Ru

Run ChatGPT and DALL-E in Emacs org-mode

Hacker News

Run ChatGPT and DALL-E in Emacs org-mode

org-ai is an Emacs package to integrate with the OpenAI API. It exposes a number of the API parameters (like temperature, system prompt, etc) so that it is easy to experiment with different combinations. The chat text is intentionally made fully modifiable. org-mode is able to embed images so that DALL-E image generation and variation can be used from within an Emacs buffer. Definitely a fun way to create an illustrated story :) Eventually I hope to connect other APIs and maybe local models as well.

Share card

Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, models · Missing: agents, macos, agent
88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: way, para · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Re
Resumemacs – DRY org-mode résumé builder53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Resumemacs – DRY org-mode résumé builder

Hacker News1
Em
Emacs org mode integration with IPython58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Emacs org mode integration with IPython

Hacker News92
AI
AI-org – org-mode powered by AI32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI-org – org-mode powered by AI

Hacker News3
Ge
Generate a mindmap from an org-mode file, with annotations56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Generate a mindmap from an org-mode file, with annotations

Hacker News34
Li
Literate Emacs Config in Org Mode53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Literate Emacs Config in Org Mode

Hacker News2
Co
Copy as Org-Mode for Chrome29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Copy as Org-Mode for Chrome

Hacker News3
Or
Org-people.el- contact management for org-mode41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Org-people.el- contact management for org-mode

Hacker News2
My
My (late) holiday hack: SOPAOpera.org51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My (late) holiday hack: SOPAOpera.org

Hacker News40
Sh
Shicray.org53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Shicray.org

Hacker News1
ai
aipwn33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

aipwn.org

TrustMRRSoftware