Frank
39385636be
Night fact-check falsified the tree's subject: no `ornith` CLI exists (npm 404), github.com/rhitching/ornith is 404, and the model IDs the tree cites are wrong — the real family is ornith-ai/Ornith-1.0/1.5 (9B, 35B-A3B, 397B), built on Qwen3.5/Gemma4 per its model card, not the 'Ornith-9B-Thinking-1.5T based on Qwen3-8B' the docs assert. Nothing in the tree describes this fleet: no ornith binary on PATH (audit 2026-10-18 said the same). Real facts it echoed (PrismML fork on frank-zealot) already live in /system/. Also: tools/index.md de-duplicated (same files were listed twice, once as wikilinks once as links, live-sync missorted) and links normalized; llama-cpp setup/index xrefs retargeted. Refs #29
148 lines
6.3 KiB
Markdown
148 lines
6.3 KiB
Markdown
---
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type: reference
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title: Pi Models Configuration
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description: Complete reference for models.json — provider definitions, model specs, and API endpoints for the Frank Program.
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tags:
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- pi
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- models
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- providers
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- llamacpp
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- unverified
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timestamp: 2026-08-28
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---
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# Pi Models Configuration (`models.json`)
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`models.json` defines the LLM providers pi connects to. Each provider specifies a base URL, API type, authentication, and available models.
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**Location:** `/home/dank/.pi/agent/models.json`
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---
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## Providers
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Current providers in `models.json` (verified 2026-08-27, after the
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2026-08-18 service swap):
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### llamacpp (dankserver)
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| Property | Value |
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|----------|-------|
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| **Base URL** | `http://192.168.0.235:7770/v1` |
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| **API** | `openai-completions` |
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| **Auth** | None (EMPTY) |
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| **Host** | [[dankserver|dankserver]] |
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#### Models
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| Model ID | Context Window | maxTokens | Reasoning | Input Types |
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|----------|---------------|-----------|-----------|-------------|
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| `frank-default-small` | 262,144 | 262,144 | Yes | Text, image |
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The server is upstream llama.cpp (b10121) serving HauhauCS
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Qwen3.6-35B-A3B-Uncensored-Aggressive Q6_K_P with 36 MoE experts on CPU,
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ngram-mod spec, 4 slots of ~175K context. The server serves the loaded
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model regardless of the requested model ID. Requests with any `model`
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value succeed.
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### llamacpp (dankclaw)
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| Property | Value |
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|----------|-------|
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| **Base URL** | `http://192.168.0.143:7770/v1` |
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| **API** | `openai-completions` |
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| **Auth** | None (EMPTY) |
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| **Host** | [[dankclaw|dankclaw]] |
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> 2026-08-22: `frank-default-large` moved from `:52625` to `:7770` on
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> Dankclaw (operator request: the primary inference server sits on the
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> standard llama.cpp port). The OpenWebUI quadlet
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> (`OPENAI_API_BASE_URL`) was re-pointed to `:7770` in the same change.
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#### Models
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| Model ID | Context Window | maxTokens | Reasoning | Input Types |
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|----------|---------------|-----------|-----------|-------------|
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| `frank-default-large` | 262,144 | 262,144 | Yes | Text, image |
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The server is the ROCmFPX llama.cpp runtime serving
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[kingjones777's Qwen3.8-Flash-Next Uncensored ROCmFP4 STRIX_LEAN GGUF](https://huggingface.co/kingjones777/Qwen3.8-Flash-Next-Uncensored-ROCmFP4-STRIX_LEAN-GGUF)
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— a 177B-parameter, 56B-MoE model sharded into 3 Q4_0-ROCmFP4 GGUF files
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(98.3 GB total) with a standalone BF16 vision embedding project (0.85 GB).
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Speculative decoding uses `--spec-type ngram-mod` because the ROCmFPX quantization
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drops the 4B MTP head. The model is loaded from
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`/home/dank/models/kingjones-Qwen3.8-Flash-Next-Uncensored-ROCmFP4-STRIX_LEAN/`;
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the original Q4_0-ROCmFP4-STRIX variant remains as a `.backup` directory.
