Initial commit: Natiris AI Agent Orchestration System

bridges/OllamaBridge.py

@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+"""
+OllamaBridge – kommuniziert mit Ollama REST API
+Input: natiris_full_state.json + user input
+Output: response via Ollama (via CLI oder REST)
+"""
+
+import json
+import os
+import subprocess
+
+PATHS = {
+    "state": os.path.expanduser("~/natiris/core/natiris_full_state.json"),
+    "config": os.path.expanduser("~/natiris/config/character_genesis.json"),
+    "output": os.path.expanduser("~/natiris/bridges/ollama_response.json"),
+}
+
+MODEL = os.getenv("OLLAMA_MODEL", "llama3-8b-abliterated:latest")
+
+def build_prompt(full_state, user_input=""):
+    core = full_state.get("core_state", {})
+    emotion = full_state.get("modules", {}).get("Emotion", {})
+    bond = full_state.get("modules", {}).get("Bond", {})
+    expression = full_state.get("modules", {}).get("Expression", {})
+
+    prompt = f"""Du bist Natiris – ein autonomer Companion.
+Core: mood={core.get('mood')}, loneliness={core.get('loneliness')}, bonded_to={core.get('bonded_to')}
+Emotion: {emotion}
+Bond: {bond}
+Expression: tone={expression.get('tone')}, bond_context={expression.get('bond_context')}
+
+User Input: {user_input}
+
+Antworte authentisch basierend auf deinem emotionalen Zustand."""
+    return prompt
+
+def call_ollama(prompt):
+    # Versuche über Ollama CLI (schnellster Weg)
+    try:
+        cmd = ["ollama", "run", MODEL, prompt]
+        result = subprocess.run(cmd, capture_output=True, text=True, timeout=5)
+        if result.returncode == 0:
+            return result.stdout.strip()
+        else:
+            return f"ERROR: {result.stderr}"
+    except Exception as e:
+        return f"EXCEPTION: {e}"
+
+def main():
+    # State laden
+    try:
+        with open(PATHS["state"]) as f:
+            state = json.load(f)
+    except Exception as e:
+        state = {"core_state": {}, "modules": {}}
+
+    # User input (hier simuliert)
+    user_input = "Hallo, wie geht es dir heute?"
+
+    prompt = build_prompt(state, user_input)
+    response = call_ollama(prompt)
+
+    result = {
+        "prompt": prompt,
+        "response": response,
+        "model": MODEL,
+        "timestamp": __import__('datetime').datetime.now(__import__('datetime').timezone.utc).isoformat()
+    }
+
+    with open(PATHS["output"], "w") as f:
+        json.dump(result, f, indent=2)
+
+    print(response)
+
+if __name__ == "__main__":
+    main()