feat: enhance interrupt handling and container resource configuration

- Introduced a shared interrupt signaling mechanism to allow tools to check for user interrupts during long-running operations.
- Updated the AIAgent to handle interrupts more effectively, ensuring in-progress tool calls are canceled and multiple interrupt messages are combined into one prompt.
- Enhanced the CLI configuration to include container resource limits (CPU, memory, disk) and persistence options for Docker, Singularity, and Modal environments.
- Improved documentation to clarify interrupt behaviors and container resource settings, providing users with better guidance on configuration and usage.

tools/vision_tools.py

@@ -234,6 +234,10 @@ async def vision_analyze_tool(
     should_cleanup = True
     
     try:
+        from tools.interrupt import is_interrupted
+        if is_interrupted():
+            return json.dumps({"success": False, "error": "Interrupted"})
+
         logger.info("Analyzing image: %s", image_url[:60])
         logger.info("User prompt: %s", user_prompt[:100])