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.scratch/distributed-gguf-runtime/PRD.md

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+# PRD: Distributed GGUF Runtime
+
+## Summary
+
+Build a distributed inference runtime that can serve large, quality-first open models by combining torrent-style model artifact distribution with sticky multi-node Inference Routes and per-shard local Hot KV State.
+
+The first runtime proof uses the existing PyTorch route because it exposes model internals and cache semantics more directly. GGUF/llama.cpp becomes the performance path after the route-session contract is proven.
+
+## Goals
+
+- Eliminate full-prompt recompute in distributed decode.
+- Keep decode activation seams proportional to `hidden_size`, not `context_length * hidden_size`.
+- Keep Hot KV State local to the node serving the relevant Shard.
+- Stream token deltas when feasible and always expose Generation Telemetry.
+- Add a local full-model GGUF backend for immediate CPU performance wins.
+- Define Model Artifact manifests so nodes can verify, seed, and advertise artifacts without depending on Hugging Face at request time.
+- Prototype an upstreamable llama.cpp/libllama layer-boundary API.
+- Use DeepSeek-V4-Flash as the first serious large-model target after smaller protocol smoke tests.
+
+## Non-Goals
+
+- No centralized hot KV cache in the per-token decode path.
+- No automatic route repair in alpha.
+- No permanent llama.cpp fork as the intended architecture.
+- No GLM-5.2 or Ornith first; they remain follow-up support audits.
+- No transport rewrite to QUIC/WebRTC before route/session semantics are proven.
+
+## Resolved Decisions
+
+- Public-network Shards are contiguous transformer layer ranges.
+- Tensor/ring parallelism belongs inside one trusted node, one colocated pod, or a future composite node abstraction.
+- Hot KV State is local to route nodes; Prefix Snapshots are optional cold recovery/reuse artifacts.
+- PyTorch distributed KV/session semantics are proven before llama.cpp distributed execution.
+- Streaming responses are preferred; Generation Telemetry is mandatory.
+- llama.cpp/GGUF work targets upstreamable `libllama`/ggml hooks.
+- Alpha fails Route Sessions on route-node loss.
+- v1 activation transfer stays on binary HTTP.
+
+## Target User Experience
+
+A client sends an OpenAI-compatible request. The Gateway or Tracker Node accepts the request, creates a Route Session, and streams token deltas when supported. The client receives live Generation Telemetry for route phase, prefill progress, generated token count, rolling tokens/sec, route health, and failure reason.
+
+If a route node drops in alpha, the request fails clearly. A retry starts a new Route Session from scratch.
+
+## Runtime Shape
+
+```text
+client request
+  -> Gateway / Tracker Node creates Route Session
+  -> Tracker selects sticky Inference Route
+  -> prefill:
+       prompt chunks move through Shards
+       each node appends local Hot KV State
+  -> decode:
+       one-step activation moves through Shards
+       each node reads/appends local Hot KV State
+       tail returns token/logits
+  -> client receives streamed token deltas where possible
+  -> Generation Telemetry continues until complete or failed
+```
+
+## Milestones
+
+| Milestone | Outcome | Issues |
+|---|---|---|
+| M1 — Session protocol proof | Stub route has stable Route Sessions, prefill/decode split, telemetry, and streaming contract | 01, 02, 03 |
+| M2 — PyTorch reference route | Distributed PyTorch decode uses local per-shard cache and stops full-prompt recompute | 04 |
+| M3 — Local GGUF performance path | Single-node GGUF backend serves through the node API and reports backend metadata | 05 |
+| M4 — Artifact plane | Model Artifact manifest supports verification, layer mapping, and node advertisement | 06 |
+| M5 — llama.cpp collaboration proof | Localhost layer-boundary prototype identifies upstreamable llama.cpp/libllama API | 07 |
+| M6 — Networked GGUF route | Multi-node GGUF route uses the resolved protocol and fails cleanly on node loss | 08 |
+| M7 — First large model | DeepSeek-V4-Flash support path is audited and converted into follow-up runtime tasks | 09 |
+
+## Acceptance Criteria
+
+- A two-node route can prefill once and decode without resending full prompt activations.
+- Decode seam payload is one token/hidden-state step after prefill.
+- Route Session telemetry is visible before first token and during decode.
+- Streaming token deltas work where the backend supports them.
+- Route-node loss produces a structured alpha failure and does not attempt unsafe repair.
+- A local GGUF model can serve via the node API.
+- A Model Artifact manifest can prove which Shards a node can serve.
+- DeepSeek-V4-Flash has a written support recommendation: PyTorch, vLLM/SGLang, llama.cpp/GGUF, or blocked.