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@@ -133,6 +133,31 @@ To supply your own QnA pair, use the data_type as `qna_pair` and enter a tuple.
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app.add_local('qna_pair', ("Question", "Answer"))
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app.add_local('qna_pair', ("Question", "Answer"))
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```
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```
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+### Reusing a Vector DB
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+
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+Default behavior is to create a persistent vector DB in the directory **./db**. You can split your application into two Python scripts: one to create a local vector DB and the other to reuse this local persistent vector DB. This is useful when you want to index hundreds of documents and separately implement a chat interface.
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+
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+Create a local index:
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+
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+```python
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+
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+from embedchain import App
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+
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+naval_chat_bot = App()
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+naval_chat_bot.add("youtube_video", "https://www.youtube.com/watch?v=3qHkcs3kG44")
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+naval_chat_bot.add("pdf_file", "https://navalmanack.s3.amazonaws.com/Eric-Jorgenson_The-Almanack-of-Naval-Ravikant_Final.pdf")
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+```
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+
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+You can reuse the local index with the same code, but without adding new documents:
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+
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+```python
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+
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+from embedchain import App
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+
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+naval_chat_bot = App()
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+print(naval_chat_bot.query("What unique capacity does Naval argue humans possess when it comes to understanding explanations or concepts?"))
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+```
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+
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### More Formats coming soon
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### More Formats coming soon
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* If you want to add any other format, please create an [issue](https://github.com/embedchain/embedchain/issues) and we will add it to the list of supported formats.
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* If you want to add any other format, please create an [issue](https://github.com/embedchain/embedchain/issues) and we will add it to the list of supported formats.
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