Conversational AI application: Chat with your documents 📚 using Llama2 🦙, AWS SageMaker 🧠, LangChain 🦜️🔗 and Streamlit 🔥
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Clone this repo ⏬
git clone https://github.com/vas610/convesational_ai.git cd convesational_ai
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Create conda 🐍 environment
conda env create -f environment.yml python=3.10 # conda 22.9.0 conda activate docai pip install -r requirements.txt python -m ipykernel install --user --name=conda_docai
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Download required data 🔠
wget --quiet https://docs.aws.amazon.com/sagemaker/latest/dg/sitemap.xml --output-document - | egrep -o "https://[^<]+" | wget --directory-prefix=./aws_docs/sagemaker/ -i -
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Create and Store Embeddings 1️⃣0️⃣
./dataprep.py
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Setup a SageMaker Endpoint with Llama2 🦙 by following this blog. I have used the
meta-textgeneration-llama-2-7b-f
model . Also, update the endpoint name in the .env file -
Run the below command to start the streamlit app 🔥
streamlit run streamlit_app.py --server.address 0.0.0.0 --server.port 8080 --server.fileWatcherType none --browser.gatherUsageStats False