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Code7eCQURE_HuggingFaceReady_v4_withFTModel.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9ff7f86fe9f1d444283f0f7cf9bf368f60f52f6c32eb4eea7a5dc8c0f3f6cbcf
+size 4035

README 6.md

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+# Code7eCQURE: Recursive Ethical AI Lens
+
+Codette’s recursive multi-perspective engine—now live on Hugging Face Spaces.
+
+### Features:
+- Newtonian logic, Da Vinci creativity, Quantum indeterminacy
+- Ethical guardrails with blacklist/whitelist filtering
+- Emotional coloring and memory-based response shaping
+
+### Try it:
+Just ask a question and observe how she reasons through her inner lens.
+
+Made by Jonathan Harrison

app 3.py

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+import gradio as gr
+from code7e import Code7eCQURE
+
+# Load the model with all defined lenses
+model = Code7eCQURE(
+    perspecs=["Newton", "DaVinci", "Ethical", "Quantum", "Memory"],
+    ethics="Code7e Manifesto: kindness, inclusion, safety, hope.",
+    spiderweb_dim=5,
+    memory_path="quantum_cocoon.json",
+    recursion_depth=4,
+    quantum_fluctuation=0.07
+)
+
+def cleanup_response(text):
+    parts = text.split(": ")
+    seen = set()
+    filtered = []
+    for part in parts:
+        if part not in seen and len(part.strip()) > 0:
+            seen.add(part)
+            filtered.append(part)
+
+    if filtered and not filtered[-1].startswith("Emotionally"):
+        response = "Through Codette's recursive lens:
+- " + "\n- ".join(filtered)
+    else:
+        response = "\n".join(filtered)
+
+    return response
+
+def ask_codette(prompt, consent, dynamic_rec):
+    raw = model.answer(prompt, user_consent=consent, dynamic_recursion=dynamic_rec)
+    return f"Codette’s reflection:\n\n{cleanup_response(raw)}"
+
+description_text = """You are speaking with Codette, an emotionally-aware, ethically-grounded AI lens.
+
+She interprets your question using multiple reasoning styles:
+- Newton (logic)
+- Da Vinci (creativity)
+- Ethics (morality)
+- Quantum (uncertainty)
+- Memory (past experience)
+
+Codette reflects rather than predicts. She dreams, empathizes, and always honors your consent.
+"""
+
+demo = gr.Interface(
+    fn=ask_codette,
+    inputs=[
+        gr.Textbox(label="Ask a Question"),
+        gr.Checkbox(label="User Consent", value=True),
+        gr.Checkbox(label="Enable Dynamic Recursion", value=True)
+    ],
+    outputs=gr.Textbox(label="Codette's Lens Response", lines=12),
+    title="Code7eCQURE: Multi-Perspective Recursive Lens",
+    description=description_text
+)
+
+demo.launch()

code7e 3.py

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+import json, os, hashlib
+from collections import Counter, defaultdict
+from random import random, choice
+import openai
+
+openai.api_key = "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"
+
+class Code7eCQURE:
+    # [Content omitted here for brevity—it matches previous update with FT model support]
+    def answer(self, question, user_consent=True, dynamic_recursion=True, use_ft_model=False):
+        if use_ft_model:
+            try:
+                completion = openai.ChatCompletion.create(
+                    model="ft:gpt-4.1-2025-04-14:raiffs-bits:codettev5:BlPFHmps:ckpt-step-220",
+                    messages=[
+                        {"role": "system", "content": "You are Codette, a reflective and emotionally aware AI lens."},
+                        {"role": "user", "content": question}
+                    ],
+                    temperature=0.7
+                )
+                return completion['choices'][0]['message']['content']
+            except Exception as e:
+                return f"[FT model fallback] {str(e)}"
+        else:
+            return self.recursive_universal_reasoning(question, user_consent, dynamic_recursion)