mirror of
https://github.com/arc53/DocsGPT.git
synced 2026-02-02 20:30:38 +00:00
e7d2af2405
* fixes setup scripts fixes to env handling in setup script plus other minor fixes * Remove var declarations Declarations such as `LLM_PROVIDER=$LLM_PROVIDER` override .env variables in compose Similar issue is present in the frontend - need to choose either to switch to separate frontend env or keep as is. * Manage apikeys in settings 1. More pydantic management of api keys. 2. Clean up of variable declarations from docker compose files, used to block .env imports. Now should be managed ether by settings.py defaults or .env
506 lines
20 KiB
Bash
Executable File
506 lines
20 KiB
Bash
Executable File
#!/bin/bash
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# Color codes
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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DEFAULT_FG='\033[39m'
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RED='\033[0;31m'
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NC='\033[0m'
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BOLD='\033[1m'
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# Base Compose file (relative to script location)
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COMPOSE_FILE="$(dirname "$(readlink -f "$0")")/deployment/docker-compose-hub.yaml"
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COMPOSE_FILE_LOCAL="$(dirname "$(readlink -f "$0")")/deployment/docker-compose.yaml"
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ENV_FILE="$(dirname "$(readlink -f "$0")")/.env"
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# Animation function
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animate_dino() {
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tput civis # Hide cursor
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local dino_lines=(
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" ######### "
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" ############# "
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" ##################"
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" ####################"
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" ######################"
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" ####################### ######"
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" ############################### "
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" ################################## "
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" ################ ############ "
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" ################## ########## "
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" ##################### ######## "
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" ###################### ###### ### "
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" ############ ########## #### ## "
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" ############# ######### ##### "
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" ############## ######### "
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" ############## ########## "
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"############ ####### "
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" ###### ###### #### "
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" ################ "
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" ################# "
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)
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# Static DocsGPT text
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local static_text=(
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" ____ ____ ____ _____ "
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" | _ \\ ___ ___ ___ / ___| _ \\_ _|"
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" | | | |/ _ \\ / __/ __| | _| |_) || | "
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" | |_| | (_) | (__\\__ \\ |_| | __/ | | "
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" |____/ \\___/ \\___|___/\\____|_| |_| "
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" "
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)
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# Print static text
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clear
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for line in "${static_text[@]}"; do
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echo "$line"
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done
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tput sc
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# Build-up animation
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for i in "${!dino_lines[@]}"; do
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tput rc
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for ((j=0; j<=i; j++)); do
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echo "${dino_lines[$j]}"
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done
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sleep 0.05
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done
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sleep 0.5
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tput rc
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tput ed
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tput cnorm
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}
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# Check and start Docker function
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check_and_start_docker() {
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# Check if Docker is running
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if ! docker info > /dev/null 2>&1; then
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echo "Docker is not running. Starting Docker..."
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# Check the operating system
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case "$(uname -s)" in
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Darwin)
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open -a Docker
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;;
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Linux)
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sudo systemctl start docker
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;;
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*)
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echo "Unsupported platform. Please start Docker manually."
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exit 1
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;;
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esac
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# Wait for Docker to be fully operational with animated dots
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echo -n "Waiting for Docker to start"
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while ! docker system info > /dev/null 2>&1; do
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for i in {1..3}; do
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echo -n "."
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sleep 1
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done
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echo -ne "\rWaiting for Docker to start "
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done
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echo -e "\nDocker has started!"
