Examples Dspy

Overview - DSPy

Overview - DSPy Working in dspy involves training sets, development sets, and test sets. this is like traditional ml, but you usually need far fewer labels (or zero labels) to use dspy effectively. the core data type for data in dspy is example. you will use examples to represent items in your training set and test set. Dspy ai program examples this repository contains a collection of example ai programs built using dspy and maitained by the langtrace ai team.

Tutorials Overview - DSPy

Tutorials Overview - DSPy The dspy sample code library shows various ai program examples built using dspy to help developers understand and apply dspy for ai program development. Try the examples below after configuring your lm above. adjust the fields to explore what tasks your lm can do well out of the box. each tab below sets up a dspy module, like dspy.predict, dspy.chainofthought, or dspy.react, with a task specific signature. Dspy is an open source tool created by stanford university that "compiles declarative language model calls into self improving pipelines." instead of spending time crafting perfect prompts, dspy lets you program the ai models directly. this makes ai apps more reliable and easier to scale. This repository contains various examples demonstrating the usage of dspy, a framework for programming with language models. each example showcases different capabilities and patterns.

Galleries - DSPY

Galleries - DSPY Dspy is an open source tool created by stanford university that "compiles declarative language model calls into self improving pipelines." instead of spending time crafting perfect prompts, dspy lets you program the ai models directly. this makes ai apps more reliable and easier to scale. This repository contains various examples demonstrating the usage of dspy, a framework for programming with language models. each example showcases different capabilities and patterns. By applying classical machine learning concepts (training and evaluation data, metrics, optimization), dspy generates better prompts for a given model and task. in this notebook, we will see how to combine dspy with the robustness of haystack pipelines. os.environ["openai api key"] = getpass("enter openai api key:"). Think of a dspy.example as: a single row: like one row in a spreadsheet or database table. a flashcard: holding a specific question and its answer, or an input and its desired output. a test case: a concrete instance of the task defined by your signature. in this chapter, we’ll learn: what a dspy.example is and how it stores data. In this lesson, we covered the basics of data handling in dspy using example objects. you learned how to create basic example objects, work with multiple fields, define input fields, and access and manipulate example data. Dspy gives you a new way to think about building with llms. instead of manually crafting long prompts, you write modular code using these three core pieces: signatures: describe what inputs and.

Complete DSPy Tutorial - Master LLM Prompt Programming in 8 amazing examples!