tokenshield 0.4.0

LLMコスト最適化SDKラッパー - 1行追加でキャッシュ・ルーティング・コスト追跡

TokenShield

Cut your LLM API costs by up to 93%. One line of code. Zero quality loss.

TokenShield sits between your code and LLM providers, automatically optimizing every API call through intelligent routing, caching, and PII protection.

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Quick Start

pip install tokenshield

import anthropic
from tokenshield import shield

client = shield(anthropic.Anthropic())

# Use it exactly as before — TokenShield optimizes behind the scenes
response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello, world!"}],
)

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Two Ways to Use

Option A: SDK Wrapper (1 line change)

from tokenshield import shield
client = shield(anthropic.Anthropic())   # Anthropic
client = shield(openai.OpenAI())         # OpenAI

Option B: API Gateway (URL change only)

python -m tokenshield.gateway

client = openai.OpenAI(
    base_url="http://localhost:8800/v1",
    api_key="your-key",
)

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How It Works

Your Code
  |
  v
+---------------------------+
|       TokenShield         |
|                           |
|  1. PII Protection        |  <- Mask personal data before external routing
|  2. Cache Check            |  <- Same query? Return instantly ($0)
|  3. Smart Routing          |  <- Simple task? Route to cheaper model
|  4. Audit Log              |  <- Full compliance trail
|  5. Cost Tracking          |  <- See exactly what you saved
|                           |
+---------------------------+
  |
  v
Claude / GPT / DeepSeek / Gemini

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Features

Smart Multi-Model Routing

Automatically routes requests to the cheapest model that can handle the task:

Task Difficulty	Routed To	Cost
Simple (translation, formatting)	DeepSeek V3 / Gemini Flash	$0.08-0.28/M
Medium (analysis, code)	DeepSeek V3	$0.28/M
Complex (strategy, multi-step reasoning)	Original model	Full price

Routing is based on keyword analysis, message structure, code complexity, and confidence scoring. No LLM call needed for routing decisions.

PII Auto-Removal

Personal data is detected and masked before routing to external models:

• Email addresses
• Phone numbers (Japanese / international)
• Credit card numbers
• API keys and tokens
• Japanese addresses
• IP addresses

Masking is reversible — PII is restored in the response before returning to your code.

Semantic Cache

Goes beyond exact-match caching:

"Translate hello to Chinese"    -> cache hit
"translate hello to Chinese"    -> cache hit (case normalization)
"Translate hello to Chinese please" -> cache hit (polite form normalization)
"Write a Python server"         -> cache miss (different query)

Audit Log & Compliance

Every request is logged with full detail:

• Timestamp, model, routing decision
• PII detection results
• Cost (original vs actual)
• Latency

Generate compliance reports:

from tokenshield.audit import AuditLogger
report = AuditLogger().generate_compliance_report(hours=720)

Dashboard

python -m tokenshield.dashboard          # CLI
python -m tokenshield.dashboard --web    # Streamlit Web UI

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Works With Every Provider

from tokenshield import shield

# Anthropic
client = shield(anthropic.Anthropic())

# OpenAI
client = shield(openai.OpenAI())

# Groq, Mistral, Together, etc.
client = shield(openai.OpenAI(base_url="https://api.groq.com/openai/v1", api_key="..."))

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Configuration

from tokenshield import shield, ShieldConfig

client = shield(anthropic.Anthropic(), config=ShieldConfig(
    # Routing
    enable_routing=True,
    deepseek_api_key="sk-xxx",           # Optional: enables DeepSeek routing
    routing_threshold_easy=0.3,          # Below = easy (route to cheap model)
    routing_threshold_hard=0.7,          # Above = hard (keep original)

    # PII
    enable_pii_removal=True,             # Mask personal data before routing

    # Cache
    enable_cache=True,
    cache_ttl=300,                       # Seconds

    # Tracking
    enable_tracking=True,
))

Without any API keys for alternative models, you still get caching and PII protection.

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Benchmarks

Tested on 10 real business tasks:

Metric	Without Shield	With Shield
Cost	$0.098	$0.054
Quality	8.3/10	8.0/10
Savings	—	45%

DeepSeek V3 quality test (9 tasks):

Metric	Result
Success Rate	9/9
Cost Reduction	93%

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Privacy & Security

• No data leaves your environment
• PII is masked before any external routing
• No telemetry — all data stays in ~/.tokenshield/
• Full audit trail for ISMS/SOC2 compliance
• DeepSeek routing is optional

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Testing

pip install pytest
python -m pytest tests/ -v
# 118 tests, all passing

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Requirements

• Python 3.9+
• anthropic and/or openai SDK

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License

MIT

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Built by TSUNAGU Inc. — Battle-tested on 80 AI agents running 24/7.