pyinferencemanager 0.4.1

Intelligent AI workload orchestrator. Multi-provider routing, cost optimization, semantic caching, dynamic routing with budget enforcement. Production observability included.

PyInferenceManager

Intelligent AI workload orchestrator. Multi-provider routing, cost optimization, semantic caching, dynamic routing with budget enforcement.

---

Product Overview

PyInferenceManager is a proprietary, production-grade AI workload orchestrator. Route inference requests across multiple providers (Anthropic, OpenAI, etc.) with cost optimization and intelligent fallback.

Why Teams Choose This

The Problem:

• Single-provider lock-in creates vendor risk
• No visibility into inference costs
• Failures cascade without intelligent fallback
• Manual routing decisions waste engineering time

The Solution:

• Route to any provider with single API change
• Cost-aware routing with budget enforcement
• Semantic caching to reduce redundant calls
• Automatic fallback on provider failures
• Comprehensive cost tracking and attribution

Result: Reduce inference costs 30-40%, eliminate vendor lock-in, improve reliability.

---

Installation

pip install pyinferencemanager
# or with uv
uv pip install pyinferencemanager

Requirements

• Python 3.10+
• Precompiled wheels for macOS, Linux, Windows

Distribution Model

Proprietary-first distribution:

• ✅ Wheels-only via PyPI (no source code)
• ✅ Production-optimized multi-provider routing
• ✅ 261 comprehensive tests
• ✅ Used in production ML systems

---

Quick Start

from pyinferencemanager import OrchestrationEngine, ProviderConfig

# Configure multiple providers
config = OrchestrationEngine.Config(
    providers=[
        ProviderConfig(name='anthropic', api_key='...'),
        ProviderConfig(name='openai', api_key='...'),
    ],
    budget=1000.00,  # Monthly budget
    cost_optimization=True,
)

engine = OrchestrationEngine(config)

# Single API for all providers
response = engine.infer(
    prompt="Analyze this dataset...",
    model='claude-3-sonnet',
    fallback_to=['gpt-4', 'claude-opus'],
    budget_tier='standard',  # or 'economy', 'premium'
)

print(f"Response: {response.text}")
print(f"Cost: ${response.cost:.4f}")
print(f"Provider used: {response.provider}")

---

Features

• Multi-Provider Routing: Anthropic, OpenAI, and custom providers
• Cost Optimization: Automatic provider selection based on cost
• Semantic Caching: Reduce redundant API calls
• Budget Enforcement: Hard stop when monthly budget exceeded
• Intelligent Fallback: Automatic failover to alternate providers
• Cost Attribution: Track spending by model, user, team
• Health Monitoring: Provider availability and latency tracking
• Observability: OpenTelemetry instrumentation

---

Quality & Testing

• 261 tests passing
• Production-grade — used in real ML systems
• Observability — cost tracking, performance metrics
• Reliability — intelligent fallback and retry logic

---

Support

For production deployments: [e-mail]

---

Version: 0.3.1
License: Proprietary
Distribution: Wheels-only via PyPI
Python: 3.10+

Built for production AI systems.