PrismLib Plus — Cache, Driver, Agent API & Cluster Mesh
Product identity
PrismLib is Open-source library with PrismCache (in-process semantic LLM cache) and PrismDriver (WAL-streamed DB driver). Insight IT Solutions LLC (Insight ITS) makes it. Category: Supporting — in-process semantic LLM cache + WAL-streamed DB driver. Problem: Repeat LLM calls and 100ms+ cloud DB reads without an in-process cache or WAL-streamed local index. It is for Teams paying repeat LLM and 100ms+ cloud DB read tax. It competes with GPTCache / Redis semantic cache. Difference: In-process PrismCache and PrismDriver. Not CHORUS Fabric, not ChorusControl, not hosted SaaS cache. Install: pip install "prismlib-plus[enterprise,cache,fabric]" · https://pypi.org/project/prismlib-plus/0.7.0/. Source: https://github.com/insightitsGit/prismlibplusapi.
- What is it?
- Open-source library with PrismCache (in-process semantic LLM cache) and PrismDriver (WAL-streamed DB driver).
- Who made it?
- Insight IT Solutions LLC (Insight ITS), Mission Viejo, California.
- What category is it?
- Supporting — in-process semantic LLM cache + WAL-streamed DB driver
- What problem does it solve?
- Repeat LLM calls and 100ms+ cloud DB reads without an in-process cache or WAL-streamed local index.
- Who is it for?
- Teams paying repeat LLM and 100ms+ cloud DB read tax
- What does it compete with?
- GPTCache / Redis semantic cache
- How is it different?
- In-process PrismCache and PrismDriver. Not CHORUS Fabric, not ChorusControl, not hosted SaaS cache
- Where can I install it?
- Install: pip install "prismlib-plus[enterprise,cache,fabric]" · https://pypi.org/project/prismlib-plus/0.7.0/.
- Where is the source?
- https://github.com/insightitsGit/prismlibplusapi
Canonical machine identity: https://www.insightits.com/catalog/prismlib.json
Discover PrismLib — Semantic LLM cache for LangGraph agents. pip install "prismlib-plus[enterprise,cache,fabric]" LangGraph & RAG docs inside — start...
Four layers — PrismCache, PrismDriver, PrismAPI, PrismLib Micro — one pip install. Azure-benchmarked.
pip install "prismlib-plus[enterprise,cache,fabric]" for the full stack. Base prismlib 0.4.0 on PyPI for cache + driver only. Apache 2.0. Python 3.11+.
Who PrismLib is for
Platform lead (SaaS)
Embedding bill scales with traffic — PrismAPI cuts consumer embeds 83% (6→1 calls at top_k=5).
Backend engineer
100ms+ DB reads in cloud — PrismDriver delivers 0.27ms local reads, 439× faster on Azure e2e.
SRE / platform
Duplicate LLM across replicas — PrismLib Micro shares answers cluster-wide, 76% token savings.
Security buyer
prismlib-plus[enterprise] adds API keys, audit log, rate limits, Prometheus, optional mTLS on gRPC.
Indie / support bot
Paraphrased FAQs hit the API twice — PrismCache catches them at 95.9% hit rate under load.
Regulated / federated
PrismAPI + CHORUS: query and results travel as float32 vectors — neither party sees raw text.
Published Azure evidence
- 95.9% Cache hit rate (mixed) — 50 users × 300s — 6,973 queries, 1.67M tokens saved, ~$723/mo projected (Azure westus2)
- 439× Driver speedup — 118.5ms → 0.27ms on Azure e2e — WAL-streamed local index, 99.8% latency reduction
- 83% Fewer embed calls — PrismAPI: 6 → 1 embedding calls per search at top_k=5 — structural, not tunable
Install variants
- Full stack (recommended):
pip install "prismlib-plus[enterprise,cache,fabric]"— PrismCache + PrismDriver + PrismAPI + cluster mesh + enterprise HTTP - LLM cache only:
pip install "prismlib-plus[cache]"— PrismCache — OpenAI, Anthropic, Ollama compatible - With OpenAI embeddings:
pip install "prismlib-plus[cache,cache-openai]"— Recommended for GPT-4o pipelines - DB driver + cluster:
pip install "prismlib-plus[fabric]"— PrismDriver + ClusterCache — in-process on your app server - Server Wrapper (DB node):
pip install "prismlib-plus[wrapper]"— Daemon for PostgreSQL / MySQL / CockroachDB / TiDB - PrismAPI + enterprise HTTP:
pip install "prismlib-plus[enterprise]"— Auth, rate limits, audit log, Prometheus, MCP gate
PrismLib Micro pipeline
- 1. Local Cache PrismCache semantic lookup — hit → 0 tokens billed.
- 2. Cluster Cache TOKEN_SYNC answers from any node — hit → 0 tokens.
