Joshua Sundance Bailey
commited on
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env file use
Browse files- README.md +39 -11
- docker-compose.yml +0 -2
- kubernetes/deploy.sh +1 -1
README.md
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@@ -42,32 +42,60 @@ This `README` was written by [Claude 2](https://www.anthropic.com/index/claude-2
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- `meta-llama/Llama-2-13b-chat-hf`
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- `meta-llama/Llama-2-70b-chat-hf`
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- Streaming output of assistant responses
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- Leverages LangChain for dialogue management
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- Integrates with [LangSmith](https://smith.langchain.com) for tracing conversations
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- Allows giving feedback on assistant's responses
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# Usage
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## Run on HuggingFace Spaces
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[![Open HuggingFace Space](https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg)](https://huggingface.co/spaces/joshuasundance/langchain-streamlit-demo)
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## With Docker (pull from Docker Hub)
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## Docker Compose
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1. Clone the repo. Navigate to cloned repo directory
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# Configuration
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- Select a model from the dropdown
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- Customize the assistant prompt and temperature
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# Code Overview
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- `app.py` - Main Streamlit app definition
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- `llm_stuff.py` - LangChain helper functions
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# Deployment
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The app is packaged as a Docker image for easy deployment. It is published to Docker Hub and Hugging Face Spaces:
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- [DockerHub](https://hub.docker.com/r/joshuasundance/langchain-streamlit-demo)
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- [HuggingFace Spaces](https://huggingface.co/spaces/joshuasundance/langchain-streamlit-demo)
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CI workflows in `.github/workflows` handle building and publishing the image.
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# Links
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- [Streamlit](https://streamlit.io)
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- `meta-llama/Llama-2-13b-chat-hf`
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- `meta-llama/Llama-2-70b-chat-hf`
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- Streaming output of assistant responses
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- Leverages LangChain for dialogue and memory management
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- Integrates with [LangSmith](https://smith.langchain.com) for tracing conversations
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- Allows giving feedback on assistant's responses
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- Tries reading API keys and default values from environment variables
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# Usage
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## Run on HuggingFace Spaces
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[![Open HuggingFace Space](https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg)](https://huggingface.co/spaces/joshuasundance/langchain-streamlit-demo)
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## With Docker (pull from Docker Hub)
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1. _Optional_: Create a `.env` file based on `.env-example`
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2. Run in terminal:
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`docker run -p 7860:7860 joshuasundance/langchain-streamlit-demo:latest`
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or
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`docker run -p 7860:7860 --env-file .env joshuasundance/langchain-streamlit-demo:latest`
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5. Open http://localhost:7860 in your browser
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## Docker Compose
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1. Clone the repo. Navigate to cloned repo directory
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2. _Optional_: Create a `.env` file based on `.env-example`
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3. Run in terminal:
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`docker compose up`
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or
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`docker compose up --env-file env`
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4. Run in terminal: `docker compose up`
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5. Open http://localhost:7860 in your browser
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## Kubernetes
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1. Clone the repo. Navigate to cloned repo directory
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2. Create a `.env` file based on `.env-example`
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3. Run in terminal: `cd kubernetes && kubectl apply -f resources.yaml`
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4. Get the IP address for your new service: `kubectl get service langchain-streamlit-demo`
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# Configuration
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- Select a model from the dropdown
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- _Optional_: Create a `.env` file based on `.env-example`, or
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- Enter an API key for the relevant provider
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- Optionally enter a LangSmith API key to enable conversation tracing
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- Customize the assistant prompt and temperature
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# Code Overview
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- `langchain-streamlit-demo/app.py` - Main Streamlit app definition
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- `langchain-streamlit-demo/llm_stuff.py` - LangChain helper functions
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- `Dockerfile`, `docker-compose.yml`: Docker deployment
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- `kubernetes/`: Kubernetes deployment files
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- `.github/workflows/`: CI/CD workflows
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# Deployment
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The app is packaged as a Docker image for easy deployment. It is published to Docker Hub and Hugging Face Spaces:
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- [DockerHub](https://hub.docker.com/r/joshuasundance/langchain-streamlit-demo)
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- [HuggingFace Spaces](https://huggingface.co/spaces/joshuasundance/langchain-streamlit-demo)
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CI/CD workflows in `.github/workflows` handle building and publishing the image.
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# Links
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- [Streamlit](https://streamlit.io)
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docker-compose.yml
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langchain-streamlit-demo:
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image: langchain-streamlit-demo:latest
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build: .
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env_file:
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- .env
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ports:
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- "${APP_PORT:-7860}:${APP_PORT:-7860}"
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command: [
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langchain-streamlit-demo:
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image: langchain-streamlit-demo:latest
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build: .
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ports:
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- "${APP_PORT:-7860}:${APP_PORT:-7860}"
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command: [
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kubernetes/deploy.sh
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echo "Secret 'langchain-streamlit-demo-secret' does not exist. Creating."
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fi
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kubectl create secret generic langchain-streamlit-demo-secret --from-env-file
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# Deploy to Kubernetes
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echo "Secret 'langchain-streamlit-demo-secret' does not exist. Creating."
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fi
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kubectl create secret generic langchain-streamlit-demo-secret --from-env-file=../.env
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# Deploy to Kubernetes
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