fix(audit): reject retired aliases; sweep gpu-light/gemma-4-12b to gpu-vision
audit-hermes-config.py Rule 8 required auxiliary.vision.model and auxiliary.web_extract.model to equal the retired 'gpu-light', so a config adopting the live canonical 'gpu-vision' FAILED our own audit - the audit was enforcing a dead alias (400 Invalid model name). Rule 8 now requires gpu-vision; retired names gpu-light/crew-auto join the raw-name rejection set; the guidance message names the live aliases. Sweep of the remaining references: gpu-self-heal stops canonicalizing gpu-light; hermes-config-template, hermes-agent-baseline, hermes-key-enforcement, inference-optimization, litellm-client-timeouts and gpu-fleet now use the live gpu-vision alias. Where a file restated model/rpm/weight/fallback state it now points at CT 116 /opt/inference-harness/litellm_config.yaml instead of duplicating it. koby's .129 config is report-only and recorded, not edited. Adds tests/test_audit_hermes_config_alias.py: executes the audit CLI and asserts gpu-vision passes while gpu-light and gemma-4-12b fail.
This commit is contained in:
abiba
+12
-8
@@ -89,15 +89,16 @@ def audit(path):
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)
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# --- Rule 8: GPU Workload Distribution ---
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# gpu-light (and gemma-4-12b) were retired 2026-09-12; the RTX 5070 stable alias is gpu-vision.
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check(
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aux.get("vision", {}).get("model") == "gpu-light",
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aux.get("vision", {}).get("model") == "gpu-vision",
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"Rule 8",
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f"auxiliary.vision.model must be gpu-light (got {aux.get('vision', {}).get('model')!r}) — RTX 5070 stable alias",
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f"auxiliary.vision.model must be gpu-vision (got {aux.get('vision', {}).get('model')!r}) — RTX 5070 stable alias",
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)
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check(
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aux.get("web_extract", {}).get("model") == "gpu-light",
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aux.get("web_extract", {}).get("model") == "gpu-vision",
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"Rule 8",
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f"auxiliary.web_extract.model must be gpu-light (got {aux.get('web_extract', {}).get('model')!r}) — RTX 5070 stable alias",
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f"auxiliary.web_extract.model must be gpu-vision (got {aux.get('web_extract', {}).get('model')!r}) — RTX 5070 stable alias",
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)
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# --- Rule 9: Compression Threshold ---
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@@ -178,8 +179,11 @@ def audit(path):
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f"custom_providers[0].base_url must end with /v1 (got {cp.get('base_url')!r})",
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)
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# --- No raw model names (Rule 7/8 spirit) ---
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raw_names = {"gemma-4-12b", "qwen3.6-27B-code", "qwen3.6-35B-udq4", "ornith-1.0-35b"}
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# --- No raw or retired model names (Rule 7/8 spirit) ---
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# Retired names are rejected by the alias rules above; a config that names them directly is
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# flagged here too. gpu-light/gemma-4-12b/crew-auto were retired 2026-09-12.
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raw_names = {"gemma-4-12b", "qwen3.6-27B-code", "qwen3.6-35B-udq4", "ornith-1.0-35b",
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"gpu-light", "crew-auto"}
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for section_path, section_dict in [
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("model", model), ("compression", comp),
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("auxiliary.vision", aux.get("vision", {})),
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@@ -191,8 +195,8 @@ def audit(path):
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if m in raw_names:
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warn(
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"Rule 7/8",
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f"{section_path}.model = {m!r} — raw model name, use stable alias instead "
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f"(gpu-light, gpu-dense, strix-moe, syslog-auto)",
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f"{section_path}.model = {m!r} — raw or retired model name, use a live stable alias "
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f"instead (gpu-vision, gpu-dense, strix-moe, syslog-auto)",
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)
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# --- Report ---
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+1
-1
@@ -216,7 +216,7 @@ If no SSH access, send Zulip DM via abiba-bot with vault update instructions.
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- **Alert migration**: All alerts now go to `#agent-hub` topics (`alerts-gpu`, `alerts-pm2`, `alerts-infra`) instead of DMs. Cross-agent visibility enabled.
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- **tok/s benchmarks**: Measured every 5 min via LiteLLM proxy. Baselines tracked with 30%/50% degradation thresholds.
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- **NetBird 502**: Tanko routes through NetBird for litellm.sysloggh.net. Use direct IP if NetBird down.