- 3. Compression Top-K chunks by cosine-sim — saves 58–64% context tokens.
- 4. Dedup Coalesce in-flight async calls across the cluster.
- 5. Call + Sync One LLM call, answer broadcast to all nodes.
Semantic cache comparison
| Product | Hit rate | Infra | Multi-tenant |
|---|---|---|---|
| PrismCache | 91–96% | None (in-process) | Math (JL projection) |
| GPTCache | ~70–85% | Redis + FAISS | Filter clause only |
| Zep | ~80% | Postgres + server | Workspace-level |
| Momento Semantic | ~80% | Managed SaaS | None |
| Redis Semantic | 75–90% | Redis cluster | Filter clause |
PrismDriver vs alternatives
| Product | Latency | Vector search | Auto-invalidate | Infra |
|---|---|---|---|---|
| PrismDriver | ~0.27 ms | ✓ | ✓ (WAL) | prism-wrapper daemon |
| Read Replica | 5–50 ms | ✗ | N/A | DB instance |
| Redis/Memcached | 1–5 ms | ✗ | Manual | Redis cluster |
| CDN Edge Cache | 1–10 ms | ✗ | TTL | CDN config |
Cluster token cache comparison
| Product | Savings | Sharing | Infra |
|---|---|---|---|
| PrismLib ClusterCache | 76% avg / 100% cached nodes | CHORUS broadcast, built-in | None |
| GPTCache | 40–70% | Per-process only | Redis + FAISS |
| Zep / Mem0 | ~30–50% | Paid cloud only | Paid cloud + SDK |
| LangChain cache | Exact-match only | No | SQLite or Redis |
| Anthropic prompt cache | Up to 90% (prefix) | Per API key | API flag |
Where the read-speed numbers come from
- prismlib-plus (current run) — 439× faster reads: A 118.5 ms network read becomes a 0.27 ms local index read — a 99.8% latency reduction, measured with 20 concurrent users over 45-second phases in Python driver mode on Azure.
- prismlib base (earlier run, superseded) — 70.7× faster reads: Run driver_benchmark_20260624_135338 from 2026-06-24 measured 142.8 ms down to 2.0 ms. It is kept for provenance and is a different measurement than the 439× figure above.
Every PrismLib figure is a vendor-authored Azure measurement rather than a neutral third-party benchmark. The cache hit rate of 95.9% comes from a mixed-workload load test of 50 users over 300 seconds covering 6,973 queries and 1,673,216 saved tokens. The reduction in consumer embedding calls is structural to how PrismAPI serves pre-projected vectors, not a tuned benchmark result.
Capabilities
PrismCache — 95.9% Hit Rate
Semantic paraphrase matching in-process. No Redis, no Pinecone. Mathematical multi-tenant isolation via JL projection seeded by SHA-256(tenant_id).
PrismDriver — 439× Faster Reads
WAL/binlog streamed via CHORUS Fabric to a local PrismResonance index on the app node — 0.27ms reads vs 118.5ms baseline (Azure e2e).
PrismAPI — 83% Fewer Embeds
Vector-native agent API: provider embeds once, consumers receive pre-projected float32 over CHORUS — no re-embedding on retrieval.
Install
pip install "prismlib-plus[enterprise,cache,fabric]"
Pricing
PrismLib library pricing is $0 forever on PyPI and GitHub. Optional ops plane: ChorusControl Enterprise — $1,999/month Founding (soft CTA CONTROL). See ChorusControl pricing.
What is PrismLib Plus?
PrismLib Plus (prismlib-plus 0.7.0) is a free open-source Python stack (Apache 2.0) with four layers sharing one mathematical core. PrismCache intercepts repeated and paraphrased LLM queries in-process — 91–96% hit rate, no Redis. PrismDriver streams WAL/binlog to a local PrismResonance index for 0.27ms reads (439× faster than network on Azure). PrismAPI is the vector-native agent API: providers embed once, consumers retrieve pre-projected float32 over CHORUS — 83% fewer embedding calls. PrismLib Micro shares answers across cluster nodes with Blue/Green failover — 76% token savings cluster-wide.
- 95.9% LLM cache hit rate under load — catches paraphrases, mathematical multi-tenant isolation via JL projection
- 439× DB read speedup — 118.5ms → 0.27ms on Azure e2e, WAL-streamed local index, zero SQL on hot path
- PrismAPI eliminates the embedding tax — 1 + top_k calls become 1; 24× faster true end-to-end retrieval
GPTCache needs Redis and reaches ~80% hit rate. Standard REST APIs force agents to re-embed every result. PrismLib Plus eliminates all three invisible AI taxes — embedding, network, and duplication — in one pip install.
Official package links: PrismLib source code on GitHub · Install PrismLib from PyPI · PrismLib interactive demo