · nearai/ironclaw

adrienlo · 2026-03-02T04:23:44Z

No description provided.

gemini-code-assist · 2026-03-02T04:24:03Z

Summary of Changes

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This pull request significantly expands the system's flexibility by incorporating Venice.ai as an additional Large Language Model provider. This integration allows users to leverage Venice.ai's specific inference features, such as uncensored models, by extending the core LLM configuration and provider creation mechanisms. The changes ensure that Venice.ai can be seamlessly configured through environment variables and the existing setup wizard, making it a straightforward option for users seeking alternative LLM backends.

Highlights

New LLM Provider Integration: Introduced Venice.ai as a new supported LLM backend, enabling uncensored inference capabilities.
Configuration and Environment Variables: Added a dedicated VeniceAiConfig struct and corresponding environment variables (VENICE_API_KEY, VENICE_MODEL, VENICE_BASE_URL, VENICE_WEB_SEARCH, VENICE_WEB_SCRAPING) for Venice.ai.
Setup Wizard and Documentation Updates: Integrated Venice.ai into the interactive setup wizard and updated relevant documentation files (.env.example, src/setup/README.md, src/settings.rs) to guide users on its configuration.
Core Logic Extension: Extended the LlmBackend enum, LlmConfig structure, and create_llm_provider function to properly handle and initialize the Venice.ai provider.

Changelog

.env.example
- Added example environment variables for Venice AI configuration, including API key, model, base URL, web search, web scraping, and embedding provider.
src/config/llm.rs
- Added VeniceAi variant to the LlmBackend enum with a description for uncensored inference.
- Updated FromStr and Display implementations for LlmBackend to recognize and represent venice, venice_ai, and veniceai.
- Mapped LlmBackend::VeniceAi to the VENICE_MODEL environment variable.
- Defined a new VeniceAiConfig struct to hold Venice.ai specific settings like API key, model, base URL, web search, and web scraping options.
- Added an Option<VeniceAiConfig> field to the LlmConfig struct.
- Implemented logic within LlmConfig::from_env to parse and load VeniceAiConfig from environment variables when LLM_BACKEND is set to veniceai.
src/config/mod.rs
- Exported the new VeniceAiConfig struct.
- Included llm_venice_api_key in the list of keys to be injected from secrets, mapping it to VENICE_API_KEY.
src/llm/mod.rs
- Added a new create_veniceai_provider function responsible for initializing the Venice.ai client using rig::providers::openai.
- Integrated the VeniceAi backend into the create_llm_provider function's match statement to correctly route to create_veniceai_provider.
- Updated the LlmConfig test initialization to include veniceai: None.
src/settings.rs
- Updated the documentation string for the llm_backend field to include "veniceai" as a valid option.
src/setup/README.md
- Added an entry for "Venice AI" to the API key table, indicating its API key and corresponding environment variable VENICE_API_KEY.
src/setup/wizard.rs
- Modified the llm_backend display logic to show "Venice AI" for venice or veniceai inputs.
- Included veniceai in the is_known check for existing LLM providers.
- Added a case to the llm_backend setup to call self.setup_veniceai().await when venice or veniceai is selected.
- Added "Venice AI" as an option in the provider selection menu with a description for uncensored inference.
- Mapped the selection index 6 to call self.setup_veniceai().await.
- Implemented the setup_veniceai asynchronous function to guide the user through collecting the Venice AI API key and storing it.

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Code Review

This pull request adds support for the Venice.ai LLM provider. The changes are comprehensive, touching configuration, provider creation, and the setup wizard. I've identified a few issues, including an unhandled configuration parameter, a documentation error, and a couple of minor inconsistencies that could affect user experience. Overall, the implementation is solid and follows existing patterns in the codebase.

gemini-code-assist · 2026-03-02T04:26:05Z

+fn create_veniceai_provider(config: &LlmConfig) -> Result<Arc<dyn LlmProvider>, LlmError> {
+    let venice = config
+        .veniceai
+        .as_ref()
+        .ok_or_else(|| LlmError::AuthFailed {
+            provider: "veniceai".to_string(),
+        })?;
+
+    use rig::providers::openai;
+
+    let base_url = venice
+        .base_url
+        .as_deref()
+        .unwrap_or(VENICEAI_BASE_URL);
+
+    let client: openai::CompletionsClient = openai::Client::builder()
+        .base_url(base_url)
+        .api_key(venice.api_key.expose_secret())
+        .build()
+        .map_err(|e| LlmError::RequestFailed {
+            provider: "veniceai".to_string(),
+            reason: format!("Failed to create Venice.ai client: {}", e),
+        })?
+        .completions_api();
+
+    let model = client.completion_model(&venice.model);
+    tracing::info!(
+        "Using Venice.ai (model: {}, base_url: {})",
+        venice.model,
+        base_url
+    );
+    Ok(Arc::new(RigAdapter::new(model, &venice.model)))
+}


The VeniceAiConfig includes web_search and web_scraping options, which are loaded from environment variables. However, these values are not used when creating the Venice.ai client or in the request logic. This means the web search and scraping features, although configurable, are not actually functional.

