SHX-setup.sh

#!/bin/bash
set -euo pipefail
IFS=$'\n\t'

# === ENV VARIABLES ===
export HF_HOME="$HOME/.cache/huggingface"
export MODEL_NAME="EleutherAI/gpt-neo-1.3B"
export WORK_DIR="$HOME/dev/shx-hfspace"
export VENV_DIR="$WORK_DIR/shx-venv"
export LOG_FILE="$WORK_DIR/shx-setup.log"
export CONFIG_FILE="$WORK_DIR/shx-config.json"
export HF_SPACE_NAME="SHX-Auto"
export HF_USERNAME="subatomicERROR"

# === COLORS ===
RED="\e[91m"
GREEN="\e[92m"
YELLOW="\e[93m"
CYAN="\e[96m"
RESET="\e[0m"

# === SELF-HEAL ===
trap 'echo -e "\n${RED}❌ Error occurred at line $LINENO: $BASH_COMMAND${RESET}" >> "$LOG_FILE"; echo -e "${YELLOW}🔧 Triggering SHX Self-Healing...${RESET}"; shx_self_heal $LINENO "$BASH_COMMAND"' ERR

shx_self_heal() {
    local line=$1
    local cmd="$2"
    echo -e "${CYAN}🛠 Self-Healing (Line $line | Command: $cmd)${RESET}"

    if [[ "$cmd" == *"pip install"* ]]; then
        echo -e "${YELLOW}🔁 Retrying pip install with --no-cache-dir...${RESET}"
        pip install --no-cache-dir transformers torch gradio git-lfs huggingface_hub || true
    fi

    if [[ "$cmd" == *"huggingface-cli login"* ]]; then
        echo -e "${YELLOW}🔁 Retrying interactive Hugging Face login...${RESET}"
        huggingface-cli login || true
    fi

    if [[ "$cmd" == *"git push"* ]]; then
        echo -e "${YELLOW}🔁 Retrying git push...${RESET}"
        git push -u origin main || true
    fi

    echo -e "${GREEN}✅ Self-Heal Complete. Please rerun if needed.${RESET}"
    exit 1
}

# === START ===
echo -e "${CYAN}\n🌌 [SHX] Launching Hyper-Intelligent Setup...\n${RESET}"

# === CLEAN + VENV ===
echo -e "${CYAN}🧹 Preparing Virtual Environment...${RESET}"
rm -rf "$VENV_DIR"
python3 -m venv "$VENV_DIR"
source "$VENV_DIR/bin/activate"
echo -e "${GREEN}✅ Venv activated at $VENV_DIR${RESET}"

# === DEPENDENCIES ===
echo -e "${CYAN}\n📦 Installing Python packages...${RESET}"
pip install --upgrade pip
pip install --no-cache-dir transformers torch gradio git-lfs huggingface_hub

# === CHECK TORCH ===
echo -e "${CYAN}🧠 Verifying PyTorch...\n${RESET}"
PYTORCH_VERSION=$(python3 -c "import torch; print(torch.__version__)")
echo -e "${GREEN}✅ PyTorch: $PYTORCH_VERSION${RESET}"

# === AUTHENTICATION ===
echo -e "\n${CYAN}🔑 Enter your Hugging Face token:${RESET}"
read -s hf_token
huggingface-cli login --token "$hf_token"
export HF_TOKEN="$hf_token"

whoami_output=$(huggingface-cli whoami)
echo -e "${GREEN}✅ Logged in as: $whoami_output${RESET}"

# === MODEL SELECTION ===
echo -e "\n${CYAN}🔧 Select a model (default: EleutherAI/gpt-neo-1.3B):${RESET}"
read -p "Model name: " selected_model
MODEL_NAME=${selected_model:-EleutherAI/gpt-neo-1.3B}
export HF_MODEL="$MODEL_NAME"

