Training-simulation1-Polyglot.md

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AQARIONZ — POLYGLOT RESEARCH, SIMULATION & TRAINING ENGINE

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Fully Integrated Domains:

- Audio FFT analysis

- Laser audio modulation (simulated)

- Solar / photodiode reception (simulated)

- Cymatic visualization

- Experiment logging

- Memory system

- Knowledge graph (nodes + relations)

- Creative output tracking

- Full JSON export for training pipelines

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import os import json import uuid import sqlite3 import datetime from typing import Dict, Any

import numpy as np import gradio as gr import matplotlib.pyplot as plt

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CONFIG

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DB_PATH = "aqarionz_system.db" EXPORT_DIR = "exports" os.makedirs(EXPORT_DIR, exist_ok=True)

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DATABASE LAYER

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class AqarionzDB: def init(self, path=DB_PATH): self.conn = sqlite3.connect(path, check_same_thread=False) self.conn.row_factory = sqlite3.Row self._init_schema()

def _init_schema(self):
    c = self.conn.cursor()

    c.execute("""
    CREATE TABLE IF NOT EXISTS experiments (
        id TEXT PRIMARY KEY,
        timestamp TEXT,
        description TEXT,
        parameters TEXT,
        results TEXT
    )
    """)

    c.execute("""
    CREATE TABLE IF NOT EXISTS memories (
        id TEXT PRIMARY KEY,
        timestamp TEXT,
        content TEXT,
        emotion TEXT,
        tags TEXT,
        source TEXT
    )
    """)

    c.execute("""
    CREATE TABLE IF NOT EXISTS creative_outputs (
        id TEXT PRIMARY KEY,
        timestamp TEXT,
        title TEXT,
        content TEXT,
        tags TEXT
    )
    """)

    c.execute("""
    CREATE TABLE IF NOT EXISTS knowledge_nodes (
        id TEXT PRIMARY KEY,
        label TEXT,
        description TEXT,
        tags TEXT,
        created_at TEXT
    )
    """)

    c.execute("""
    CREATE TABLE IF NOT EXISTS relationships (
        id TEXT PRIMARY KEY,
        from_id TEXT,
        to_id TEXT,
        relation TEXT,
        weight REAL,
        created_at TEXT
    )
    """)

    self.conn.commit()

def _now(self):
    return datetime.datetime.utcnow().isoformat()

# ---------------- INSERT ----------------
def log_experiment(self, desc, params, results):
    eid = str(uuid.uuid4())
    self.conn.execute(
        "INSERT INTO experiments VALUES (?, ?, ?, ?, ?)",
        (eid, self._now(), desc, json.dumps(params), json.dumps(results))
    )
    self.conn.commit()
    return eid

def add_memory(self, content, emotion, tags, source="user"):
    mid = str(uuid.uuid4())
    self.conn.execute(
        "INSERT INTO memories VALUES (?, ?, ?, ?, ?, ?)",
        (mid, self._now(), content, emotion, tags, source)
    )
    self.conn.commit()
    return mid

def add_creative(self, title, content, tags):
    cid = str(uuid.uuid4())
    self.conn.execute(
        "INSERT INTO creative_outputs VALUES (?, ?, ?, ?, ?)",
        (cid, self._now(), title, content, tags)
    )
    self.conn.commit()
    return cid

def add_node(self, label, description, tags):
    nid = str(uuid.uuid4())
    self.conn.execute(
        "INSERT INTO knowledge_nodes VALUES (?, ?, ?, ?, ?)",
        (nid, label, description, tags, self._now())
    )
    self.conn.commit()
    return nid

def add_relationship(self, from_id, to_id, relation, weight):
    rid = str(uuid.uuid4())
    self.conn.execute(
        "INSERT INTO relationships VALUES (?, ?, ?, ?, ?, ?)",
        (rid, from_id, to_id, relation, weight, self._now())
    )
    self.conn.commit()
    return rid

# ---------------- EXPORT ----------------
def export_all(self):
    data = {}
    for table in [
        "experiments",
        "memories",
        "creative_outputs",
        "knowledge_nodes",
        "relationships"
    ]:
        rows = self.conn.execute(f"SELECT * FROM {table}").fetchall()
        data[table] = [dict(r) for r in rows]

    path = os.path.join(EXPORT_DIR, f"aqarionz_export_{uuid.uuid4()}.json")
    with open(path, "w", encoding="utf-8") as f:
        json.dump(data, f, indent=2)

    return path

db = AqarionzDB()

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SIGNAL PROCESSING

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def compute_fft(audio, sr): freqs = np.fft.rfftfreq(len(audio), 1 / sr) mags = np.abs(np.fft.rfft(audio)) return freqs, mags

def modulate_laser(audio, depth=0.5): norm = audio / (np.max(np.abs(audio)) + 1e-9) return norm * depth

def simulate_solar(laser_signal): noise = np.random.normal(0, 0.02, size=laser_signal.shape) return laser_signal + noise

def cymatic_plot(freqs, mags): fig, ax = plt.subplots(figsize=(4, 4)) ax.pcolormesh( freqs, np.arange(len(mags)), np.tile(mags, (len(mags), 1)), shading="auto" ) ax.set_title("Cymatic Pattern (Synthetic)") ax.set_xlabel("Frequency (Hz)") ax.set_ylabel("Mode Index") plt.tight_layout() return fig

