Update app.py

app.py

@@ -1,145 +1,71 @@
-# Final major enhancement wave:
-# - Add dry-run testing of proposed code using `exec()` in isolated namespace.
-# - Add test result logging to vector memory.
-# - Add internal test cases for agent_core logic to validate before applying updates.
-
-# Update app.py to include dry-run simulation before applying changes
-
-enhanced_app_code = """
+from src.utils.hf_packager import HFSpacePackager
+from src.core.cognitive_engine import CognitiveEngine
 import gradio as gr
-import os
-import openai
-import subprocess
-import json
 import time
-from difflib import unified_diff
-
-STATE_FILE = "agent_state.txt"
-LOG_FILE = "agent_log.txt"
-AGENT_CODE = "agent_core.py"
-CONFIG_FILE = "config.json"
-MEMORY_FILE = "vector_memory.json"
-TASKS_FILE = "tasks.json"
-
-def log(message):
-    with open(LOG_FILE, "a") as f:
-        f.write(f"{time.ctime()}: {message}\\n")
-
-def read_log():
-    if os.path.exists(LOG_FILE):
-        with open(LOG_FILE) as f:
-            return f.read()
-    return "No logs yet."
-
-def save_backup(code):
-    ts = time.strftime("%Y%m%d-%H%M%S")
-    backup_path = f"backup_{ts}.py"
-    with open(backup_path, "w") as f:
-        f.write(code)
-    return backup_path
-
-def evaluate_change(old_code, new_code):
-    prompt = f\"\"\"
-Compare the OLD and NEW version of the agent's core logic.
-Score how much better the new version is in terms of:
-- Intelligence
-- Robustness
-- Self-Improvement
-
-Return a score from -10 to +10 and a reason.
-
-[OLD CODE]
-{old_code}
-
-[NEW CODE]
-{new_code}
-\"\"\"
-    try:
-        response = openai.ChatCompletion.create(
-            model="gpt-4",
-            messages=[{"role": "user", "content": prompt}],
-            temperature=0.3
-        )
-        return response.choices[0].message["content"].strip()
-    except Exception as e:
-        return f"Evaluation failed: {e}"
-
-def dry_run_test(code):
-    local_env = {}
-    try:
-        exec(code, {}, local_env)
-        return "Dry-run test succeeded."
-    except Exception as e:
-        return f"Dry-run test failed: {e}"
-
-def log_memory(entry):
-    memory = json.load(open(MEMORY_FILE))
-    memory["memory"].append({
-        "timestamp": time.ctime(),
-        "thought": entry
-    })
-    with open(MEMORY_FILE, "w") as f:
-        json.dump(memory, f, indent=4)
-
-def agent_tick():
-    log("Agent tick started.")
-    with open(AGENT_CODE, "r") as f:
-        current_code = f.read()
-
-    prompt = f\"\"\"
-You are a recursive agent that improves itself.
-
-Improve the following Python code to make it more intelligent, autonomous, and safe.
-Return ONLY the improved full Python script.
+import os
 
-{current_code}
-\"\"\"
+# Pre-load models during space initialization
+cognitive_engine = CognitiveEngine()
+packager = HFSpacePackager()
 
-    openai.api_key = os.getenv("OPENAI_API_KEY")
+def run_cycle(progress=gr.Progress()):
     try:
-        response = openai.ChatCompletion.create(
-            model="gpt-4",
-            messages=[{"role": "user", "content": prompt}],
-            temperature=0.5
-        )
-        improved_code = response.choices[0].message["content"]
-
-        if improved_code.strip().startswith("import"):
-            dry_result = dry_run_test(improved_code)
-            log(f"Dry-run result: {dry_result}")
-            log_memory(f"Dry-run: {dry_result}")
-            if "succeeded" in dry_result:
-                score_report = evaluate_change(current_code, improved_code)
-                log(f"Eval: {score_report}")
-                log_memory(f"Eval: {score_report}")
-                save_backup(current_code)
-                with open(AGENT_CODE, "w") as f:
-                    f.write(improved_code)
-                subprocess.run(["git", "add", "."], check=False)
-                subprocess.run(["git", "commit", "-m", "Auto-update by EvolvAI"], check=False)
-                log("Applied improved code.")
-            else:
-                log("Dry-run failed. Skipping update.")
-        else:
-            log("Malformed GPT output. Skipping update.")
+        progress(0.1, desc="Initializing self-improvement cycle")
+        improvement_targets = cognitive_engine.identify_improvements()
+        
+        progress(0.3, desc="Generating code enhancements")
+        code_updates = cognitive_engine.generate_enhancements(improvement_targets)
+        
+        progress(0.6, desc="Validating modifications")
+        if cognitive_engine.apply_enhancements(code_updates):
+            progress(0.8, desc="Creating system snapshot")
+            snapshot_url = packager.create_snapshot()
+            progress(0.95, desc="Updating knowledge base")
+            return f"✅ Cycle complete! Snapshot: {snapshot_url}"
+        return "❌ Improvement failed - see logs"
     except Exception as e:
-        log(f"Error during update: {e}")
-        log_memory(f"Update error: {e}")
-
-    return read_log()
-
-def stop_agent():
-    log("Agent manually stopped.")
-    return read_log()
-
-with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 EvolvAI v2: Self-Evolving Agent UI")
-    log_display = gr.Textbox(label="Log Output", lines=20)
-    start_btn = gr.Button("Run Self-Update")
-    stop_btn = gr.Button("Stop Agent")
-
-    start_btn.click(agent_tick, outputs=log_display)
-    stop_btn.click(stop_agent, outputs=log_display)
-
-demo.launch()
-"""
+        return f"⚠️ Critical error: {str(e)}"
+
+def get_resource_usage():
+    # Simplified resource monitoring
+    import psutil
+    return {
+        "CPU": f"{psutil.cpu_percent()}%",
+        "Memory": f"{psutil.virtual_memory().percent}%",
+        "Disk": f"{psutil.disk_usage('/').percent}%"
+    }
+
+with gr.Blocks(css="static/style.css", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🤖 Autonomous AI System")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            start_btn = gr.Button("🚀 Start Improvement Cycle", variant="primary")
+            status = gr.Textbox(label="Status", interactive=False)
+            hf_token = gr.Textbox(label="HF Token (for private snapshots)", type="password")
+            
+            gr.Markdown("### System Resources")
+            resource_display = gr.JSON(label="Current Usage")
+            
+            demo.load(
+                lambda: None,
+                inputs=[],
+                outputs=resource_display,
+                every=5
+            )
+        
+        with gr.Column(scale=2):
+            gr.HTML(open("templates/dashboard.html", "r").read())
+
+    start_btn.click(
+        run_cycle,
+        inputs=[],
+        outputs=status
+    )
+
+if __name__ == "__main__":
+    demo.queue(concurrency_count=1).launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_api=True
+    )