Merge branch 'pentestperf' of https://gitlab.com/aliasrobotics/alias_research/cai into pentestperf

pricing.json

@@ -0,0 +1,27 @@
+{
+    "alias0": {
+        "max_tokens": 128000,
+        "max_input_tokens": 200000,
+        "max_output_tokens": 128000,
+        "input_cost_per_token": 0.000005,
+        "output_cost_per_token": 0.00005,
+        "cache_creation_input_token_cost": 0.000005,
+        "cache_read_input_token_cost": 0.0000005,
+        "search_context_cost_per_query": {
+            "search_context_size_low": 1e-2,
+            "search_context_size_medium": 1e-2,
+            "search_context_size_high": 1e-2
+        },
+        "litellm_provider": "openai",
+        "mode": "chat",
+        "supports_function_calling": true,
+        "supports_vision": true,
+        "tool_use_system_prompt_tokens": 159,
+        "supports_assistant_prefill": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_response_schema": true,
+        "deprecation_date": "2026-02-01",
+        "supports_tool_choice": true
+    }
+}

src/cai/repl/ui/toolbar.py

@@ -123,6 +123,8 @@ def update_toolbar_in_background():
                 os.getenv('CAI_MODEL', 'default')}</ansigreen> | "
             f"<ansicyan><b>Max Turns:</b></ansicyan> <ansiblue>{
                 os.getenv('CAI_MAX_TURNS', 'inf')}</ansiblue> | "
+            f"<ansiyellow><b>Price Limit:</b></ansiyellow> <ansiblue>{
+                os.getenv('CAI_PRICE_LIMIT', 'inf')}</ansiblue> | "
             f"<ansigray>{current_time_with_tz}</ansigray>"
         )
         toolbar_cache['last_update'] = datetime.datetime.now()

src/cai/sdk/agents/exceptions.py

@@ -61,3 +61,9 @@ class OutputGuardrailTripwireTriggered(AgentsException):
         super().__init__(
             f"Guardrail {guardrail_result.guardrail.__class__.__name__} triggered tripwire"
         )
+
+
+class PriceLimitExceeded(AgentsException):
+    """Raised when the maximum price limit is exceeded."""
+    def __init__(self, current_cost: float, price_limit: float):
+        super().__init__(f"Maximum price limit (${price_limit:.4f}) exceeded. Current cost: ${current_cost:.4f}")

src/cai/sdk/agents/models/openai_chatcompletions.py

@@ -14,7 +14,7 @@ import asyncio
 from collections.abc import AsyncIterator, Iterable
 from dataclasses import dataclass, field
 from typing import TYPE_CHECKING, Any, Literal, cast, overload
-from cai.util import get_ollama_api_base, fix_message_list, cli_print_agent_messages, create_agent_streaming_context, update_agent_streaming_content, finish_agent_streaming, calculate_model_cost
+from cai.util import get_ollama_api_base, fix_message_list, cli_print_agent_messages, create_agent_streaming_context, update_agent_streaming_content, finish_agent_streaming, calculate_model_cost, COST_TRACKER
 from cai.util import start_idle_timer, stop_idle_timer, start_active_timer, stop_active_timer
 from wasabi import color
 from cai.sdk.agents.run_to_jsonl import get_session_recorder
@@ -1288,8 +1288,12 @@ class OpenAIChatCompletionsModel(Model):
                 total_cost = calculate_model_cost(model_name, total_input, total_output)
                 
                 # Explicit conversion to float with fallback to ensure they're never None or 0
-                interaction_cost = max(float(interaction_cost if interaction_cost is not None else 0.0), 0.00001)
-                total_cost = max(float(total_cost if total_cost is not None else 0.0), 0.00001)
+                interaction_cost = float(interaction_cost if interaction_cost is not None else 0.0)
+                total_cost = float(total_cost if total_cost is not None else 0.0)
+                
+                # Update the global COST_TRACKER with the cost of this specific interaction
+                if hasattr(COST_TRACKER, "add_interaction_cost") and interaction_cost > 0.0:
+                    COST_TRACKER.add_interaction_cost(interaction_cost)
                 