# === CLEAR BROKEN CACHE ===
echo -e "${CYAN}\n🔄 Clearing broken cache for $MODEL_NAME...${RESET}"
rm -rf ~/.cache/huggingface/hub/models--EleutherAI--gpt-neo-1.3B

# === MODEL DOWNLOAD ===
echo -e "${CYAN}\n🚀 Downloading $MODEL_NAME Model (via GPTNeoForCausalLM)...\n${RESET}"
python3 - <<EOF
from transformers import GPT2Tokenizer, GPTNeoForCausalLM
print("🔍 Downloading tokenizer & model (GPTNeoForCausalLM)...")
tokenizer = GPT2Tokenizer.from_pretrained("$MODEL_NAME")
tokenizer.pad_token = tokenizer.eos_token
model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME")
print("✅ Model ready (GPTNeoForCausalLM).")
EOF

# === GRADIO APP ===
echo -e "${CYAN}🖥️ Writing Gradio Interface...${RESET}"
cat <<EOF > "$WORK_DIR/app.py"
import gradio as gr
from transformers import GPT2Tokenizer, GPTNeoForCausalLM
import torch
import json
import os

# Load configuration
config_file = "shx-config.json"
with open(config_file, "r") as f:
    config = json.load(f)

tokenizer = GPT2Tokenizer.from_pretrained(config["model_name"])
tokenizer.pad_token = tokenizer.eos_token
model = GPTNeoForCausalLM.from_pretrained(config["model_name"])

chat_history = []

def shx_terminal(prompt, history):
    inputs = tokenizer(prompt, return_tensors="pt", padding=True)
    input_ids = inputs.input_ids
    attention_mask = inputs.attention_mask
    pad_token_id = tokenizer.eos_token_id

    try:
        with torch.no_grad():
            output = model.generate(
                input_ids=input_ids,
                attention_mask=attention_mask,
                pad_token_id=pad_token_id,
                max_length=config["max_length"],
                temperature=config["temperature"],
                top_k=config["top_k"],
                top_p=config["top_p"],
                do_sample=True
            )
        response = tokenizer.decode(output[0], skip_special_tokens=True)
        chat_history.append((prompt, response))
        return response, chat_history
    except Exception as e:
        return f"⚠️ SHX caught an error during generation:\\n{str(e)}", chat_history

with gr.Blocks(css="body { background-color: black; color: #00FF41; font-family: monospace; }") as demo:
    gr.Markdown("## 🤖 **SHX-Auto: Multiversal System Builder**")
    with gr.Row():
        with gr.Column():
            input_box = gr.Textbox(label="Your Command")
            output_box = gr.Textbox(label="SHX Response")
            run_btn = gr.Button("Run")
            run_btn.click(shx_terminal, inputs=[input_box, gr.State(chat_history)], outputs=[output_box, gr.State(chat_history)])
        with gr.Column():
            chat_box = gr.Chatbot(label="Chat History")
            chat_box.update(chat_history)

demo.launch()
EOF

# === REQUIREMENTS & README ===
echo -e "${CYAN}📦 Writing requirements.txt and README.md...${RESET}"
cat <<EOF > "$WORK_DIR/requirements.txt"
transformers
torch
gradio
git-lfs
huggingface_hub
EOF

cat <<EOF > "$WORK_DIR/README.md"
---
title: SHX-Auto GPT Space
emoji: 🧠
colorFrom: gray
colorTo: blue
sdk: gradio
sdk_version: "3.50.2"
app_file: app.py
pinned: true
---

# 🚀 SHX-Auto: Hyperintelligent Neural Interface

> Built on **[EleutherAI/gpt-neo-1.3](https://huggingface.co/EleutherAI/gpt-neo-1.3)**  
> Powered by ⚡ Gradio + Hugging Face Spaces + Quantum-AI Concepts

---

## 🧬 Purpose

SHX-Auto is a **self-evolving AI agent** designed to generate full-stack solutions, SaaS, and code with real-time inference using the `EleutherAI/gpt-neo-1.3` model. It is a powerful tool for quantum-native developers, enabling them to build and automate complex systems with ease.