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fi
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}
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# Function to prompt the user for the main menu choice
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prompt_main_menu() {
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echo -e "\n${DEFAULT_FG}${BOLD}Welcome to DocsGPT Setup!${NC}"
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echo -e "${DEFAULT_FG}How would you like to proceed?${NC}"
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echo -e "${YELLOW}1) Use DocsGPT Public API Endpoint (simple and free, uses pre-built Docker images from Docker Hub for fastest setup)${NC}"
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echo -e "${YELLOW}2) Serve Local (with Ollama)${NC}"
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echo -e "${YELLOW}3) Connect Local Inference Engine${NC}"
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echo -e "${YELLOW}4) Connect Cloud API Provider${NC}"
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echo -e "${YELLOW}5) Advanced: Build images locally (for developers)${NC}"
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echo
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echo -e "${DEFAULT_FG}By default, DocsGPT uses pre-built images from Docker Hub for a fast, reliable, and consistent experience. This avoids local build errors and speeds up onboarding. Advanced users can choose to build images locally if needed.${NC}"
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echo
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read -p "$(echo -e "${DEFAULT_FG}Choose option (1-5): ${NC}")" main_choice
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}
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# Function to prompt for Local Inference Engine options
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prompt_local_inference_engine_options() {
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clear
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echo -e "\n${DEFAULT_FG}${BOLD}Connect Local Inference Engine${NC}"
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echo -e "${DEFAULT_FG}Choose your local inference engine:${NC}"
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echo -e "${YELLOW}1) LLaMa.cpp${NC}"
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echo -e "${YELLOW}2) Ollama${NC}"
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echo -e "${YELLOW}3) Text Generation Inference (TGI)${NC}"
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echo -e "${YELLOW}4) SGLang${NC}"
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echo -e "${YELLOW}5) vLLM${NC}"
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echo -e "${YELLOW}6) Aphrodite${NC}"
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echo -e "${YELLOW}7) FriendliAI${NC}"
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echo -e "${YELLOW}8) LMDeploy${NC}"
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echo -e "${YELLOW}b) Back to Main Menu${NC}"
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echo
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read -p "$(echo -e "${DEFAULT_FG}Choose option (1-8, or b): ${NC}")" engine_choice
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}
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# Function to prompt for Cloud API Provider options
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prompt_cloud_api_provider_options() {
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clear
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echo -e "\n${DEFAULT_FG}${BOLD}Connect Cloud API Provider${NC}"
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echo -e "${DEFAULT_FG}Choose your Cloud API Provider:${NC}"
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echo -e "${YELLOW}1) OpenAI${NC}"
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echo -e "${YELLOW}2) Google (Vertex AI, Gemini)${NC}"
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echo -e "${YELLOW}3) Anthropic (Claude)${NC}"
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echo -e "${YELLOW}4) Groq${NC}"
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echo -e "${YELLOW}5) HuggingFace Inference API${NC}"
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echo -e "${YELLOW}6) Azure OpenAI${NC}"
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echo -e "${YELLOW}7) Novita${NC}"
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echo -e "${YELLOW}b) Back to Main Menu${NC}"
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echo
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read -p "$(echo -e "${DEFAULT_FG}Choose option (1-6, or b): ${NC}")" provider_choice
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}
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# Function to prompt for Ollama CPU/GPU options
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prompt_ollama_options() {
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clear
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echo -e "\n${DEFAULT_FG}${BOLD}Serve Local with Ollama${NC}"
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echo -e "${DEFAULT_FG}Choose how to serve Ollama:${NC}"
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echo -e "${YELLOW}1) CPU${NC}"
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echo -e "${YELLOW}2) GPU${NC}"
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echo -e "${YELLOW}b) Back to Main Menu${NC}"
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echo
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read -p "$(echo -e "${DEFAULT_FG}Choose option (1-2, or b): ${NC}")" ollama_choice
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}
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# 1) Use DocsGPT Public API Endpoint (simple and free)
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use_docs_public_api_endpoint() {
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echo -e "\n${NC}Setting up DocsGPT Public API Endpoint...${NC}"
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echo "LLM_PROVIDER=docsgpt" > "$ENV_FILE"
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echo "VITE_API_STREAMING=true" >> "$ENV_FILE"
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echo -e "${GREEN}.env file configured for DocsGPT Public API.${NC}"
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check_and_start_docker
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echo -e "\n${NC}Starting Docker Compose...${NC}"
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docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" pull && docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" up -d
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docker_compose_status=$? # Capture exit status of docker compose
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echo "Docker Compose Exit Status: $docker_compose_status"
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if [ "$docker_compose_status" -ne 0 ]; then
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echo -e "\n${RED}${BOLD}Error starting Docker Compose. Please ensure Docker Compose is installed and in your PATH.${NC}"
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echo -e "${RED}Refer to Docker documentation for installation instructions: https://docs.docker.com/compose/install/${NC}"
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exit 1 # Indicate failure and EXIT SCRIPT
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fi
