Commit Graph

10 Commits

Author SHA1 Message Date
Teknium
3576f44a57 feat: add Vercel AI Gateway provider (#1628)
* feat: add Vercel AI Gateway as a first-class provider

Adds AI Gateway (ai-gateway.vercel.sh) as a new inference provider
with AI_GATEWAY_API_KEY authentication, live model discovery, and
reasoning support via extra_body.reasoning.

Based on PR #1492 by jerilynzheng.

* feat: add AI Gateway to setup wizard, doctor, and fallback providers

* test: add AI Gateway to api_key_providers test suite

* feat: add AI Gateway to hermes model CLI and model metadata

Wire AI Gateway into the interactive model selection menu and add
context lengths for AI Gateway model IDs in model_metadata.py.

* feat: use claude-haiku-4.5 as AI Gateway auxiliary model

* revert: use gemini-3-flash as AI Gateway auxiliary model

* fix: move AI Gateway below established providers in selection order

---------

Co-authored-by: jerilynzheng <jerilynzheng@users.noreply.github.com>
Co-authored-by: jerilynzheng <zheng.jerilyn@gmail.com>
2026-03-17 00:12:16 -07:00
teknium1
cd4e995d54 fix(anthropic): live model fetching + adaptive thinking for 4.5+ models
- Add _fetch_anthropic_models() to hermes_cli/models.py — hits the
  Anthropic /v1/models endpoint to get the live model catalog. Handles
  both API key and OAuth token auth headers.

- Wire it into provider_model_ids() so both 'hermes model' and
  'hermes setup model' show the live list instead of a stale static one.

- Update static _PROVIDER_MODELS fallback with full current catalog:
  opus-4-6, sonnet-4-6, opus-4-5, sonnet-4-5, opus-4, sonnet-4, haiku-4-5

- Update model_metadata.py with context lengths for all current models.

- Fix thinking parameter for 4.5+ models: use type='adaptive' instead
  of type='enabled' (Anthropic deprecated 'enabled' for newer models,
  warns at runtime). Detects model version from the model name string.

Verified live:
  hermes model → Anthropic → auto-detected creds → shows 7 live models
  hermes chat --provider anthropic --model claude-opus-4-6 → works
2026-03-12 17:04:31 -07:00
teknium1
5e12442b4b feat: native Anthropic provider with Claude Code credential auto-discovery
Add Anthropic as a first-class inference provider, bypassing OpenRouter
for direct API access. Uses the native Anthropic SDK with a full format
adapter (same pattern as the codex_responses api_mode).

## Auth (three methods, priority order)
1. ANTHROPIC_API_KEY env var (regular API key, sk-ant-api-*)
2. ANTHROPIC_TOKEN / CLAUDE_CODE_OAUTH_TOKEN env var (setup-token, sk-ant-oat-*)
3. Auto-discovery from ~/.claude/.credentials.json (Claude Code subscription)
   - Reads Claude Code's OAuth credentials
   - Checks token expiry with 60s buffer
   - Setup tokens use Bearer auth + anthropic-beta: oauth-2025-04-20 header
   - Regular API keys use standard x-api-key header

## Changes by file

### New files
- agent/anthropic_adapter.py — Client builder, message/tool/response
  format conversion, Claude Code credential reader, token resolver.
  Handles system prompt extraction, tool_use/tool_result blocks,
  thinking/reasoning, orphaned tool_use cleanup, cache_control.
- tests/test_anthropic_adapter.py — 36 tests covering all adapter logic