## 🧠 Model Used

- **Model:** [`EleutherAI/gpt-neo-1.3`](https://huggingface.co/EleutherAI/gpt-neo-1.3)
- **Architecture:** Transformer Decoder
- **Training Data:** The Pile (825GB diverse dataset)
- **Use Case:** Conversational AI, Code Generation, SaaS Bootstrapping

---

## 🎮 How to Use

Interact with SHX below 👇  
Type in English — it auto-generates:

- ✅ Python Code
- ✅ Websites / HTML / CSS / JS
- ✅ SaaS / APIs
- ✅ AI Agent Logic

---

## ⚙️ Technologies

- ⚛️ GPT-Neo 1.3B
- 🧠 SHX Agent Core
- 🌀 Gradio SDK 3.50.2
- 🐍 Python 3.10
- 🌐 Hugging Face Spaces

---

## 🚀 Getting Started

### Overview

SHX-Auto is a powerful, GPT-Neo-based terminal agent designed to assist quantum-native developers in building and automating complex systems. With its advanced natural language processing capabilities, SHX-Auto can understand and execute a wide range of commands, making it an indispensable tool for developers.

### Features

- **Advanced NLP**: Utilizes the EleutherAI/gpt-neo-1.3 model for sophisticated language understanding and generation.
- **Gradio Interface**: User-friendly interface for interacting with the model.
- **Customizable Configuration**: Easily adjust model parameters such as temperature, top_k, and top_p.
- **Real-time Feedback**: Get immediate responses to your commands and see the chat history.

### Usage

1. **Initialize the Space**:
   - Clone the repository or create a new Space on Hugging Face.
   - Ensure you have the necessary dependencies installed.

2. **Run the Application**:
   - Use the Gradio interface to interact with SHX-Auto.
   - Enter your commands in the input box and click "Run" to get responses.

### Configuration

- **Model Name**: `EleutherAI/gpt-neo-1.3`
- **Max Length**: 150
- **Temperature**: 0.7
- **Top K**: 50
- **Top P**: 0.9