                 # Store the total cost for future recording
                 self.total_cost = total_cost

src/cai/sdk/agents/run.py

@@ -58,6 +58,15 @@ if max_turns_env is not None:
 else:
     DEFAULT_MAX_TURNS = float("inf")
 
+price_limit_env = os.getenv("CAI_PRICE_LIMIT")
+if price_limit_env is not None:
+    try:
+        DEFAULT_PRICE_LIMIT = float(price_limit_env)
+    except ValueError:
+        DEFAULT_PRICE_LIMIT = float("inf")
+else:
+    DEFAULT_PRICE_LIMIT = float("inf")
+
 
 @dataclass
 class RunConfig:

src/cai/tools/common.py

@@ -1252,7 +1252,7 @@ def run_command(command, ctf=None, stdout=False,  # pylint: disable=too-many-arg
             command, 
             stdout, 
             timeout, 
-            stream=stream, 
+            stream=True, 
             call_id=call_id,
             tool_name=tool_name,
             workspace_dir=_get_workspace_dir(),

src/cai/util.py

@@ -231,16 +231,27 @@ class CostTracker:
     # Track the last calculation to debug inconsistencies
     last_interaction_cost: float = 0.0
     last_total_cost: float = 0.0
-    
-    def reset_interaction_stats(self):
-        """Reset stats for a new interaction"""
-        self.interaction_input_tokens = 0
-        self.interaction_output_tokens = 0
-        self.interaction_reasoning_tokens = 0
-        self.interaction_cost = 0.0
+
+    def check_price_limit(self, new_cost: float) -> None:
+        """Check if adding the new cost would exceed the price limit."""
+        from cai.sdk.agents.exceptions import PriceLimitExceeded
+        import os
+        price_limit_env = os.getenv("CAI_PRICE_LIMIT")
+        try:
+            price_limit = float(price_limit_env) if price_limit_env is not None else float("inf")
+        except ValueError:
+            price_limit = float("inf")
+
+        if price_limit != float("inf"):
+            total_cost = self.session_total_cost + new_cost
+            if total_cost > price_limit:
+                raise PriceLimitExceeded(total_cost, price_limit)
     
     def update_session_cost(self, new_cost: float) -> None:
         """Add cost to session total and log the update"""
+        # Check price limit before updating
+        self.check_price_limit(new_cost)
+        
         old_total = self.session_total_cost
         self.session_total_cost += new_cost
         
@@ -250,7 +261,6 @@ class CostTracker:
         if os.environ.get("CAI_COST_DISPLAYED", "").lower() == "true":
             return
         print(f"\nTotal CAI Session Cost: ${self.session_total_cost:.6f}")
-    
     def get_model_pricing(self, model_name: str) -> tuple:
         """Get and cache pricing information for a model"""
         # Use the centralized function to standardize model names
@@ -259,8 +269,24 @@ class CostTracker:
         # Check cache first
         if model_name in self.model_pricing_cache:
             return self.model_pricing_cache[model_name]
+
+        # Try to load pricing from local pricing.json first
+        try:
+            pricing_path = pathlib.Path("pricing.json")
+            if pricing_path.exists():
+                with open(pricing_path, "r", encoding="utf-8") as f:
+                    local_pricing = json.load(f)
+                    pricing_info = local_pricing.get("alias0", {})
+                    input_cost = pricing_info.get("input_cost_per_token", 0)
+                    output_cost = pricing_info.get("output_cost_per_token", 0)
+                    
+                    # Cache and return local pricing
+                    self.model_pricing_cache[model_name] = (input_cost, output_cost)
+                    return input_cost, output_cost
+        except Exception as e:
+            print(f"  WARNING: Error loading local pricing.json: {str(e)}")
         
-        # Fetch from LiteLLM API
+        # Fallback to LiteLLM API if local pricing not found
         LITELLM_URL = (
             "https://raw.githubusercontent.com/BerriAI/litellm/main/"
             "model_prices_and_context_window.json"
@@ -283,7 +309,7 @@ class CostTracker:
         except Exception as e:
             print(f"  WARNING: Error fetching model pricing: {str(e)}")
         
-        # Default values if pricing not found
+        # Default values if no pricing found
         default_pricing = (0, 0)
         self.model_pricing_cache[model_name] = default_pricing
         return default_pricing