My new tweet generation workflow automation
All the tools buffer, tweethunter, hyperfury charge money to generate tweets.
I had an itch to try running local llms and play with it.
I had also been re-reading Content OS by Justin Welsh. He talks about generating content with various perspective about the same content. So I thought, I can automate a bunch of it by using prompt templates, inspiration tweet examples and mistral 7B.
Packages & Tooling:
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Vanilla Python
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notion-sdk-py
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LlamaIndex
-
Ollama
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Mistral 7B
Code is at https://github.com/nehiljain/tweet-automation
Quick Introspection:
- Coding difficulty: Low
- Time to develop end to end: 6 hr for V1
- Usefulness: Instantly I was able to schedule 5 tweets in 15 mins
- Enjoyment: Felt great playing with Notion, Ollama, Obsidian
Ship30for30
But once you start writing, and building your library, you start to build momentum.
- You write...
- Which creates data points...
- Which reveals patterns (what works/what doesn’t)...
- Which shows you where there are opportunities to double-down...
- Which makes it easy to write the next thing...
- And the next thing...
And so on...
This is the game of Digital Writing.