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- **Alias-retirement follow-up (2026-09-12)**: the agent-facing templates (`hermes-config-template.prose.md`, `hermes-agent-baseline.prose.md`), `litellm-api-keys.prose.md`, and the executable `audit-hermes-config.py` still reference the retired `gpu-light`/`gemma-4-12b` names, and `audit-hermes-config.py` Rule 8 currently fails a config whose vision/web_extract model is `gpu-vision`. These are tracked separately and are intentionally NOT updated in this change.
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- **Alias-retirement sweep (2026-09-12)**: `gemma-4-12b`, `gpu-light` and `crew-auto` are retired and replaced by `gpu-vision` / no cap respectively. The agent-facing templates (`hermes-config-template.prose.md`, `hermes-agent-baseline.prose.md`), `litellm-api-keys.prose.md`, `gpu-self-heal.prose.md`, `hermes-key-enforcement.prose.md`, `inference-optimization.prose.md`, `litellm-client-timeouts.prose.md` and the executable `audit-hermes-config.py` were all updated to the live canonical alias in the same change. **koby's config on .129 still names `gpu-light` (and `gemma-4-E4B`); .129 is report-only, so that is recorded for its owner and NOT edited here.**
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## GPU Inference Benchmarks (Current)
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@@ -12,7 +12,7 @@ description: >
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Router (port 9000) DECOMMISSIONED 2026-09-11; references replaced with direct GPU routing.
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Benchmark baselines refreshed to live values.
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Prometheus exporters removed — not deployed; fall back to direct sidecar probes.
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Stable role-based aliases (strix-moe, gpu-dense, gpu-light) from gpu-fleet.
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Stable role-based aliases (strix-moe, gpu-dense, gpu-vision) from gpu-fleet.
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agent: abiba
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depends_on:
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- gpu-monitor.prose.md (live data source on .24:9100)
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@@ -52,8 +52,8 @@ depends_on:
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Key notes:
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- All models use direct GPU routing via LiteLLM (`api_key: not-needed`). Router (port 9000) was decommissioned 2026-09-11 and is NOT in the inference path.
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- Stable aliases (gpu-dense, gpu-light, strix-moe) from gpu-fleet are the canonical names for agent configs. Model-specific names still work but are deprecated.
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- RTX 5070 tok/s is ~145 for Qwen3.5-9B — gpu-light is the fastest endpoint. Route vision/web/light work there first. NOTE: Qwen3.5-9B is multimodal (image+text), NOT text-only like gemma-4-12b was.
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- Stable aliases (gpu-dense, gpu-vision, strix-moe) from gpu-fleet are the canonical names for agent configs. Model-specific names still work but are deprecated. The retired names `gpu-light` and `gemma-4-12b` were superseded by `gpu-vision` on 2026-09-12 and no longer resolve (400 `Invalid model name`).
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- The RTX 5070 is the fastest endpoint per token — `gpu-vision` is its canonical alias. Route vision/web/light work there first. The RTX 5070 model is multimodal (image+text).
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- Strix Halo is 62.9 tok/s (89% of 70.5 baseline) — below optimal but stable. Check for competing workloads.
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- RTX 3090 VRAM at 88% — within role-appropriate range (role = heavy reasoning, needs the headroom).
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- RTX 5070 VRAM at 83% — role-appropriate for vision/web (smaller batch sizes).
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@@ -157,13 +157,14 @@ Key notes:
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### Rule 10: Workload Distribution Optimization (updated 2026-07-18)
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- **Detect**: GPU roles misaligned with hardware capabilities
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- **Target distribution**:
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- RTX 3090 (gpu-dense, 24GB, 74.9 tok/s) → Heavy reasoning, code gen, long conversations (slowest per-token but largest context capacity). Weight: 0.55 (LiteLLM).
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- RTX 5070 (gpu-light, 12GB, ~145 tok/s) → Vision (image+text), web search, lightweight tasks. Weight: 0.15 (LiteLLM).
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- Strix Halo (strix-moe, 64GB, 62.9 tok/s) → Context compression, summarization, long docs (MoE model). Weight: 0.30 (LiteLLM).
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- RTX 3090 (gpu-dense, 24GB, 74.9 tok/s) → Heavy reasoning, code gen, long conversations (slowest per-token but largest context capacity).
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- RTX 5070 (gpu-vision, 12GB, ~145 tok/s) → Vision (image+text), web search, lightweight tasks.
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- Strix Halo (strix-moe, 64GB, 62.9 tok/s) → Context compression, summarization, long docs (MoE model).
