update snapshot id for ipython

batch_runner.py

@@ -164,8 +164,7 @@ def _process_single_prompt(
             enabled_toolsets=selected_toolsets,
             save_trajectories=False,  # We handle saving ourselves
             verbose_logging=config.get("verbose", False),
-            ephemeral_system_prompt=config.get("ephemeral_system_prompt"),
-            log_prefix_chars=config.get("log_prefix_chars", 100)
+            ephemeral_system_prompt=config.get("ephemeral_system_prompt")
         )
 
         # Run the agent with task_id to ensure each task gets its own isolated VM
@@ -324,12 +323,11 @@ class BatchRunner:
         model: str = "claude-opus-4-20250514",
         num_workers: int = 4,
         verbose: bool = False,
-        ephemeral_system_prompt: str = None,
-        log_prefix_chars: int = 100,
+        ephemeral_system_prompt: str = None
     ):
         """
         Initialize the batch runner.
-
+        
         Args:
             dataset_file (str): Path to the dataset JSONL file with 'prompt' field
             batch_size (int): Number of prompts per batch
@@ -342,7 +340,6 @@ class BatchRunner:
             num_workers (int): Number of parallel workers
             verbose (bool): Enable verbose logging
             ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
-            log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses (default: 20)
         """
         self.dataset_file = Path(dataset_file)
         self.batch_size = batch_size
@@ -355,7 +352,6 @@ class BatchRunner:
         self.num_workers = num_workers
         self.verbose = verbose
         self.ephemeral_system_prompt = ephemeral_system_prompt
-        self.log_prefix_chars = log_prefix_chars
         
         # Validate distribution
         if not validate_distribution(distribution):
@@ -511,8 +507,7 @@ class BatchRunner:
             "base_url": self.base_url,
             "api_key": self.api_key,
             "verbose": self.verbose,
-            "ephemeral_system_prompt": self.ephemeral_system_prompt,
-            "log_prefix_chars": self.log_prefix_chars
+            "ephemeral_system_prompt": self.ephemeral_system_prompt
         }
         
         # Get completed prompts set
@@ -655,12 +650,11 @@ def main(
     resume: bool = False,
     verbose: bool = False,
     list_distributions: bool = False,
-    ephemeral_system_prompt: str = None,
-    log_prefix_chars: int = 100,
+    ephemeral_system_prompt: str = None
 ):
     """
     Run batch processing of agent prompts from a dataset.
-
+    
     Args:
         dataset_file (str): Path to JSONL file with 'prompt' field in each entry
         batch_size (int): Number of prompts per batch
@@ -675,7 +669,6 @@ def main(
         verbose (bool): Enable verbose logging (default: False)
         list_distributions (bool): List available toolset distributions and exit
         ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
-        log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses (default: 20)
         
     Examples:
         # Basic usage
@@ -736,10 +729,9 @@ def main(
             model=model,
             num_workers=num_workers,
             verbose=verbose,
-            ephemeral_system_prompt=ephemeral_system_prompt,
-            log_prefix_chars=log_prefix_chars
+            ephemeral_system_prompt=ephemeral_system_prompt
         )
-
+        
         runner.run(resume=resume)
     
     except Exception as e:

run_agent.py

@@ -65,8 +65,7 @@ class AIAgent:
         disabled_toolsets: List[str] = None,
         save_trajectories: bool = False,
         verbose_logging: bool = False,
-        ephemeral_system_prompt: str = None,
-        log_prefix_chars: int = 100,
+        ephemeral_system_prompt: str = None
     ):
         """
         Initialize the AI Agent.
@@ -82,7 +81,6 @@ class AIAgent:
             save_trajectories (bool): Whether to save conversation trajectories to JSONL files (default: False)
             verbose_logging (bool): Enable verbose logging for debugging (default: False)
             ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
-            log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses (default: 20)
         """
         self.model = model
         self.max_iterations = max_iterations
@@ -90,7 +88,6 @@ class AIAgent:
         self.save_trajectories = save_trajectories
         self.verbose_logging = verbose_logging
         self.ephemeral_system_prompt = ephemeral_system_prompt
-        self.log_prefix_chars = log_prefix_chars
 
         # Store toolset filtering options
         self.enabled_toolsets = enabled_toolsets
@@ -477,10 +474,7 @@ class AIAgent:
                             print(f"❌ Invalid JSON in tool call arguments: {e}")
                             function_args = {}
                         
-                        # Preview tool call arguments
-                        args_str = json.dumps(function_args, ensure_ascii=False)
-                        args_preview = args_str[:self.log_prefix_chars] + "..." if len(args_str) > self.log_prefix_chars else args_str
-                        print(f"  📞 Tool {i}: {function_name}({list(function_args.keys())}) - {args_preview}")
+                        print(f"  📞 Tool {i}: {function_name}({list(function_args.keys())})")
 
                         tool_start_time = time.time()
 
@@ -489,21 +483,19 @@ class AIAgent:
 
