feat: add Tinfoil private inference provider by lwlee2608 · Pull Request #62 · nearai/ironclaw

lwlee2608 · 2026-02-13T08:05:27Z

Summary

Add a dedicated LLM_BACKEND=tinfoil provider for Tinfoil private inference
Tinfoil is not compatible with the openai_compatible backend because rig-core 0.30.0 defaults to the OpenAI Responses API (/v1/responses), which Tinfoil does not support — it only implements the Chat Completions API (/v1/chat/completions), returning 403 "shim: path not allowed"
Rather than changing openai_compatible to use Chat Completions (which would break users expecting the Responses API), this adds a dedicated provider that explicitly uses rig's .completions_api() client
This lays the groundwork for integrating Tinfoil's privacy wrapper client (enclave attestation, TLS certificate pinning) once their Rust SDK is available — currently only Go and Python clients exist. The provider can be swapped to use the Tinfoil Rust client without changing the LlmProvider interface

Configuration

LLM_BACKEND=tinfoil
TINFOIL_API_KEY=tk_...
TINFOIL_MODEL=kimi-k2-5   # optional, default

Files changed

src/config.rs — Tinfoil variant in LlmBackend, TinfoilConfig struct, env var resolution
src/llm/mod.rs — create_tinfoil_provider() using rig's Chat Completions client
src/setup/wizard.rs — Add tinfoil: None to wizard's LlmConfig initializer

Test plan

Verified LLM_BACKEND=tinfoil with kimi-k2-5 model responds successfully
All 747 existing tests pass
CI passes

Add a dedicated Tinfoil LLM backend (`LLM_BACKEND=tinfoil`) for Tinfoil's private inference service (https://tinfoil.sh). The existing `openai_compatible` backend cannot be used with Tinfoil because rig-core 0.30.0 defaults to the OpenAI Responses API (`/v1/responses`), which Tinfoil does not support — it only implements the Chat Completions API (`/v1/chat/completions`), returning 403 "shim: path not allowed" when hit on the responses endpoint. Rather than changing `openai_compatible` to use Chat Completions (which would break users expecting the Responses API), this adds a dedicated provider that explicitly uses rig's `.completions_api()` client. This also lays the groundwork for integrating Tinfoil's privacy wrapper client (enclave attestation, TLS certificate pinning) once their Rust SDK is available. The provider implementation can be swapped to use the Tinfoil Rust client without changing the LlmProvider interface. Configuration: LLM_BACKEND=tinfoil TINFOIL_API_KEY=tk_... TINFOIL_MODEL=kimi-k2-5 # optional, default

gemini-code-assist · 2026-02-13T08:05:47Z

Summary of Changes

Hello @lwlee2608, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces Tinfoil as a new, dedicated LLM backend provider, enabling users to leverage its private inference capabilities. The integration addresses Tinfoil's specific API requirements by using the Chat Completions API, differentiating it from other OpenAI-compatible services. The changes encompass adding necessary configuration structures, environment variable parsing, and a client adapter to facilitate interaction with Tinfoil's services, while also preparing the codebase for future SDK enhancements.

Highlights

New LLM Backend: Introduced a dedicated Tinfoil LLM backend provider for private inference, distinct from the existing openai_compatible backend due to API differences.
Configuration: Implemented specific configuration for Tinfoil, allowing users to set LLM_BACKEND=tinfoil, TINFOIL_API_KEY, and optionally TINFOIL_MODEL (defaults to kimi-k2-5) via environment variables.
API Compatibility: Ensured the Tinfoil integration explicitly uses the Chat Completions API (/v1/chat/completions) via rig's client, as Tinfoil does not support the OpenAI Responses API (/v1/responses).
Future-proofing: Laid the groundwork for integrating Tinfoil's privacy wrapper client (enclave attestation, TLS certificate pinning) once their Rust SDK becomes available, allowing for a seamless swap without altering the LlmProvider interface.

Changelog

src/config.rs
- Added Tinfoil variant to the LlmBackend enum.
- Updated FromStr and Display implementations for LlmBackend to recognize and represent Tinfoil.
- Defined a new TinfoilConfig struct to hold the API key and model for Tinfoil.
- Included a tinfoil field in the main LlmConfig struct.
- Implemented logic within LlmConfig::new to parse TINFOIL_API_KEY and TINFOIL_MODEL environment variables when LLM_BACKEND is set to Tinfoil.
src/llm/mod.rs
- Extended the create_llm_provider function to instantiate a Tinfoil provider when LlmBackend::Tinfoil is selected.
- Added the create_tinfoil_provider function, which constructs a rig::providers::openai::Client configured with Tinfoil's base URL and API key, specifically utilizing its completions_api().
src/setup/wizard.rs
- Modified the LlmConfig initialization within the setup wizard to include tinfoil: None.

