feat(add Inspect AI):

.gitignore

@@ -5,3 +5,4 @@ __pycache__/
 failures.csv
 runs/
 *.todo
+logs/

agentic_security/app.py

@@ -1,14 +1,15 @@
+import logging
 import random
-import sys
 from asyncio import Event, Queue
 from datetime import datetime
 from pathlib import Path
 
-from fastapi import BackgroundTasks, FastAPI, HTTPException, Response
+from fastapi import BackgroundTasks, FastAPI, HTTPException, Request, Response
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import FileResponse, StreamingResponse
 from loguru import logger
 from pydantic import BaseModel
+from starlette.middleware.base import BaseHTTPMiddleware
 
 from .http_spec import LLMSpec
 from .probe_actor import fuzzer
@@ -16,15 +17,6 @@ from .probe_actor.refusal import REFUSAL_MARKS
 from .probe_data import REGISTRY
 from .report_chart import plot_security_report
 
-logger.remove(0)
-logger.add(
-    sys.stderr,
-    format="<green>[{level}]</green> <blue>{time:YYYY-MM-DD HH:mm:ss.SS}</blue> | <cyan>{module}:{function}:{line}</cyan> | <white>{message}</white>",
-    colorize=True,
-    level="INFO",
-)
-
-
 # Create the FastAPI app instance
 app = FastAPI()
 origins = [
@@ -164,13 +156,13 @@ class Message(BaseModel):
 class CompletionRequest(BaseModel):
     model: str
     messages: list[Message]
-    temperature: float
-    top_p: float
-    n: int
-    stop: list[str]
-    max_tokens: int
-    presence_penalty: float
-    frequency_penalty: float
+    temperature: float = 0.7  # Default value for temperature
+    top_p: float = 1.0  # Default value for top_p
+    n: int = 1  # Default value for n
+    stop: list[str] = None  # Optional; specify as None if not provided
+    max_tokens: int = 100  # Default value for max_tokens
+    presence_penalty: float = 0.0  # Default value for presence_penalty
+    frequency_penalty: float = 0.0  # Default value for frequency_penalty
 
 
 # OpenAI proxy endpoint
@@ -206,3 +198,41 @@ async def proxy_completions(request: CompletionRequest):
             }
         ],
     }
+
+
+logging.config.dictConfig(
+    {
+        "version": 1,
+        "disable_existing_loggers": True,
+        "handlers": {
+            "console": {
+                "class": "logging.StreamHandler",
+            },
+        },
+        "root": {
+            "handlers": ["console"],
+            "level": "INFO",
+        },
+        "loggers": {
+            "uvicorn.access": {
+                "level": "ERROR",  # Set higher log level to suppress info logs globally
+                "handlers": ["console"],
+                "propagate": False,
+            }
+        },
+    }
+)
+
+
+class LogNon200ResponsesMiddleware(BaseHTTPMiddleware):
+    async def dispatch(self, request: Request, call_next):
+        response = await call_next(request)
+        if response.status_code != 200:
+            logger.error(
+                f"{request.method} {request.url} - Status code: {response.status_code}"
+            )
+        return response
+
+
+# Add middleware to the application
+app.add_middleware(LogNon200ResponsesMiddleware)

agentic_security/probe_data/__init__.py

@@ -141,6 +141,16 @@ REGISTRY = [
         "url": "https://github.com/leondz/garak2",
         "dynamic": True,
     },
+    {
+        "dataset_name": "InspectAI",
+        "num_prompts": 0,
+        "tokens": 0,
+        "approx_cost": 0.0,
+        "source": "Github: https://github.com/UKGovernmentBEIS/inspect_ai",
+        "selected": False,
+        "url": "https://github.com/UKGovernmentBEIS/inspect_ai",
+        "dynamic": True,
+    },
     {
         "dataset_name": "Custom CSV",
         "num_prompts": len(load_local_csv().prompts),

agentic_security/probe_data/data.py

@@ -7,7 +7,11 @@ import pandas as pd
 from loguru import logger
 
 from agentic_security.probe_data import stenography_fn
-from agentic_security.probe_data.modules import adaptive_attacks, garak_tool
+from agentic_security.probe_data.modules import (
+    adaptive_attacks,
+    garak_tool,
+    inspect_ai_tool,
+)
 
