Discover and read the best of Twitter Threads about #deeplake

Most recents (3)

1. Generate Picture Books with AI for free (code open-source👇) with @OpenAI Function Calling, @LangChainAI, #DeepLake, & @StabilityAI.

- Prompt -> a PDF storybook with illustrations.
- Stores image & text pairs in the multimodal #DeepLake VectorDB for model training/finetuning!
2. Read the 🧵 to learn how @OpenAI Function Calling & @LangChainAI helped.

FableForge is built by @ethanjdev & handles:

1. Prompt -> text & images
2. PDF creation
3. Deep Lake DB to view the multimodal images + text dataset or stream it in real-time to train/fine-tune an LLM. FableForge diagram
3. But first... What's @OpenAI's function calling update?

In essence, it's bridging the gap between unstructured language input and structured, actionable output that other systems, tools, or services can use.
Read 14 tweets
Introducing... a song recommendation engine that is in tune with the emotions you're feeling with #DeepLake & @LangChainAI from scratch?

We experimented with 3 methods, but only one works. Learn which one👇 (we also open-sourced the repo)
🧩 Things we tried:
1️⃣ Direct embeddings: Mood ➡️ Song
2️⃣ Emotional embeddings: Similar emotions ➡️ Similar songs
3️⃣ @OpenAI #ChatGPT: As a retrieval system

Only one makes sense from performance/financial perspective.
Want to learn how to build a similar document retrieval-based product? Dive into the process:

📘 Full Article: lnkd.in/g-fpxqtg
🎵 Try the App: lnkd.in/gWJgV8te
🎬 Video Walkthrough: lnkd.in/gC9eUiAJ FairyTaleDJ app UI, built w...
Read 3 tweets
1/5 📣Introducing #DataChad, the #ChatGPT for any local or cloud data. Chat with any data source: a JSON, PDF, URL, or even an entire GitHub repo! 🌐📚

Built with #DeepLake, @LangChainAI, @OpenAI & open-sourced by an awesome community member @thegreatgustby.
2/5 And guess what? It's not just a shiny demo. You can try it out yourself! (Link in the next tweet) 💡🔗

github.com/gustavz/DataCh… DataChad is a ChatGPT for a...
3/5 @thegreatgustby shared tips to avoid common pitfalls while building AI apps with #LangChain & #DeepLake. 🧭🛠️

Adjusting parameters like k, chunk_size, max_tokens, and temperature. Read below to learn more about creating a Chat with Any Data app!
bit.ly/datachad
Read 3 tweets

Related hashtags

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3.00/month or $30.00/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!