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cortecs.aiDedicated ModelsServerless ModelsLogin
  • Introduction
  • DEDICATED INFERENCE
    • Quickstart
    • Provisioning API
      • Authentication
      • User
      • Instances
      • Models
      • Hardware Types
    • Python client
      • Objects
      • Langchain integration
    • Examples
      • Batch jobs
      • Realtime streams
  • SERVERLESS INFERENCE
    • Quickstart
    • About Serverless Routing
    • API
      • Chat Completions
      • Models
  • Discord
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  1. DEDICATED INFERENCE

Examples

Dedicated provisioning is used for high-throughput or latency-sensitive applications. Whether you're processing large volumes of documents or streaming real-time events, having compute resources reserved just for your workload ensures performance and control.

This section provides hands-on examples for common use cases:

🔁 Batch Jobs

Run inference over thousands of documents in parallel with no rate limits. With LangChain’s batch() support, you can efficiently summarize, classify, or extract data at scale.

⚡ Real-Time Streaming

Process live data streams (like Reddit comments or tweets) with consistent, low-latency inference. Ideal for chatbots, moderation tools, and classification pipelines.

PreviousLangchain integrationNextBatch jobs

Last updated 11 days ago