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Merge pull request #9 from embedchain/improvement-2

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Update Readme
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Taranjeet Singh
2023-06-20 21:18:28 +05:30
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@@ -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. 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 ```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') 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 ### 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: 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 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 - [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 - [Chroma](https://github.com/chroma-core/chroma) as the vector database to store embeddings