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add: add embedchainjs github repo to readme (#123)

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This commit is contained in:
Sahil Kumar Yadav
2023-07-05 01:17:41 +05:30
committed by GitHub
parent 5c19da74e5
commit 5fa2f5c5a2
3 changed files with 6 additions and 4 deletions
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2
.gitignore vendored
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@@ -165,3 +165,5 @@ cython_debug/
# Database # Database
db db
.vscode

4
README.md
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@@ -1,9 +1,9 @@
# embedchain # embedchain
[![](https://dcbadge.vercel.app/api/server/nhvCbCtKV?style=flat)](https://discord.gg/nhvCbCtKV) [![](https://dcbadge.vercel.app/api/server/nhvCbCtKV?style=flat)](https://discord.gg/nhvCbCtKV)
![PyPI](https://img.shields.io/pypi/v/embedchain) [![PyPI](https://img.shields.io/pypi/v/embedchain)](https://pypi.org/project/embedchain/)
embedchain is a framework to easily create LLM powered bots over any dataset. embedchain is a framework to easily create LLM powered bots over any dataset. If you want a javascript version, check out [embedchain-js](https://github.com/embedchain/embedchainjs)
It abstracts the entire process of loading a dataset, chunking it, creating embeddings and then storing in a vector database. It abstracts the entire process of loading a dataset, chunking it, creating embeddings and then storing in a vector database.

4
embedchain/loaders/pdf_file.py
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@@ -4,7 +4,7 @@ from embedchain.utils import clean_string
class PdfFileLoader: class PdfFileLoader:
def load_data(self, url): def load_data(self, url):
loader = PyPDFLoader(url) loader = PyPDFLoader(url)
output = [] output = []
@@ -20,4 +20,4 @@ class PdfFileLoader:
"content": content, "content": content,
"meta_data": meta_data, "meta_data": meta_data,
}) })
return output return output