dspy-predict

name

dspy-predict

description

Build fast direct LM calls with dspy.Predict - the atomic DSPy module for simple input-to-output mapping with no reasoning overhead. Use when the mapping from input to output is straightforward and does not need reasoning steps — simple classification, extraction, formatting, or Q&A where minimal latency matters. Common scenarios - simple classification tasks, basic extraction, format conversion, straightforward Q&A, or any task that does not benefit from chain-of-thought reasoning — when you want the fastest possible LM call. Related - ai-sorting, ai-parsing-data, dspy-chain-of-thought. Also used for dspy.Predict, simplest DSPy module, basic LM call in DSPy, direct prediction no reasoning, when to use Predict vs ChainOfThought, fast classification with DSPy, minimal latency LM call, simple input-output mapping, Predict vs ChainOfThought, zero overhead DSPy call, straightforward text generation, quick extraction without reasoning, one-shot prediction, basic DSPy hello world.

Direct LM Calls with dspy.Predict

Guide the user through using dspy.Predict -- the simplest and fastest DSPy module for calling a language model. It takes inputs, calls the LM, and returns typed outputs. No intermediate reasoning, no extra steps.

Step 1: Gather context

Before writing code, clarify:

1. What is the task? Classification, extraction, formatting, or Q&A?
2. What output type is needed? A plain string, a constrained Literal list, or a structured Pydantic model?
3. Do you need batch processing? Thousands of items at once, or single calls?
4. Is there an existing signature, or does it need to be designed from scratch? (If from scratch, see /dspy-signatures.)

What is dspy.Predict

dspy.Predict is the atomic building block of every DSPy program -- one LM call, no reasoning chain, no tool loops. It takes a signature and calls the LM once to produce the output fields. Every other DSPy module (, , etc.) builds on top of it.