Merge branch 'main' of github.com:aritroCoder/Aptos-snap into main

.gitignore

@@ -81,4 +81,6 @@ server/yarn.lock
 yarn.lock
 server/.yarn/
 
-packages/snap/snap.manifest.json
+packages/snap/snap.manifest.json
+
+__pycache__

forecaster/.dockerignore

@@ -0,0 +1,17 @@
+__pycache__/
+.git
+.vscode
+.dockerignore
+.gitignore
+.env
+config
+build
+node_modules
+docker-compose.dev.yaml
+docker-compose.prod.yaml
+docker-compose.yaml
+Dockerfile
+Dockerfile.dev
+Dockerfile.prod
+Makefile
+README.md

forecaster/Dockerfile

@@ -0,0 +1,22 @@
+# Use the official Python base image
+FROM pytorch/pytorch:latest
+
+# Set the working directory inside the container
+WORKDIR /app
+
+# Copy the requirements file to the working directory
+COPY requirements.txt .
+
+RUN echo $(python3 -m site --user-base)
+
+# Install the Python dependencies
+RUN pip install -r requirements.txt
+
+# Copy the application code to the working directory
+COPY . .
+
+# Expose the port on which the application will run
+EXPOSE 8000
+
+# Run the FastAPI application using uvicorn server
+CMD ["uvicorn", "server:app", "--host", "0.0.0.0", "--port", "8000"]

forecaster/README.md

@@ -0,0 +1,18 @@
+# Python APT to USD rate forecasting engine
+This is a simple python script that uses the BiLSTM model architecture to forecast the APT to USD rate for the next few minutes,given the data of last 16 minutes.
+
+## Start the server
+```bash
+cd bin/
+./deploy.sh up
+```
+This command might take more than 10 minutes on first run as it will download the docker images and build the containers.
+Server will run on localhost:9000
+View the documentation at localhost:9000/docs
+
+## Stop the server
+```bash
+cd bin/
+./deploy.sh down
+```
+