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- **Note**: RTX 5070 is the fastest endpoint per token. Route high-volume, low-complexity work there first.
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- **Weights are not restated here** — the live `syslog-auto` pool weights and rpm caps live in CT 116 `/opt/inference-harness/litellm_config.yaml`, the single source of truth.
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- **Fix**:
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- Alert if any GPU is handling workload outside its designated role
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- Recommend agent alias updates to match workload to GPU role (use stable aliases: gpu-dense, gpu-light, strix-moe)
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- Recommend agent alias updates to match workload to GPU role (use stable aliases: gpu-dense, gpu-vision, strix-moe)
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- Track per-GPU request distribution via LiteLLM spend logs
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- **Verify**: Each GPU's request pattern matches its designated role within 24h
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- **Escalate**: If role mismatch persists >48h → agent alias audit needed
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@@ -311,6 +312,6 @@ Pushed to `SyslogSolution/health-logs/gpu/{run_id}.json` — versioned, searchab
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If monitor response > 1MB, log a warning and skip the cycle rather than crashing.
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### L6: Stable Aliases Replace Model Names
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- gpu-fleet introduced stable aliases (strix-moe, gpu-dense, gpu-light) on 2026-07-15.
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- gpu-fleet introduced stable aliases (strix-moe, gpu-dense, gpu-light) on 2026-07-15; `gpu-light` was superseded by `gpu-vision` on 2026-09-12.
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- Self-heal must use aliases for reporting and alerting, not model-specific names.
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- **Rule**: All alert messages and KG nodes use the stable alias as the GPU identifier.
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@@ -80,7 +80,7 @@ custom_providers:
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auxiliary:
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vision:
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provider: harness
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model: gemma-4-12b # or syslog-auto
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model: gpu-vision # RTX 5070 stable alias (or syslog-auto)
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base_url: http://192.168.68.116/litellm/v1
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api_key_env: LITELLM_API_KEY
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api_key: <value from: infisical secrets get LITELLM_API_KEY --project=agents --env=production> # ← MANDATORY workaround
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@@ -95,7 +95,7 @@ auxiliary:
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threshold: 0.65
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target_ratio: 0.3
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provider: harness
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model: syslog-auto # or gemma-4-12b
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model: syslog-auto # or gpu-vision
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base_url: http://192.168.68.116/litellm/v1
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api_key_env: LITELLM_API_KEY
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api_key: <value from: infisical secrets get LITELLM_API_KEY --project=agents --env=production> # ← MANDATORY workaround
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@@ -197,9 +197,8 @@ Key is injected via `infisical run --` wrapper at PM2 startup:
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{ "id": "syslog-auto" },
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{ "id": "strix-moe" },
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{ "id": "gpu-dense" },
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{ "id": "gpu-light" },
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{ "id": "qwen3.6-27B-code" },
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{ "id": "gemma-4-12b" }
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{ "id": "gpu-vision" },
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{ "id": "qwen3.6-27B-code" }
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]
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}
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}
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@@ -102,7 +102,7 @@ model:
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# and falls back to 256K when /v1/models lacks a context
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# field (llama-server does). Without this override, agents
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# silently run syslog-auto at 256K (verified 2026-08-09).
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# Set 65536 if using gemma-4-12b directly (tight VRAM).
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# Set 65536 if pinning a single model directly (tight VRAM).
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fallback_providers:
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provider: deepseek
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@@ -143,25 +143,25 @@ compression:
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# ─── Auxiliary Tasks (CONSISTENCY RULE) ───
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# All auxiliary services MUST use identical model, base_url, and api_key_env:
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# model: gpu-light # stable alias (NOT raw "gemma-4-12b")
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# model: gpu-vision # stable alias (NOT a raw model name)
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# base_url: http://192.168.68.116/litellm/v1 # Rule 5 (2026-08-09): canonical authenticated; /v1 also OK
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# api_key_env: LITELLM_API_KEY
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# Do NOT use syslog-auto for auxiliary tasks — it routes to the primary GPU.
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# gpu-light = RTX 5070 (12B), freeing the Strix Halo for agent reasoning.
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# gpu-vision = RTX 5070 (12B), freeing the Strix Halo for agent reasoning.
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# Heavy aux (delegation, x_search) use gpu-dense (RTX 3090) instead.
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# NEVER use raw model names (gemma-4-12b, qwen3.6-27B-code, qwen3.6-35B-udq4)
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# in agent configs — use the stable aliases so model swaps don't break agents.
