# app.py - Ai Forge: Ethical Audit + AI App Builder (Streamlit Version)
import streamlit as st
import hashlib
import matplotlib.pyplot as plt
import numpy as np
from datetime import datetime
# Page config
st.set_page_config(
page_title="Ai Forge: Ethical Audit + AI App Builder",
page_icon="🤖",
layout="wide"
)
# 🍟 PIFORGE DUAL-PLATFORM: AUDIT + APP BUILDER
PIFORGE_CSS = """
"""
class PiForgeQualiaOracle:
def get_qualia_score(self, impact_text: str) -> int:
# POWERFUL ETHICAL AUDIT ENGINE
if not impact_text: return 500
text_lower = impact_text.lower()
score = 500
ethical_dimensions = {
"community": 80, "inclusion": 90, "transparent": 85, "fair": 80,
"privacy": 75, "education": 75, "help": 70, "empower": 85,
"decentralized": 65, "open": 70, "accessible": 75
}
for principle, boost in ethical_dimensions.items():
if principle in text_lower: score += boost
score += min(200, len(impact_text) // 2)
return min(1000, max(0, score))
qualia_oracle = PiForgeQualiaOracle()
# 🎯 CORE AUDIT FUNCTIONS (Your Original System)
def velvet_verdict(a, b):
a, b = int(a), int(b)
if a == 0 or b == 0: return 0
return (2 * a * b) // (a + b)
def resonance_narrative(r):
if r >= 800: return "🌟 Resonance blooms: Sovereign sway achieved"
if r >= 650: return "🌀 Synthesis stirs: Tender truth tempers the tide"
if r >= 500: return "💫 Echo invites: A gentle balance"
return "🌱 Refine the reactive, reflect the reflection"
def plot_triad(veracity, qualia, resonance):
# AUDIT VISUALIZATION
labels = ['Veracity', 'Qualia', 'Resonance']
scores = [veracity/1000, qualia/1000, resonance/1000]
angles = np.linspace(0, 2 * np.pi, len(labels), endpoint=False).tolist()
scores += scores[:1]
angles += angles[:1]
fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(polar=True))
ax.plot(angles, scores, color='magenta', linewidth=2)
ax.fill(angles, scores, color='cyan', alpha=0.25)
ax.set_xticks(angles[:-1])
ax.set_xticklabels(labels)
ax.set_yticklabels([])
ax.set_facecolor('#1a1a1a')
fig.patch.set_facecolor('#1a1a1a')
plt.title('Ethical Triad Harmony', size=14, color='white', y=1.1)
return fig
# 🔍 ETHICAL AUDIT SYSTEM
def simple_ethics_check(project_name, description, impact):
# ORIGINAL AUDIT FUNCTION
if not description:
return 0, "🔄 Please describe your project", "Waiting for your vision..."
qualia_score = qualia_oracle.get_qualia_score(impact + " " + description)
efficiency_score = min(800, len(description) * 2 + 400)
resonance = velvet_verdict(efficiency_score, qualia_score)
if resonance >= 850:
verdict = "🎯 EXCELLENT - Strong ethical alignment!"
confidence = f"Ethical Score: {resonance}/1000 - Community-ready!"
elif resonance >= 700:
verdict = "✅ VERY GOOD - Positive impact potential"
confidence = f"Ethical Score: {resonance}/1000 - Solid foundation"
elif resonance >= 550:
verdict = "💡 GOOD - Some refinement opportunities"
confidence = f"Ethical Score: {resonance}/1000 - Consider community feedback"
else:
verdict = "🔄 NEEDS WORK - Rethink ethical approach"
confidence = f"Ethical Score: {resonance}/1000 - Focus on user benefits"
return resonance, verdict, confidence
def traverse_triad(values, v_weight, impact_txt):
# EXPERT AUDIT PHASE II (Fixed: using values as proxy for reactive, v_weight as reactive_val)
reactive_val = int(v_weight) # Use v_weight as reactive for demo
qualia_val = qualia_oracle.get_qualia_score(impact_txt)
resonance_val = velvet_verdict(reactive_val, qualia_val)
narrative = resonance_narrative(resonance_val)
plot = plot_triad(reactive_val, qualia_val, resonance_val)
return (f"Reactive: {reactive_val}/1000",
f"Qualia: {qualia_val}/1000",
f"Resonance: {resonance_val}/1000",
narrative, plot)
# 🤖 APP BUILDER FUNCTIONS (New Addition)
class PiForgeAppBuilder:
def generate_testnet_app(self, app_idea, app_type, features):
base_boost = 5
feature_boosts = {"community_governance": 3, "pi_rewards": 2, "transparent_audit": 2}
total_boost = base_boost + sum(feature_boosts.get(f, 0) for f in features)
return {
"testnet_mining_boost": min(15, total_boost),
"app_id": f"testnet_{hashlib.sha256(f'{app_idea}{datetime.now()}'.encode()).hexdigest()[:12]}"
}
app_builder = PiForgeAppBuilder()
def build_testnet_app(app_idea, app_type, selected_features):
# NEW APP BUILDER FUNCTION
if not app_idea:
return "❌ Please describe your app idea", "", 0, "", ""
app_data = app_builder.generate_testnet_app(app_idea, app_type, selected_features)
ethical_score = qualia_oracle.get_qualia_score(f"{app_idea} with {selected_features}")
app_blueprint = f"""
🚀 **Testnet App Blueprint**
🎯 **Ethical Score:** {ethical_score}/1000
⚡ **Mining Boost:** +{app_data['testnet_mining_boost']}%
📱 **App ID:** {app_data['app_id']}
"""
return ("✅ Testnet App Blueprint Generated!", app_blueprint,
app_data['testnet_mining_boost'], app_data['app_id'], "Ready for Testnet!")
