exo/lm-lib
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

lm-lib refactoring;

Browse Source 
git-svn-id: svn://home0/lm-lib@3610 71dcc7fd-b1f2-4e5d-bb8e-274146e81173
This commit is contained in:
(no author)
2024-12-18 18:58:27 +00:00
parent 35b59043e1
commit f01309526a
28 changed files with 63 additions and 57 deletions
Download Patch File Download Diff File Expand all files Collapse all files

26
README.md
View File

@@ -1,19 +1,23 @@
This suite of Java packages provides a comprehensive framework for building, deploying, and interacting with conversational AI agents powered by language models.
**Core Functionality:**
* **Agent Framework:** Enables the creation of modular and scalable agents with complex branching logic and concurrent execution capabilities.
* **Language Model Interaction:** Provides tools for accessing and interacting with various language models, including Azure AI's text generation service. This includes retrieving model information, managing conversations, generating completions, and customizing parameters.
* **Prompt Engineering:** Offers functionalities for constructing and manipulating prompts tailored to specific language models, supporting various formatting strategies.
* **Text Processing:** Includes tools for tokenizing and detokenizing text, essential for preparing input for language models and interpreting their output.
This suite of Java packages provides a comprehensive framework for building and deploying conversational agents powered by language models.
**Purpose:**
The primary purpose of this program is to simplify the development and deployment of sophisticated conversational AI agents. By providing a robust set of tools for agent management, language model interaction, prompt engineering, and text processing, the program empowers developers to create powerful and engaging AI-driven conversational experiences.
The primary purpose is to simplify the development and management of AI-driven chatbot applications.
*gemma2-27b requests=49, requestDuration=PT7M4.534240136S, inTokens=26243, outTokens=2159, tps=5.091981132075472*
**Functionality:**
## Introducing a Powerful Framework for Building Intelligent Agents
* **Agent Framework:** The core package enables the creation of agents capable of interacting with language models, processing text, maintaining conversation context, tracking statistics, and executing in a structured manner. It supports chaining agents, handling responses, and flexible configuration.
* **Language Model Interaction:** Several packages provide tools for interacting with various language models, including Azure AI's text generation service and remote text completion models. These tools handle tasks like retrieving models, managing conversations, generating completions, and tracking API usage.
* **Prompt Engineering:** A dedicated package focuses on constructing and manipulating prompts tailored to specific language models. It supports different formatting strategies and allows for fine-grained control over prompt structure.
* **Tokenization:** Another package handles text tokenization and detokenization, crucial for preparing text for input to language models and interpreting their outputs.
**Overall, this collection of packages offers a powerful and flexible toolkit for developers looking to build sophisticated conversational agents leveraging the capabilities of modern language models.**
*gemma2-27b requests=50, requestDuration=PT3M36.921314511S, inTokens=26737, outTokens=2207, tps=10.217592592592593*
*[Below announcement has been generated by the unit test AgentTest#agenticFlow:]*
Title: Introducing a Powerful Framework for Building Intelligent Agents
We're excited to announce the development of a new Java codebase designed to build intelligent agents capable of interacting with language models like GPT. This framework offers a flexible and extensible architecture, empowering developers to create sophisticated conversational agents for a wide range of applications.