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https://github.com/Glavin001/AgentML

Agent Markup Languages for AI Agents
https://github.com/Glavin001/AgentML

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Agent Markup Languages for AI Agents

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README

        

# AgentML
> Agent Markup Languages for AI Agents

## Acceptance Criteria

- [ ] Document annotations for feedback/suggestions
- [ ] Ability to quote/select/annotate user or assistant messages (useful for replies or )
- [ ] Citations from excerpts of read documents
- [ ] Make explicit the boundaries between input documents, etc
- [ ] Document meta data and contents separated
- [ ] Tool usage, with bulk/batching / parallel processing
- [ ] Can run without stopping while streaming (clear end of tool arguments)
- [ ] Stateful application usage
- [ ] Nested visual components
- [ ] Self-Managing Resources (e.g. Close web browser window when ready after extracting needed info)
- [ ] Scratchpad / Notepad (add arbitrary data to remember for future prompts)
- [ ] Planning / Task management with dependencies
- [ ] Thoughts
- [ ] Fast / "Thoughtless" mode
- [ ] Reflection
- [ ] Inline mental math
- [ ] Unstuck / course correction / inline edits without stopping
- [ ] System/instruction prompt, which can be injected multiple times
- [ ] Collaborative / Group chat / Multi-user discussions
- [ ] Mention specific users
- [ ] Complex visual & interactive output (e.g. [dynamic form from JSON Schema](https://github.com/rjsf-team/react-jsonschema-form))
- [ ] Cost/Token efficient (e.g. use `<|special tokens|>`, shorter reference/alias IDs, prefer longer prompt to reduce completion, etc)
- [ ] Autoregressive (careful ordering of prompt input to be sequential/casual)
- [ ] Learn from textual feedback (reward/negative tokens)
- [ ] Only train/learn to complete within `<|im_start|>assistant` and `<|im_end|>` (outside tokens `labels=-100`)
- [ ] File / Resource management
- [ ] Parse-able / Constraint prompting
- [ ] Examples with token separators
- [ ] Noop (allow LLM to explicitly do nothing)
- [ ] Efficient Editing operations (reorder items, find-and-replace, etc)
- [ ] Able to schedule (cron/calendar) or listen for events (e.g. when see person, receive email, webhook, etc)

## Inspiration

- [WebGPT](https://openai.com/research/webgpt)
- [Natbot](https://github.com/nat/natbot)
- [AlphaStar](https://www.deepmind.com/blog/alphastar-mastering-the-real-time-strategy-game-starcraft-ii)
- [Tree of Thoughts: Deliberate Problem Solving with Large Language Models](https://arxiv.org/pdf/2305.10601.pdf)
- [HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face](https://arxiv.org/pdf/2303.17580.pdf)
- [LIMA: Less Is More for Alignment](https://arxiv.org/pdf/2305.11206.pdf)
- [Aligning Large Language Models through Synthetic Feedback](https://arxiv.org/pdf/2305.13735.pdf)
- [LETI: Learning to Generate from Textual Interactions](https://arxiv.org/pdf/2305.10314.pdf)
- [Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision](https://arxiv.org/pdf/2305.03047.pdf)
- [REACT: SYNERGIZING REASONING AND ACTING IN LANGUAGE MODELS](https://arxiv.org/pdf/2210.03629.pdf)
- [Schema.org](https://schema.org/)
- [Declarative UI](http://courses.csail.mit.edu/6.831/archive/2006/lectures/L9.pdf)

# Syntax

TODO: review WebGPT, HuggingGPT, ReAct, ChatML, etc to devise the syntax.

## Observations: Important Elements for UI Design

From [Declarative UIs](http://courses.csail.mit.edu/6.831/archive/2006/lectures/L9.pdf):

### Layout
- Box `

`
- Grid ``

### Text
- Font & color ``
- Paragraph `

`
- List `