From b6304550de35e873f37bdcdc80acdfb9bf5e57f7 Mon Sep 17 00:00:00 2001 From: Taranjeet Singh Date: Tue, 20 Jun 2023 21:17:59 +0530 Subject: [PATCH] Update Readme --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index dffac26d..d758c9e9 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ It abstracts the enitre process of loading dataset, chunking it, creating embedd You can add a single or multiple dataset using `.add` function and then use `.query` function to find an answer from the added datasets. -* If you want to create a Naval Ravikant bot which has 1 youtube video, 1 book as pdf and 2 of his blog posts, all you need to do is add the links to the videos, pdf and blog posts and embedchain will create a bot for you. +If you want to create a Naval Ravikant bot which has 1 youtube video, 1 book as pdf and 2 of his blog posts, all you need to do is add the links to the videos, pdf and blog posts and embedchain will create a bot for you. ```python @@ -95,7 +95,7 @@ To add any pdf file, use the data_type as `pdf_file`. Eg: app.add('pdf_file', 'a_valid_url_where_pdf_file_can_be_accessed') ``` -Note that we do not support password protected pdfs as of now. +Note that we do not support password protected pdfs. ### Web Page @@ -138,7 +138,7 @@ In the first release, we are making it easier for anyone to get a chatbot over a embedchain is built on the following stack: -- [langchain](https://github.com/hwchase17/langchain) as an LLM framework to load, chunk and index data +- [Langchain](https://github.com/hwchase17/langchain) as an LLM framework to load, chunk and index data - [OpenAI's Ada embedding model](https://platform.openai.com/docs/guides/embeddings) to create embeddings - [OpenAI's ChatGPT API](https://platform.openai.com/docs/guides/gpt/chat-completions-api) as LLM to get answers given the context - [Chroma](https://github.com/chroma-core/chroma) as the vector database to store embeddings