tPjPUddlZddlZddlmZmZmZddlmZddlm Z ddl m Z m Z ddl mZddlmZmZddlmZdd lmZmZdd lmZdd lmZdd lmZd Zeed<dZ eed<Gdde Z!y)N)AnyFinalLiteral) HTTPException)verbose_proxy_logger)CustomGuardraillog_guardrail_information)Logging)get_async_httpx_clienthttpxSpecialProvider)get_secret_str)GuardrailEventHooks LitellmParams)AllMessageValues)GuardrailConfigModel)GenericGuardrailAPIInputs qualifireGUARDRAIL_NAMEzhttps://proxy.qualifire.aiDEFAULT_QUALIFIRE_API_BASEcbeZdZedeefdZ d(dedzdedzdedzdedzdedzd edzd edzd edzd edzd eedzdedzffd Z deddfdZ de ddffd Z defdZ deedeeeeffdZdeedzdeeeefdzfdZdeeefdefdZdeeeefdedzd eedzdeeeefdzdeeeff dZ d)deededzdeeefdeedzddf dZe d)d ed!ed"ed#d$edzdef d%Zeded&dzfd'ZxZS)*QualifireGuardrailreturnc`tjtjtjgSN)rpre_call during_call post_call)clss /home/oem/CyberBrain26-unified/.venv/lib/python3.12/site-packages/litellm/proxy/guardrails/guardrail_hooks/qualifire/qualifire.pyget_supported_event_hooksz,QualifireGuardrail.get_supported_event_hooks#s) ( (  + +  ) )  Napi_keyapi_base evaluation_idprompt_injectionshallucinations_checkgrounding_check pii_checkcontent_moderation_checktool_selection_quality_check assertions on_flaggedc  |xs,tdxstjjd|_|xs4tdxs'tjjdxst |_||_||_||_ ||_ ||_ ||_ | |_ | |_| xsd|_|j!|j|j#s|jsd|_t%t&j(|_| j-dt/|j1t3 |hdi| y) al Initialize the QualifireGuardrail class. Args: api_key: API key for Qualifire (or use QUALIFIRE_API_KEY env var) api_base: Optional custom API base URL (defaults to https://api.qualifire.ai) evaluation_id: Pre-configured evaluation ID from Qualifire dashboard prompt_injections: Enable prompt injection detection (default if no other checks) hallucinations_check: Enable hallucination detection grounding_check: Enable grounding verification pii_check: Enable PII detection content_moderation_check: Enable content moderation tool_selection_quality_check: Enable tool selection quality check assertions: Custom assertions to validate against the output on_flagged: Action when content is flagged: "block" or "monitor" QUALIFIRE_API_KEYQUALIFIRE_BASE_URLblockT) llm_providersupported_event_hooksN)r osenvirongetqualifire_api_keyrqualifire_api_baser$r%r&r'r(r)r*r+r,_validate_on_flagged_has_any_check_enabledr r GuardrailCallback async_handler setdefaultlistr super__init__)selfr"r#r$r%r&r'r(r)r*r+r,kwargs __class__s rr@zQualifireGuardrail.__init__+s*>")!vN;N,O!vSUS]S]SaSabuSv  *23 *zz~~23 **  +!2$8!."(@%,H)$$/ !!$//2**,T5G5G%)D "4AUAgAgh148V8V8X3YZ "6"r!c*|dvrtd|dy)N)r0monitorz0Qualifire guardrail does not support on_flagged=z+; only 'block' and 'monitor' are supported.) ValueError)rAr,s rr9z'QualifireGuardrail._validate_on_flaggedfs1 1 1 B:.Q<<  2r!litellm_paramsc||jxs |j}|j|t| |y)aT The base implementation blindly ``setattr``s every field on ``litellm_params`` (including ``on_flagged``) onto this live instance with no revalidation, so an in-place config update (via the DB/UI, without a restart) could otherwise reintroduce the exact invalid on_flagged value __init__ rejects. Validate the prospective post-update value *before* mutating, so a rejected update leaves the live instance untouched instead of raising after it's already been corrupted. Mirrors LakeraAIGuardrail's own override of this same method. )rGN)r,r9r?update_in_memory_litellm_params)rArGprospective_on_flaggedrCs rrIz2QualifireGuardrail.update_in_memory_litellm_paramsrs9)7(A(A(TT__ !!"89 /~/Nr!c t|j|j|j|j|j |j |jgS)z4Check if any evaluation check is explicitly enabled.)anyr%r&r'r(r)r*r+)rAs rr:z)QualifireGuardrail._has_any_check_enabledsO&&))$$--11   r!messagesc g}|D]}|jdd}|jdd}t|trg}|D]j}t|tr6|jddk(r"|j |jddIt|t sZ|j |ldj |}|t|t r|n t |d}|jd } | r| |d <|jd } | rt| trg} | D]} t| ts| jd i} | jd i}t|t r tj|}| j | jd xsd| jdxsdt|tr|nid| r| |d <|j ||S#tj$ri}YwxYw)a Convert LiteLLM messages to Qualifire API format. Supports tool calls for tool_selection_quality_check. Returns a list of dicts matching the API's ModelInvocationCanonicalMessage schema: { "role": "user" | "assistant" | "system" | "tool", "content": "...", "tool_call_id": "...", # optional "tool_calls": [{"id": "...", "name": "...", "arguments": {...