Agents

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Start your project with conversation history, support for any LLM, agentic workflows, integrations & more.

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Why Julep?

We've built a lot of AI apps and... See more

🤖 Create perpetual chatbots with self-editing memory!

🗃️ Chat with your data - talk to your SQL database or your local files!

📄 You can also talk to docs - for example ask about LlamaIndex!

Here are example ways to increase the success rate of these custom agents:

Provide a more focused, use-case specific system prompt to kick things off. Since you know what kinds of goals the agent supports, you can improve the odds of coming up with the right set of tasks initially. In fact, there’s nothing wrong with actually defining the set of... See more

The problem I've found with all of them is it is difficult to get consistent solid results that you would want to build around. Even listening to podcasts this seems to be a theme with the people at the forefront of MAS LLMs.

AgentTuning: Enabling Generalized Agent Abilities For LLMs

🤗 Model (AgentLM-70B) • 🤗 Dataset (AgentInstruct) • 📃 Paper • 🌐 Project Page

中文版(Chinese)

AgentTuning represents the very first attempt to instruction-tune LLMs using interaction trajectories across multiple agent tasks. Evaluation results indicate that AgentTuning enables the agent... See more

ht - headless terminal

ht (short for headless terminal ) is a command line program that wraps an arbitrary other binary (e.g. bash , vim , etc.) with a VT100 style terminal interface--i.e. a pseudoterminal client (PTY) plus terminal server--and allows easy programmatic access to the input and output of that terminal (via JSON over stdin/stdout). ht... See more

Large Language Model State Machine (llmstatemachine)

Introduction

llmstatemachine is a library for creating agents with GPT-based language models and state machine logic.

• Chat History as Memory : Leverages large context window models, making chat history the primary source of agent memory.


• Custom Python Functions with JSON Generation : Allows the

... See more

Adala is an Autonomous DA ta (Labeling) Agent framework.

Adala offers a robust framework for implementing agents specialized in data processing, with an emphasis on diverse data labeling tasks. These agents are autonomous, meaning they can independently acquire one or more skills through iterative learning. This learning process is influenced by... See more

In the open-source community, there are huge numbers of people leveraging AutoGen in creative ways, and solving surprising problems. One pattern that we see as fundamental is the "generator+critic" pattern, where one agent generates content (writing, code, etc.) and another agent critiques it (finds bugs, etc.) They can iterate until the solution... See more