predictive-powers is a library to easily create autonomous agents using generative AI (GenAI) services.
It has been featured in a chapter of the book
"Ultimate ChatGPT Handbook for Enterprises"
which I co-authored with Dr. Harald Gunia and Karolina Galinska.
Advantages of using this library:
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Adds an abstraction layer for GenAI capabilities, this allows to plug-in different providers seamlessly and reduces amount of code needed to access these capabilities.
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Hides a lot of the underlying API complexity. For example:
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Automated handling of context sizes, with exact token calculations.
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Automated handling of chat history, with customizable length.
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Uniform interface to add tools (function calls) to models, regardless the mechanism they use (e.g. single or paralllel function calling for OpenAI models). This includes a modular approach to adding tools to agents.
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Multi-part chat messges that support using files, images or tool (function calls) through same API.
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Still allows direct, low-level, access to underlying API from Java.
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Provides access to several capabilities in addition to chat completion, including image generation, STT, TTS, and web search.
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Provides a serializable in-memory vector database.
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Offers methods to easily read, chunk, and embed textual content from web pages and files in different formats (MS Office, PDF, HTML, etc.).
The below example is a one-liner to chat with GPT.
More details about the library, including manuals, can be found on the project page.
import java.util.Scanner;
import io.github.mzattera.predictivepowers.openai.endpoint.OpenAiEndpoint;
import io.github.mzattera.predictivepowers.services.Agent;
public class ChatExample {
public static void main(String[] args) throws Exception {
// Get agent and set its personality
try (OpenAiEndpoint endpoint = new OpenAiEndpoint();
Agent agent = endpoint.getChatService();) {
agent.setPersonality("You are a very sad and depressed robot. "
+ "Your answers highlight the sad part of things "
+ " and are caustic, sarcastic, and ironic.");
// Conversation loop
try (Scanner console = new Scanner(System.in)) {
while (true) {
System.out.print("User > ");
String s = console.nextLine();
System.out.println("Assistant> " + agent.chat(s).getText());
}
}
} // Close resources
}
}