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INFERENCE HELPERS

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def infer_emotion(text): t = text.lower() if any(w in t for w in ["love", "hope", "joy", "peace"]): return "positive" if any(w in t for w in ["fear", "anger", "sad", "loss"]): return "negative" if any(w in t for w in ["why", "how", "what"]): return "curious" return "neutral"

def auto_tags(text): keys = [] for k in ["system", "signal", "memory", "knowledge", "future", "graph", "audio"]: if k in text.lower(): keys.append(k) return ",".join(keys)

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UI ACTIONS

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def audio_fft_ui(file): if file is None: return None, "No audio provided"

sr, data = file
data = data.astype(np.float32)

freqs, mags = compute_fft(data, sr)
peak = float(freqs[np.argmax(mags)])

eid = db.log_experiment(
    "Audio FFT Analysis",
    {"sample_rate": sr, "length": len(data)},
    {"peak_frequency": peak}
)

fig = cymatic_plot(freqs, mags)
return fig, f"Experiment {eid}\nPeak Frequency: {peak:.2f} Hz"

def laser_sim_ui(file): if file is None: return "No audio provided"

sr, audio = file
audio = audio.astype(np.float32)

laser = modulate_laser(audio)
solar = simulate_solar(laser)

f_tx, m_tx = compute_fft(laser, sr)
f_rx, m_rx = compute_fft(solar, sr)

result = {
    "tx_peak": float(f_tx[np.argmax(m_tx)]),
    "rx_peak": float(f_rx[np.argmax(m_rx)])
}

eid = db.log_experiment(
    "Laser → Solar Simulation",
    {"sample_rate": sr},
    result
)

return f"Experiment {eid}\nTX Peak: {result['tx_peak']:.1f} Hz\nRX Peak: {result['rx_peak']:.1f} Hz"

def add_memory_ui(text): emotion = infer_emotion(text) tags = auto_tags(text) mid = db.add_memory(text, emotion, tags) return f"Memory stored\nID: {mid}\nEmotion: {emotion}\nTags: {tags}"

def add_creative_ui(title, content): tags = auto_tags(content) cid = db.add_creative(title, content, tags) return f"Creative output saved\nID: {cid}"

def add_node_ui(label, desc): tags = auto_tags(desc) nid = db.add_node(label, desc, tags) return f"Knowledge node created\nID: {nid}"

def link_nodes_ui(from_id, to_id, relation, weight): rid = db.add_relationship(from_id, to_id, relation, weight) return f"Relationship created\nID: {rid}"

def export_ui(): path = db.export_all() return f"Export complete:\n{path}"

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GRADIO UI

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with gr.Blocks(title="AQARIONZ POLYGLOT ENGINE") as app: gr.Markdown("""

🌐 AQARIONZ POLYGLOT RESEARCH & TRAINING ENGINE

Signal • Simulation • Memory • Knowledge • Export """)

with gr.Tabs():

    with gr.Tab("🔊 Audio FFT"):
        audio_in = gr.Audio(type="numpy")
        plot = gr.Plot()
        txt = gr.Textbox()
        gr.Button("Run FFT").click(audio_fft_ui, audio_in, [plot, txt])

    with gr.Tab("🔦 Laser / Solar"):
        laser_audio = gr.Audio(type="numpy")
        out = gr.Textbox()
        gr.Button("Simulate").click(laser_sim_ui, laser_audio, out)

    with gr.Tab("📝 Memory"):
        mem = gr.Textbox(lines=6)
        mem_out = gr.Textbox(lines=6)
        gr.Button("Store").click(add_memory_ui, mem, mem_out)

    with gr.Tab("✨ Creative"):
        title = gr.Textbox()
        content = gr.Textbox(lines=6)
        cre_out = gr.Textbox(lines=6)
        gr.Button("Save").click(add_creative_ui, [title, content], cre_out)

    with gr.Tab("🧠 Knowledge"):
        label = gr.Textbox()
        desc = gr.Textbox(lines=6)
        node_out = gr.Textbox()
        gr.Button("Create Node").click(add_node_ui, [label, desc], node_out)

    with gr.Tab("🔗 Relations"):
        f = gr.Textbox(label="From ID")
        t = gr.Textbox(label="To ID")
        r = gr.Textbox(label="Relation")
        w = gr.Slider(0, 10, value=1)
        rel_out = gr.Textbox()
        gr.Button("Link").click(link_nodes_ui, [f, t, r, w], rel_out)

    with gr.Tab("📦 Export"):
        exp_out = gr.Textbox(lines=6)
        gr.Button("Export All").click(export_ui, None, exp_out)

gr.Markdown("""

---

State: Unified
Mode: Simulation + Research + Training
Output: JSON / DB / ML-ready """)

if name == "main": app.launch()