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echo -e "\n${GREEN}DocsGPT is now running on http://localhost:5173${NC}"
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echo -e "${YELLOW}You can stop the application by running: docker compose -f \"${COMPOSE_FILE}\" down${NC}"
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}
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# 2) Serve Local (with Ollama)
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serve_local_ollama() {
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local ollama_choice model_name
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local docker_compose_file_suffix
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local model_name_prompt
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local default_model="llama3.2:1b"
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get_model_name_ollama() {
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read -p "$(echo -e "${DEFAULT_FG}Enter Ollama Model Name (leave empty for default: ${default_model} (1.3GB)): ${NC}")" model_name_input
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if [ -z "$model_name_input" ]; then
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model_name="$default_model" # Set default model if input is empty
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else
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model_name="$model_name_input" # Use user-provided model name
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fi
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}
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while true; do
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clear
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prompt_ollama_options
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case "$ollama_choice" in
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1) # CPU
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docker_compose_file_suffix="cpu"
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get_model_name_ollama
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break ;;
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2) # GPU
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echo -e "\n${YELLOW}For this option to work correctly you need to have a supported GPU and configure Docker to utilize it.${NC}"
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echo -e "${YELLOW}Refer to: https://hub.docker.com/r/ollama/ollama for more information.${NC}"
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read -p "$(echo -e "${DEFAULT_FG}Continue with GPU setup? (y/b): ${NC}")" confirm_gpu
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case "$confirm_gpu" in
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y|Y)
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docker_compose_file_suffix="gpu"
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get_model_name_ollama
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break ;;
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b|B) clear; return ;; # Back to Main Menu
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*) echo -e "\n${RED}Invalid choice. Please choose y or b.${NC}" ; sleep 1 ;;
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esac
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;;
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b|B) clear; return ;; # Back to Main Menu
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*) echo -e "\n${RED}Invalid choice. Please choose 1-2, or b.${NC}" ; sleep 1 ;;
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esac
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done
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echo -e "\n${NC}Configuring for Ollama ($(echo "$docker_compose_file_suffix" | tr '[:lower:]' '[:upper:]'))...${NC}" # Using tr for uppercase - more compatible
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echo "API_KEY=xxxx" > "$ENV_FILE" # Placeholder API Key
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echo "LLM_PROVIDER=openai" >> "$ENV_FILE"
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echo "LLM_NAME=$model_name" >> "$ENV_FILE"
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echo "VITE_API_STREAMING=true" >> "$ENV_FILE"
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echo "OPENAI_BASE_URL=http://ollama:11434/v1" >> "$ENV_FILE"
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echo "EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2" >> "$ENV_FILE"
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echo -e "${GREEN}.env file configured for Ollama ($(echo "$docker_compose_file_suffix" | tr '[:lower:]' '[:upper:]')${NC}${GREEN}).${NC}"
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check_and_start_docker
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local compose_files=(
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-f "${COMPOSE_FILE}"
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-f "$(dirname "${COMPOSE_FILE}")/optional/docker-compose.optional.ollama-${docker_compose_file_suffix}.yaml"
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)
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echo -e "\n${NC}Starting Docker Compose with Ollama (${docker_compose_file_suffix})...${NC}"
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docker compose --env-file "${ENV_FILE}" "${compose_files[@]}" pull
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docker compose --env-file "${ENV_FILE}" "${compose_files[@]}" up -d
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docker_compose_status=$?
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echo "Docker Compose Exit Status: $docker_compose_status" # Debug output
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if [ "$docker_compose_status" -ne 0 ]; then
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echo -e "\n${RED}${BOLD}Error starting Docker Compose. Please ensure Docker Compose is installed and in your PATH.${NC}"
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echo -e "${RED}Refer to Docker documentation for installation instructions: https://docs.docker.com/compose/install/${NC}"
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exit 1 # Indicate failure and EXIT SCRIPT
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fi
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echo "Waiting for Ollama container to be ready..."
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OLLAMA_READY=false
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while ! $OLLAMA_READY; do
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CONTAINER_STATUS=$(docker compose "${compose_files[@]}" ps --services --filter "status=running" --format '{{.Service}}')
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if [[ "$CONTAINER_STATUS" == *"ollama"* ]]; then # Check if 'ollama' service is in running services
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OLLAMA_READY=true
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echo "Ollama container is running."
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else
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echo "Ollama container not yet ready, waiting..."
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sleep 5
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fi
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done
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echo "Pulling $model_name model for Ollama..."