To fix this, you'll need to pass these parameters to the Venice.ai API. Since Venice.ai uses an OpenAI-compatible API, these would likely be passed as additional_params in the request body. The current RigAdapter is generic and doesn't support provider-specific parameters.

A potential solution is to create a new provider struct specifically for Venice.ai that wraps the rig model. This new provider would implement the LlmProvider trait and add the web_search and web_scraping fields to the additional_params of the RigRequest before calling the model.

Gemini's comment seems like a red herring here, additional_params is added on this PR.

…configs Replace the hardcoded LlmBackend enum and per-provider config structs with a declarative JSON registry. Adding a new OpenAI-compatible provider now requires zero Rust code changes -- just add an entry to providers.json. - Add providers.json with 14 providers (openai, anthropic, ollama, openai_compatible, tinfoil, openrouter, groq, nvidia, venice, together, fireworks, deepseek, cerebras, sambanova) - Add src/llm/registry.rs with ProviderProtocol, SetupHint, ProviderDefinition, and ProviderRegistry types - Rewrite src/config/llm.rs: remove LlmBackend enum and 5 per-provider config structs, replace with generic RegistryProviderConfig - Simplify src/llm/mod.rs: remove 5 create_*_provider functions, dispatch on ProviderProtocol (3 code paths for all providers) - Dynamic setup wizard: menu built from registry.selectable(), generic credential collection dispatched by SetupHint kind - Dynamic secret injection: inject_llm_keys_from_secrets() discovers secret-to-env mappings from registry instead of hardcoded list - Users can extend with ~/.ironclaw/providers.json (no recompile) - Subsumes open provider PRs: Groq #570, NVIDIA NIM #576, Venice.ai #451 (Gemini #476 excluded -- not OpenAI-compatible) [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat(llm): declarative provider registry, replace hardcoded provider configs Replace the hardcoded LlmBackend enum and per-provider config structs with a declarative JSON registry. Adding a new OpenAI-compatible provider now requires zero Rust code changes -- just add an entry to providers.json. - Add providers.json with 14 providers (openai, anthropic, ollama, openai_compatible, tinfoil, openrouter, groq, nvidia, venice, together, fireworks, deepseek, cerebras, sambanova) - Add src/llm/registry.rs with ProviderProtocol, SetupHint, ProviderDefinition, and ProviderRegistry types - Rewrite src/config/llm.rs: remove LlmBackend enum and 5 per-provider config structs, replace with generic RegistryProviderConfig - Simplify src/llm/mod.rs: remove 5 create_*_provider functions, dispatch on ProviderProtocol (3 code paths for all providers) - Dynamic setup wizard: menu built from registry.selectable(), generic credential collection dispatched by SetupHint kind - Dynamic secret injection: inject_llm_keys_from_secrets() discovers secret-to-env mappings from registry instead of hardcoded list - Users can extend with ~/.ironclaw/providers.json (no recompile) - Subsumes open provider PRs: Groq #570, NVIDIA NIM #576, Venice.ai #451 (Gemini #476 excluded -- not OpenAI-compatible) [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(llm): self-sufficient provider auth, onboard --provider-only, extract SessionConfig - NearAiChatProvider handles its own session auth lazily in resolve_bearer_token() instead of requiring main.rs to pre-check. Triggers OAuth/API-key login on first request when no token exists. - Add `ironclaw onboard --provider-only` to reconfigure just the LLM provider and model selection without re-running the full wizard. - Extract auth_base_url and session_path from NearAiConfig into LlmConfig::session (SessionConfig). Callers now use config.llm.session directly instead of reaching into nearai fields. [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(llm): address PR review comments on provider registry - Use registry.selectable() instead of registry.all() for secret injection to avoid duplicates from user provider overrides. - Fix selectable() dedup bug: check setup hint on the final (overridden) definition, not the first occurrence. User overrides that add a setup hint are now included correctly. - Only store openai_compatible_base_url for providers that actually use LLM_BASE_URL, preventing base URL pollution for groq/nvidia/etc. - Normalize provider_id to canonical registry def.id instead of using the raw user-supplied alias string. - Add comment explaining why .completions_api() is used over the default Responses API path. [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(docker): copy providers.json into build context The declarative provider registry uses `include_str!