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feat: add z.ai/GLM, Kimi/Moonshot, MiniMax as first-class providers

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Adds 4 new direct API-key providers (zai, kimi-coding, minimax, minimax-cn)
to the inference provider system. All use standard OpenAI-compatible
chat/completions endpoints with Bearer token auth.

Core changes:
- auth.py: Extended ProviderConfig with api_key_env_vars and base_url_env_var
  fields. Added providers to PROVIDER_REGISTRY. Added provider aliases
  (glm, z-ai, zhipu, kimi, moonshot). Added auto-detection of API-key
  providers in resolve_provider(). Added resolve_api_key_provider_credentials()
  and get_api_key_provider_status() helpers.
- runtime_provider.py: Added generic API-key provider branch in
  resolve_runtime_provider() — any provider with auth_type='api_key'
  is automatically handled.
- main.py: Added providers to hermes model menu with generic
  _model_flow_api_key_provider() flow. Updated _has_any_provider_configured()
  to check all provider env vars. Updated argparse --provider choices.
- setup.py: Added providers to setup wizard with API key prompts and
  curated model lists.
- config.py: Added env vars (GLM_API_KEY, KIMI_API_KEY, MINIMAX_API_KEY,
  etc.) to OPTIONAL_ENV_VARS.
- status.py: Added API key display and provider status section.
- doctor.py: Added connectivity checks for each provider endpoint.
- cli.py: Updated provider docstrings.

Docs: Updated README.md, .env.example, cli-config.yaml.example,
cli-commands.md, environment-variables.md, configuration.md.

Tests: 50 new tests covering registry, aliases, resolution, auto-detection,
credential resolution, and runtime provider dispatch.

Inspired by PR #33 (numman-ali) which proposed a provider registry approach.
Credit to tars90percent (PR #473) and manuelschipper (PR #420) for related
provider improvements merged earlier in this changeset.
This commit is contained in:
teknium1 2026-03-06 18:55:12 -08:00
parent fdebca4573
commit 388dd4789c
15 changed files with 1032 additions and 15 deletions
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36
website/docs/user-guide/configuration.md
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@ -64,6 +64,10 @@ You need at least one way to connect to an LLM. Use `hermes model` to switch pro
| **Nous Portal** | `hermes model` (OAuth, subscription-based) |
| **OpenAI Codex** | `hermes model` (ChatGPT OAuth, uses Codex models) |
| **OpenRouter** | `OPENROUTER_API_KEY` in `~/.hermes/.env` |
| **z.ai / GLM** | `GLM_API_KEY` in `~/.hermes/.env` (provider: `zai`) |
| **Kimi / Moonshot** | `KIMI_API_KEY` in `~/.hermes/.env` (provider: `kimi-coding`) |
| **MiniMax** | `MINIMAX_API_KEY` in `~/.hermes/.env` (provider: `minimax`) |
| **MiniMax China** | `MINIMAX_CN_API_KEY` in `~/.hermes/.env` (provider: `minimax-cn`) |
| **Custom Endpoint** | `OPENAI_BASE_URL` + `OPENAI_API_KEY` in `~/.hermes/.env` |
:::info Codex Note
@ -74,6 +78,37 @@ The OpenAI Codex provider authenticates via device code (open a URL, enter a cod
Even when using Nous Portal, Codex, or a custom endpoint, some tools (vision, web summarization, MoA) use OpenRouter independently. An `OPENROUTER_API_KEY` enables these tools.
:::
### First-Class Chinese AI Providers
These providers have built-in support with dedicated provider IDs. Set the API key and use `--provider` to select:
```bash
# z.ai / ZhipuAI GLM
hermes chat --provider zai --model glm-4-plus
# Requires: GLM_API_KEY in ~/.hermes/.env
# Kimi / Moonshot AI
hermes chat --provider kimi-coding --model moonshot-v1-auto
# Requires: KIMI_API_KEY in ~/.hermes/.env
# MiniMax (global endpoint)
hermes chat --provider minimax --model MiniMax-Text-01
# Requires: MINIMAX_API_KEY in ~/.hermes/.env
# MiniMax (China endpoint)
hermes chat --provider minimax-cn --model MiniMax-Text-01
# Requires: MINIMAX_CN_API_KEY in ~/.hermes/.env
```
Or set the provider permanently in `config.yaml`:
```yaml
model:
provider: "zai" # or: kimi-coding, minimax, minimax-cn
default: "glm-4-plus"
```
Base URLs can be overridden with `GLM_BASE_URL`, `KIMI_BASE_URL`, `MINIMAX_BASE_URL`, or `MINIMAX_CN_BASE_URL` environment variables.
## Custom & Self-Hosted LLM Providers
Hermes Agent works with **any OpenAI-compatible API endpoint**. If a server implements `/v1/chat/completions`, you can point Hermes at it. This means you can use local models, GPU inference servers, multi-provider routers, or any third-party API.
@ -290,6 +325,7 @@ LLM_MODEL=meta-llama/Llama-3.1-70B-Instruct-Turbo
| **Cost optimization** | ClawRouter or OpenRouter with `sort: "price"` |
| **Maximum privacy** | Ollama, vLLM, or llama.cpp (fully local) |
| **Enterprise / Azure** | Azure OpenAI with custom endpoint |
| **Chinese AI models** | z.ai (GLM), Kimi/Moonshot, or MiniMax (first-class providers) |
:::tip
You can switch between providers at any time with `hermes model` — no restart required. Your conversation history, memory, and skills carry over regardless of which provider you use.