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virat Profile picture
@virattt
Jun 18 • 2 tweets • 2 min read • Read on X
Our OSS financial agent now has a python backend.

I migrated the agent code to use the latest @LangChainAI gen ui framework

• set up langgraph
• set up langserve
• set up fastapi
• set up agent tools

Super excited about this project.

We'll have a true client + server app with a python backend and nextjs frontend.

Eventually, will launch this into production.

Since it is open source, you all can do the same!

Right now, we have 4 agent tools:
• get ticker news
• get ticker financials
• get ticker current price
• get ticker historical prices

Will set up the nextjs frontend next.

Fantastic work by @BraceSproul in the YT videos, which demystified everything.Image
Code:

Brace's video: github.com/virattt/financ…

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More from @virattt

virat Profile picture
May 12, 2023
So, I'm learning how to build LLM-powered chat apps that are more production-ready, from scratch.

I've created an open-source repo that contains my ongoing explorations.

The stack:
• Django backend
• React frontend
• @LangChainAI agents
• Websocket protocol

GitHub below. ImageImage
In my free time, my main focus will be to evolve this codebase.

Functionalities I want to add:
• Streaming LLM output
• Storage (e.g. vector db)
• More agent tools
• Short-term memory
• BabyAGI
• Plan-and-Execute agent
• More sophisticated UI
• Error handling

What else?
Here's the repo: github.com/virattt/chat_a…

I just created the codebase this week and there's a lot of (exciting!) work to do.

However, the core functionality of chatting with a @LangChainAI agent is implemented.

Fun fact: this is my first open source project 🙂🎢
Read 4 tweets
virat Profile picture
Apr 18, 2023
Alright, I finally understand @LangChainAI agents and tools.

I can now create a custom:
1. Tool that "reads" annual reports
2. Agent that answers queries via the tool

For my example, I am using $META's 2022 annual report.

Code is below. Happy learning 🙂
(1/3) About the custom Tool

Under the hood, the Annual Report tool is forwarding queries to a @LangChainAI chain.

This chain answers queries using:
• @trychroma's Chroma DB
• @OpenAI's GPT-3.5 Turbo model

I still don't have API access to GPT-4. Sigh.
(2/3) About the custom Agent

The agent is given a list of tools that it can use to answer queries.

For my example, I am just giving it the Annual Report tool.

However, you can create or add more tools as you see fit!
Read 4 tweets
virat Profile picture
Apr 7, 2023
I've seen multiple questions about how to build a Chatbot that:

• Retrieves data from PDFs and
• Has conversational memory

Turns out, it's really simple to do with @LangChainAI.

So, I wrote a quick tutorial with a real-world example for you all.

Code below.
1/4
Prompt: "What was Airbnb's net income in 2022?"

Response: "$1.9 billion"
2/4
Prompt: "What was it two years before that?"

Response: "Airbnb's net income in 2020 was -$4.6 billion."

Nice.

It figured out that I want to know what net income was two years before 2022.
Read 6 tweets

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