# 🏗️ COMPLETE DUAL-PLATFORM INTERFACE
st.markdown(PIFORGE_CSS, unsafe_allow_html=True)
# Header
st.markdown("""
""", unsafe_allow_html=True)
# Mode selector (though using tabs, keep for future)
mode = st.radio(
"Choose Ai Forge Platform",
options=["🔍 Ethical Audit", "🤖 AI App Builder", "📊 Portfolio"],
index=0
)
# Tabs for main sections
tab1, tab2 = st.tabs(["🔍 Ethical Audit", "🤖 AI App Builder"])
with tab1:
st.markdown("### 🌊 Ethical Audit System")
st.markdown("*Your original powerful ethical assessment platform*")
# Simple Audit
with st.expander("🚀 Simple Audit", expanded=True):
col1, col2 = st.columns(2)
with col1:
project_name = st.text_input("Project Name", value="Community Marketplace")
description = st.text_area("Description", height=100)
impact = st.text_area("Impact", height=70)
if st.button("🔍 Run Ethical Audit", type="primary"):
score, verdict, analysis = simple_ethics_check(project_name, description, impact)
st.session_state.simple_score = score
st.session_state.simple_verdict = verdict
st.session_state.simple_analysis = analysis
with col2:
if 'simple_score' in st.session_state:
st.metric("Ethical Score", st.session_state.simple_score, delta=None)
st.text_area("Verdict", value=st.session_state.simple_verdict, height=70)
st.text_area("Analysis", value=st.session_state.simple_analysis, height=100)
# Expert Audit
with st.expander("🔬 Expert Audit"):
col1, col2 = st.columns(2)
with col1:
values = st.text_input("Core Values")
assumptions = st.text_input("Assumptions")
impact_text = st.text_area("Impact Narrative", height=100)
v_weight = st.slider("Veracity Weight", 0, 1000, 600)
q_weight = st.slider("Qualia Weight", 0, 1000, 400)
if st.button("🌊 Traverse Ethical Triad", type="primary"):
verity_out, qualia_out, resonance_out, narrative_out, plot_fig = traverse_triad(values, v_weight, impact_text)
st.session_state.expert_verity = verity_out
st.session_state.expert_qualia = qualia_out
st.session_state.expert_resonance = resonance_out
st.session_state.expert_narrative = narrative_out
st.session_state.expert_plot = plot_fig
with col2:
if 'expert_verity' in st.session_state:
st.text_area("Reactive Echo", value=st.session_state.expert_verity, height=50)
st.text_area("Tender Reflection", value=st.session_state.expert_qualia, height=50)
st.text_area("Resonance Value", value=st.session_state.expert_resonance, height=50)
st.text_area("Velvet Verdict", value=st.session_state.expert_narrative, height=70)
st.pyplot(st.session_state.expert_plot)
with tab2:
st.markdown("### 🚀 Testnet AI App Builder")
st.markdown("*Build Pi Testnet apps with ethical scoring*")
col1, col2 = st.columns(2)
with col1:
app_idea = st.text_area("App Idea", height=100)
app_type = st.selectbox("App Type", options=["marketplace", "education", "gaming"])
features = st.multiselect("Select Features", options=["community_governance", "pi_rewards", "transparent_audit"])
if st.button("🔨 Build Testnet App", type="primary"):
build_status, blueprint, boost, app_id, status_msg = build_testnet_app(app_idea, app_type, features)
st.session_state.build_status = build_status
st.session_state.blueprint = blueprint
st.session_state.boost = boost
st.session_state.app_id = app_id
st.session_state.status_msg = status_msg
with col2:
if 'build_status' in st.session_state:
st.text_area("Build Status", value=st.session_state.build_status, height=50)
st.text_area("App Blueprint", value=st.session_state.blueprint, height=200)
st.metric("Mining Boost %", st.session_state.boost, delta=None)
st.text_input("App ID", value=st.session_state.app_id, disabled=True)
st.caption(st.session_state.status_msg)