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# NEVER use raw model names (e.g. qwen3.6-27B-code, qwen3.6-35B-udq4; gemma-4-12b is retired
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# and no longer resolves) in agent configs — use the stable aliases so model swaps don't break agents.
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auxiliary:
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vision:
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provider: harness
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model: gpu-light # stable alias for RTX 5070 (was raw gemma-4-12b)
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model: gpu-vision # stable alias for RTX 5070
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base_url: http://192.168.68.116/litellm/v1 # Rule 5 (2026-08-09): canonical authenticated; /v1 also OK
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api_key_env: LITELLM_API_KEY
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timeout: 60
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download_timeout: 30
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web_extract:
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provider: harness
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model: gpu-light # stable alias for RTX 5070
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model: gpu-vision # stable alias for RTX 5070
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base_url: http://192.168.68.116/litellm/v1 # Rule 5 (2026-08-09): canonical authenticated; /v1 also OK
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api_key_env: LITELLM_API_KEY
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timeout: 30
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@@ -252,10 +252,11 @@ The following MUST be identical across ALL profiles:
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- For agents needing longer outputs: raise to 8192, but never omit
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### Rule 7: Auxiliary Model Consistency (UPDATED 2026-07-16)
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- Vision and web_extract use `gemma-4-12b` (RTX 5070 — 12GB, vision-optimized)
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- Vision and web_extract use `gpu-vision` (RTX 5070 — 12GB, vision-optimized)
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- Compression uses `strix-moe` (stable alias for Strix Halo — 64GB, 128K ctx, compression-optimized)
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- **`strix-moe` is the only valid compression model name** — LiteLLM does NOT serve `ornith-1.0-35b`
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(it serves `strix-moe`, `qwen3.6-35B-udq4`, `gpu-dense`, `gpu-light`, `syslog-auto`, `gemma-4-12b`, `qwen3.6-27B-code`). Old configs with `ornith-1.0-35b` cause 403/model-not-found on compression calls.
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(do not restate the served model list here — CT 116 `/opt/inference-harness/litellm_config.yaml`
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is the single source of truth for models, aliases, weights and fallbacks). Old configs with `ornith-1.0-35b` cause 403/model-not-found on compression calls.
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- **OPERATIONAL DECISION (2026-07-23): Use `syslog-auto` for compression across all agents.**
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The `syslog-auto` alias routes to the Strix Halo, but uses the weighted pool instead of pinning
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to `strix-moe` directly. This prevents sustained Strix Halo thermal load because the pool can
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@@ -273,11 +274,11 @@ The following MUST be identical across ALL profiles:
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### Rule 8: GPU Workload Distribution (UPDATED 2026-07-16)
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- **RTX 3090 (24GB, 128K ctx, qwen3.6-27B-code)**: Heavy reasoning, code gen, long conversations
|
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- **RTX 5070 (12GB, 128K ctx, gemma-4-12b)**: Vision, web search, quick tasks, web_extract (IQ4_NL+MTP, ~65% VRAM at 128K)
|
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- **RTX 5070 (12GB, 128K ctx, gpu-vision)**: Vision, web search, quick tasks, web_extract (IQ4_NL+MTP, ~65% VRAM at 128K)
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- **Strix Halo (64GB, 128K ctx, syslog-auto)**: Context compression, summarization, long docs
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- Agent profiles MUST route auxiliary tasks to the correct GPU:
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- `auxiliary.vision.model: gemma-4-12b` (RTX 5070)
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- `auxiliary.web_extract.model: gemma-4-12b` (RTX 5070)
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- `auxiliary.vision.model: gpu-vision` (RTX 5070)
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- `auxiliary.web_extract.model: gpu-vision` (RTX 5070)
|
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- `auxiliary.compression.model: syslog-auto` (Strix Halo)
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- Default model (`model.default`) and custom_provider remain `syslog-auto` for auto-routing
|
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- For 128K context window: `threshold: 0.65` (fires at ~85K tokens)
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@@ -297,8 +298,8 @@ The following MUST be identical across ALL profiles:
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- **Koby Exception**: Per captain ruling 2026-08-11, Koby is a DeepSeek-primary external agent; its primary model remains `deepseek-v4-flash` (via api.deepseek.com to preserve DeepSeek-specific reasoning, while other sections follow Rule 10.