### Modified files
- pyproject.toml — Add anthropic>=0.39.0 dependency
- hermes_cli/auth.py — Add 'anthropic' to PROVIDER_REGISTRY with
  three env vars, plus 'claude'/'claude-code' aliases
- hermes_cli/models.py — Add model catalog, labels, aliases, provider order
- hermes_cli/main.py — Add 'anthropic' to --provider CLI choices
- hermes_cli/runtime_provider.py — Add Anthropic branch returning
  api_mode='anthropic_messages' (before generic api_key fallthrough)
- hermes_cli/setup.py — Add Anthropic setup wizard with Claude Code
  credential auto-discovery, model selection, OpenRouter tools prompt
- agent/auxiliary_client.py — Add claude-haiku-4-5 as aux model
- agent/model_metadata.py — Add bare Claude model context lengths
- run_agent.py — Add anthropic_messages api_mode:
  * Client init (Anthropic SDK instead of OpenAI)
  * API call dispatch (_anthropic_client.messages.create)
  * Response validation (content blocks)
  * finish_reason mapping (stop_reason -> finish_reason)
  * Token usage (input_tokens/output_tokens)
  * Response normalization (normalize_anthropic_response)
  * Client interrupt/rebuild
  * Prompt caching auto-enabled for native Anthropic
- tests/test_run_agent.py — Update test_anthropic_base_url_accepted to
  expect native routing, add test_prompt_caching_native_anthropic
2026-03-12 15:47:45 -07:00
Teknium
e9c3317158 fix: improve Kimi model selection — auto-detect endpoint, add missing models (#1039)
* fix: /reasoning command output ordering, display, and inline think extraction

Three issues with the /reasoning command:

1. Output interleaving: The command echo used print() while feedback
   used _cprint(), causing them to render out-of-order under
   prompt_toolkit's patch_stdout. Changed echo to use _cprint() so
   all output renders through the same path in correct order.

2. Reasoning display not working: /reasoning show toggled a flag
   but reasoning never appeared for models that embed thinking in
   inline <think> blocks rather than structured API fields. Added
   fallback extraction in _build_assistant_message to capture
   <think> block content as reasoning when no structured reasoning
   fields (reasoning, reasoning_content, reasoning_details) are
   present. This feeds into both the reasoning callback (during
   tool loops) and the post-response reasoning box display.

3. Feedback clarity: Added checkmarks to confirm actions, persisted
   show/hide to config (was session-only before), and aligned the
   status display for readability.

Tests: 7 new tests for inline think block extraction (41 total).

* feat: add /reasoning command to gateway (Telegram/Discord/etc)

The /reasoning command only existed in the CLI — messaging platforms
had no way to view or change reasoning settings. This adds:

1. /reasoning command handler in the gateway:
   - No args: shows current effort level and display state
   - /reasoning <level>: sets reasoning effort (none/low/medium/high/xhigh)
   - /reasoning show|hide: toggles reasoning display in responses
   - All changes saved to config.yaml immediately

2. Reasoning display in gateway responses:
   - When show_reasoning is enabled, prepends a 'Reasoning' block
     with the model's last_reasoning content before the response
   - Collapses long reasoning (>15 lines) to keep messages readable
   - Uses last_reasoning from run_conversation result dict

3. Plumbing:
   - Added _show_reasoning attribute loaded from config at startup
   - Propagated last_reasoning through _run_agent return dict
   - Added /reasoning to help text and known_commands set
   - Uses getattr for _show_reasoning to handle test stubs

* fix: improve Kimi model selection — auto-detect endpoint, add missing models

Kimi Coding Plan setup:
- New dedicated _model_flow_kimi() replaces the generic API-key flow
  for kimi-coding. Removes the confusing 'Base URL' prompt entirely —
  the endpoint is auto-detected from the API key prefix:
    sk-kimi-* → api.kimi.com/coding/v1 (Kimi Coding Plan)
    other     → api.moonshot.ai/v1 (legacy Moonshot)

- Shows appropriate models for each endpoint:
    Coding Plan: kimi-for-coding, kimi-k2.5, kimi-k2-thinking, kimi-k2-thinking-turbo
    Moonshot:    full model catalog

- Clears any stale KIMI_BASE_URL override so runtime auto-detection
  via _resolve_kimi_base_url() works correctly.

Model catalog updates:
- Added kimi-for-coding (primary Coding Plan model) and kimi-k2-thinking-turbo
  to models.py, main.py _PROVIDER_MODELS, and model_metadata.py context windows.