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docker compose --env-file "${ENV_FILE}" "${compose_files[@]}" exec -it ollama ollama pull "$model_name"
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echo -e "\n${GREEN}DocsGPT is now running with Ollama (${docker_compose_file_suffix}) on http://localhost:5173${NC}"
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printf -v compose_files_escaped "%q " "${compose_files[@]}"
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echo -e "${YELLOW}You can stop the application by running: docker compose ${compose_files_escaped}down${NC}"
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}
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# 3) Connect Local Inference Engine
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connect_local_inference_engine() {
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local engine_choice
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local model_name_prompt model_name openai_base_url
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get_model_name() {
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read -p "$(echo -e "${DEFAULT_FG}Enter Model Name (leave empty to set later as None): ${NC}")" model_name
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if [ -z "$model_name" ]; then
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model_name="None"
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fi
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}
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while true; do
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clear
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prompt_local_inference_engine_options
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case "$engine_choice" in
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1) # LLaMa.cpp
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engine_name="LLaMa.cpp"
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openai_base_url="http://host.docker.internal:8000/v1"
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get_model_name
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break ;;
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2) # Ollama
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engine_name="Ollama"
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openai_base_url="http://host.docker.internal:11434/v1"
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get_model_name
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break ;;
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3) # TGI
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engine_name="TGI"
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openai_base_url="http://host.docker.internal:8080/v1"
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get_model_name
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break ;;
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4) # SGLang
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engine_name="SGLang"
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openai_base_url="http://host.docker.internal:30000/v1"
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get_model_name
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break ;;
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5) # vLLM
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engine_name="vLLM"
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openai_base_url="http://host.docker.internal:8000/v1"
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get_model_name
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break ;;
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6) # Aphrodite
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engine_name="Aphrodite"
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openai_base_url="http://host.docker.internal:2242/v1"
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get_model_name
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break ;;
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7) # FriendliAI
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engine_name="FriendliAI"
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openai_base_url="http://host.docker.internal:8997/v1"
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get_model_name
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break ;;
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8) # LMDeploy
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engine_name="LMDeploy"
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openai_base_url="http://host.docker.internal:23333/v1"
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get_model_name
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break ;;
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b|B) clear; return ;; # Back to Main Menu
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*) echo -e "\n${RED}Invalid choice. Please choose 1-8, or b.${NC}" ; sleep 1 ;;
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esac
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done
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echo -e "\n${NC}Configuring for Local Inference Engine: ${BOLD}${engine_name}...${NC}"
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echo "API_KEY=None" > "$ENV_FILE"
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echo "LLM_PROVIDER=openai" >> "$ENV_FILE"
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echo "LLM_NAME=$model_name" >> "$ENV_FILE"
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echo "VITE_API_STREAMING=true" >> "$ENV_FILE"
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echo "OPENAI_BASE_URL=$openai_base_url" >> "$ENV_FILE"
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echo "EMBEDDINGS_NAME=huggingface_sentence-transformers/all-mpnet-base-v2" >> "$ENV_FILE"
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echo -e "${GREEN}.env file configured for ${BOLD}${engine_name}${NC}${GREEN} with OpenAI API format.${NC}"
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echo -e "${YELLOW}Note: MODEL_NAME is set to '${BOLD}$model_name${NC}${YELLOW}'. You can change it later in the .env file.${NC}"
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check_and_start_docker
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echo -e "\n${NC}Starting Docker Compose...${NC}"
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docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" pull && docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" up -d
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docker_compose_status=$?
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echo "Docker Compose Exit Status: $docker_compose_status" # Debug output
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if [ "$docker_compose_status" -ne 0 ]; then
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echo -e "\n${RED}${BOLD}Error starting Docker Compose. Please ensure Docker Compose is installed and in your PATH.${NC}"
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echo -e "${RED}Refer to Docker documentation for installation instructions: https://docs.docker.com/compose/install/${NC}"
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exit 1 # Indicate failure and EXIT SCRIPT
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fi
