SuperAGI VS openlibrary

Repo : https://github.com/TransformerOptimus/SuperAGI

The recent introduction of the “Agent Summary” feature in SuperAGI version 0.0.10 has brought a drastic difference in agent performance – improving the quality of agent output. Agent Summary helps AI agents maintain a larger context about their goals while executing complex tasks that require longer conversations (iterations).

Checkout the full release here: https://github.com/TransformerOptimus/SuperAGI/releases/tag/v0.0.10

10. SuperAGI

Currently, PaLM2 Bison is live on the dev branch of SuperAGI GitHub for the community to try: https://github.com/TransformerOptimus/SuperAGI/tree/dev

SuperAGI is made with developers in mind, therefore it takes into account their requirements and preferences when making autonomous AI agents. It has a number of advantages, including:

I think for agents to truly find adoption in real world, agent trajectory fine tuning is critical component - how do you make an agent perform better to achieve particular objective with every subsequent run. Basically making the agents learn similar to how we learn when we

Also I think current LLMs might not fit well for agent use cases in mid to long term because the RL they go through is based on input-best output methods whereas the intelligence that you need in agents is more around how to build an algorithm to achieve an objective on the fly - this requires perhaps new type of large models ( Large Agent Models ? ) which are trained using RLfD ( Reinforcement Learning from demonstration )

Also I think one of the key missing piece is a highly configurable software middle ware between Intelligence ( LLMs ), Memory ( Vector Dbs ~LTMs, STMs ), Tools and workflows across every iteration. Current agent core loop to find next best action is too simplistic. For example if core self prompting loop or iteration of an agent can be configured for the use case in hand. Eg for BabyAGI, every iteration goes through workflow of Plan, Prioritize and Execute or in AutoGPT it finds the next best action based on LTM/STM, or GPTEngineer it is to write specs > write tests > write code. Now for dev infra monitoring agent this workflow might be totally different - it would look like consume logs from different tools like Grafana, Splunk, APMs > See if it doesnt have an anomaly > if it has an anomaly then take human input for feedback. Every use case in real world has it's own workflow and current construct of agent frameworks have this thing hard coded in base prompt. In SuperAGI( https://superagi.com) ( disclaimer : Im creator of it ), core iteration workflow of agent can be defined as part of agent provisioning.

Another missing piece is notion of Knowledge. Agents currently depend entirely upon knowledge of LLMs or search results to execute on tasks, but if a specialised knowledge set is plugged to an agent, it performs significantly better.

Build your own game here: https://github.com/TransformerOptimus/SuperAGI

I'd like to make a pitch for Openlibrary.org the free online library from Internet Archive that includes a fulltext search of millions of books.

I've been volunteering with them on and off for several years and it's always a lovely experience. Their backend is python and frontend mostly from python templates and some Vue for librarian stuff.

Every Tuesday they have a call on Zoom that everyone is welcome to join to share what they're working on, ask for help, and generally chat a bit. It's a great time.

Depending on what you're interested in there's a lot to do from helping build import pipelines for more book entries, writing bots to cleanup data, Performance improvements, better documenting public APIs, etc

I'm currently slowly working on a wikidata integration for their authors page. We also could use some help upgrading to Vue 3, mentors for Google summer of code would be helpful, find of ML projects needing help, moving away from old jQuery libraries, etc.

They can be quite responsive to PRs too like I blogged about here: https://blog.rayberger.org/idea-to-merged-in-less-than-30-mi...

For example, here's a small issue that could use some help on the python side: https://github.com/internetarchive/openlibrary/issues/8928

OpenLibrary does provide search access to full texts. For example: https://openlibrary.org/search/inside?q=%22institutional+thi...

It is open source and they're always looking for contributors. I think they'd especially welcome help improving search!

https://github.com/internetarchive/openlibrary/

Check out https://openlibrary.org. You can search ´library science’, librarian’, etc, and something should come up. Just select the ‘ebooks’ option to search for items within the collection. And you can narrow the search by subject, etc.

Right now I'm in the middle of the chicken and the egg problem where we don't have enough authors cataloging their publications and b/c of that obviously readers are not interested in using the site.

I've gone back and forth with taking Open Libray's [0] catalog as that would at least flesh out our collection of books but then I'd have to deal with verifying authors to accounts so they can access their books. Which sounds like a major headache and also just defeats the concept of building a community.

Since this is really a weekend project, I'm just going to keep building the tools out to perfection and hope people will trickle in over time.

Luckily for me I just want to write, so the tools I'm building are exactly what works for my writing goals and I think overtime others will find the same value.

[0] https://openlibrary.org

Here's one: https://openlibrary.org/

The Internet Archive runs what they call the Open Library, which is a unique concept on the traditional library. You can sign-up with minimal details and digitally check out many scanned books from libraries all over the world. The only caveat is that almost all of the books are older editions - ones that would be impossible to find locally. It's great if you're looking for old routes, a look back in time, details about obscure areas, or just prefer to read a book rather than browse AllTrails. Please do still support local authors whenever you can as guidebooks take hundreds of hours to create and are slowly going extinct.

Repo : https://github.com/internetarchive/openlibrary