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I don't think specialized vector databases will survive for much longer. They were a big thing for a while, but now, you have pro-grade databases like MongoDB offering native support for vector search. If you don't understand how vector search is an absolutely bonkers, mind-blowing invention, watch the attached... video. Give me 4 minutes, and I promise you'll understand how vectors have completely changed the game. Honestly, MongoDB is cracked! They have become a one-stop shop for AI implementations in addition to its document and non-relational model. You'll find a link below to the source code of 7 examples of AI agents that use MongoDB: 1. A factory safety assistant agent 2. A research assistant agent 3. An investment researcher agent 4. A recommendation system agent using RAG 5. A human resources chatbot agent 6. An AWS Bedrock agent 7. An asset manager assistant agent Everything is on a GitHub repository. Link below.show more

Santiago

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60,065 views • 1 year ago •via X (Twitter)

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11 Comments

Santiago1 year ago

The source code of every example is on this GitHub Repository: Every one of these AI examples uses MongoDB. You can run them all for free, change them, and start from there. Thanks to MongoDB for working with me on this post and sponsoring my work.

Tembo - Multi-Workload Managed Postgres2 years ago

It’d be cool if someone would make a specialized stack for each Postgres use case, with nice docs, perf comparisons, tutorials, etc - so you don’t have to leave Postgres :)

Gaius1 year ago

@MongoDB I have PTSD from using an early version of MongoDB on a project. Im a strong believer in using rock solid SQL databases, such as Postgres. And you can have vectors there too... (pgvector, etc)

Santiago1 year ago

@MongoDB MongoDB is an acquired taste for those of us who came from a traditional RDBMS background. But it's pretty neat once you get the hang of it. And if MongoDB makes you uncomfortable, wait until I tell you about a one-table design using DynamoDB. Crazy stuff!

Tenkaizen1 year ago

@MongoDB Adapt or fade away, it's the law of the digital jungle

Alian1 year ago

@MongoDB Elasticsearch is also a great product, you can combine vector proximity, and bm25 with a lot of features and rerank off the shelf.

Jimi V. (Bitswired)1 year ago

@MongoDB that’s great, less moving parts. however I would definitely prefer having these features on a sql database. I know there are postgres and sqlite extensions but I lost track of their progress.

Santiago1 year ago

@MongoDB Yes, Postgres support vectors as well through pgvector (extension). Not sure about MySQL, but I wouldn't be surprised if they have something like this as well.

Al Clark1 year ago

@MongoDB yes, this a thousand times - there's just no need for it

Zachary Royals priv/acc1 year ago

@MongoDB Using PgVector, agreed vector databases are becoming less appropriate. A trad database with a vector extension seems to offer more flexibility and reliability.

Edrick🕗1 year ago

@MongoDB Mongodb is actually in a pretty good spot to offer this as a feature

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82,154 views • 2 months ago

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.

Santiago

17,438 views • 14 days ago