LLM Chat
Run text through a language model for writing, reasoning, extraction, or transformation.
Overview#
LLM Chat is the main text-generation block. It accepts upstream data plus instructions, runs a selected model, and returns a response for the next step.
Use it for rewriting, summarising, classifying, analysing, or any job that needs language understanding. Default model is Claude Sonnet 4.6 for strong creator quality.
Workflow Preview
LLM Chat
Read-only builder graph
Ports#
- Input , Input: The data to work on , connected upstream text or JSON-like content.
- Output , Response: The model's generated text for downstream blocks.
Inspector#
- Prompt: Instructions used when Input is not connected, or as guidance alongside connected data.
- Style / System (optional): Tone, role, and constraints for the model.
- Model: Choose among GPT, Claude, or Gemini options , trade off quality, cost, and speed. Match the provider key in the run modal.
- Temperature: Lower for precise extraction; higher for creative variation.
- Max Tokens: Cap on response length , align with what the product should return.
- Stream and Safe Mode: Inline toggles for live streaming and safer defaults.
Tips#
- Give each LLM block one clear job instead of stacking many tasks in one prompt.
- Feed raw data through Input; keep transformation instructions in the prompt.
- Use a stronger model for nuanced writing; lighter models for fast utility work.
- Set max tokens close to the expected answer length to avoid waste.