Users are confused about the difference between `hermes model` (terminal
command for full provider setup) and `/model` (session command for switching
between already-configured providers). This distinction was not documented
anywhere.
Changes across 4 doc pages:
- cli-commands.md: Added warning callout explaining the difference, added
--global flag docs, added 'only see OpenRouter models?' info box
- slash-commands.md: Added notes on both TUI and messaging /model entries
that /model only switches between configured providers
- providers.md: Added 'Two Commands for Model Management' comparison table
near top of page, added warning callout in switching section
- faq.md: Added new FAQ entry '/model only shows one provider' with quick
reference table
Prompted by user feedback in Discord — new users consistently hit this
confusion when trying to add providers from inside a session.
Adds Arcee AI as a standard direct provider (ARCEEAI_API_KEY) with
Trinity models: trinity-large-thinking, trinity-large-preview, trinity-mini.
Standard OpenAI-compatible provider checklist: auth.py, config.py,
models.py, main.py, providers.py, doctor.py, model_normalize.py,
model_metadata.py, setup.py, trajectory_compressor.py.
Based on PR #9274 by arthurbr11, simplified to a standard direct
provider without dual-endpoint OpenRouter routing.
When the API returns "max_tokens too large given prompt" (input tokens
are within the context window, but input + requested output > window),
the old code incorrectly routed through the same handler as "prompt too
long" errors, calling get_next_probe_tier() and permanently halving
context_length. This made things worse: the window was fine, only the
requested output size needed trimming for that one call.
Two distinct error classes now handled separately:
Prompt too long — input itself exceeds context window.
Fix: compress history + halve context_length (existing behaviour,
unchanged).
Output cap too large — input OK, but input + max_tokens > window.
Fix: parse available_tokens from the error message, set a one-shot
_ephemeral_max_output_tokens override for the retry, and leave
context_length completely untouched.
Changes:
- agent/model_metadata.py: add parse_available_output_tokens_from_error()
that detects Anthropic's "available_tokens: N" error format and returns
the available output budget, or None for all other error types.
- run_agent.py: call the new parser first in the is_context_length_error
block; if it fires, set _ephemeral_max_output_tokens (with a 64-token
safety margin) and break to retry without touching context_length.
_build_api_kwargs consumes the ephemeral value exactly once then clears
it so subsequent calls use self.max_tokens normally.
- agent/anthropic_adapter.py: expand build_anthropic_kwargs docstring to
clearly document the max_tokens (output cap) vs context_length (total
window) distinction, which is a persistent source of confusion due to
the OpenAI-inherited "max_tokens" name.
- cli-config.yaml.example: add inline comments explaining both keys side
by side where users are most likely to look.
- website/docs/integrations/providers.md: add a callout box at the top
of "Context Length Detection" and clarify the troubleshooting entry.
- tests/test_ctx_halving_fix.py: 24 tests across four classes covering
the parser, build_anthropic_kwargs clamping, ephemeral one-shot
consumption, and the invariant that context_length is never mutated
on output-cap errors.
The old setup wizard (pre-March 2026) wrote LLM_MODEL to ~/.hermes/.env
across 12 provider flows. Commit 9302690e removed the writes but never
cleaned up existing .env files, leaving a dead variable that:
- Nothing in the codebase reads (zero os.getenv calls)
- The docs incorrectly claimed the gateway still used as fallback
- Caused user confusion when debugging model resolution issues
Changes:
- config.py: Bump _config_version 12 → 13, add migration to clear
LLM_MODEL and OPENAI_MODEL from .env (both dead since March 2026)
- environment-variables.md: Remove LLM_MODEL row, fix HERMES_MODEL
description to stop referencing it
- providers.md: Update deprecation notice from 'deprecated' to 'removed'
- Add full Supermemory section to memory-providers.md with config table,
tools, setup instructions, and key features
- Update provider count from 7 to 8 across memory.md and memory-providers.md
- Add SUPERMEMORY_API_KEY to environment-variables.md
- Add Supermemory to integrations/providers.md optional API keys table
- Add supermemory to cli-commands.md provider list
- Add Supermemory to profile isolation section (config file providers)
Windows users running Hermes in WSL2 with model servers on the Windows
host hit 'connection refused' because WSL2's NAT networking means
localhost points to the VM, not Windows.