Activity

The author verified that LLM_BACKEND=tinfoil with the kimi-k2-5 model successfully responded.
All 747 existing tests passed.
CI pass status is pending.

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Code Review

This pull request introduces support for the Tinfoil private inference provider. The implementation is solid, adding the necessary configuration, provider creation logic, and updating the relevant enums and structs. The changes align well with the existing architecture for LLM providers. I have one minor suggestion to enhance configuration consistency.

Copilot

Pull request overview

This PR adds support for Tinfoil, a private inference provider, as a new LLM backend option. Tinfoil is specifically designed for privacy-focused model inference and requires the Chat Completions API rather than the Responses API that rig-core 0.30.0 defaults to for OpenAI-compatible endpoints. This necessitates a dedicated provider implementation rather than using the generic openai_compatible backend.

Changes:

Added Tinfoil variant to LlmBackend enum with corresponding FromStr and Display implementations
Created TinfoilConfig struct and environment variable resolution logic (TINFOIL_API_KEY, TINFOIL_MODEL)
Implemented create_tinfoil_provider() function that explicitly uses rig's Chat Completions API client via .completions_api()
Updated setup wizard to initialize tinfoil: None in LlmConfig construction

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated no comments.

File	Description
src/config.rs	Adds Tinfoil backend enum variant, configuration struct, and environment variable resolution with "kimi-k2-5" as default model
src/llm/mod.rs	Implements Tinfoil provider creation using OpenAI client with explicit Chat Completions API and hardcoded base URL
src/setup/wizard.rs	Initializes tinfoil field to None in wizard's LlmConfig construction

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serrrfirat

PR #62 Review: feat: add Tinfoil private inference provider

Author: lwlee2608 | Reviewed: 2026-02-13T12:36:00+04:00

Verdict: APPROVE ✅

Clean, well-structured PR that follows established patterns from other provider integrations (OpenRouter, OpenAI-compatible). No significant issues found.

Findings

P3 - Minor: Hardcoded base URL (informational)

File: src/llm/mod.rs:144

const TINFOIL_BASE_URL: &str = "https://inference.tinfoil.sh/v1";

The base URL is hardcoded. Other providers like OpenAI-compatible allow configurable endpoints. For a specific provider like Tinfoil this is acceptable, but consider adding an optional TINFOIL_BASE_URL env override for flexibility (e.g., self-hosted instances or staging).

P3 - Minor: Default model choice

File: src/config.rs:434

.unwrap_or_else(|| "kimi-k2-5".to_string());

Default model is kimi-k2-5. This is fine but worth confirming it's a valid model on Tinfoil's inference API.

Positives

Follows the exact same pattern as other provider implementations
Proper use of SecretString for API key handling
Good error messages with provider context
Config parsing correctly gated behind LlmBackend::Tinfoil check
Wizard properly initialized with tinfoil: None
Uses the existing RigAdapter via OpenAI-compatible client — clean reuse

Security Assessment

✅ API key stored in SecretString, accessed via expose_secret()
✅ No secrets logged (only model name in tracing::info)
✅ HTTPS endpoint hardcoded
✅ No user input passed unsanitized

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serrrfirat · 2026-02-14T12:27:14Z

@copilot review again

tribendu · 2026-02-15T01:02:10Z

PR Review: feat: add Tinfoil private inference provider

PR Author: Jason Lee
Size: 141 lines (+57/-1)

Summary

This PR adds support for Tinfoil, a private inference provider, to the IronClaw framework. It implements a new Tinfoil backend option for LLM operations that integrates with the Tinfoil API (https://inference.tinfoil.sh/v1) using the OpenAI-compatible client interface via the rig library. The implementation follows the existing pattern seen in other providers like Anthropic, Ollama, and OpenAI-compatible backends.

The changes are minimal and focused: adding the backend enum variant, configuration struct, environment variable parsing, provider creation logic, and a field in the setup wizard.

