Initial commit. Added Docker compose with 3 containers - postgre, flowise, ollama.

Works on fly. Just fill the .env creds.

.env.Example

+HF_TOKEN=
 LANGCHAIN_API_KEY=
+
 PORT=3000
 FLOWISE_USERNAME=
 FLOWISE_PASSWORD=
@@ -15,3 +17,4 @@ DATABASE_NAME=flowise
 DATABASE_USER=
 DATABASE_PASSWORD=
 PGSSLMODE=require
+

docker-compose.yml

@@ -44,21 +44,24 @@ services:
       DATABASE_NAME: ${DATABASE_NAME}
       DATABASE_USER: ${DATABASE_USER}
       DATABASE_PASSWORD: ${DATABASE_PASSWORD}
-#    restart: on-failure:5
     depends_on:
       - ollama
       - flowise-db
     entrypoint: /bin/sh -c "sleep 3; flowise start"
 
   ollama:
-    image: ollama/ollama
+    build:
+      context: ./ollama-models
+      dockerfile: Dockerfile
     container_name: ollama
-    restart: unless-stopped
+#    restart: unless-stopped
     volumes:
       - ollama_data:/root/.ollama
     ports:
       - "11434:11434"
+    environment:
+      HF_TOKEN: ${HF_TOKEN}
 
 volumes:
   flowise-db-data:
-  ollama_data:
\ No newline at end of file
+  ollama_data:

ollama-models/Dockerfile

+# Use the official Python image as the base image
+FROM ollama/ollama
+
+# Install necessary dependencies
+RUN apt-get update && apt-get install -y curl
+
+# Set the working directory in the container
+RUN mkdir /app
+
+# Set the working directory
+WORKDIR /app
+
+# Copy the script to download the model
+COPY load_model.py /app/load_model.py
+
+# Set Hugging Face token for authentication
+ARG HF_TOKEN
+ENV HF_TOKEN=${HF_TOKEN}
+
+COPY start.sh /app/start.sh
+RUN chmod +x /app/start.sh
+
+# Use the start.sh script as the entrypoint
+ENTRYPOINT ["/app/start.sh"]
\ No newline at end of file

ollama-models/load_model.py

+import os
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Set the Hugging Face token for authentication
+hf_token = os.environ.get("HF_TOKEN")
+if hf_token is None:
+    raise ValueError("Hugging Face token is not set")
+
+model_name = "meta-llama/Llama-3.2-1B"
+
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+print("Model loaded successfully!")

ollama-models/start.sh

+#!/bin/bash
+# Pull the Ollama model
+ollama pull llama3.2:1b
+# Run the Ollama model
+ollama run llama3.2:1b &
+# Serve the Ollama model
+ollama serve