("../../providers.json")` at compile time, so the file must be present in the Docker builder stage. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(llm): address second-round PR review comments (#618) - Make --channels-only and --provider-only mutually exclusive via clap conflicts_with (Copilot: cli/mod.rs) - Add 5s timeout to fetch_openai_compatible_models(), matching the other three model-fetch helpers (Copilot: wizard.rs) - Apply models_filter from setup hints when listing models, so Groq's "chat" filter actually excludes non-chat models (Copilot: wizard.rs) - Normalize LlmConfig.backend to the canonical provider ID instead of the raw user-supplied alias string (Copilot: llm.rs) - Add models_filter() accessor to SetupHint with regression test Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(test): relax flaky parallel speedup timing threshold The test_parallel_speedup test asserted <500ms but CI runners can be slow enough to exceed that while still proving parallelism. Bumped to 800ms which still validates parallel execution (sequential would be ~600ms minimum) while tolerating CI jitter. [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(llm): handle api_key_login path in resolve_bearer_token, warn on missing keys - resolve_bearer_token() now checks NEARAI_API_KEY env var after ensure_authenticated(), handling the case where the user entered an API key via the interactive login flow (which sets the env var but not a session token) - Add tracing::warn when creating an OpenAI-compatible provider without an API key, making 401 errors easier to diagnose - Add regression test for resolve_bearer_token auth paths Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * style: fix formatting in nearai_chat test [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(llm): correct bearer token priority, handle setup-less providers (#618) - resolve_bearer_token(): session token now takes priority over NEARAI_API_KEY env var, preventing unexpected auth mode switches. The env var fallback only triggers after ensure_authenticated() when no session token was stored (api_key_login path). - run_provider_setup(): providers with setup: None no longer error, allowing env-var-only providers to be kept during re-onboarding. - Split bearer token test into 3 focused tests: config api_key path, session token path, and session-beats-env-var precedence test. - Add test for wizard handling of providers without setup hints. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * test(llm): comprehensive tests for provider registry, config, and auth Add 13 new tests covering the critical paths in the provider system: Bearer token auth priority (nearai_chat.rs): - config api_key wins over session token and env var - session token wins over env var (prevents mid-run auth mode switches) - config api_key path works in isolation - session token path works in isolation Config resolution (config/llm.rs): - backend alias normalization (open_ai → openai) - unknown backend falls back to openai_compatible - nearai aliases (nearai, near_ai, near) all resolve correctly - base URL resolution priority (env > settings > registry default) Registry dedup (registry.rs): - user override adds setup hint → appears in selectable() - user override removes setup hint → excluded from selectable() - selectable() preserves insertion order during dedup - all built-in ApiKey providers have api_key_env set Wizard (wizard.rs): - setup: None providers don't error during re-onboarding Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