Covers:
- Mirrored networking mode (Win 11 22H2+) — makes localhost work
- NAT mode fallback using the host IP via ip route
- Per-server bind address table (Ollama, LM Studio, llama-server,
vLLM, SGLang)
- Detailed Ollama Windows service config for OLLAMA_HOST
- Windows Firewall rules for WSL2 connections
- Quick verification steps
- Cross-reference from Troubleshooting section
Audit found 24+ discrepancies between docs and code. Fixed:
HIGH severity:
- Remove honcho toolset from tools-reference, toolsets-reference, and tools.md
(converted to memory provider plugin, not a built-in toolset)
- Add note that Honcho is available via plugin
MEDIUM severity:
- Add hermes memory command family to cli-commands.md (setup/status/off)
- Add --clone-all, --clone-from to profile create in cli-commands.md
- Add --max-turns option to hermes chat in cli-commands.md
- Add /btw slash command to slash-commands.md
- Fix profile show example output (remove nonexistent disk usage,
add .env and SOUL.md status lines)
- Add missing hermes-webhook toolset to toolsets-reference.md
- Add 5 missing providers to fallback-providers.md table
- Add 7 missing providers to providers.md fallback list
- Fix outdated model examples: glm-4-plus→glm-5, moonshot-v1-auto→kimi-for-coding
* docs: update llama.cpp section with --jinja flag and tool calling guide
The llama.cpp docs were missing the --jinja flag which is required for
tool calling to work. Without it, models output tool calls as raw JSON
text instead of structured API responses, making Hermes unable to
execute them.
Changes:
- Add --jinja and -fa flags to the server startup example
- Replace deprecated env vars (OPENAI_BASE_URL, LLM_MODEL) with
hermes model interactive setup
- Add caution block explaining the --jinja requirement and symptoms
- List models with native tool calling support
- Add /props endpoint verification tip
* docs+feat: comprehensive local LLM provider guides and context length warning
Docs (providers.md):
- Rewrote Ollama section with context length warning (defaults to 4k on
<24GB VRAM), three methods to increase it, and verification steps
- Rewrote vLLM section with --max-model-len, tool calling flags
(--enable-auto-tool-choice, --tool-call-parser), and context guidance
- Rewrote SGLang section with --context-length, --tool-call-parser,
and warning about 128-token default max output
- Added LM Studio section (port 1234, context length defaults to 2048,
tool calling since 0.3.6)
- Added llama.cpp context length flag (-c) and GPU offload (-ngl)
- Added Troubleshooting Local Models section covering:
- Tool calls appearing as text (with per-server fix table)
- Silent context truncation and diagnosis commands
- Low detected context at startup
- Truncated responses
- Replaced all deprecated env vars (OPENAI_BASE_URL, LLM_MODEL) with
hermes model interactive setup and config.yaml examples
- Added deprecation warning for legacy env vars in General Setup
Code (cli.py):
- Added context length warning in show_banner() when detected context
is <= 8192 tokens, with server-specific fix hints:
- Ollama (port 11434): suggests OLLAMA_CONTEXT_LENGTH env var
- LM Studio (port 1234): suggests model settings adjustment
- Other servers: suggests config.yaml override
Tests:
- 9 new tests covering warning thresholds, server-specific hints,
and no-warning cases
Major reorganization of the documentation site for better discoverability
and navigation. 94 pages across 8 top-level sections (was 5).
Structural changes:
- Promote Features from 3-level-deep subcategory to top-level section
with new Overview hub page categorizing all 26 feature pages
- Promote Messaging Platforms from User Guide subcategory to top-level
section, add platform comparison matrix (13 platforms x 7 features)
- Create new Integrations section with hub page, grouping MCP, ACP,
API Server, Honcho, Provider Routing, Fallback Providers
- Extract AI provider content (626 lines) from configuration.md into
dedicated integrations/providers.md — configuration.md drops from
1803 to 1178 lines
- Subcategorize Developer Guide into Architecture, Extending, Internals
- Rename "User Guide" to "Using Hermes" for top-level items
Orphan fixes (7 pages now reachable via sidebar):
- build-a-hermes-plugin.md added to Guides
- sms.md added to Messaging Platforms
- context-references.md added to Features > Core
- plugins.md added to Features > Core
- git-worktrees.md added to Using Hermes
- checkpoints-and-rollback.md added to Using Hermes
- checkpoints.md (30-line stub) deleted, superseded by
checkpoints-and-rollback.md (203 lines)
New files:
- integrations/index.md — Integrations hub page
- integrations/providers.md — AI provider setup (extracted)
- user-guide/features/overview.md — Features hub page
Broken link fixes:
- quickstart.md, faq.md: update context-length-detection anchors
- configuration.md: update checkpoints link
- overview.md: fix checkpoint link path
Docusaurus build verified clean (zero broken links/anchors).