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echo -e "\n${GREEN}DocsGPT is now configured to connect to ${BOLD}${engine_name}${NC}${GREEN} at ${BOLD}$openai_base_url${NC}"
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echo -e "${YELLOW}Ensure your ${BOLD}${engine_name} inference server is running at that address${NC}"
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echo -e "\n${GREEN}DocsGPT is running at http://localhost:5173${NC}"
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echo -e "${YELLOW}You can stop the application by running: docker compose -f \"${COMPOSE_FILE}\" down${NC}"
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}
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# 4) Connect Cloud API Provider
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connect_cloud_api_provider() {
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local provider_choice api_key llm_provider
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local setup_result # Variable to store the return status
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get_api_key() {
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echo -e "${YELLOW}Your API key will be stored locally in the .env file and will not be sent anywhere else${NC}"
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read -p "$(echo -e "${DEFAULT_FG}Please enter your API key: ${NC}")" api_key
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}
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while true; do
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clear
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prompt_cloud_api_provider_options
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case "$provider_choice" in
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1) # OpenAI
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provider_name="OpenAI"
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llm_provider="openai"
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model_name="gpt-4o"
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get_api_key
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break ;;
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2) # Google
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provider_name="Google (Vertex AI, Gemini)"
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llm_provider="google"
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model_name="gemini-2.0-flash"
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get_api_key
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break ;;
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3) # Anthropic
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provider_name="Anthropic (Claude)"
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llm_provider="anthropic"
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model_name="claude-3-5-sonnet-latest"
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get_api_key
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break ;;
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4) # Groq
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provider_name="Groq"
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llm_provider="groq"
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model_name="llama-3.1-8b-instant"
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get_api_key
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break ;;
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5) # HuggingFace Inference API
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provider_name="HuggingFace Inference API"
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llm_provider="huggingface"
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model_name="meta-llama/Llama-3.1-8B-Instruct"
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get_api_key
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break ;;
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6) # Azure OpenAI
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provider_name="Azure OpenAI"
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llm_provider="azure_openai"
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model_name="gpt-4o"
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get_api_key
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break ;;
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7) # Novita
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provider_name="Novita"
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llm_provider="novita"
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model_name="deepseek/deepseek-r1"
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get_api_key
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break ;;
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b|B) clear; return ;; # Clear screen and Back to Main Menu
|
|
*) echo -e "\n${RED}Invalid choice. Please choose 1-6, or b.${NC}" ; sleep 1 ;;
|
|
esac
|
|
done
|
|
|
|
echo -e "\n${NC}Configuring for Cloud API Provider: ${BOLD}${provider_name}...${NC}"
|
|
echo "API_KEY=$api_key" > "$ENV_FILE"
|
|
echo "LLM_PROVIDER=$llm_provider" >> "$ENV_FILE"
|
|
echo "LLM_NAME=$model_name" >> "$ENV_FILE"
|
|
echo "VITE_API_STREAMING=true" >> "$ENV_FILE"
|
|
echo -e "${GREEN}.env file configured for ${BOLD}${provider_name}${NC}${GREEN}.${NC}"
|
|
|
|
check_and_start_docker
|
|
|
|
echo -e "\n${NC}Starting Docker Compose...${NC}"
|
|
docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" pull && docker compose --env-file "${ENV_FILE}" -f "${COMPOSE_FILE}" up -d
|
|
docker_compose_status=$?
|
|
|
|
echo "Docker Compose Exit Status: $docker_compose_status" # Debug output
|
|
|
|
if [ "$docker_compose_status" -ne 0 ]; then
|
|
echo -e "\n${RED}${BOLD}Error starting Docker Compose. Please ensure Docker Compose is installed and in your PATH.${NC}"
|
|
echo -e "${RED}Refer to Docker documentation for installation instructions: https://docs.docker.com/compose/install/${NC}"
|
|
exit 1 # Indicate failure and EXIT SCRIPT
|
|
fi
|
|
|
|
echo -e "\n${GREEN}DocsGPT is now configured to use ${BOLD}${provider_name}${NC}${GREEN} on http://localhost:5173${NC}"
|
|
echo -e "${YELLOW}You can stop the application by running: docker compose -f \"${COMPOSE_FILE}\" down${NC}"
|
|
}
|
|
|
|
|
|
# Main script execution
|
|
animate_dino
|
|
|
|
|
|
while true; do # Main menu loop
|
|
clear # Clear screen before showing main menu again
|
|
prompt_main_menu
|
|
|
|
case $main_choice in
|
|
1) # Use DocsGPT Public API Endpoint (Docker Hub images)
|
|
COMPOSE_FILE="$(dirname "$(readlink -f "$0")")/deployment/docker-compose-hub.yaml"
|
|
use_docs_public_api_endpoint
|
|
break ;;
|
|
2) # Serve Local (with Ollama)
|
|
serve_local_ollama
|
|
break ;;
|
|
3) # Connect Local Inference Engine
|
|
connect_local_inference_engine
|
|
break ;;
|
|
4) # Connect Cloud API Provider
|
|
connect_cloud_api_provider
|
|
break ;;
|
|
5) # Advanced: Build images locally
|
|
echo -e "\n${YELLOW}You have selected to build images locally. This is recommended for developers or if you want to test local changes.${NC}"
|
|
COMPOSE_FILE="$COMPOSE_FILE_LOCAL"
|
|
use_docs_public_api_endpoint
|
|
break ;;
|
|
*)
|
|
echo -e "\n${RED}Invalid choice. Please choose 1-5.${NC}" ; sleep 1 ;;
|
|
esac
|
|
done
|
|
|
|
echo -e "\n${GREEN}${BOLD}DocsGPT Setup Complete.${NC}"
|
|
|
|
exit 0 |