### Example

```python
# Example command
prompt = "Create a simple web application with a form to collect user data."
response = shx_terminal(prompt)
print(f"🤖 SHX Response: {response}")

Final Steps

    Initialize git in this folder:

    git init

    Commit your SHX files:

    git add . && git commit -m "Initial SHX commit"

    Create the Space manually (choose SDK: gradio/static/etc):

    huggingface-cli repo create SHX-Auto --type space --space-sdk gradio

    Add remote:

    git remote add origin https://huggingface.co/spaces/$HF_USERNAME/SHX-Auto

    Push your space:

    git branch -M main && git push -u origin main

🌐 After that, visit: https://huggingface.co/spaces/$HF_USERNAME/SHX-Auto

SHX interface will now be live on Hugging Face. HAPPY CODING!

For more information and support, visit our GitHub repository:
https://github.com/subatomicERROR
EOF
=== CONFIGURATION FILE ===

echo -e "CYAN⚙®Writingconfigurationfile...{CYAN}⚙️ Writing configuration file...CYAN⚙R◯Writingconfigurationfile...{RESET}"
cat <<EOF > "WORK_DIR/shx-config.json" { "model_name": "MODEL_NAME",
"max_length": 150,
"temperature": 0.7,
"top_k": 50,
"top_p": 0.9
}
EOF
=== FINAL TEST ===

echo -e "CYAN\n🧪RunningFinalTest...{CYAN}\n🧪 Running Final Test...CYAN\n🧪RunningFinalTest...{RESET}"
python3 - <<EOF
from transformers import GPT2Tokenizer, GPTNeoForCausalLM
import json
Load configuration

config_file = "shx-config.json"
with open(config_file, "r") as f:
config = json.load(f)

tokenizer = GPT2Tokenizer.from_pretrained(config["model_name"])
tokenizer.pad_token = tokenizer.eos_token
model = GPTNeoForCausalLM.from_pretrained(config["model_name"])
prompt = "SHX is"
inputs = tokenizer(prompt, return_tensors="pt", padding=True)
output = model.generate(
input_ids=inputs.input_ids,
attention_mask=inputs.attention_mask,
pad_token_id=tokenizer.eos_token_id,
max_length=config["max_length"],
temperature=config["temperature"],
top_k=config["top_k"],
top_p=config["top_p"],
do_sample=True
)
print("🧠 SHX Test Output:", tokenizer.decode(output[0], skip_special_tokens=True))
EOF

echo -e "\nGREEN✅SHXisFULLYONLINEandOPERATIONAL(with{GREEN}✅ SHX is FULLY ONLINE and OPERATIONAL (withGREEN✅SHXisFULLYONLINEandOPERATIONAL(withMODEL_NAME)!RESET"echo−e"{RESET}" echo -e "RESET"echo−e"{CYAN}🌐 Access: https://huggingface.co/spaces/$HF_USERNAME/$HF_SPACE_NAME${RESET}"
=== AI-DRIVEN AUTOMATION ===

echo -e "CYAN\n🤖InitializingAI−DrivenAutomation...{CYAN}\n🤖 Initializing AI-Driven Automation...CYAN\n🤖InitializingAI−DrivenAutomation...{RESET}"
cat <<EOF > "$WORK_DIR/shx-ai.py"
import json
import subprocess
import os
Load configuration

config_file = "shx-config.json"
with open(config_file, "r") as f:
config = json.load(f)

def run_command(command):
try:
result = subprocess.run(command, shell=True, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
return result.stdout
except subprocess.CalledProcessError as e:
return f"⚠️ Error: {e.stderr}"

def shx_ai(prompt):
# Generate response using the model
response = run_command(f"python3 app.py --prompt '{prompt}'")
return response
Example usage

if name == "main":
prompt = "Create a simple web application with a form to collect user data."
response = shx_ai(prompt)
print(f"🤖 SHX Response: {response}")
EOF

echo -e "GREEN✅AI−DrivenAutomationInitialized.Readytobuildalmostanything!{GREEN}✅ AI-Driven Automation Initialized. Ready to build almost anything!GREEN✅AI−DrivenAutomationInitialized.Readytobuildalmostanything!{RESET}"
=== FINAL MESSAGE ===

echo ""
echo "🚀 ☁️ Boom your SHX is ready! And now fully configured."
echo ""
echo "✅ PyTorch: PYTORCHVERSION"echo"✅Model:PYTORCH_VERSION" echo "✅ Model:PYTORCHV​ERSION"echo"✅Model:HF_MODEL"
echo "✅ Hugging Face Token saved for: HF_USERNAME" echo "" echo "🛠️ Now to push your SHX Space manually to Hugging Face, follow these final steps:" echo "" echo "1. Initialize git in this folder:" echo " git init" echo "" echo "2. Commit your SHX files:" echo " git add . && git commit -m \"Initial SHX commit\"" echo "" echo "3. Create the Space manually (choose SDK: gradio/static/etc):" echo " huggingface-cli repo create SHX-Auto --type space --space-sdk gradio" echo "" echo "4. Add remote:" echo " git remote add origin https://huggingface.co/spaces/HF_USERNAME/SHX-Auto"
echo ""
echo "5. Push your space:"
echo " git branch -M main && git push -u origin main"
echo ""
echo "🌐 After that, visit: https://huggingface.co/spaces/$HF_USERNAME/SHX-Auto"
echo ""
echo "SHX interface will now be live on Hugging Face. HAPPY CODING!"
echo ""
echo "For more information and support, visit our GitHub repository:"
echo "https://github.com/subatomicERROR"
echo ""