Management API: Deploy, pause, resume, scale, and monitor dedicated endpoints programmatically with the Parasail REST API.
FP8 Quantization: Quantize dedicated models to FP8 with llm-compressor to halve memory use and speed up inference with minimal accuracy loss.
Auto-Scaling: Configure auto-scaling for dedicated endpoints using max concurrent requests, target concurrency, and smoothing factor.
Dedicated Serverless: Understand the concurrency limits and max requests per minute that govern autoscaling capacity on Dedicated Serverless endpoints.
Batch: Get started with Parasail's Batch Processing through the UI or the OpenAI-compatible Python batch helper library.
Batch File Format: Format batch input and output .jsonl files for Parasail's OpenAI-compatible Batch API.
Troubleshooting: Diagnose and fix common batch job failures, from JSONL validation errors to quota and authentication issues.
Image Generation: Run diffusion models for batch image generation and editing with Parasail.
Authentication: API key creation, base URLs, and authentication for the Parasail API.
Chat Completions: OpenAI-compatible chat completions API for serverless and dedicated model inference.
Responses API: Responses API reference for multi-turn agentic workflows with tool calling on the new gateway.
Embeddings: Embeddings API for generating vector representations of text using open-source models.
Batch API: OpenAI-compatible Batch API reference for Parasail batch processing.
Billing API: Programmatically retrieve invoices, real-time month-to-date spend, and hourly or daily usage breakdowns with the Parasail Billing API.
Models Endpoint: List available models on the Parasail platform using the /v1/models endpoint.
Parameters: Sampling parameters for the Parasail chat completions and text completions APIs.
Chat Completions: Send chat messages to instruct-tuned models with Parasail's OpenAI-compatible Chat Completions API.
RAG: Build Retrieval-Augmented Generation systems that combine embeddings, vector retrieval, and LLM generation on Parasail.
Multi-Modal: Send images to vision-language models like Qwen2.5-VL using base64 data URLs through Parasail's OpenAI-compatible API.
Structured Output: Get reliable, schema-conformant JSON from Parasail models using guided_json and response_format.
Tool/Function Calling: Let Parasail models call your functions and tools via the Chat Completions and Responses APIs.
Model Selection: Choose Parasail models by capability, deployment tier, latency, cost, and validation workflow instead of relying on stale static rankings.
Pricing: Understand Parasail pricing across the Serverless per-token, Dedicated per-GPU-hour, and Batch discounted per-token tiers.
Overview: Run Parasail in production with rate-limit handling, quota planning, dedicated scaling, batch operations, and safe retries.
Retries and Idempotency: Handle 429 responses and transient errors with exponential backoff, sensible timeouts, and safe retries against the Parasail API.
Limits and Quotas: Rate limits, GPU quotas, and quota increase guidance for Parasail production workloads.
Security Overview: A security and account-management entry point for Parasail data handling, privacy, compliance, and API-key controls.
Account and API Keys: Manage Parasail organizations, account access, and read-only API keys.
Chat and Text Generation: Build chatbots, assistants, and text generation pipelines with Parasail's OpenAI-compatible API.
RAG and Embeddings: Build retrieval-augmented generation (RAG) pipelines and vector search systems with Parasail embeddings.
Batch Processing at Scale: Process large volumes of LLM inferences, embeddings, and multimodal inputs at scale with Parasail Batch.
Agents and Tool Calling: Build agentic workflows with function calling, multi-step reasoning, and tool use on Parasail.