Pros

Consistent pattern: Follows the established pattern for LLM providers (Anthropic, Ollama, OpenAI-compatible)
Minimal footprint: Only 57 lines added, clean and focused changes
Proper error handling: Uses appropriate LlmError variants (AuthFailed, RequestFailed)
Secret handling: Correctly uses SecretString for API key storage (prevents accidental logging)
Good documentation: Clear doc comments (/// Configuration for Tinfoil private inference.)
Sensible defaults: Default model kimi-k2-5 if TINFOIL_MODEL not specified
Informative logging: tracing::info! log entry when Tinfoil provider is initialized
Environment variable hints: Helpful error message suggests setting TINFOIL_API_KEY

Concerns

Missing tests: No test coverage added for:
- LlmBackend::from_str with "tinfoil" input
- LlmBackend::Display for Tinfoil variant
- TinfoilConfig parsing from environment variables
- create_tinfoil_provider function
Hardcoded URL: The base URL https://inference.tinfoil.sh/v1 is a constant. Consider if this should be:
- Configurable via environment variable (e.g., TINFOIL_BASE_URL)
- Part of TinfoilConfig struct (like some other providers might do)
Secret exposure: In create_tinfoil_provider, the API key is exposed via tf.api_key.expose_secret(). While this is passed to the OpenAI client builder, ensure:
- The rig library doesn't log this value
- No debug/trace logs inadvertently expose this secret
- Consider if there's a way to pass secrets without exposing them
Incomplete Display implementation: The Display impl for LlmBackend includes Tinfoil, but there's no test for this formatting consistency.
No documentation update: If there's a README or CONTRIBUTING guide with LLM backend examples, it should be updated to include Tinfoil.
Wizard integration: The wizard only sets tinfoil: None but doesn't appear to have interactive setup for the Tinfoil provider. Consider whether this is intentional or should be added.

Suggestions

Add unit tests:

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_tinfoil_backend_from_str() {
        assert_eq!(LlmBackend::from_str("tinfoil"), Ok(LlmBackend::Tinfoil));
    }

    #[test]
    fn test_tinfoil_backend_display() {
        assert_eq!(LlmBackend::Tinfoil.to_string(), "tinfoil");
    }
}

Make base URL configurable:

/// Configuration for Tinfoil private inference.
#[derive(Debug, Clone)]
pub struct TinfoilConfig {
    pub api_key: SecretString,
    pub model: String,
    #[serde(default = "default_tinfoil_base_url")]
    pub base_url: String,
}

fn default_tinfoil_base_url() -> String {
    "https://inference.tinfoil.sh/v1".to_string()
}

Consider integration test: Add a test that verifies the provider can be created (mocking the API call or using a test flag).
Update documentation: If user-facing docs exist, add a section explaining how to configure Tinfoil:
- Required env vars: TINFOIL_API_KEY
- Optional env var: TINFOIL_MODEL (default: kimi-k2-5)
- Backend selection: LLM_BACKEND=tinfoil
Wizard enhancement: If interactive setup is desired, add a prompt for Tinfoil credentials in src/setup/wizard.rs.
Error message consistency: Ensure the hint in the MissingRequired error is consistent with other providers' hints.
Consider model validation: Add validation that the model name is non-empty or matches expected patterns.
Add tracing at secret exposure point: Consider adding a tracing::debug! note when passing secrets to external libraries, to help with debugging if secrets leak.

Overall Assessment

Status: 🟢 Approve with minor suggestions

This is a clean, well-structured implementation that follows the project's existing patterns. The code is minimal, uses appropriate Rust idioms, and handles secrets correctly. The primary concern is the lack of test coverage, which should be addressed before merge. The hardcoded base URL is acceptable for an initial implementation but should be considered for future flexibility.

The PR successfully adds Tinfoil as a new LLM backend with proper configuration, error handling, and integration with the existing provider infrastructure.

Copilot

Pull request overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated 1 comment.

Comments suppressed due to low confidence (1)

src/config.rs:362

The documentation comment for LlmConfig lists examples of backend values but does not include the newly added tinfoil backend. Consider updating the examples to include tinfoil for completeness, e.g., (e.g. 'openai', 'anthropic', 'ollama', 'openai_compatible', 'tinfoil').

/// NEAR AI remains the default backend. Users can switch to other providers
/// by setting `LLM_BACKEND` (e.g. `openai`, `anthropic`, `ollama`).

