Can You Tell Me About DSPy Signatures: How To Implement Class Based Signatures & Generate Data

Can you Tell me about DSPy Signatures
What are DSPy Signatures
Framework or Template for prompts, to which the fixed inputs and outputs
Define and Control the behavior of the modules that follows
Field names matter, and carry semantic roles in plain english

What are the parts inside the Signatures
Inline Signatures:
Used inside the Modules directly
Follows the "Input - Output" pattern
Class Based:
Clarify about the task to be done with Docstring
Supply hints on nature of input fields with desc args
Supply constraints on nature of output fields with desc args

How they help in Programming LLMs
Can be represented as classes / objects
Assigned to variables
Modified with Programmatically
Used in Modules Directly as Classes

Before that Why?

DSPy takes a Modular approach to achieve the task that is to be completed. Which is to Optimize the prompts / models to get best results most of the time.

Building the prompts from variables provided to Signature, can make it easy for LLMs themselves to modify the prompts

Each NLP Task can be implemented as Signatures. Then Optimized to yield better results with both generated and real world data.

Signatures are Integrated with Modules like Predict, ChainOfThought, React, ProgramOfThought, MultiChainComparison and Majority

Chapter Navigation:
0:00 Intro
0:30 Why Signatures
1:30 What are Signatures
1:55 Two Types of Signatures
2:45 How Signatures Help
3:45 Code Walkthrough Imports
4:45 Taking Notes as Python Data Structures
6:25 NLP Tasks & its Signatures
7:25 Inline Signature In Detail
9:50 Inline Signature with ChainOfThought
11:40 Class Based Signatures
13:50 Creating Predict for ZeroShot Classification
14:40 Creating Signature for Getting JsonData
17:20 Classifying With Signature Object
18:50 Recap
19:50 Try Working with Open Source Models
21:30 Outro


The data and the code is located at
https://github.com/insightbuilder/pyt...

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