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Build and Deploy a LangChain-Powered Chat App with Docker and Streamlit
We are happy to have another great AI/ML story to share from our community. In this article, we will explore the process of creating a chat app using LangChain, OpenAI API, and Streamlit frameworks.
We have created and deployed a demo app (Figure on Streamlit Public Cloud and Google App Engine for a quick preview.
To deploy the chat app on Google App Engine, we used the following commands after installing the gcloud Python SDK: gcloud app create --project=[YOUR_PROJECT_ID] gcloud config set project [YOUR_PROJECT_ID] gcloud app deploy app.yaml A sample app deployed on Google App Engine (Figure can be accessed through: Figure 3: Link to a sample app deployed on Google App Engine.
We have created and deployed a demo app (Figure on Streamlit Public Cloud and Google App Engine for a quick preview.
To deploy the chat app on Google App Engine, we used the following commands after installing the gcloud Python SDK: gcloud app create --project=[YOUR_PROJECT_ID] gcloud config set project [YOUR_PROJECT_ID] gcloud app deploy app.yaml A sample app deployed on Google App Engine (Figure can be accessed through: Figure 3: Link to a sample app deployed on Google App Engine.
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