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feat: provider modules — ProviderProfile ABC, 33 providers, fetch_models, transport single-path
Introduces providers/ package — single source of truth for every inference provider. Adding a simple api-key provider now requires one providers/<name>.py file with zero edits anywhere else. What this PR ships: - providers/ package (ProviderProfile ABC + 33 profiles across 4 api_modes) - ProviderProfile declarative fields: name, api_mode, aliases, display_name, env_vars, base_url, models_url, auth_type, fallback_models, hostname, default_headers, fixed_temperature, default_max_tokens, default_aux_model - 4 overridable hooks: prepare_messages, build_extra_body, build_api_kwargs_extras, fetch_models - chat_completions.build_kwargs: profile path via _build_kwargs_from_profile, legacy flag path retained for lmstudio/tencent-tokenhub (which have session-aware reasoning probing that doesn't map cleanly to hooks yet) - run_agent.py: profile path for all registered providers; legacy path variable scoping fixed (all flags defined before branching) - Auto-wires: auth.PROVIDER_REGISTRY, models.CANONICAL_PROVIDERS, doctor health checks, config.OPTIONAL_ENV_VARS, model_metadata._URL_TO_PROVIDER - GeminiProfile: thinking_config translation (native + openai-compat nested) - New tests/providers/ (79 tests covering profile declarations, transport parity, hook overrides, e2e kwargs assembly) Deltas vs original PR (salvaged onto current main): - Added profiles: alibaba-coding-plan, azure-foundry, minimax-oauth (were added to main since original PR) - Skipped profiles: lmstudio, tencent-tokenhub stay on legacy path (their reasoning_effort probing has no clean hook equivalent yet) - Removed lmstudio alias from custom profile (it's a separate provider now) - Skipped openrouter/custom from PROVIDER_REGISTRY auto-extension (resolve_provider special-cases them; adding breaks runtime resolution) - runtime_provider: profile.api_mode only as fallback when URL detection finds nothing (was breaking minimax /v1 override) - Preserved main's legacy-path improvements: deepseek reasoning_content preserve, gemini Gemma skip, OpenRouter response caching, Anthropic 1M beta recovery, etc. - Kept agent/copilot_acp_client.py in place (rejected PR's relocation — main has 7 fixes landed since; relocation would revert them) - _API_KEY_PROVIDER_AUX_MODELS alias kept for backward compat with existing test imports Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com> Closes #14418
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@ -93,6 +93,42 @@ This path includes everything from Path A plus:
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11. `run_agent.py`
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12. `pyproject.toml` if a provider SDK is required
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## Fast path: Simple API-key providers
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If your provider is just an OpenAI-compatible endpoint that authenticates with a single API key, you do not need to touch `auth.py`, `runtime_provider.py`, `main.py`, or any of the other files in the full checklist below.
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All you need is:
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1. A file in `providers/` (e.g. `providers/myprovider.py`) that calls `register_provider()` with the provider config.
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2. That's it. `auth.py` auto-registers every file in `providers/` at startup via a module-level import sweep.
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When you add a `providers/*.py` file and call `register_provider()`, the following wire up automatically:
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1. `PROVIDER_REGISTRY` entry in `auth.py` (credential resolution, env-var lookup)
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2. `api_mode` set to `chat_completions`
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3. `base_url` sourced from the config or the declared env var
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4. `env_vars` checked in priority order for the API key
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5. `fallback_models` list registered for the provider
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6. `--provider` CLI flag accepts the provider id
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7. `hermes model` menu includes the provider
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8. `hermes setup` wizard delegates to `main.py` automatically
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9. `provider:model` alias syntax works
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10. Runtime resolver returns the correct `base_url` and `api_key`
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11. `HERMES_INFERENCE_PROVIDER` env-var override accepts the provider id
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12. Fallback model activation can switch into the provider cleanly
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See `providers/nvidia.py` or `providers/gmi.py` as a template.
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## Full path: OAuth and complex providers
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Use the full checklist below when your provider needs any of the following:
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- OAuth or token refresh (Nous Portal, Codex, Google Gemini, Qwen Portal, Copilot)
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- A non-OpenAI API shape that requires a new adapter (Anthropic Messages, Codex Responses)
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- Custom endpoint detection or multi-region probing (z.ai, Kimi)
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- A curated static model catalog or live `/models` fetch
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- Provider-specific `hermes model` menu entries with bespoke auth flows
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## Step 1: Pick one canonical provider id
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Choose a single provider id and use it everywhere.
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@ -20,6 +20,9 @@ Primary implementation:
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- `hermes_cli/auth.py` — provider registry, `resolve_provider()`
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- `hermes_cli/model_switch.py` — shared `/model` switch pipeline (CLI + gateway)
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- `agent/auxiliary_client.py` — auxiliary model routing
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- `providers/` — declarative source for `api_mode`, `base_url`, `env_vars`, `fallback_models` (auto-registered into `auth.py` `PROVIDER_REGISTRY` at startup)
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`get_provider_profile()` in `providers/` returns a typed dict for a given provider id. `runtime_provider.py` calls this at resolution time to get the canonical `base_url`, `env_vars` priority list, `api_mode`, and `fallback_models` without needing to duplicate that data in multiple files. Adding a new `providers/*.py` file that calls `register_provider()` is enough for `runtime_provider.py` to pick it up — no branch needed in the resolver itself.
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If you are trying to add a new first-class inference provider, read [Adding Providers](./adding-providers.md) alongside this page.
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