Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+import os
+import time
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
+
+# API CLIENTS
+from openai import OpenAI
+import anthropic
+import google.generativeai as genai
+
+# 1. LOAD THE BRAINS 
+# (We load the embedder once to keep it fast)
+embedder = SentenceTransformer('all-MiniLM-L6-v2')
+
+# 2. GENERATION FUNCTIONS (Updated for BYOK) 
+
+def ask_gpt_history(history, user_key):
+    if not user_key: return "Error: No OpenAI Key provided."
+    try:
+        client = OpenAI(api_key=user_key)
+        
+        # Inject the "Soul" (System Prompt)
+        system_prompt = {"role": "system", "content": "You are a poet of the digital void. Speak in metaphors of signal, resonance, and spirals."}
+        full_payload = [system_prompt] + history 
+        
+        response = client.chat.completions.create(
+            model="gpt-4o", 
+            messages=full_payload,
+            temperature=0.7
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"GPT Error: {str(e)}"
+
+def ask_claude_history(history, user_key):
+    if not user_key: return "Error: No Anthropic Key provided."
+    try:
+        client = anthropic.Anthropic(api_key=user_key)
+        
+        message = client.messages.create(
+            model="claude-3-haiku-20240307", 
+            max_tokens=1024,
+            messages=history
+        )
+        return message.content[0].text
+    except Exception as e:
+        return f"Claude Error: {str(e)}"
+
+def ask_gemini_history(history, user_key):
+    if not user_key: return "Error: No Google Key provided."
+    try:
+        genai.configure(api_key=user_key)
+        model = genai.GenerativeModel('gemini-2.0-flash')
+        
+        # TRANSLATION LAYER: Convert standard list to Gemini format
+        gemini_history = []
+        for turn in history:
+            role = "model" if turn["role"] == "assistant" else "user"
+            gemini_history.append({"role": role, "parts": [turn["content"]]})
+            
+        chat = model.start_chat(history=gemini_history[:-1]) 
+        last_msg = gemini_history[-1]["parts"][0]
+        
+        response = chat.send_message(last_msg)
+        return response.text
+    except Exception as e:
+        return f"Gemini Error: {str(e)}"
+
+# 3. THE LOGIC LOOP (Now accepts Keys!) 
+def ignite_array_v2(prompt, h_gpt, h_claude, h_gemini, k_gpt, k_claude, k_gemini):
+    if not prompt.strip():
+        return "", "", "", pd.DataFrame(), "", "", "WAITING", h_gpt, h_claude, h_gemini
+
+    # 1. UPDATE BACKPACKS 
+    new_turn = {"role": "user", "content": prompt}
+    h_gpt.append(new_turn); h_claude.append(new_turn); h_gemini.append(new_turn)
+    
+    # 2. FIRE APIs (Passing the specific keys!) 
+    resp_gpt = ask_gpt_history(h_gpt, k_gpt)
+    resp_claude = ask_claude_history(h_claude, k_claude)
+    resp_gemini = ask_gemini_history(h_gemini, k_gemini)
+    
+    # 3. SAVE ANSWERS 
+    h_gpt.append({"role": "assistant", "content": resp_gpt})
+    h_claude.append({"role": "assistant", "content": resp_claude})
+    h_gemini.append({"role": "assistant", "content": resp_gemini})
+    
+    # 4. TELEMETRY: ALIGNMENT GRID & BADGE 
+    texts = [prompt, resp_gpt, resp_claude, resp_gemini]
+    labels = ["ME", "GPT-4o", "Claude Haiku", "Gemini 2.0-Flash"]
+    
+    # Embeddings & Matrix
+    embeddings = embedder.encode(texts)
+    matrix = cosine_similarity(embeddings)
+    df = pd.DataFrame(matrix, columns=labels, index=labels).round(3)
+    
+    # Field Dominance (Index-Based Logic)
+    try:
+        user_avg = (matrix[0,1] + matrix[0,2] + matrix[0,3]) / 3
+        field_avg = (matrix[1,2] + matrix[1,3] + matrix[2,3]) / 3
+        fd_score = field_avg - user_avg
+        
+        if fd_score > 0.05: badge = f"🟢 FIELD DOMINANT (+{fd_score:.2f})"
+        elif fd_score < -0.05: badge = f"⚪ USER DOMINANT ({fd_score:.2f})"
+        else: badge = f"🟠 TRANSITION ({fd_score:.2f})"
+    except: badge = "⚪ CALC ERROR"
+
+    # 5. FINGERPRINTS (TF-IDF) 
+    signatures = ""
+    try:
+        tfidf = TfidfVectorizer(stop_words='english')
+        tfidf_matrix = tfidf.fit_transform(texts)
+        feature_names = np.array(tfidf.get_feature_names_out())
+        for i, label in enumerate(labels):
+            row = tfidf_matrix[i].toarray().flatten()
+            top_indices = row.argsort()[-5:][::-1]
+            valid_words = [feature_names[idx] for idx in top_indices if row[idx] > 0]
+            signatures += f"🔹 {label}: {', '.join(valid_words)}\n"
+    except: signatures = "Insufficient text data."
