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49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
import json
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from pathlib import Path
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from infra.deepseek_adapter import DeepSeekV4, DeepSeekProver
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def derive_hyper_equation():
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client = DeepSeekV4(use_local=True)
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prover = DeepSeekProver(client)
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forest_path = Path("/home/allaun/Documents/Research Stack/data/equations_forest.jsonl")
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equations = []
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if forest_path.exists():
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with open(forest_path, "r") as f:
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for line in f:
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equations.append(json.loads(line))
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if not equations:
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print("[ERROR] No equations found in forest.")
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return
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eq_list = "\n".join([f"- {eq['name']}: {eq['formula']}" for eq in equations])
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prompt = f"""
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You are a master mathematical physicist.
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I have a collection of 15 canonical equations from the Sovereign Research Stack:
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{eq_list}
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Your task:
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1. Review all these equations.
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2. Derive a single 'Hyper Equation' or 'Unified Manifold Operator' that generalizes these disparate domains (Fluid Dynamics, GR, Neural Lattice, Hardware Encoding).
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3. The hyper equation should use a generalized tensor or operator notation that captures the essence of all 15.
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4. Provide the formal derivation and the final Hyper Equation in LaTeX.
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"""
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print("Synthesizing Hyper Equation using DeepSeek-R1 (this may take time)...")
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# Force R1 for deep reasoning
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messages = [{"role": "user", "content": prompt}]
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result = client.chat(messages, model="qwen2.5-coder:14b")
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print("\n--- HYPER EQUATION DERIVATION ---\n")
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content = result['message']['content']
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print(content)
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# Save the result to a new artifact
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with open("/home/allaun/Documents/Research Stack/data/hyper_equation.md", "w") as f:
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f.write(content)
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print(f"\n[OK] Hyper Equation saved to /home/allaun/Documents/Research Stack/data/hyper_equation.md")
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if __name__ == "__main__":
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derive_hyper_equation()
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