SemBlend vLLM Connector

vLLM KVConnector for SemBlend-backed semantic KV donor discovery.

This repo is the open-source adapter layer between vLLM and SemBlend.

SemBlend is a semantic KV reuse research library. It exists to evaluate when similar prompts may safely reuse or blend previously computed KV state. This connector exposes that work through vLLM's KVConnectorBase_V1 lifecycle.

Status

Experimental, with safe defaults. Verified paraphrase reuse in semantic_span_experimental mode has been validated end to end on stock vLLM 0.26 (Qwen2.5-7B, A10G) and through an llm-d gateway with semantic-affinity placement; start with docs/QUICKSTART_VLLM.md.

Default behavior is discovery-only:

• exact vLLM prefix caching remains authoritative;
• semantic lookup runs only after exact prefix coverage is insufficient;
• the connector records donor hits, misses, and rejection reasons;
• it returns (0, False) from get_num_new_matched_tokens() unless a configured materialization mode can prove a block-aligned exact token prefix or an explicitly opted-in isolated proof path;
• normal vLLM execution continues on every provider error or unsupported case.

Install

From PyPI:

pip install "semblend-vllm-connector[semblend]"

Development:

pip install -e ".[semblend,dev]"

Run local checks:

make check

vLLM Configuration

Discovery-only mode:

vllm serve meta-llama/Llama-3.1-8B-Instruct \
  --enable-prefix-caching \
  --kv-transfer-config '{
    "kv_connector": "SemBlendVllmConnector",
    "kv_connector_module_path": "semblend_vllm_connector.connector",
    "kv_role": "kv_both",
    "kv_load_failure_policy": "recompute",
    "kv_connector_extra_config": {
      "mode": "discovery_only",
      "provider": "local",
      "min_prompt_tokens": 256,
      "min_similarity": 0.70
    }
  }'

SemBlend provider mode:

{
  "kv_connector": "SemBlendVllmConnector",
  "kv_connector_module_path": "semblend_vllm_connector.connector",
  "kv_role": "kv_both",
  "kv_load_failure_policy": "recompute",
  "kv_connector_extra_config": {
    "mode": "discovery_only",
    "provider": "semblend",
    "min_prompt_tokens": 256,
    "min_similarity": 0.70,
    "min_reuse_ratio": 0.50,
    "embedder_type": "minilm",
    "model_id": "meta-llama/Llama-3.1-8B-Instruct"
  }
}

Equivalent JSON examples live in examples/.

Optional audit stream for reproducible validation:

{
  "kv_connector_extra_config": {
    "audit_path": "/tmp/semblend-vllm-audit.jsonl",
    "log_decisions": true
  }
}

The audit file is JSONL. Runtime KV reuse should be counted only from runtime_materialized events. Semantic lookup hits and advertised loads are reported separately so benchmark runners can distinguish discovery from backend-confirmed materialization.

Modes

In semantic_span_experimental the connector never advertises more than the donor KV it actually captured: spans trim to the stored donor window, a load that materializes zero layers fails loudly rather than decoding over uninitialized blocks, and every load leaves separate advertised and runtime_materialized audit records so reuse is only ever counted from the latter.

request_only_experimental defaults to exact-token-prefix materialization. The old zero-exact semantic proof behavior requires allow_non_identical_request_only=true or SEMBLEND_VLLM_ALLOW_NON_IDENTICAL_REQUEST_ONLY=1. Keep that flag limited to quality-gated validation experiments; it is not a production-safe substitute for a segmented/recompute engine path.

Safety Rules

The connector must not:

• weaken exact prefix-cache semantics;
• report semantic hits as computed tokens unless KV can actually be loaded;
• publish non-identical semantic donor KV into vLLM's exact prefix cache;
• treat non-identical semantic discovery as materializable unless an explicit validation flag is set and the run has separate quality gates;
• cross model, tokenizer, adapter, or cache-salt namespaces;
• fail inference because semantic lookup failed.

Repository Layout

src/semblend_vllm_connector/
  connector.py        vLLM KVConnectorBase_V1 implementation
  config.py           config/env parsing
  provider.py         provider protocol + local deterministic provider
  providers/
    semblend.py       lazy SemBlendPipeline adapter
  types.py            shared dataclasses/enums
  namespace.py        vLLM request namespace extraction

docs/
  ARCHITECTURE.md     detailed architecture and rollout plan
  SEMBLEND_PROVIDER.md
  VLLM_CONNECTOR_CONTRACT.md

examples/
  discovery_kv_transfer_config.json
  semblend_discovery_kv_transfer_config.json

Open Source Posture

This project follows the dynamic connector pattern used by mature vLLM KV cache projects: vLLM loads the connector from a Python module path, connector-specific settings live in kv_connector_extra_config, and unsafe materialization cases fail closed to normal vLLM prefill.

See:

• SEMBLEND_PROVIDER.md
• VLLM_CONNECTOR_CONTRACT.md
• CONTRIBUTING.md
• SECURITY.md