Kicking of 2024 with giving all
@superagent_ai
Assistants to do HTTP requests 💥
In a nutshell, this allows the assistants to make API requests to any third-party API.
Created a little Assistant that can write to a
@supabase
instance using GPT-3.5.
Stoked for everything we
We are currently experimenting with Open Source LLMs, Embedding Models, Vector DBs and Observability platforms.
Drop in OSS replacements for all proprietary models and infra will be out soon 🔥
In late April 2023, prior to releasing
@superagent_ai
, I made a list of three high level assumptions to guide decision making:
1) In 1-2 years all enterprises will be using AI Assistants.
2) The developers tasked with building these Assistants won't be ML-engineers but your
Announcing Replit Core: Everything you need to build, deploy, and scale.
- powerful dev machines: 4 vCPU & 8GB
- state of the art AI (moving target)
- 3GB PostgresDB
- 2.5m autoscale deployment reqs
- 4 months
@perplexity_ai
Pro
- premium 1:1 support
-
@googlecloud
LLMs via
Real-time RAG using headless browsers and
@superagent_ai
✨
RAG without chunking/splitting/embeddings/encoder pipelines is something I've been experimenting with for a while.
We've implemented this as a part of our Web Research pipeline. Perfect for real-time analysis of files
I've finally started rolling out support from other models (OSS included) to
@superagent_ai
. You are now able to build workflows by connecting together different agents and language models together in an easy and maintainable way.
My fav right now is
@perplexity_ai
Just created an AI Scrum Master for Jira using
@superagent_ai
and
@Replit
Autoscale.
The agent is trained on a repo and takes a
@Jira
ticket as input and generates child issues automatically.
Next step would be to do the PR. But I'll leave that for a future enhancement 🌸
I don't ship alone. I have a team of over 100 🥷🥷🥷 shipping each and every day across all our repos.
Openness + Collaboration + Transparency takes you a long way.
✨Testing our new data mapper that adapts LLM outputs to your internal data structure. You can do pretty amazing things with it. Below I've created a leads list that auto-populates based on my table schema in
@airtable
.
Side note: I have been meaning to try out
@vercel
@nextjs
Demo shows the beta with LCM🧪✅
Uses
@superagent_ai
for multi-agent use-case, enabling sequential workflows with simple YAML configurations🤖 Multi-agent demo soon!👀
Inspired to create your own collaborative AI tools? Build them seamlessly with us🛠️
Really excited to announce support for
@algolia
indexes in
@superagent_ai
. 🥷
🤔 I sometimes feel we focus a lot on how to best do predictions over unstructured data (RAG, fine-tuning embedding models etc. etc.).
💡In fact, enterprises have a bunch of unstructured data (xlsx,
Mistral-7B-Instruct as a drop-in replacement for
#GPT
.
Pipeline will support fine-tuning for function calling and retrieval which means Assistants on
@superagent_ai
could be run on Open Source LLMs.
Below is a demo of mistral-7b-instruct-v0.1 running as a drop-in replacement
Astra DB is now integrated with
@superagent_ai
! 🥷
Plugging into SuperAgent's open-source framework will make it easy for developers to build and deploy production AI assistants.
Learn about the combined powers of Superagent and Astra DB:
#VectorDB
Have a demo call in 20 minutes with an HR company. Decided to build a couple of candidate sourcing workflows using
@superagent_ai
+
@airtable
🔍
It takes the candidate name, finds the LinkedIn profile and researches that to find skills and current employer.
Tables + AI
@timmyj1023
@pelaseyed
@abacaj
We call them Assistant as to not confuse anyone. Assistants being the orchestration of one or many agents. Autonomous or less autonomous.
Never deploy an AI powered chat without this feature.
Human Hand-offs are essential for any production use case of AI Assistants 🧬
Full example on
@Replit
:
YT tutorial:
❌ Developer shouldn't build their own frameworks
✅ They should use
@FastAPI
@nextjs
etc.
❌ Developers shouldn't build their own infra
✅ They should use
@vercel
@render
etc.
So why should developers build complex, inaccurate RAG pipelines? They shouldn't.
Well, they
@amadad
@vercel
@superagent_ai
The question is if
@vercel
would support superagent. I'm up for contributing if they are up for it.
Nevertheless, Superagent already has support for the same functionality as show in my tweet from dec.
Big news from
@superagent_ai
— we're introducing AI-agents for
@airtable
! Build your own custom agents can navigate and collect data from the web and files, turning data into insights, right in your Airtable.
Apply for early access:
Just pushed support for tools using enums. ⛏️
This comes in handy when segmenting, tagging or refining data. Also working on a SDK that will make agent configs much easier across the most popular frameworks such as
#autogen
#langchain
#bedrock
,
#superagent
and
#llamaindex
.
The intersection between UI component libraries and LLMs are really interesting.
Below is a demo I made using a custom
@alpha_vantage
tool to fetch stock prices and plot a chart. 📈
Custom functions allows you attach any tool/function/api to your
@superagent_ai
Assistant and
We are on a mission to help developers take their ideas from prototype to production.
Payments will be a major part of it!
Excited to partner up with to make that happen. Stay tuned!
Soon AIs will be everywhere. To ease development, companies like
@superagent_ai
, backed by
@ycombinator
, are simplifying the AI agent creation process w/ their easy-to-use framework.
We're super excited to partner w/
@superagent_ai
to provide AI payments to their 7k+ builders!
🤗a tiny update from , this beta feature test made me incredibly happy as it was several weeks in the making
Running
@Gradio
demos collaboratively in a group chat room.
enabling an interface like Midjourney in discord, to run any opensource model
👇Here
Just released NO-7B, built on top of Mistral-7B-Instruct-v01 and designed to surpass the knowledge cut-off date by leveraging real-time data.
It's influenced by the work of
@perplexity_ai
and their pplx-online models as well as the FreshLLMs paper.
Play:
I'm creating a README for a new open source project I'm releasing. Tried passing the url to the repo to ChatGPT and it didn't even go look at it. What is going on?
Created a workflow connecting
@perplexity_ai
to
@superagent_ai
and with great results 🥷
The pplx-70B-online is
Fine-tuning Mistral-7B-Instruct-v0.1 for structured responses opens up a bunch of use cases, such as creating dynamic charts on private data.
I decided to instruct it to return data in the format of ChartJS (you could use which ever charting lib you want) and hooked everything
Here are the 8 open-source startups YC invested in 2024 👇
Launched in March 2005,
@ycombinator
(YC) is arguably the most successful pre-seed fund in the world.
In its 19-year run, it has backed legendary companies such as Gitlab, Airbnb, Stripe, Reddit, Twitch, Instacart and
LOL
Amidst this backdrop of uncertainty, a group of rogue AI researchers, known as the Codebreakers, discovers a new form of LLM capable of self-improvement. This breakthrough sparks a race among the galaxy's powers to harness these potent LLMs for their own ends.
A long time ago, in a galaxy not so far away...
Episode I: The Rise of Intelligence
It is a period of technological revolution. Large Language Models (LLMs), advanced forms of artificial intelligence, have emerged across the galaxy, transforming life in countless ways.
As the
1:1 interview with the founder of Superagent.
Why did you start Superagent?
Initially I was building an application layer startup called Clickable. This was pre ChatGPT and there was basically no documentation/tools on how to train, deploy or orchestrate Language Models in a
Just merged a PR making the
@superagent_ai
browsing capabilities 25% faster and 40% cheaper.
Been chatting with several founders from the current
@ycombinator
batch about embracing open source.
The real question isn't WHY go open source, but rather, WHY NOT?