breviadev 0.1.0

Local proxy that optimizes LLM context by 55-97%. Same quality, fraction of the cost.

Brevia

Save 55-93% on LLM tokens. Same quality, fraction of the cost.

Brevia is a local proxy that sits between your tools and the Anthropic API. It algorithmically optimizes context before it reaches Claude — cutting tokens by 55-97% on large contexts while maintaining full recall and producing more precise answers.

Works with Claude Code, Cursor, Continue, aider, and any tool that uses the Anthropic SDK.

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Quick Start

pip install brevia
brevia login          # Opens browser — sign in with GitHub or Google
brevia serve          # Starts proxy on localhost:8420

Then add to your shell profile (~/.zshrc, ~/.bashrc):

export ANTHROPIC_BASE_URL=http://localhost:8420

That's it. Everything works exactly as before — but cheaper and often smarter.

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How It Works

Your Tool (Claude Code, Cursor, etc.)
    │
    │  ANTHROPIC_BASE_URL=http://localhost:8420
    ▼
┌─────────────────────────────────┐
│         Brevia Proxy            │  ← Runs locally
│                                 │     Zero LLM cost
│  1. Analyze context structure   │     ~5ms latency
│  2. Score relevance by query    │
│  3. Extract key sections        │
│  4. Inject liberation prompt    │
└─────────────────────────────────┘
    │
    │  Optimized payload (55-97% smaller)
    ▼
┌─────────────────────────────────┐
│      api.anthropic.com          │  ← Your API key
│                                 │     Your account
│  Claude processes focused       │     You pay less
│  context = better answers       │
└─────────────────────────────────┘
    │
    │  Response streams back
    ▼
Your Tool (unchanged behavior)

Key insight: Less noise = better answers. When Claude sees 2.4k tokens of the RIGHT code instead of 95k tokens of everything, it produces more precise diagnoses.

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Benchmarks

Tested against Claude Opus 4.6/4.7 on real codebases (Django, FastAPI, psf/requests):

Context Size	Cost Savings	Quality Impact
< 2k tokens	0% (passthrough)	None
10k tokens	~55%	None
50k tokens	76-93%	None
95k tokens	76%	Improved (more precise)

Real Code Analysis (4-Path Comparison)

Path	Total Cost	vs Direct
Direct Opus (full context)	$0.836	baseline
Brevia + Opus	$0.278	67% cheaper

Structured Data (50k token billing report)

Metric	Value
Token reduction	97.4%
Cost savings	93.3%
Recall	1.0/1.0 (perfect)

Full benchmark methodology and raw data: benchmarks/BENCHMARKS.md

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Commands

Command	Description
brevia login	Authenticate (opens browser)
brevia serve	Start the proxy
brevia serve -p 9000	Start on custom port
brevia stats	Show your savings stats
brevia stats -d 30	Show last 30 days
brevia logout	Remove credentials

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What You'll See

When brevia serve is running:

╭─ 🏛️  Brevia ──────────────────────────────────╮
│ Brevia is running                              │
│                                                │
│   Proxy:    http://127.0.0.1:8420              │
│   User:     @yourname                          │
│   Status:   Optimizing all Anthropic API calls │
│                                                │
│   Set this in your shell:                      │
│   export ANTHROPIC_BASE_URL=http://127.0.0.1:8420 │
╰────────────────────────────────────────────────╯

Run brevia stats anytime:

╭─ 📊 Brevia Stats ─────────────────────────────╮
│ All-time savings                               │
│                                                │
│   Days active:    12                           │
│   Total requests: 847                          │
│   Tokens saved:   4,230,000                    │
│   Avg reduction:  71%                          │
│   Est. $ saved:   $63.45                       │
╰────────────────────────────────────────────────╯

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Where Brevia Helps Most

• Large contexts (50k+ tokens): 76-97% savings with equal or better quality
• Noisy contexts: Relevant info buried in boilerplate — Brevia extracts what matters
• Multi-file contexts: Only sends relevant files to Claude

Where Brevia Does NOT Help

• Tiny contexts (< 2k tokens): Passed through unchanged (no overhead)
• Already-focused queries: If you're already sending only relevant code, nothing to cut
• Full-file reasoning tasks: Some tasks need the entire file flow

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Privacy & Security

• Your API key is passed through — Brevia never stores it
• Optimization happens locally — your code never leaves your machine
• Telemetry is aggregated stats only: token counts, savings, request count
• No content is ever sent to Brevia servers
• Credentials stored in ~/.brevia/ with restricted permissions

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Platform Support

• macOS (Intel + Apple Silicon)
• Linux (x86_64 + ARM64)
• Windows 10+

Requires Python 3.10+.

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Enterprise

Need team-wide deployment, custom optimization rules, or priority support?

Contact us: [e-mail]

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How It's Different

	Brevia	Prompt caching	Summarization
Approach	Algorithmic extraction	Cache repeated prefixes	LLM summarizes context
Cost	Zero (local CPU)	Reduced on cache hit	Adds an LLM call
Latency	~5ms	None on hit	+1-3s per call
Quality	Equal or better	Same	Often degrades
Works with	Any Anthropic tool	SDK only	Custom code only

Brevia stacks with prompt caching — use both for maximum savings.

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License

MIT

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Built by engineers who got tired of paying for noise.