Initial SHX commit 🚀 Ready to launch!

.gitignore

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+shx-venv/

README.md

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+# SHX-Auto: Multiversal System Builder
+## 🤯 GPT-Neo-based automation terminal agent for quantum-native devs.
+✨ By: subatomicERROR

SHX-setup.sh

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+#!/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 > "$WORK_DIR/app.py"
+import gradio as gr
+from transformers import GPT2Tokenizer, GPTNeoForCausalLM
+import torch
+import json
+import os
+
+# Load configuration
+with open("$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"
+# SHX-Auto: Multiversal System Builder
+## 🤯 GPT-Neo-based automation terminal agent for quantum-native devs.
+✨ By: subatomicERROR
+EOF
+
+# === CONFIGURATION FILE ===
+echo -e "${CYAN}⚙️ Writing configuration file...${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 "${CYAN}\n🧪 Running Final Test...${RESET}"
+python3 - <<EOF
+from transformers import GPT2Tokenizer, GPTNeoForCausalLM
+import json
+
+# Load configuration
+with open("$WORK_DIR/shx-config.json", "r") as f:
+    config = json.load(f)
+
+tokenizer = GPT2Tokenizer.from_pretrained(config["model_name"])
+tokenizer.pad_token = tokenizer.eos_token
+model = GPTNeoForCausalLM.from_pretrained(config["model_name"])
+prompt = "SHX is"
+inputs = tokenizer(prompt, return_tensors="pt", padding=True)
+output = model.generate(
+    input_ids=inputs.input_ids,
+    attention_mask=inputs.attention_mask,
+    pad_token_id=tokenizer.eos_token_id,
+    max_length=config["max_length"],
+    temperature=config["temperature"],
+    top_k=config["top_k"],
+    top_p=config["top_p"],
+    do_sample=True
+)
+print("🧠 SHX Test Output:", tokenizer.decode(output[0], skip_special_tokens=True))
+EOF
+
+echo -e "\n${GREEN}✅ SHX is FULLY ONLINE and OPERATIONAL (with $MODEL_NAME)!${RESET}"
+echo -e "${CYAN}🌐 Access: https://huggingface.co/spaces/$HF_USERNAME/$HF_SPACE_NAME${RESET}"
+
+# === AI-DRIVEN AUTOMATION ===
+echo -e "${CYAN}\n🤖 Initializing AI-Driven Automation...${RESET}"
+cat <<EOF > "$WORK_DIR/shx-ai.py"
+import json
+import subprocess
+import os
+
+# Load configuration
+with open("$WORK_DIR/shx-config.json", "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 $WORK_DIR/app.py --prompt '{prompt}'")
+    return response
+
+# Example usage
+if __name__ == "__main__":
+    prompt = "Create a simple web application with a form to collect user data."
+    response = shx_ai(prompt)
+    print(f"🤖 SHX Response: {response}")
+EOF
+
+echo -e "${GREEN}✅ AI-Driven Automation Initialized. Ready to build almost anything!${RESET}"
+
+# === FINAL MESSAGE ===
+echo ""
+echo "🚀  ☁️ Boom your SHX is ready! And now fully configured."
+echo ""
+echo "✅ PyTorch: $PYTORCH_VERSION"
+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 ""

app.py

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+import gradio as gr
+from transformers import GPT2Tokenizer, GPTNeoForCausalLM
+import torch
+import json
+import os
+
+# Load configuration
+with open("/home/subatomicERROR/dev/shx-hfspace/shx-config.json", "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()

requirements.txt

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+transformers
+torch
+gradio
+git-lfs
+huggingface_hub

shx-ai.py

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+import json
+import subprocess
+import os
+
+# Load configuration
+with open("/home/subatomicERROR/dev/shx-hfspace/shx-config.json", "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 /home/subatomicERROR/dev/shx-hfspace/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}")

shx-config.json

@@ -0,0 +1,7 @@
+{
+    "model_name": "EleutherAI/gpt-neo-1.3B",
+    "max_length": 150,
+    "temperature": 0.7,
+    "top_k": 50,
+    "top_p": 0.9
+}

shx-error.log

@@ -0,0 +1,2 @@
+
+❌ Error occurred at line 72: git lfs track "*.bin"

shx-setup.log

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+
+❌ Error occurred at line 76: python3 - <<EOF
+from transformers import AutoTokenizer, AutoModelForCausalLM
+print("🔍 Downloading tokenizer & model...")
+tokenizer = AutoTokenizer.from_pretrained("$MODEL_NAME")
+model = AutoModelForCausalLM.from_pretrained("$MODEL_NAME")
+print("✅ Model ready.")
+EOF
+
+
+❌ Error occurred at line 76: python3 - <<EOF
+from transformers import AutoTokenizer, GPTNeoForCausalLM
+print("🔍 Downloading tokenizer & model (GPTNeoForCausalLM)...")
+tokenizer = AutoTokenizer.from_pretrained("$MODEL_NAME")
+model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME")
+print("✅ Model ready (GPTNeoForCausalLM).")
+EOF
+
+
+❌ Error occurred at line 76: python3 - <<EOF
+from transformers import AutoTokenizer, GPTNeoForCausalLM
+print("🔍 Downloading tokenizer & model (GPTNeoForCausalLM)...")
+tokenizer = AutoTokenizer.from_pretrained("$MODEL_NAME")
+model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME")
+print("✅ Model ready (GPTNeoForCausalLM).")
+EOF
+
+
+❌ Error occurred at line 74: python3 - <<EOF
+from transformers import AutoTokenizer, GPTNeoForCausalLM
+print("🔍 Downloading tokenizer & model (GPTNeoForCausalLM)...")
+tokenizer = AutoTokenizer.from_pretrained("$MODEL_NAME")
+model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME")
+print("✅ Model ready (GPTNeoForCausalLM).")
+EOF
+
+
+❌ Error occurred at line 88: python3 - <<EOF
+from transformers import GPT2Tokenizer, GPTNeoForCausalLM
+print("🔍 Downloading tokenizer & model (GPTNeoForCausalLM)...")
+tokenizer = GPT2Tokenizer.from_pretrained("$MODEL_NAME")
+model = GPTNeoForCausalLM.from_pretrained("$MODEL_NAME")
+print("✅ Model ready (GPTNeoForCausalLM).")
+EOF
+
+
+❌ Error occurred at line 182: huggingface-cli repo create "$HF_USERNAME/$HF_SPACE_NAME" --type space --space-sdks gradio
+
+❌ Error occurred at line 182: huggingface-cli repo create "$HF_USERNAME/$HF_SPACE_NAME" --type space
+
+❌ Error occurred at line 182: huggingface-cli repo create "$HF_USERNAME/$HF_SPACE_NAME" --type space
+
+❌ Error occurred at line 182: huggingface-cli repo create "$HF_USERNAME/$HF_SPACE_NAME" --type space
+
+❌ Error occurred at line 182: huggingface-cli repo create "$HF_SPACE_NAME" --type space
+
+❌ Error occurred at line 216: huggingface-cli repo create "$HF_SPACE_NAME" --type space --space-sdk gradio
+
+❌ Error occurred at line 184: python3 - <<EOF
+from transformers import GPT2Tokenizer, GPTNeoForCausalLM
+import json
+
+# Load configuration
+with open("$WORK_DIR/shx-config.json", "r") as f:
+    config = json.load(f)
+
+tokenizer = GPT2Tokenizer.from_pretrained(config["model_name"])
+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"]
+)
+print("🧠 SHX Test Output:", tokenizer.decode(output[0], skip_special_tokens=True))
+EOF
+