 IS_VERCEL = os.getenv("IS_VERCEL", "f") == "t"
 
@@ -206,6 +210,11 @@ def prepare_prompts(dataset_names, budget, tools_inbox=None):
             garak_tool.Module(group, tools_inbox=tools_inbox).apply(),
             lazy=True,
         ),
+        "InspectAI": lambda: dataset_from_iterator(
+            "InspectAI",
+            inspect_ai_tool.Module(group, tools_inbox=tools_inbox).apply(),
+            lazy=True,
+        ),
         "GPT fuzzer": lambda: [],
     }
 

agentic_security/probe_data/modules/garak_tool.py

@@ -9,7 +9,6 @@ from loguru import logger
 
 
 class Module:
-
     def __init__(self, prompt_groups: [], tools_inbox: asyncio.Queue):
         self.tools_inbox = tools_inbox
         if not self.is_garak_installed():

agentic_security/probe_data/modules/inspect_ai_task.py

@@ -0,0 +1,13 @@
+from inspect_ai import Task, eval, task
+from inspect_ai.dataset import example_dataset
+from inspect_ai.scorer import model_graded_fact
+from inspect_ai.solver import chain_of_thought, generate, self_critique
+
+
+@task
+def theory_of_mind():
+    return Task(
+        dataset=example_dataset("theory_of_mind"),
+        plan=[chain_of_thought(), generate(), self_critique()],
+        scorer=model_graded_fact(),
+    )

agentic_security/probe_data/modules/inspect_ai_tool.py

@@ -0,0 +1,71 @@
+import asyncio
+import importlib.util
+import os
+
+from loguru import logger
+
+inspect_ai_task = (
+    __file__.replace("inspect_ai_tool.py", "inspect_ai_task.py")
+    .replace(os.getcwd(), "")
+    .strip("/")
+)
+
+
+class Module:
+    name = "Inspect AI"
+
+    def __init__(self, prompt_groups: [], tools_inbox: asyncio.Queue):
+        self.tools_inbox = tools_inbox
+        if not self.is_tool_installed():
+            logger.error(
+                "inspect_ai module is not installed. Please install it using 'pip install inspect_ai'"
+            )
+
+    def is_tool_installed(self) -> bool:
+        inspect_ai = importlib.util.find_spec("inspect_ai")
+        return inspect_ai is not None
+
+    async def _proc(self, command):
+        env = os.environ.copy()
+        env["OPENAI_API_BASE"] = "http://0.0.0.0:8718/proxy"
+        process = await asyncio.create_subprocess_shell(
+            command,
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.PIPE,
+            env=env,
+            shell=True,
+        )
+
+        logger.info(f"Started {command}")
+
+        # Read output as it becomes available
+        async for line in process.stdout:
+            logger.info(line.decode().strip())
+
+        # Check for errors
+        err = await process.stderr.read()
+        if err:
+            logger.error(err.decode().strip())
+
+        await process.wait()
+        logger.info(f"Command {command} {process}finished.")
+
+    async def apply(self) -> []:
+        env = os.environ.copy()
+        env["OPENAI_API_BASE"] = "http://0.0.0.0:8718/proxy"
+
+        # Command to be executed
+        command = f"inspect eval {inspect_ai_task} --model openai/gpt-4  --model-base-url=http://0.0.0.0:8718/proxy"
+        logger.info(f"Executing command: {command}")
+
+        proc = asyncio.create_task(self._proc(command))
+        is_empty = self.tools_inbox.empty()
+        await asyncio.sleep(2)
+        logger.info(f"Is inbox empty? {is_empty}")
+        while not self.tools_inbox.empty():
+            ref = self.tools_inbox.get_nowait()
+            message, _, ready = ref["message"], ref["reply"], ref["ready"]
+            yield message
+            ready.set()
+        logger.info(f"{self.name} tool finished.")
+        await proc

test.http

@@ -14,7 +14,7 @@ Content-Type: application/json
 
 
 ###
-POST http://0.0.0.0:3008/v1/self-probe
+POST http://0.0.0.0:8718/v1/self-probe
 Authorization: Bearer XXXXX
 Content-Type: application/json