--- title: vespa-engine/fasthtml-vespa emoji: 🚀 colorFrom: purple colorTo: red sdk: docker app_file: main.py pinned: false termination_grace_period: 2m --- #Vespa # FastHTML Vespa frontend This is a simple frontend for Vespa search engine. It is built using [FastHTML](https://www.fastht.ml/) and written in pure Python. Check out the [live demo](https://huggingface.co/spaces/vespa-engine/fasthtml-vespa) on Huggingface Spaces. Search page | Login page | Query logs :-------------------------:|:-------------------------:|:-------------------------: ![search](assets/search-page.png) | ![admin-login](assets/admin-login.png) | ![query-log](assets/query-log.png) ### Features - Simple search interface, with links to search results. - Accordion with full JSON-response from Vespa. - SQLite DB for storing queries. - Admin authentication for viewing and downloading queries. - Deployment options - Docker + [Huggingface spaces](https://huggingface.co/spaces/). ### Why? We have recognized the need, both for ourselves and others, to be able to set up a simple frontend for Vespa, without having to navigate the frontend framework jungle. This sample-app can serve as an example of how you can build and deploy a simple frontend for Vespa, using FastHTML. ### How to use #### 1. Clone this folder to your local machine 📂 The command below will clone the repository and only fetch the `fasthtml-frontend` folder. ```bash git clone --depth 1 --filter=blob:none --sparse https://github.com/vespa-engine/sample-apps.git temp-sample-apps && cd temp-sample-apps && git sparse-checkout set fasthtml-frontend && mkdir -p ../fasthtml-frontend && mv fasthtml-frontend/* ../fasthtml-frontend/ && cd .. && rm -rf temp-sample-apps ``` #### 2. Install dependencies 🔧 ```bash pip install -r requirements.txt ``` #### 3. Run the app locally 💻 ```bash python main.py ``` At this point, you should be able to access the app at [http://localhost:5001](http://localhost:5001). But, you will _not_ be able to search for anything, as your environment variables are not set up. #### 4. Deploy and feed your Vespa application ▶️ By running the `deploy_app.ipynb` notebook, you will deploy a Vespa application to the Vespa Cloud. The application is just a sample hybrid search application using the [BEIR/nfcorpus](https://huggingface.co/datasets/BeIR/nfcorpus) dataset. Feel free to replace the dataset and application with your own. Make sure to replace these variables at the top of the notebook with your own values: ```python # Replace with your tenant name from the Vespa Cloud Console tenant_name = "mytenant" # Replace with your application name (does not need to exist yet) application = "fasthtml" # Token id (from Vespa Cloud Console) token_id = "fasthtmltoken" ``` #### 5. Set up environment variables 🔐 Make sure to add the output of the `token_endpoint` from the `deploy_app.ipynb`- notebook to your `.env.example` file. This value should be placed in the `VESPA_APP_URL` environment variable. At the same time, you should rename the `.env.example` file to `.env`. This is added to the `.gitignore` file. #### 6. Run the app locally 🚀 Now, you should be able to run the app locally and search for queries. ```bash python main.py ``` Open your browser and navigate to [http://localhost:5001](http://localhost:5001). ### Deployment If you want to deploy the app, you set the `DEV_MODE=False` in `main.py`. This will disable loading of environment variables from the `.env` file, and instead use the environment variables set in the deployment environment. #### Docker 🐳 You can build and run the app using Docker. Note that there are two Dockerfiles in the repo: - `Dockerfile` is for building the image for Huggingface Spaces. - `Dockerfile.nonhf` is for building an image that can be run locally or on any other platform. Build the image: ```bash docker build -t fhtdemoimg . -f Dockerfile.nonhf ``` **Run the container:** - Makes the environment variables in the `.env` file available to the container. - Will mount the `db/` folder to the container, so that the SQLite database is persisted between runs. - Sets the hostname to `dockerhost`, so that we can know use that to enable hot-reloading in the FastHTML app. - Maps the default Starlette port `5001` to `8000` on the host. ```bash docker run --name fhtdemo --rm --env-file .env -p 8000:5001 -h dockerhost -v $(pwd)/db:/code/db fhtdemoimg ``` #### Huggingface 🤗 Spaces This deployment option is free. The deployment script is shamelessly copied from the [fasthtml-hf](https://github.com/AnswerDotAI/fasthtml-hf) repo. Check it out for details on cli-options, configuration and DB-backup options. 1. Get a huggingface token with `write` permissions. You can do this by going to your [Huggingface profile](https://huggingface.co/settings/tokens) and create a new token. 2. Set the `HF_TOKEN` environment variable to the token you just created. 3. Run `python deploy_hf.py [--private true]` to deploy the app to Huggingface Spaces. 4. Remember to add `VESPA_APP_URL` and `VESPA_CLOUD_SECRET_TOKEN` to the environment variables in the [Huggingface Spaces settings.](https://huggingface.co/docs/hub/en/spaces-overview#managing-secrets) ### Go build some cool Vespa apps! 🚀