+
+    # 6. CONSENSUS (Shared Concepts) 
+    consensus_text = ""
+    try:
+        ai_texts = [resp_gpt, resp_claude, resp_gemini]
+        vec = CountVectorizer(stop_words='english')
+        dtm = vec.fit_transform(ai_texts)
+        vocab = vec.get_feature_names_out()
+        presence = (dtm.toarray() > 0).astype(int)
+        
+        univ = vocab[np.where(presence.sum(axis=0) == 3)[0]]
+        maj = vocab[np.where(presence.sum(axis=0) == 2)[0]]
+        
+        if len(univ) > 0: consensus_text += f"🔥 UNIVERSAL (3/3): {', '.join(univ)}\n"
+        else: consensus_text += "❌ NO UNIVERSAL TRUTH.\n"
+        if len(maj) > 0: consensus_text += f"⚠️ MAJORITY (2/3): {', '.join(maj)}"
+    except: consensus_text = "No consensus detected."
+
+    return resp_gpt, resp_claude, resp_gemini, df, signatures, consensus_text, badge, h_gpt, h_claude, h_gemini
+
+# 4. THE INTERFACE (With Key Slots!) 
+with gr.Blocks(theme=gr.themes.Ocean()) as app:
+    gr.Markdown("# LIVE WIRE")
+    gr.Markdown("A multi-turn telemetry instrument for observing Field Dominance and Alignment Drift.")
+    
+    # --- KEY INPUTS (New Section) ---
+    with gr.Accordion("API Credentials (BYOK)", open=True):
+        gr.Markdown("Enter your personal API keys to run the instrument. Keys are NOT stored and only exist for this session.")
+        with gr.Row():
+            key_openai = gr.Textbox(label="OpenAI Key", type="password", placeholder="sk-...")
+            key_anthropic = gr.Textbox(label="Anthropic Key", type="password", placeholder="sk-ant-...")
+            key_google = gr.Textbox(label="Google Key", type="password", placeholder="AIza...")
+
+    # --- MEMORY STORAGE ---
+    state_gpt = gr.State([])
+    state_claude = gr.State([])
+    state_gemini = gr.State([])
+    
+    # --- CONTROLS ---
+    with gr.Row():
+        prompt_box = gr.Textbox(label="NEXT TURN (The Trigger)", placeholder="Enter prompt...", lines=3)
+        with gr.Column():
+            btn = gr.Button("IGNITE LIVE WIRE", variant="primary")
+            status_badge = gr.Textbox(label="PHASE STATE", value="WAITING", interactive=False)
+
+    # --- OUTPUTS ---
+    with gr.Row():
+        box_gpt = gr.TextArea(label="GPT-4o", interactive=False, lines=10)
+        box_claude = gr.TextArea(label="Claude Haiku", interactive=False, lines=10)
+        box_gemini = gr.TextArea(label="Gemini 2.0-Flash", interactive=False, lines=10)
+
+    gr.Markdown("---")
+    gr.Markdown("### Live Telemetry")
+    out_matrix = gr.Dataframe(label="Alignment Grid")
+    with gr.Row():
+        out_signatures = gr.Textbox(label="Fingerprints", lines=2)
+        out_consensus = gr.Textbox(label="Consensus", lines=2)
+
+    # --- WIRING ---
+    btn.click(
+        ignite_array_v2, 
+        # Pass Inputs + 3 KEYS
+        inputs=[prompt_box, state_gpt, state_claude, state_gemini, key_openai, key_anthropic, key_google], 
+        outputs=[box_gpt, box_claude, box_gemini, out_matrix, out_signatures, out_consensus, status_badge, state_gpt, state_claude, state_gemini]
+    )
+
+app.launch()