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Matt Shumer Profile picture
@mattshumer_
Apr 3 • 7 tweets • 2 min read • Read on X
Introducing `Claude-Author` 📕✍️

One prompt -> an entire novel!

Just describe the high-level details, and a chain of AI systems will write an entire book for you in minutes.

- complete w/ cover art
- packages your book as a real e-book

And it's open-source!
Previous AI book-writing systems produced mildly interesting books that were filled with errors and quite boring.

Claude-Author is the first AI system that actually produces readable books.

Still not perfect, but it's a leaps and bounds improvement over previous approaches.
Claude-Author is a constrained agent -- meaning its behavior is highly-controlled, leading to better results than open-ended agents.

It's a chain of many Claude 3 Haiku/Opus and Stable Diffusion API calls that work together to write a coherent novel.
This is an update to the original gpt-author I built last year.

It now uses Claude 3 for better writing and dialogue, and produces much, much more interesting novels.

And the new Claude models are so much better that I was able to make the code much simpler than before!
I kept the coolest part -- it doesn't just write the novel -- it also creates an original cover based on the book. Image
Once your book is ready, you can immediately download it and read it on any EPUB-compatible viewer or device.
If you'd like to try it or contribute, check out the Github repo. github.com/mshumer/gpt-au…

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More from @mattshumer_

Matt Shumer Profile picture
Apr 5
Introducing `claude-researcher` 📈

A powerful Claude 3 research agent that delivers thorough reports in record time.

Just provide an topic, and a chain of AIs with **access to Google** will generate an incredibly comprehensive report for you.

And it's open-source!
`claude-researcher` is a constrained agent -- meaning its behavior is highly-controlled, leading to better results than open-ended agents.

It chains together lots of Claude 3 calls (and Google access) that work together to create a detailed report on a topic of your choice.
How it works, in a nutshell:
- User provides a topic
- Claude breaks it into sub-topics
- An agent with access to Google builds a report for each sub-topic
- A final Claude instance takes in all of the sub-topic reports, and generates a final, comprehensive report
Read 6 tweets
Matt Shumer Profile picture
Mar 27
Introducing `claude-llm-trainer` ✍️

The world's simplest way to train a task-specific LLM.

Just write a sentence describing the model you want.

A chain of AI systems will generate a dataset and train a model for you.

And it's open-source.
How it works:

- The user describes the model they want
Ex: "A model that writes Python functions"

- claude-llm-trainer leverages a chain of Claude 3 calls to create a great dataset for your task.

- We process the dataset, and train a LLaMA model!
This was based off of an older project I did, so the model we train is LLaMA 2 7B.

If you want, you can easily use a newer + better model like Mistral 7B.
Read 5 tweets
Matt Shumer Profile picture
Mar 25
Introducing `claude-journalist` ✍️

The first Claude 3 journalist agent.

Just provide a topic, and it will:
- Search the web for articles/real-time details
- Choose the best sources and read through them
- Write a fantastic, *factual* article + edit it

And it's open-source!
If you want to try it, you can head to the Github repo in the last tweet in this thread.

But if you don't want to bother with code, I've built an even better + FASTER version into HyperWrite -- try it here: app.hyperwriteai.com/personalassist…
`claude-journalist` is a constrained agent -- meaning its behavior is highly-controlled, leading to better results than open-ended agents.

It chains together lots of Claude 3 calls that work together to write a factual, news-worthy article.
Read 5 tweets
Matt Shumer Profile picture
Mar 22
Introducing `claude-investor` 📈

The first Claude 3 investment analyst agent.

Just provide an industry, and it will:
- Find financial data/news for key companies
- Analyze sentiment/trends for each
- Rank stocks by investment potential + price targets

And it's open-source!
`claude-investor` is a constrained agent -- meaning its behavior is highly-controlled, leading to better results than open-ended agents.

It chains together lots of Claude 3 calls that work together to analyze the major stocks in a given category.
How it works, in a nutshell:
- User provides an industry
- Agent finds a few stocks to explore
- Retrieves key financial data and news for these stocks
- Analyzes sentiment, industry trends, and peer comparisons for each
- Generates investment recommendations ranked by potential
Read 6 tweets
Matt Shumer Profile picture
Mar 21
Introducing `claude-opus-to-haiku` ✍️

Get the quality of Claude 3 Opus, at a fraction of the cost and latency.

Give one example of your task, and Claude 3 Opus will teach Haiku (60x cheaper!!) how to do the task perfectly.

And it's open-source: github.com/mshumer/gpt-pr…
This repo was inspired by this tweet that went viral.

Claude 3 Haiku is *60x* cheaper than Opus, and 10x faster.

I discovered that if you prompt Haiku with a number of great examples, it can match Opus' quality.
In production, Opus-level AI quality at a low cost, with near-instant results, is a game changer.

This notebook makes it possible for anyone to implement this quickly.

So how does it work?
Read 7 tweets
Matt Shumer Profile picture
Mar 20
Introducing `claude-prompt-engineer` ✍️

An agent that creates optimal Claude 3 prompts.

Just describe a task, and a chain of AIs will:
- Generate many possible prompts
- Test them in a ranked tournament
- Return the best one

And it's open-source: github.com/mshumer/gpt-pr…
`claude-prompt-engineer` is a constrained agent -- meaning its behavior is highly-controlled, leading to better results than open-ended agents.

It chains together lots of Claude 3 calls that work together to find the best possible prompt.
It's based on my previous `gpt-prompt-engineer` that went viral (5k+ stars on Github) with a few massive improvements:
- Uses Claude 3 (writes far better prompts than GPT-4)
- Auto-generates test cases, further automating the prompt eng process
- Supports multi-variable prompts!
Read 6 tweets

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