master

#!/usr/bin/env bash
# ai.sh v50 — Hyper-Reasoning AI Orchestrator
# Local + Deepseek cloud, CLI + file-processing + dashboard
set -euo pipefail
IFS=$'\n\t'

BASE_DIR="$HOME/_/ai"
TMP_DIR="$BASE_DIR/tmp"
DB_FILE="$BASE_DIR/db/qbits.db"
mkdir -p "$TMP_DIR" "$(dirname "$DB_FILE")"

# Models
LOCAL_MODELS=("core" "loop" "2244" "coin" "code")
CLOUD_MODEL="deepseek-v3.1:671b-cloud"

# Defaults
TEMP_FACTOR="${TEMP_FACTOR:-0.5}"
RECUR_DEPTH="${RECUR_DEPTH:-5}"
MAX_LOOP="${MAX_LOOP:-10}"

# --- SQLite3 Setup ---
sqlite3 "$DB_FILE" "CREATE TABLE IF NOT EXISTS qbits (
    agent TEXT,
    prompt TEXT,
    hash TEXT,
    iteration INTEGER,
    response TEXT,
    timestamp REAL,
    temp REAL
);"

# --- Utility Functions ---
hash_prompt(){ date +%s%N | sha256sum | cut -c1-64; }

log_qbit(){
    local agent="$1" prompt="$2" hash="$3" iter="$4" resp="$5"
    sqlite3 "$DB_FILE" \
    "INSERT INTO qbits (agent,prompt,hash,iteration,response,timestamp,temp) VALUES ('$agent','$prompt','$hash',$iter,'$resp',$(date +%s),$TEMP_FACTOR);"
}

# --- File Processor Functions ---
scan_dir() {
    local path="$1"
    find "$path" -type f
}

read_file() {
    local file="$1"
    cat "$file"
}

backup_file() {
    local file="$1"
    cp "$file" "$file.bak"
}

replace_in_file() {
    local file="$1" search="$2" replace="$3"
    sed -i "s|$search|$replace|g" "$file"
}

process_files() {
    local path="$1"
    for f in $(scan_dir "$path"); do
        backup_file "$f"
        # example: replace placeholder with prompt info
        replace_in_file "$f" "PLACEHOLDER" "$PROMPT_HASH"
        # log to SQLite3
        sqlite3 "$DB_FILE" "INSERT INTO qbits (agent,prompt,hash,iteration,response,timestamp,temp) VALUES ('fileproc','$f','$PROMPT_HASH',0,'processed',$(date +%s),$TEMP_FACTOR);"
    done
}

# --- Python Neuro ---
run_python_neuro(){
    local prompt="$1"
    local hash=$(hash_prompt)
    python3 "$BASE_DIR/ai.py" "$prompt" "$hash" "$TEMP_FACTOR" "$RECUR_DEPTH" &
    PID_PY=$!
}

# --- Node.js Crew AI ---
run_node_ai(){
    local prompt="$1" model="$2"
    node "$BASE_DIR/ai.js" "$prompt" "$model" &
}

# --- Deepseek Cloud ---
run_deepseek_cloud(){
    local prompt="$1"
    node -e "
        import fetch from 'node-fetch';
        const res=await fetch('http://localhost:11434/api/generate',{
            method:'POST',
            headers:{'Content-Type':'application/json'},
            body:JSON.stringify({model:'$CLOUD_MODEL',prompt:'$prompt',stream:true})
        });
        if(!res.ok){console.error('[CLOUD] Stream failed',res.status);}
        else{console.log('[CLOUD] Stream complete.');}
    " &
    PID_CLOUD=$!
}

# --- Main ---
main(){
    local prompt="${*:-}"
    [[ -z "$prompt" ]] && read -rp "Enter human prompt: " prompt
    PROMPT_HASH=$(hash_prompt)

    # Parallel execution
    run_python_neuro "$prompt"
    for model in "${LOCAL_MODELS[@]}"; do run_node_ai "$prompt" "$model"; done
    run_deepseek_cloud "$prompt"

    # File-processing
    process_files "$BASE_DIR"

    # Wait
    wait $PID_PY $PID_CLOUD
    echo "[NEXUS] ✅ Hyper-reasoning complete. JSON/qbits updated in $TMP_DIR and SQLite3 DB."
}

main "$@"