ilblackdragon · 2026-03-07T02:19:57Z

Thank you for contribution. We have moved to a declarative configuration for providers and yours was added into it (#618)

adrienlo · 2026-03-07T03:57:46Z

Thank you for contribution. We have moved to a declarative configuration for providers and yours was added into it (#618)

Thank you!

* feat(llm): declarative provider registry, replace hardcoded provider configs Replace the hardcoded LlmBackend enum and per-provider config structs with a declarative JSON registry. Adding a new OpenAI-compatible provider now requires zero Rust code changes -- just add an entry to providers.json. - Add providers.json with 14 providers (openai, anthropic, ollama, openai_compatible, tinfoil, openrouter, groq, nvidia, venice, together, fireworks, deepseek, cerebras, sambanova) - Add src/llm/registry.rs with ProviderProtocol, SetupHint, ProviderDefinition, and ProviderRegistry types - Rewrite src/config/llm.rs: remove LlmBackend enum and 5 per-provider config structs, replace with generic RegistryProviderConfig - Simplify src/llm/mod.rs: remove 5 create_*_provider functions, dispatch on ProviderProtocol (3 code paths for all providers) - Dynamic setup wizard: menu built from registry.selectable(), generic credential collection dispatched by SetupHint kind - Dynamic secret injection: inject_llm_keys_from_secrets() discovers secret-to-env mappings from registry instead of hardcoded list - Users can extend with ~/.ironclaw/providers.json (no recompile) - Subsumes open provider PRs: Groq nearai#570, NVIDIA NIM nearai#576, Venice.ai nearai#451 (Gemini nearai#476 excluded -- not OpenAI-compatible) [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(llm): self-sufficient provider auth, onboard --provider-only, extract SessionConfig - NearAiChatProvider handles its own session auth lazily in resolve_bearer_token() instead of requiring main.rs to pre-check. Triggers OAuth/API-key login on first request when no token exists. - Add `ironclaw onboard --provider-only` to reconfigure just the LLM provider and model selection without re-running the full wizard. - Extract auth_base_url and session_path from NearAiConfig into LlmConfig::session (SessionConfig). Callers now use config.llm.session directly instead of reaching into nearai fields. [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(llm): address PR review comments on provider registry - Use registry.selectable() instead of registry.all() for secret injection to avoid duplicates from user provider overrides. - Fix selectable() dedup bug: check setup hint on the final (overridden) definition, not the first occurrence. User overrides that add a setup hint are now included correctly. - Only store openai_compatible_base_url for providers that actually use LLM_BASE_URL, preventing base URL pollution for groq/nvidia/etc. - Normalize provider_id to canonical registry def.id instead of using the raw user-supplied alias string. - Add comment explaining why .completions_api() is used over the default Responses API path. [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(docker): copy providers.json into build context The declarative provider registry uses `include_str!("../../providers.json")` at compile time, so the file must be present in the Docker builder stage. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(llm): address second-round PR review comments (nearai#618) - Make --channels-only and --provider-only mutually exclusive via clap conflicts_with (Copilot: cli/mod.rs) - Add 5s timeout to fetch_openai_compatible_models(), matching the other three model-fetch helpers (Copilot: wizard.rs) - Apply models_filter from setup hints when listing models, so Groq's "chat" filter actually excludes non-chat models (Copilot: wizard.rs) - Normalize LlmConfig.backend to the canonical provider ID instead of the raw user-supplied alias string (Copilot: llm.rs) - Add models_filter() accessor to SetupHint with regression test Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(test): relax flaky parallel speedup timing threshold The test_parallel_speedup test asserted <500ms but CI runners can be slow enough to exceed that while still proving parallelism. Bumped to 800ms which still validates parallel execution (sequential would be ~600ms minimum) while tolerating CI jitter. [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(llm): handle api_key_login path in resolve_bearer_token, warn on missing keys - resolve_bearer_token() now checks NEARAI_API_KEY env var after ensure_authenticated(), handling the case where the user entered an API key via the interactive login flow (which sets the env var but not a session token) - Add tracing::warn when creating an OpenAI-compatible provider without an API key, making 401 errors easier to diagnose - Add regression test for resolve_bearer_token auth paths Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * style: fix formatting in nearai_chat test [skip-regression-check] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(llm): correct bearer token priority, handle setup-less providers (nearai#618) - resolve_bearer_token(): session token now takes priority over NEARAI_API_KEY env var, preventing unexpected auth mode switches. The env var fallback only triggers after ensure_authenticated() when no session token was stored (api_key_login path). - run_provider_setup(): providers with setup: None no longer error, allowing env-var-only providers to be kept during re-onboarding. - Split bearer token test into 3 focused tests: config api_key path, session token path, and session-beats-env-var precedence test. - Add test for wizard handling of providers without setup hints. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * test(llm): comprehensive tests for provider registry, config, and auth Add 13 new tests covering the critical paths in the provider system: Bearer token auth priority (nearai_chat.rs): - config api_key wins over session token and env var - session token wins over env var (prevents mid-run auth mode switches) - config api_key path works in isolation - session token path works in isolation Config resolution (config/llm.rs): - backend alias normalization (open_ai → openai) - unknown backend falls back to openai_compatible - nearai aliases (nearai, near_ai, near) all resolve correctly - base URL resolution priority (env > settings > registry default) Registry dedup (registry.rs): - user override adds setup hint → appears in selectable() - user override removes setup hint → excluded from selectable() - selectable() preserves insertion order during dedup - all built-in ApiKey providers have api_key_env set Wizard (wizard.rs): - setup: None providers don't error during re-onboarding Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

github-actions bot added scope: llm LLM integration scope: config Configuration scope: setup Onboarding / setup scope: docs Documentation size: M 50-199 changed lines risk: high Safety, secrets, auth, or critical infrastructure contributor: new First-time contributor labels Mar 2, 2026

adrienlo force-pushed the add-veniceai-provider branch from 262a9e1 to 7d55323 Compare March 2, 2026 04:24

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feat: add Venice AI as first-class LLM backend #95

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Add Venice.ai provider

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🦞 OpenClaw 生态日报 2026-03-04 duanyytop/agents-radar#71

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feat(llm): declarative provider registry #618

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Add Venice.ai provider#451

Add Venice.ai provider#451
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