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lwlee2608 · 2026-02-17T13:39:24Z

Yep will merge it after CI succeeds.

Thanks @serrrfirat , CI fixed

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lwlee2608 · 2026-02-17T18:25:16Z

Hi @serrrfirat - just to clarify clearly: this CI failure was not caused by the Tinfoil feature changes in this PR. It was from a pre-existing rustfmt mismatch in src/llm/session.rs on the merge ref. I pushed a formatting-only fix in commit 02cce46 to unblock Code Style. Thank you!

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Pull request overview

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Pull request overview

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Copilot · 2026-02-18T06:00:27Z

+        })?;
+
+    // Tinfoil currently only supports the Chat Completions API and not the newer Responses API,
+    // so we must explicitly select the completions API here (unlike other OpenAI-compatible providers).


The comment phrase "unlike other OpenAI-compatible providers" is ambiguous. Consider rephrasing to "unlike the openai_compatible backend" or "unlike the default behavior for OpenAI client" to clarify that you're referring to the openai_compatible backend in this codebase, which relies on the default Responses API behavior.

Suggested change

// so we must explicitly select the completions API here (unlike other OpenAI-compatible providers).

// so we must explicitly select the completions API here, unlike the openai_compatible backend,

// which relies on the default OpenAI Responses API behavior.

* feat: add Tinfoil private inference provider Add a dedicated Tinfoil LLM backend (`LLM_BACKEND=tinfoil`) for Tinfoil's private inference service (https://tinfoil.sh). The existing `openai_compatible` backend cannot be used with Tinfoil because rig-core 0.30.0 defaults to the OpenAI Responses API (`/v1/responses`), which Tinfoil does not support — it only implements the Chat Completions API (`/v1/chat/completions`), returning 403 "shim: path not allowed" when hit on the responses endpoint. Rather than changing `openai_compatible` to use Chat Completions (which would break users expecting the Responses API), this adds a dedicated provider that explicitly uses rig's `.completions_api()` client. This also lays the groundwork for integrating Tinfoil's privacy wrapper client (enclave attestation, TLS certificate pinning) once their Rust SDK is available. The provider implementation can be swapped to use the Tinfoil Rust client without changing the LlmProvider interface. Configuration: LLM_BACKEND=tinfoil TINFOIL_API_KEY=tk_... TINFOIL_MODEL=kimi-k2-5 # optional, default * style: fix rustfmt formatting in Tinfoil provider * style: remove unnecessary tin_foil alias for Tinfoil backend * Update src/llm/mod.rs Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: add tinfoil field to LlmConfig test fixture * style: fix rustfmt output in session manager --------- Co-authored-by: firat.sertgoz <f@nuff.tech> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Illia Polosukhin <ilblackdragon@gmail.com>

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lwlee2608 and others added 3 commits February 13, 2026 21:31

style: fix rustfmt formatting in Tinfoil provider

969d864

style: remove unnecessary tin_foil alias for Tinfoil backend

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Merge branch 'main' into feat/tinfoil-provider

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ilblackdragon mentioned this pull request Feb 14, 2026

feat: Multi-provider LLM support (failover, auto-discovery, Ollama, Bedrock, Gemini) #80

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Merge branch 'main' into feat/tinfoil-provider

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Merge branch 'main' into feat/tinfoil-provider

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Merge branch 'main' into feat/tinfoil-provider

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Merge branch 'main' into feat/tinfoil-provider

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Merge branch 'main' into feat/tinfoil-provider

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Update src/llm/mod.rs

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feat(memory): add citation support, line tracking, and cognitive routines #63

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Merge branch 'main' into feat/tinfoil-provider

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Merge branch 'main' into feat/tinfoil-provider

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chore: release v0.6.0 #136

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feat: add Avian as a named LLM provider #396

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	// so we must explicitly select the completions API here (unlike other OpenAI-compatible providers).
	// so we must explicitly select the completions API here, unlike the openai_compatible backend,
	// which relies on the default OpenAI Responses API behavior.

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PR #62 Review: feat: add Tinfoil private inference provider

Verdict: APPROVE ✅

Findings

P3 - Minor: Hardcoded base URL (informational)

P3 - Minor: Default model choice

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serrrfirat commented Feb 14, 2026

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tribendu commented Feb 15, 2026

PR Review: feat: add Tinfoil private inference provider

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lwlee2608 commented Feb 13, 2026 •

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