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9da4215d1f25b433d59d0f90aa2661b76058b6dd
DocsGPT/setup.sh

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