This Python project creates a search engine for OpenAI's ChatGPT conversation history, enabling users to search, view, and interact with archived conversations. It leverages text embeddings for semantic search capabilities.

• Load and update conversation and index data dynamically from files.
• Generate and store text embeddings for efficient semantic search.
• Provide interactive search and conversation replay in the terminal.

1. Install required packages:

   pip install -r requirements.txt

2. Export chat history and add them to the project:

   • Navigate to the ChatGPT website and go to Settings -> Data controls -> Export data.
   • Wait for the data to be prepared and download the zip file.
   • Extract the conversations.json from the zip file and place it in the data/exported directory within the project.

3. Add OpenAI API key for API access: Add your OpenAI API key to the keys.env file:

   API_KEY_OPENAI=your_openai_api_key

4. Run the program:

   • Execute the program with the following command:

     python main.py

   • On the first run, the program will reformat conversations.json and prepare messages for text embeddings.

   - Processing Exported Chats - New Chats: 1632 - Total Chats: 1620 - Total Msg Chunks: 17495 -

   • Then it will notify you of generating all embeddings.

   - New API Calls: 17495 - Tokens: 9219971 - Cost: $1.1986 - Model: text-embedding-3-large - Fetched Successfully -

   • After indexing, these embeddings are stored for future use.

   - Finalizing and Storing Processed Data - Done -

   • To update the chat history with a new conversations.json, simply replace the old one and rerun the program. New messages will be processed and indexed accordingly.

After executing a search, you'll receive a list of chat results with their titles, URLs, and creation dates. You can either:

• Use the provided URLs to view and continue the conversation directly on the ChatGPT website.
• Continue the conversation using the Chat Completions API. Enter your prompt and receive responses. You can adjust the model and temperature settings as needed in the core.py file.

Here's a sample output of the console:

- Search Query (0 to Exit): chromedriver update and install on ubuntu server
- Page Size (Default: 10): 3
- Search Results for 'chromedriver update and install on ubuntu server':
+---------+-----------------------------------------+---------------------+------------------------------------------------------------+
|   INDEX | TITLE                                   | CREATED AT          | URL                                                        |
+=========+=========================================+=====================+============================================================+
|       1 | Migrating Project to Ubuntu             | 2023-06-14 11:00:57 | https://chatgpt.com/c/291a78b1-7b23-474c-96c2-e123c2712263 |
+---------+-----------------------------------------+---------------------+------------------------------------------------------------+
|       2 | Using Browserless.io on Ubuntu Server   | 2023-08-02 01:02:01 | https://chatgpt.com/c/911424e0-3b94-4b89-8528-3e27c7b3fceb |
+---------+-----------------------------------------+---------------------+------------------------------------------------------------+
|       3 | ChromeDriver Error: Unexpected Argument | 2024-04-28 23:31:55 | https://chatgpt.com/c/6259c441-f5c9-493d-b49c-87d2525afeb9 |
+---------+-----------------------------------------+---------------------+------------------------------------------------------------+

- Index to Continue Chat With (0 to Return): : 1


- Title: Migrating Project to Ubuntu -
- Length: 51 Messages - Context: 13109 Tokens -
- API Input Cost: ~$0.0655+ Per Prompt Using gpt-4o Model -
- ChatGPT URL: https://chatgpt.com/c/800693d5-9715-4bf9-9d08-251126da782c -


- User: ...
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- Assistant: ...
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- User (0 to Return): Okay, got it fixed. One more thing, can you elaborate more on the process of updating ChromeDriver on Ubuntu?
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- Assistant: ...