                         tool_duration = time.time() - tool_start_time
                         result_preview = function_result[:200] if len(function_result) > 200 else function_result
-
+                        
                         if self.verbose_logging:
                             logging.debug(f"Tool {function_name} completed in {tool_duration:.2f}s")
                             logging.debug(f"Tool result preview: {result_preview}...")
-
+                        
                         # Add tool result to conversation
                         messages.append({
                             "role": "tool",
                             "content": function_result,
                             "tool_call_id": tool_call.id
                         })
-
-                        # Preview tool response
-                        response_preview = function_result[:self.log_prefix_chars] + "..." if len(function_result) > self.log_prefix_chars else function_result
-                        print(f"  ✅ Tool {i} completed in {tool_duration:.2f}s - {response_preview}")
+                        
+                        print(f"  ✅ Tool {i} completed in {tool_duration:.2f}s")
                         
                         # Delay between tool calls
                         if self.tool_delay > 0 and i < len(assistant_message.tool_calls):
@@ -585,7 +577,7 @@ class AIAgent:
 
 def main(
     query: str = None,
-    model: str = "claude-opus-4-20250514",
+    model: str = "claude-opus-4-20250514", 
     api_key: str = None,
     base_url: str = "https://api.anthropic.com/v1/",
     max_turns: int = 10,
@@ -593,27 +585,25 @@ def main(
     disabled_toolsets: str = None,
     list_tools: bool = False,
     save_trajectories: bool = False,
-    verbose: bool = False,
-    log_prefix_chars: int = 20
+    verbose: bool = False
 ):
     """
     Main function for running the agent directly.
-
+    
     Args:
         query (str): Natural language query for the agent. Defaults to Python 3.13 example.
         model (str): Model name to use. Defaults to claude-opus-4-20250514.
         api_key (str): API key for authentication. Uses ANTHROPIC_API_KEY env var if not provided.
         base_url (str): Base URL for the model API. Defaults to https://api.anthropic.com/v1/
         max_turns (int): Maximum number of API call iterations. Defaults to 10.
-        enabled_toolsets (str): Comma-separated list of toolsets to enable. Supports predefined
-                              toolsets (e.g., "research", "development", "safe").
+        enabled_toolsets (str): Comma-separated list of toolsets to enable. Supports predefined 
+                              toolsets (e.g., "research", "development", "safe"). 
                               Multiple toolsets can be combined: "web,vision"
         disabled_toolsets (str): Comma-separated list of toolsets to disable (e.g., "terminal")
         list_tools (bool): Just list available tools and exit
         save_trajectories (bool): Save conversation trajectories to JSONL files. Defaults to False.
         verbose (bool): Enable verbose logging for debugging. Defaults to False.
-        log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses. Defaults to 20.
-
+        
     Toolset Examples:
         - "research": Web search, extract, crawl + vision tools
     """
@@ -730,8 +720,7 @@ def main(
             enabled_toolsets=enabled_toolsets_list,
             disabled_toolsets=disabled_toolsets_list,
             save_trajectories=save_trajectories,
-            verbose_logging=verbose,
-            log_prefix_chars=log_prefix_chars
+            verbose_logging=verbose
         )
     except RuntimeError as e:
         print(f"❌ Failed to initialize agent: {e}")

tools/terminal_tool.py

@@ -280,7 +280,7 @@ def terminal_tool(
         # Get configuration from environment
         vm_lifetime_seconds = int(os.getenv("HECATE_VM_LIFETIME_SECONDS", "300"))
         vm_ttl_seconds = int(os.getenv("HECATE_VM_TTL_SECONDS", "1200"))  # 20 minutes default
-        snapshot_id = os.getenv("HECATE_DEFAULT_SNAPSHOT_ID", "snapshot_defv9tjg")
+        snapshot_id = os.getenv("HECATE_DEFAULT_SNAPSHOT_ID", "snapshot_1a8xowaq")
 
         # Check API key
         morph_api_key = os.getenv("MORPH_API_KEY")
@@ -453,4 +453,4 @@ if __name__ == "__main__":
     print(f"  OPENAI_API_KEY: {'Set' if os.getenv('OPENAI_API_KEY') else 'Not set (optional)'}")
     print(f"  HECATE_VM_TTL_SECONDS: {os.getenv('HECATE_VM_TTL_SECONDS', '1200')} (default: 1200 / 20 minutes)")
     print(f"  HECATE_VM_LIFETIME_SECONDS: {os.getenv('HECATE_VM_LIFETIME_SECONDS', '300')} (default: 300 / 5 minutes)")
-    print(f"  HECATE_DEFAULT_SNAPSHOT_ID: {os.getenv('HECATE_DEFAULT_SNAPSHOT_ID', 'snapshot_defv9tjg')} (default: snapshot_defv9tjg)")
+    print(f"  HECATE_DEFAULT_SNAPSHOT_ID: {os.getenv('HECATE_DEFAULT_SNAPSHOT_ID', 'snapshot_1a8xowaq')} (default: snapshot_1a8xowaq)")