文件列表:

.env.local (29, 2023-12-04)
main.py (9859, 2023-12-04)
requirements.txt (160, 2023-12-04)
summary/ (0, 2023-12-04)
summary/2023-12-04.md (2743, 2023-12-04)

# Gmail LLM Using GPT4 to extract interesting links from my daily newsletters **Why?** I spend too much time opening and checking through all my newsletters subscriptions, would rather have all interesting links in one page. Inspired by [isafulf/inbox_cleaner](https://github.com/isafulf/inbox_cleaner) ## Prerequisites - Python 3.10 or higher - Gmail account - Google Cloud account with Gmail API enabled - OpenAI API key ## Setup 1. Clone repo: ``` git clone https://github.com/benthecoder/gmail_llm.git cd gmail_llm ``` 2. Install packages: ``` pip install -r requirements.txt ``` 3. Set up Google API credentials: - create a new OAuth 2.0 Client ID ([instructions](https://developers.google.com/workspace/guides/create-credentials)) - Download JSON file and rename it to `credentials.json`. - Put `credentials.json` in the `gmail_llm` directory. 4. Set OpenAI API key: - Get an OpenAI API key [here](https://platform.openai.com/api-keys) - Rename` .env.local` to `.env` and set your key ``` OPENAI_API_KEY= ``` ## Usage Run the script: ``` python main.py ``` see an example in [summary](summary/2023-12-04.md) folder ## TODO - [ ] improve prompt to extract as many links as possible and have better categorization - [ ] Experiment with different forms of output, maybe article form? Have it copy someone's writing style, publish it to substack, could be a newsletter automation with AI thing - [ ] Check if text extracted from emails can be cleaned up, any redundant info fed into prompt? - [ ] Run this on cloud/local and dump results in DB so I can read into my blog or in notion ## Links - Docs for listing emails [users.messages.list](https://developers.google.com/gmail/api/reference/rest/v1/users.messages/list) - Docs for querying [Searching for Messages](https://developers.google.com/gmail/api/guides/filtering) - [Counting tokens with tiktoken](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb)

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