Agents
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 tas... See more
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 tas... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
In an Agentic UX, an AI agent pulls weight across 3 categories: cognitive, creative, and logistical.
- Cognitive weight — the built-in agent pulls analysis and decision-making weight
- Creative weight — the built-in agent takes on visualization and media creation weight
- Logistical weight — the built-in agent takes tasks on operational and workflow weig
The agentic era of UX
The LLM doesn’t call the tool directly (yet), but it does pass back to the application what functions should be called — and with which parameters. And, now, OpenAI lets multiple function calls be “invoked” at once.
But, this idea is not just about GPT. The open source world is moving towards this model as well.
This Is The Future…It’s Just Not Here ... See more
But, this idea is not just about GPT. The open source world is moving towards this model as well.
This Is The Future…It’s Just Not Here ... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
🔎 GPT Researcher
GPT Researcher is an autonomous agent designed for comprehensive online research on a variety of tasks.
The agent can produce detailed, factual and unbiased research reports, with customization options for focusing on relevant resources, outlines, and lessons. Inspired by the recent Plan-and-Solve and RAG (Retrieval Augmented Gene... See more
GPT Researcher is an autonomous agent designed for comprehensive online research on a variety of tasks.
The agent can produce detailed, factual and unbiased research reports, with customization options for focusing on relevant resources, outlines, and lessons. Inspired by the recent Plan-and-Solve and RAG (Retrieval Augmented Gene... See more
assafelovic • GitHub - assafelovic/gpt-researcher: GPT based autonomous agent that does online comprehensive research on any given topic
Large Language Model State Machine (llmstatemachine)
Introduction
llmstatemachine is a library for creating agents with GPT-based language models and state machine logic.
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 c
GitHub - robocorp/llmstatemachine: A Python library for building GPT-powered agents with state machine logic and chat history memory.
memary: Open-Source Longterm Memory for Autonomous Agents
memary demo
Why use memary?
Agents use LLMs that are currently constrained to finite context windows. memary overcomes this limitation by allowing your agents to store a large corpus of information in knowledge graphs, infer user knowledge through our memory modules, and only retrieve relevan... See more
memary demo
Why use memary?
Agents use LLMs that are currently constrained to finite context windows. memary overcomes this limitation by allowing your agents to store a large corpus of information in knowledge graphs, infer user knowledge through our memory modules, and only retrieve relevan... See more
GitHub - kingjulio8238/memary: Longterm Memory for Autonomous Agents.
Data
Self-Operating Computer Framework
A framework to enable multimodal models to operate a computer.
Using the same inputs and outputs of a human operator, the model views the screen and decides on a series of mouse and keyboard actions to reach an objective.
Key Features
A framework to enable multimodal models to operate a computer.
Using the same inputs and outputs of a human operator, the model views the screen and decides on a series of mouse and keyboard actions to reach an objective.
Key Features
- Compatibility : Designed for various multimodal models.
- Integration : Currently
OthersideAI • GitHub - OthersideAI/self-operating-computer: A framework to enable multimodal models to operate a computer.
The Semantic Layer
for every data app
Connect data silos, drive consistent metrics, and power your AI and analytics with context.
for every data app
Connect data silos, drive consistent metrics, and power your AI and analytics with context.
Cube — Semantic Layer for Building Data Applications
📖 Introduction
XAgent is an open-source experimental Large Language Model (LLM) driven autonomous agent that can automatically solve various tasks. It is designed to be a general-purpose agent that can be applied to a wide range of tasks. XAgent is still in its early stages, and we are working hard to improve it.
🏆 Our goal is to create a super-in... See more
XAgent is an open-source experimental Large Language Model (LLM) driven autonomous agent that can automatically solve various tasks. It is designed to be a general-purpose agent that can be applied to a wide range of tasks. XAgent is still in its early stages, and we are working hard to improve it.
🏆 Our goal is to create a super-in... See more
OpenBMB • GitHub - OpenBMB/XAgent: An Autonomous LLM Agent for Complex Task Solving
🤖 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!
🗃️ Chat with your data - talk to your SQL database or your local files!
📄 You can also talk to docs - for example ask about LlamaIndex!