Rose 1 production benchmarks are liveView API docs

Resources

Everything around the compression hop.

Docs, billing notes, implementation patterns, and dashboard links for putting Adola in front of production LLM traffic.

Open API docs

Reduce LLM costs

Cut input tokens before expensive model calls without changing providers.

Prompt compressor

Run a no-signup compression tool for RAG, support, or agent context.

Context compression API

Compress retrieved context, tickets, and agent traces before any LLM call.

LLMLingua alternative

Use Rose 1 as a hosted prompt-compression API with production receipts.

OpenAI compression

Reduce long context before Responses or chat model calls.

Claude compression

Compress RAG and agent context before Anthropic model calls.

DeepSeek compression

Compress long prompts before DeepSeek chat and agent calls.

RAG compression pattern

Where to put prompt compression in a retrieval or agent pipeline.

RAG token reduction

Reduce retrieved-context tokens after reranking and before the final model call.

RAG quickstart

Copy-paste the compression hop into a server-side RAG call.

Terminal quickstart

Run the no-key demo from curl, then switch the same body to production.

LangChain compression

Insert Rose 1 between LangChain context assembly and the final model call.

ContextualCompressionRetriever alternative

Compress the final LangChain prompt after retrieval, reranking, and assembly.

LlamaIndex compression

Compress retrieved nodes before LlamaIndex response synthesis.

Rose 1 outcomes

How teams use Rose 1 to reduce long context before expensive model calls.

Agent trace compression

Compress tool traces, prior turns, and retrieved context before the next agent step.

AI agent API costs

Reduce repeated context, logs, and tool output before expensive agent calls.

Claude Code token costs

Reduce stale tool output, logs, and prior context in long coding-agent runs.

Codex usage limits

Reduce repeated tool output and stale context in long Codex-style runs.

Support copilot compression

Shrink long tickets, policies, account notes, and prior replies before support answers.

API reference

Request shape, auth headers, response receipts, batch jobs, and error codes.

OpenAPI spec

Machine-readable schema for the no-key demo and production compression endpoints.

Pricing guide

Saved-token billing, example workloads, and the free playground path.

Project keys

Create scoped bearer keys, rotate credentials, and isolate production traffic.

Receipt format

Understand token counts, compression ratio, latency, risk flags, and audit metadata.

Deployment notes

Docker services, migrations, readiness checks, Azure Container Apps, and Postgres.

Fastest path to production

The same sequence works for agents, RAG retrieval, support copilots, and model gateways.

Create workspace

Issue key

Generate a bearer key for the service that owns the model request.

Compress context

Send the query plus retrieved context to Adola before your model call.

Audit receipt

Track saved tokens, output ratio, latency, and risk flags by request.