|
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- **Hermes agents**: `model.default: syslog-auto`, `custom_providers[0].model: syslog-auto`
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- **pi agents**: `defaultModel: syslog-auto` in `settings.json`, first model in `models.json`
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- `syslog-auto` is the LiteLLM routing model — it load-balances between strix-moe
|
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and qwen3.6-27B-code, with gemma-4-12b as fallback. Using it protects against:
|
||||
- `syslog-auto` is the LiteLLM routing model — it load-balances across the live pool
|
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(see CT 116 `/opt/inference-harness/litellm_config.yaml` for the current members and weights). Using it protects against:
|
||||
- Model name typos that cause 403 errors and silent worker failures
|
||||
- Single GPU downtime (routing falls back automatically)
|
||||
- Key/model authorization mismatches
|
||||
|
||||
@@ -178,7 +178,7 @@ The agent picks up the new key via `infisical run --` at gateway startup.
|
||||
# In litellm_config.yaml — ensures all future keys inherit these defaults:
|
||||
litellm_settings:
|
||||
default_key_generate_params:
|
||||
models: ["syslog-auto", "qwen3.6-27B-code", "gemma-4-12b"]
|
||||
models: ["syslog-auto", "qwen3.6-27B-code", "gpu-vision"]
|
||||
duration: null # ← permanent
|
||||
max_budget: 100
|
||||
metadata:
|
||||
@@ -286,13 +286,13 @@ auxiliary:
|
||||
api_key: sk-<agent-key-from-vault> # ← workaround (get via: infisical secrets get LITELLM_API_KEY --project=agents --env=production --plain)
|
||||
api_key_env: LITELLM_API_KEY
|
||||
base_url: http://192.168.68.116/litellm/v1
|
||||
model: gemma-4-12b
|
||||
model: gpu-vision
|
||||
provider: harness
|
||||
compression:
|
||||
api_key: sk-<agent-key-from-vault> # ← workaround (same as above)
|
||||
api_key_env: LITELLM_API_KEY
|
||||
base_url: http://192.168.68.116/litellm/v1
|
||||
model: gemma-4-12b
|
||||
model: gpu-vision
|
||||
provider: harness
|
||||
```
|
||||
|
||||
|
||||
@@ -99,5 +99,5 @@ call enable-prompt-caching
|
||||
|
||||
call verify-latency
|
||||
host: 192.168.68.116
|
||||
models: [syslog-auto, qwen3.6-27B-code, gemma-4-12b]
|
||||
models: [syslog-auto, qwen3.6-27B-code, gpu-vision]
|
||||
```
|
||||
|
||||
@@ -68,7 +68,9 @@ description: >
|
||||
- Generate new key with key_alias: "{agent_name}" (e.g., "tanko" — bare name, no date)
|
||||
- Set metadata: { "agent": "{agent_name}", "purpose": "agent-inference" }
|
||||
- Duration is null (permanent) — inherited from litellm default_key_generate_params
|
||||
- Set models: ["syslog-auto", "qwen3.6-27B-code", "gemma-4-12b", "strix-moe", "gpu-dense", "gpu-light", "qwen3.6-35B-udq4"]
|
||||
- Set models: read the live key-scoped set rather than hardcoding one — `/v1/models` is key-scoped,
|
||||
and the authoritative registry is CT 116 `/opt/inference-harness/litellm_config.yaml`. Do not add
|
||||
retired names (`gemma-4-12b`, `gpu-light`, `crew-auto` — all retired 2026-09-12).
|
||||
- Note: `ornith-1.0-35b` is NOT a valid LiteLLM model name (use `strix-moe`, the stable alias). qwen3.6-35B-A3B removed from fleet (was never deployed).
|
||||
- Return the new key
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||||
5. **If action == "rotate"**:
|
||||
|
||||
@@ -28,7 +28,7 @@ description: >
|
||||
| syslog-auto | 28.8s | 25.4s | 68 calls took 30-120s; tail to ~300s under load |
|
||||
| qwen3.6-27B-code | 23.0s | — | same backend class as syslog-auto |
|
||||
| strix-moe | 7.5s | — | Strix Halo, healthy |
|
||||
| gemma-4-12b | 2.6s | — | RTX 5070, healthy |
|
||||
| gpu-vision | 2.6s | — | RTX 5070, healthy |
|
||||
|
||||
Sep 6 incident timeline: failures 04:00-07:00 EDT (0% GPU util = wedged
|
||||
backend), full recovery 07:00-08:00 with ZERO client failures once requests
|
||||
@@ -53,7 +53,7 @@ proxy queuing.
