actual-setup

Configure actual.inc as an Indagis inference provider via relay or local daemon.

1|Updated Aug 6, 2026
One-click install
npx skills add https://github.com/agtktID/indagis-agent --skill actual-setup-agtktid
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: actual-setup
Source: https://github.com/agtktID/indagis-agent/tree/main/optional-skills/devops/actual-setup
Command: npx skills add https://github.com/agtktID/indagis-agent --skill actual-setup-agtktid

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Setting up Actual Computer (actual.inc) as an inference provider involves two distinct modes (hosted relay and local daemon), device authorization that requires a human in a browser, and several cryptic failure modes like HTTP 400s from reasoning_effort values and empty streams from context-window overflow. This Skill walks through the correct configuration path and documents the known pitfalls. ## Core Features & Use Cases - Relay/API Mode Setup: Configure the hosted end-to-end-encrypted relay at api.actual.inc using an ACTUAL_API_KEY, with model discovery via the /v1/models endpoint. - Local Daemon Mode: Point Indagis at the on-device daemon at 127.0.0.1:8080 with no-auth loopback, including model search, download with explicit quantization, and load by installed name. - Pitfall Troubleshooting: Diagnose reasoning_effort clamping, context-window overflow on small GGUF models, download-id vs installed-name mismatches, and empty-content reasoning models. - Use Case: A user with an ac_ key wants Indagis routed through their Actual cluster; the Skill sets the env var, selects the provider and model, and verifies end-to-end with a hermes chat command. ## Quick Start Ask the agent to set up actual.inc as the Indagis inference provider using your ACTUAL_API_KEY and verify it with a test chat message.

Frequently Asked Questions about actual-setup

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up actual.inc as an inference provider?▼

Add ACTUAL_API_KEY=ac_... to ~/.hermes/.env, verify the key with a curl to https://api.actual.inc/v1/models, then set model.provider to actual and model.default to a discovered model ID. Verify with hermes chat using the actual provider.

How to run fully local inference with the Actual daemon?▼

Install the daemon, run actual once and open the printed device authorization URL in a browser, then download and load a GGUF model. Set ACTUAL_BASE_URL=http://127.0.0.1:8080 to switch the built-in provider into local no-auth mode.

Why does Actual return an empty stream with no finish_reason?▼

This is context-window overflow, not an SSE bug. Indagis' default toolset is roughly 26k tokens of schemas plus a 9k-token system prompt, which overflows a model loaded with 32k context. Restrict tools, increase n_ctx, or use a 64k-context model.

Why do Actual requests fail with cryptic HTTP 400 errors?▼

Actual's SGLang/vLLM backends only accept reasoning_effort values of none, low, medium, high, or max. The built-in Indagis provider clamps xhigh to high and ultra to max; on older versions set a per-model cap via agent.reasoning_overrides in config.yaml.

Can I configure Actual as a custom provider in Indagis?▼

No. Indagis has first-class actual provider support that owns the name and handles base-url normalization, the Responses transport, and local no-auth automatically. Stale custom provider blocks named actual are ignored or conflict and should be removed.

What are the limitations of small local GGUF models with Indagis?▼

Small models like 0.5B Q4_K_M are toys with limited context, and reasoning variants can burn a small max_tokens entirely on thinking, returning empty content. Use 7-8B Q4_K_M as a daily driver and give generous max_tokens to reasoning models.