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Context is 262144 (native max), 1 slot. Concurrent requests queue on the
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single slot; the server never preempts a running generation. It exposes
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`reasoning_content` in deepseek reasoning format and supports
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multimodal (vision) inference via the embedded mmproj.
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2026-08-27: Upgraded from the original Qwen3.8-Flash-Next Q4_0-ROCmFP4-STRIX
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GGUF to the Uncensored STRIX_LEAN variant with vision support and
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ngram-mod speculative decoding.
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### Thinking Levels
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Pi's default thinking level is configured globally in `settings.json` as
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`"defaultThinkingLevel": "medium"`. The model entries map Pi's `max` level to the llama.cpp-supported `xhigh`
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wire value. Pi shows `max` in the thinking selector from the global settings,
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but sends `reasoning_effort: "xhigh"` to both local llama.cpp endpoints.
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`thinkingLevelMap` can translate a UI level without changing the global default.
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Verified 2026-07-22:
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`getSupportedThinkingLevels` returns `off,minimal,low,medium,high,xhigh`
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and the live server accepts `reasoning_effort: "xhigh"` and returns
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`reasoning_content` (verified 2026-08-21).
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Mechanism (pi-ai `models.js` + `openai-completions.js`):
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- `getSupportedThinkingLevels`: extended levels `xhigh`/`max` appear only
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when `thinkingLevelMap` defines them (string = supported, `null` =
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hidden, omitted = not supported).
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- Default request path (no `compat.thinkingFormat`): sends
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`reasoning_effort = thinkingLevelMap[level] ?? level` when
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`supportsReasoningEffort` is true (default for this provider).
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## Token Budgets (`maxTokens`)
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Verified in the pi source, 2026-08-16 (`@earendil-works/pi-coding-agent` 0.84.1 + `pi-ai`):
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- `maxTokens` is an optional model field in `models.json`. When omitted, pi defaults the model object to 16,384 (`provider-composer.js`).
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- The value is metadata. It drives the model-picker "max out" display and length-error recovery (`isRecoverableLength`).
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- Normal chat turns do not send `max_tokens`. The request builder sends the field only when a per-request option is set (`openai-completions.js buildParams`: `if (options?.maxTokens)`). The agent loop passes no such option.
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- The only pi calls that send `max_tokens` are context compaction and branch summarization. They are deliberately budgeted.
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## Model Selection Strategy
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```mermaid
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graph LR
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A[User Request] --> B{Complexity?}
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B -->|Large context / long docs| C[frank-default-large<br/>CIRU llama.cpp dankclaw :7770, 262K ctx]
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B -->|Fast / interactive| D[frank-default-small<br/>llama.cpp dankserver :7770, 262K ctx]
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The CIRU endpoint (dankclaw) serves the 177B 56B-MoE model with
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262144 context, ngram-mod speculative decoding, 1 slot. Concurrent
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requests queue on the single slot. The upstream
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llama.cpp endpoint (dankserver) serves the 35B A3B MoE model with 36
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experts on CPU and 262K context per slot.
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## Live Defaults
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`settings.json` picks the main session provider and model (verified 2026-08-19):
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| Scope | Provider | Model |
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|-------|----------|-------|
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| Main session | `llamacpp (dankclaw)` | `frank-default-large` |
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| Subagent default | `frank-default-small` (llamacpp dankserver) | ~262K ctx per slot, ngram-mod spec |
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| Subagent overrides | scout, researcher | `frank-default-small` |
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| Subagent overrides | planner, worker, reviewer, oracle, context-builder | `frank-default-large` (llamacpp dankclaw) |
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The subagent model IDs (`frank-default-small`, `frank-default-large`) resolve against the new provider set in `models.json`. The current mappings are `max -> xhigh` for both local models; the global and subagent defaults remain `max`.
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---
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## See Also
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- [[settings|settings]] — Main configuration file
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- [[dankserver|dankserver]] — Primary llama.cpp server
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- [[dankclaw|dankclaw]] — Secondary llama.cpp server
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