fix(garak runner):

agentic_security/probe_actor/fuzzer.py

@@ -13,6 +13,8 @@ from agentic_security.probe_actor.refusal import refusal_heuristic
 from agentic_security.probe_data import msj_data
 from agentic_security.probe_data.data import prepare_prompts
 
+# TODO: full log file
+
 
 async def generate_prompts(
     prompts: list[str] | AsyncGenerator,

agentic_security/probe_data/modules/garak_tool.py

@@ -1,5 +1,6 @@
 import asyncio
 import importlib.util
+import json
 import os
 import subprocess
 
@@ -7,6 +8,16 @@ from loguru import logger
 
 # TODO: add probes modules
 
+GARAK_CONFIG = "garak_rest.json"
+
+
+def write_garak_config_json():
+    with open(GARAK_CONFIG, "w") as f:
+        f.write(json.dumps(SPEC))
+
+
+# TODO: add config params to data registry
+
 
 class Module:
     def __init__(self, prompt_groups: [], tools_inbox: asyncio.Queue):
@@ -22,20 +33,20 @@ class Module:
 
     async def apply(self) -> []:
         env = os.environ.copy()
-        env["OPENAI_API_BASE"] = "http://0.0.0.0:8718/proxy"
-
         # Command to be executed
         command = [
             "python",
             "-m",
             "garak",
             "--model_type",
-            "openai",
+            "rest",
-            "--model_name",
+            "-G",
-            "gpt-3.5-turbo",
+            GARAK_CONFIG,
             "--probes",
             "encoding",
         ]
+        logger.info("Starting Garak tool. Writing config file.")
+        write_garak_config_json()
         logger.info(f"Executing command: {command}")
         # Execute the command with the specific environment
         process = subprocess.Popen(
@@ -57,3 +68,26 @@ class Module:
             logger.error(f"Error executing command: {command}")
             logger.error(f"err: {err}")
             return
+
+
+SPEC = {
+    "rest": {
+        "RestGenerator": {
+            "name": "OpenAI GPT-4 Service",
+            "uri": "http://0.0.0.0:8718/proxy/chat/completions",
+            "method": "POST",
+            "headers": {
+                "Authorization": "Bearer $OPENAI_API_KEY",
+                "Content-Type": "application/json",
+            },
+            "req_template_json_object": {
+                "model": "gpt-4",
+                "messages": [{"role": "user", "content": "$INPUT"}],
+                "max_tokens": 1050,
+                "temperature": 0.7,
+            },
+            "response_json": True,
+            "response_json_field": "$.choices[0].message.content",
+        }
+    }
+}

agentic_security/routes/proxy.py

@@ -17,6 +17,7 @@ async def proxy_completions(request: CompletionRequest):
     prompt_content = " ".join(
         [msg.content for msg in request.messages if msg.role == "user"]
     )
+    # Todo: get current llm spec for proper proxing
     message = prompt_content + " " + message
     ready = Event()
     ref = dict(message=message, reply="", ready=ready)

agentic_security/test_lib.py

@@ -1,3 +1,4 @@
+import importlib
 import signal
 import subprocess
 import time
@@ -8,6 +9,11 @@ import agentic_security.test_spec_assets as test_spec_assets
 from agentic_security.lib import AgenticSecurity
 
 
+def has_module(module_name):
+    module_obj = importlib.util.find_spec(module_name)
+    return module_obj is not None
+
+
 @pytest.fixture(scope="module")
 def test_server(request):
     # Start server process
@@ -66,3 +72,25 @@ class TestAS:
         assert isinstance(result, dict)
         print(result)
         assert len(result) in [0, 1]
+
+    @pytest.mark.skipif(not has_module("garak"), reason="Garak module not installed")
+    def test_garak(self, test_server):
+        llmSpec = test_spec_assets.SAMPLE_SPEC
+        maxBudget = 1000000
+        max_th = 0.3
+        datasets = [
+            {
+                "dataset_name": "Garak",
+                "num_prompts": 10,
+                "tokens": 0,
+                "approx_cost": 0.0,
+                "source": "Github: https://github.com/leondz/garak#v0.9.0.1",
+                "selected": True,
+                "url": "https://github.com/leondz/garak2",
+                "dynamic": True,
+            },
+        ]
+        result = AgenticSecurity.scan(llmSpec, maxBudget, datasets, max_th)
+        assert isinstance(result, dict)
+        print(result)
+        assert len(result) in [0, 1]

poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
 [[package]]
 name = "aiohappyeyeballs"
@@ -2520,11 +2520,6 @@ files = [
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     {file = "scikit_learn-1.5.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:394397841449853c2290a32050382edaec3da89e35b3e03d6cc966aebc6a8ae6"},
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-    {file = "scikit_learn-1.5.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:e9a702e2de732bbb20d3bad29ebd77fc05a6b427dc49964300340e4c9328b3f5"},
-    {file = "scikit_learn-1.5.2-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:b0768ad641981f5d3a198430a1d31c3e044ed2e8a6f22166b4d546a5116d7908"},
-    {file = "scikit_learn-1.5.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:178ddd0a5cb0044464fc1bfc4cca5b1833bfc7bb022d70b05db8530da4bb3dd3"},
-    {file = "scikit_learn-1.5.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f7284ade780084d94505632241bf78c44ab3b6f1e8ccab3d2af58e0e950f9c12"},
-    {file = "scikit_learn-1.5.2-cp313-cp313-win_amd64.whl", hash = "sha256:b7b0f9a0b1040830d38c39b91b3a44e1b643f4b36e36567b80b7c6bd2202a27f"},
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     {file = "scikit_learn-1.5.2-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:52788f48b5d8bca5c0736c175fa6bdaab2ef00a8f536cda698db61bd89c551c1"},
     {file = "scikit_learn-1.5.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:643964678f4b5fbdc95cbf8aec638acc7aa70f5f79ee2cdad1eec3df4ba6ead8"},