fix importing _ENTERPRISE_Aporia

litellm/proxy/common_utils/callback_utils.py

@@ -119,7 +119,9 @@ def initialize_callbacks_on_proxy(
                 )
                 imported_list.append(lakera_moderations_object)
             elif isinstance(callback, str) and callback == "aporia_prompt_injection":
-                from enterprise.enterprise_hooks.aporia_ai import _ENTERPRISE_Aporia
+                from litellm.proxy.guardrails.guardrail_hooks.aporia_ai import (
+                    _ENTERPRISE_Aporia,
+                )
 
                 if premium_user is not True:
                     raise Exception(

litellm/proxy/guardrails/guardrail_hooks/aporia_ai.py

@@ -0,0 +1,212 @@
+# +-------------------------------------------------------------+
+#
+#           Use AporiaAI for your LLM calls
+#
+# +-------------------------------------------------------------+
+#  Thank you users! We ❤️ you! - Krrish & Ishaan
+
+import os
+import sys
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import asyncio
+import json
+import sys
+import traceback
+import uuid
+from datetime import datetime
+from typing import Any, List, Literal, Optional, Union
+
+import aiohttp
+import httpx
+from fastapi import HTTPException
+
+import litellm
+from litellm._logging import verbose_proxy_logger
+from litellm.caching import DualCache
+from litellm.integrations.custom_guardrail import CustomGuardrail
+from litellm.litellm_core_utils.logging_utils import (
+    convert_litellm_response_object_to_str,
+)
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.guardrails.guardrail_helpers import should_proceed_based_on_metadata
+from litellm.types.guardrails import GuardrailEventHooks
+
+litellm.set_verbose = True
+
+GUARDRAIL_NAME = "aporia"
+
+
+class _ENTERPRISE_Aporia(CustomGuardrail):
+    def __init__(
+        self, api_key: Optional[str] = None, api_base: Optional[str] = None, **kwargs
+    ):
+        self.async_handler = AsyncHTTPHandler(
+            timeout=httpx.Timeout(timeout=600.0, connect=5.0)
+        )
+        self.aporia_api_key = api_key or os.environ["APORIO_API_KEY"]
+        self.aporia_api_base = api_base or os.environ["APORIO_API_BASE"]
+        self.event_hook: GuardrailEventHooks
+
+        super().__init__(**kwargs)
+
+    #### CALL HOOKS - proxy only ####
+    def transform_messages(self, messages: List[dict]) -> List[dict]:
+        supported_openai_roles = ["system", "user", "assistant"]
+        default_role = "other"  # for unsupported roles - e.g. tool
+        new_messages = []
+        for m in messages:
+            if m.get("role", "") in supported_openai_roles:
+                new_messages.append(m)
+            else:
+                new_messages.append(
+                    {
+                        "role": default_role,
+                        **{key: value for key, value in m.items() if key != "role"},
+                    }
+                )
+
+        return new_messages
+
+    async def prepare_aporia_request(
+        self, new_messages: List[dict], response_string: Optional[str] = None
+    ) -> dict:
+        data: dict[str, Any] = {}
+        if new_messages is not None:
+            data["messages"] = new_messages
+        if response_string is not None:
+            data["response"] = response_string
+
+        # Set validation target
+        if new_messages and response_string:
+            data["validation_target"] = "both"
+        elif new_messages:
+            data["validation_target"] = "prompt"
+        elif response_string:
+            data["validation_target"] = "response"
+
+        verbose_proxy_logger.debug("Aporia AI request: %s", data)
+        return data
+
+    async def make_aporia_api_request(
+        self, new_messages: List[dict], response_string: Optional[str] = None
+    ):
+        data = await self.prepare_aporia_request(
+            new_messages=new_messages, response_string=response_string
+        )
+
+        _json_data = json.dumps(data)
+
+        """
+        export APORIO_API_KEY=<your key>
+        curl https://gr-prd-trial.aporia.com/some-id \
+            -X POST \
+            -H "X-APORIA-API-KEY: $APORIO_API_KEY" \
+            -H "Content-Type: application/json" \
+            -d '{
+                "messages": [
