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Configuration error
Configuration error
| 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:PYTORCHVERSION"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 "" |