Skip to content

fix: update langchain-huggingface import and llama31 blog URL in hell… #1049

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
riyamit241 wants to merge 1 commit into
base: main
Choose a base branch
from
Open

fix: update langchain-huggingface import and llama31 blog URL in hell… #1049

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 5 additions & 4 deletions getting-started/RAG/hello_llama_cloud.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,7 @@
"* How to use LangChain to ask Llama general questions and follow up questions\n",
"* How to use LangChain to load a recent web page - Hugging Face's [blog post on Llama 3.1](https://huggingface.co/blog/llama31) - and chat about it. This is the well known RAG (Retrieval Augmented Generation) method to let LLM such as Llama 3 be able to answer questions about the data not publicly available when Llama 3 was trained, or about your own data. RAG is one way to prevent LLM's hallucination\n",
"\n",
"**Note** We will be using [Replicate](https://replicate.com/meta/meta-llama-3.1-405b-instruct) to run the examples here. You will need to first sign in with Replicate with your github account, then create a free API token [here](https://replicate.com/account/api-tokens) that you can use for a while. You can also use other Llama 3.1 cloud providers such as [Groq](https://console.groq.com/), [Together](https://api.together.xyz/playground/language/meta-llama/Llama-3-8b-hf), or [Anyscale](https://app.endpoints.anyscale.com/playground) - see Section 2 of the Getting to Know Llama [notebook](https://github.com/meta-llama/llama-recipes/blob/main/recipes/quickstart/Getting_to_know_Llama.ipynb) for more information."
"**Note** We will be using [Replicate](https://replicate.com/meta/meta-llama-3.1-405b-instruct/versions) to run the examples here. You will need to first sign in with Replicate with your github account, then create a free API token [here](https://replicate.com/account/api-tokens) that you can use for a while. You can also use other Llama 3.1 cloud providers such as [Groq](https://console.groq.com/), [Together](https://api.together.xyz/playground/language/meta-llama/Llama-3-8b-hf), or [Anyscale](https://app.endpoints.anyscale.com/playground) - see Section 2 of the Getting to Know Llama [notebook](https://github.com/meta-llama/llama-recipes/blob/main/recipes/quickstart/Getting_to_know_Llama.ipynb) for more information."
]
},
{
Expand All @@ -38,7 +38,8 @@
"!pip install faiss-cpu\n",
"!pip install bs4\n",
"!pip install replicate\n",
"!pip install langchain-community"
"!pip install langchain-community\n",
"!pip install langchain-huggingface"
]
},
{
Expand Down Expand Up @@ -201,13 +202,13 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.embeddings import HuggingFaceEmbeddings\n",
"from langchain_huggingface import HuggingFaceEmbeddings\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
"from langchain_community.document_loaders import WebBaseLoader\n",
"import bs4\n",
"\n",
"loader = WebBaseLoader([\"https://huggingface.co/blog/llama3\"])\n",
"loader = WebBaseLoader([\"https://huggingface.co/blog/llama31\"])\n",
"docs = loader.load()\n"
]
},
Expand Down