- Updated User-Agent from KimiCLI/1.0 to KimiCLI/1.3 (Kimi's coding
  endpoint whitelists known coding agents via User-Agent sniffing).
2026-03-12 05:58:48 -07:00
teknium1
9742f11fda chore: add context lengths for Kimi and MiniMax models
Adds DEFAULT_CONTEXT_LENGTHS entries for kimi-k2.5 (262144), kimi-k2-thinking
(262144), kimi-k2-turbo-preview (262144), kimi-k2-0905-preview (131072),
MiniMax-M2.5/M2.5-highspeed/M2.1 (204800), and glm-4.5/4.5-flash (131072).

Avoids unnecessary 2M-token probe on first use with direct providers.
2026-03-06 19:01:38 -08:00
teknium1
3c6c11b7c9 Merge PR #420: fix: respect OPENAI_BASE_URL when resolving API key priority
Authored by manuelschipper. Adds GLM-4.7 and GLM-5 context lengths (202752)
to model_metadata.py. The key priority fix (prefer OPENAI_API_KEY for
non-OpenRouter endpoints) was already applied in PR #295; merged the Z.ai
mention into the comment.
2026-03-06 18:43:13 -08:00
teknium1
e9f05b3524 test: comprehensive tests for model metadata + firecrawl config
model_metadata tests (61 tests, was 39):
  - Token estimation: concrete value assertions, unicode, tool_call messages,
    vision multimodal content, additive verification
  - Context length resolution: cache-over-API priority, no-base_url skips cache,
    missing context_length key in API response
  - API metadata fetch: canonical_slug aliasing, TTL expiry with time mock,
    stale cache fallback on API failure, malformed JSON resilience
  - Probe tiers: above-max returns 2M, zero returns None
  - Error parsing: Anthropic format ('X > Y maximum'), LM Studio, empty string,
    unreasonably large numbers — also fixed parser to handle Anthropic format
  - Cache: corruption resilience (garbage YAML, wrong structure), value updates,
    special chars in model names

Firecrawl config tests (8 tests, was 4):
  - Singleton caching (core purpose — verified constructor called once)
  - Constructor failure recovery (retry after exception)
  - Return value actually asserted (not just constructor args)
  - Empty string env vars treated as absent
  - Proper setup/teardown for env var isolation
2026-03-05 18:22:39 -08:00
teknium1
c886333d32 feat: smart context length probing with persistent caching + banner display
Replaces the unsafe 128K fallback for unknown models with a descending
probe strategy (2M → 1M → 512K → 200K → 128K → 64K → 32K). When a
context-length error occurs, the agent steps down tiers and retries.
The discovered limit is cached per model+provider combo in
~/.hermes/context_length_cache.yaml so subsequent sessions skip probing.

Also parses API error messages to extract the actual context limit
(e.g. 'maximum context length is 32768 tokens') for instant resolution.

The CLI banner now displays the context window size next to the model
name (e.g. 'claude-opus-4 · 200K context · Nous Research').

Changes:
- agent/model_metadata.py: CONTEXT_PROBE_TIERS, persistent cache
  (save/load/get), parse_context_limit_from_error(), get_next_probe_tier()
- agent/context_compressor.py: accepts base_url, passes to metadata
- run_agent.py: step-down logic in context error handler, caches on success
- cli.py + hermes_cli/banner.py: context length in welcome banner
- tests: 22 new tests for probing, parsing, and caching

Addresses #132. PR #319's approach (8K default) rejected — too conservative.
2026-03-05 16:09:57 -08:00
Dev User
3221818b6e fix: respect OPENAI_BASE_URL when resolving API key priority
When base_url points to a non-OpenRouter endpoint (e.g. Z.ai),
OPENROUTER_API_KEY incorrectly takes priority over OPENAI_API_KEY,
sending the wrong credentials. This causes 401 errors on the main
inference path and forces users to comment out OPENROUTER_API_KEY,
which then breaks auxiliary clients (compression, vision).

Fix: check whether base_url contains "openrouter" and swap the key
priority accordingly. Also adds GLM-4.7 and GLM-5 context lengths
to DEFAULT_CONTEXT_LENGTHS.
2026-03-05 08:25:16 +00:00
teknium1
9123cfb5dd Refactor Terminal and AIAgent cleanup 2026-02-21 22:31:43 -08:00