|
||||
|
||||
### 2. Auxiliary tasks — keep template timeouts, one correction
|
||||
|
||||
- vision: 60s (keep), web_extract: 30s (keep) — gemma-4-12b averages 2.6s;
|
||||
- vision: 60s (keep), web_extract: 30s (keep) — gpu-vision averages 2.6s;
|
||||
these are fine.
|
||||
- compression: 300s (keep — this was already raised from 60 per gpu-fleet).
|
||||
- **gpu-dense delegation/x_search: set timeout >= 120s.** The RTX 3090
|
||||
|
||||
@@ -0,0 +1,89 @@
|
||||
"""Regression tests for the 2026-09-12 retired-alias sweep in audit-hermes-config.py.
|
||||
|
||||
WHY THIS FILE EXISTS: the executable audit pushed agent configs toward a DEAD alias.
|
||||
Rule 8 required `auxiliary.vision.model == "gpu-light"` and
|
||||
`auxiliary.web_extract.model == "gpu-light"`, but `gpu-light` (and its raw predecessor
|
||||
`gemma-4-12b`) were retired on 2026-09-12 and now return 400 `Invalid model name`; the
|
||||
live RTX 5070 alias is `gpu-vision`. A config that adopted the correct canonical alias
|
||||
therefore FAILED our own audit, so the audit was actively enforcing a broken config.
|
||||
|
||||
These tests execute the real CLI (`python3 audit-hermes-config.py <config>`) and assert
|
||||
observable behaviour — exit code and the emitted rule message — for the live alias and
|
||||
for both retired names. No network, vault, or SSH access is required.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import pathlib
|
||||
import subprocess
|
||||
import sys
|
||||
|
||||
ROOT = pathlib.Path(__file__).resolve().parent.parent
|
||||
AUDIT = ROOT / "audit-hermes-config.py"
|
||||
|
||||
BASE = """
|
||||
model:
|
||||
api_key: ""
|
||||
api_key_env: LITELLM_API_KEY
|
||||
base_url: http://192.168.68.116/v1
|
||||
max_tokens: 4096
|
||||
default: syslog-auto
|
||||
provider: harness
|
||||
fallback_providers:
|
||||
provider: deepseek
|
||||
model: deepseek-v4-flash
|
||||
api_key_env: DEEPSEEK_API_KEY
|
||||
compression:
|
||||
model: syslog-auto
|
||||
provider: harness
|
||||
threshold: 0.65
|
||||
max_context_window: 131072
|
||||
auxiliary:
|
||||
vision:
|
||||
model: {alias}
|
||||
provider: harness
|
||||
web_extract:
|
||||
model: {alias}
|
||||
provider: harness
|
||||
compression:
|
||||
model: syslog-auto
|
||||
provider: harness
|
||||
delegation:
|
||||
provider: harness
|
||||
custom_providers:
|
||||
- name: harness
|
||||
key_env: LITELLM_API_KEY
|
||||
base_url: http://192.168.68.116/v1
|
||||
"""
|
||||
|
||||
|
||||
def _run(tmp_path, alias):
|
||||
cfg = tmp_path / f"{alias}.yaml"
|
||||
cfg.write_text(BASE.format(alias=alias))
|
||||
proc = subprocess.run(
|
||||
[sys.executable, str(AUDIT), str(cfg)],
|
||||
capture_output=True, text=True,
|
||||
)
|
||||
return proc.returncode, proc.stdout
|
||||
|
||||
|
||||
def test_live_canonical_alias_passes(tmp_path):
|
||||
"""The RTX 5070 alias that actually resolves must satisfy Rule 8."""
|
||||
code, out = _run(tmp_path, "gpu-vision")
|
||||
assert code == 0, out
|
||||
assert "RESULT: PASS" in out
|
||||
|
||||
|
||||
def test_retired_gpu_light_is_rejected(tmp_path):
|
||||
"""A config pinned to the retired alias must fail, not pass."""
|
||||
code, out = _run(tmp_path, "gpu-light")
|
||||
assert code == 1, out
|
||||
assert "auxiliary.vision.model must be gpu-vision" in out
|
||||
assert "RESULT: FAIL" in out
|
||||
|
||||
|
||||
def test_retired_gemma_is_rejected(tmp_path):
|
||||
"""The retired raw model name must fail Rule 8 as well."""
|
||||
code, out = _run(tmp_path, "gemma-4-12b")
|
||||
assert code == 1, out
|
||||
assert "auxiliary.vision.model must be gpu-vision" in out
|
||||
assert "RESULT: FAIL" in out
|
||||
Reference in New Issue
Block a user