+                    {
+                    "role": "user",
+                    "content": "This is a test prompt"
+                    }
+                ],
+                }
+'
+        """
+
+        response = await self.async_handler.post(
+            url=self.aporia_api_base + "/validate",
+            data=_json_data,
+            headers={
+                "X-APORIA-API-KEY": self.aporia_api_key,
+                "Content-Type": "application/json",
+            },
+        )
+        verbose_proxy_logger.debug("Aporia AI response: %s", response.text)
+        if response.status_code == 200:
+            # check if the response was flagged
+            _json_response = response.json()
+            action: str = _json_response.get(
+                "action"
+            )  # possible values are modify, passthrough, block, rephrase
+            if action == "block":
+                raise HTTPException(
+                    status_code=400,
+                    detail={
+                        "error": "Violated guardrail policy",
+                        "aporia_ai_response": _json_response,
+                    },
+                )
+
+    async def async_post_call_success_hook(
+        self,
+        data: dict,
+        user_api_key_dict: UserAPIKeyAuth,
+        response,
+    ):
+        from litellm.proxy.common_utils.callback_utils import (
+            add_guardrail_to_applied_guardrails_header,
+        )
+        from litellm.types.guardrails import GuardrailEventHooks
+
+        """
+        Use this for the post call moderation with Guardrails
+        """
+        event_type: GuardrailEventHooks = GuardrailEventHooks.post_call
+        if self.should_run_guardrail(data=data, event_type=event_type) is not True:
+            return
+
+        response_str: Optional[str] = convert_litellm_response_object_to_str(response)
+        if response_str is not None:
+            await self.make_aporia_api_request(
+                response_string=response_str, new_messages=data.get("messages", [])
+            )
+
+            add_guardrail_to_applied_guardrails_header(
+                request_data=data, guardrail_name=self.guardrail_name
+            )
+
+        pass
+
+    async def async_moderation_hook(  ### 👈 KEY CHANGE ###
+        self,
+        data: dict,
+        user_api_key_dict: UserAPIKeyAuth,
+        call_type: Literal["completion", "embeddings", "image_generation"],
+    ):
+        from litellm.proxy.common_utils.callback_utils import (
+            add_guardrail_to_applied_guardrails_header,
+        )
+        from litellm.types.guardrails import GuardrailEventHooks
+
+        event_type: GuardrailEventHooks = GuardrailEventHooks.during_call
+        if self.should_run_guardrail(data=data, event_type=event_type) is not True:
+            return
+
+        # old implementation - backwards compatibility
+        if (
+            await should_proceed_based_on_metadata(
+                data=data,
+                guardrail_name=GUARDRAIL_NAME,
+            )
+            is False
+        ):
+            return
+
+        new_messages: Optional[List[dict]] = None
+        if "messages" in data and isinstance(data["messages"], list):
+            new_messages = self.transform_messages(messages=data["messages"])
+
+        if new_messages is not None:
+            await self.make_aporia_api_request(new_messages=new_messages)
+            add_guardrail_to_applied_guardrails_header(
+                request_data=data, guardrail_name=self.guardrail_name
+            )
+        else:
+            verbose_proxy_logger.warning(
+                "Aporia AI: not running guardrail. No messages in data"
+            )
+            pass

litellm/proxy/guardrails/init_guardrails.py

@@ -113,9 +113,7 @@ def init_guardrails_v2(all_guardrails: dict):
 
         # Init guardrail CustomLoggerClass
         if litellm_params["guardrail"] == "aporia":
-            from litellm.proxy.enterprise.enterprise_hooks.aporia_ai import (
+            from guardrail_hooks.aporia_ai import _ENTERPRISE_Aporia
-                _ENTERPRISE_Aporia,
-            )
 
             _aporia_callback = _ENTERPRISE_Aporia(
                 api_base=litellm_params["api_base"],