Documentation

Local Model Integration

Deploy Sypha with local AI infrastructure using Ollama or LM Studio for absolute privacy and offline development.

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Sypha supports the integration of local AI infrastructure, allowing you to run reasoning models directly on your hardware via Ollama or LM Studio.

Strategic Incentives for Local Deployment

  • Absolute Privacy: Your source code and technical data never exit your physical infrastructure.
  • Offline Sovereignty: Maintain full development capabilities without a consistent internet connection.
  • Total Expenditure Control: Eliminate reliance on cloud-resident API usage fees.
  • Architectural Flexibility: Experiment with diverse open-source models tailored for specialized tasks.

Technical Considerations

  • Hardware Prerequisites: Requires high-performance CPU/GPU architectures and substantial memory (RAM) allocation.
  • Infrastructure Setup: The initial configuration is more technical compared to standardized cloud-based APIs.
  • Reasoning Depth: Local models may not yet match the ultra-high reasoning capabilities of massive cloud-resident frontier models (e.g., Claude 3.x).
  • Propietary Limitations: Advanced features such as server-side prompt caching may not be natively supported.

Supported Local Ecosystems

  1. Ollama: A high-speed, open-source CLI engine for local model orchestration.
  2. LM Studio: A refined desktop application featuring a local server that emulates the industry-standard OpenAI API schema.

Deployment Guides

Troubleshooting & Connectivity

  • Communication Failures: Ensure the Ollama or LM Studio background server is active and that the Base URL matches your local handshake settings.
  • Latency Optimization: If the reasoning speed is insufficient, consider deploying a more agile model parameter-size (e.g., Llama 3B instead of 70B).
  • Model Resolution: Confirm the model identifier exactly matches your local inventory (audit via ollama list).