}}] # optional } roleusercontenttypetext rOrQ tool_call_id tool_callsfunction argumentsidname)r[r\rZ) r6 isinstancer>dictappendstrjoinjsonloadsJSONDecodeError)rArM api_messagesmsgrOrQ text_partspart api_messagerWrXapi_tool_callstc function_infoargss r_convert_messages_to_api_formatz2QualifireGuardrail._convert_messages_to_api_formats! 0 -C7766*Dggi,G'4( #0D!$-$((62Bf2L"))$((62*>?#D#."))$/ 0 ))J/&0#&>7CL+K 77>2L.: N+.JjT:!#$B!"d+(*z2(> ,00bA%dC0*'+zz$'7'--&(ffTl&8b(5(9(9&(A(GR5?d5KTQS""0>K -    ,a0 -d$(#7#7*')*s'G((H?Htoolsc |syg}|D]}t|ts|jddk(rX|jdi}|j|jdd|jdd|jdidd|vs|j|jdd|jdd|jdid|r|SdS) a Convert OpenAI-format tools to Qualifire API format. Returns a list of dicts matching the API's ModelInvocationToolDefinition schema: { "name": "...", "description": "...", "parameters": {...} } NrSrYr\rR description parameters)r\rqrr)r]r^r6r_)rAro api_toolstool function_defs r_convert_tools_to_api_formatz/QualifireGuardrail._convert_tools_to_api_formats  D$%88F#z1#'88J#;L$$$0$4$4VR$@+7+;+;M2+N*6*:*:<*Lt^$$$(HHVR$8+/88M2+F*.((<*D ,&y/4/r!resultc|jdgxsg}|D]3}|jdgxsg}|D]}|jdsy5y)a  Check if the Qualifire evaluation result indicates flagged content. Returns True only if there are explicitly flagged items in the evaluation results. A high score (close to 100) indicates GOOD content, low score indicates problems. evaluationResultsresultsflaggedTF)r6)rArwevaluation_results eval_resultrzrs r_check_if_flaggedz$QualifireGuardrail._check_if_flaggedsb%+JJ/BB$G$M2- K!ooi4:G 55#  r!reoutputavailable_toolsc0d|i}|||d<|jrd|d<|jrd|d<|jrd|d<|jrd|d<|jrd|d<|j r"|r d|d <||d <nt jd |r||d <|S) zCBuild payload dictionary for the /api/evaluation/evaluate endpoint.rMrTr%r&r'r(r)r*rznQualifire Guardrail: tool_selection_quality_check enabled but no available_tools provided, skipping this checkr+)r%r&r'r(r)r*rdebug)rArerr+rpayloads r_build_evaluate_payloadz*QualifireGuardrail._build_evaluate_payload s+5l)C   &GH   ! !+/G' (  $ $.2G* +   )-G% & >>#'GK  ( (26G. /  , ,:>67-<)*$**E $.GL !r!dynamic_paramscK|jdxs |j}|jdxs |j}|jdxs |j}|jxsddd} |j |} |rd} t |D]<} | jddk(s| jd d} t| tr| } n|| |xsd| d } |j|}|r|| d <|jd }n5|j|}|j| ||| } |jd}tjd||jj||| d{}|j!|j#}|jd|jdd}tjd|d|d|j%|}|r,|dk(rtj&d|yt)dd|dy7#t($rt*$r}tj,d|d}~wwxYww)a Core Qualifire check logic - shared between hooks. Args: messages: The conversation messages output: The LLM output text (for post_call) dynamic_params: Dynamic parameters from request body available_tools: Available tools from the request (for tool_selection_quality_check) Raises: HTTPException: If content is blocked r$r+r,rRzapplication/json)zX-Qualifire-API-Keyz Content-TyperOrPrQ)r$inputrrMrz/api/evaluation/invoke)rerr+rz/api/evaluation/evaluatez)Qualifire Guardrail: Making request to %s)urlheadersrbNscorestatus)rrz=Qualifire Guardrail: Got result from API, score=%s, status=%srEz\Qualifire Guardrail: Monitoring mode - violation detected but allowing request. Response: %sizViolated guardrail policy)errorqualifire_response) status_codedetailzQualifire Guardrail error: %s)r6r$r+r,r7rnreversedr]r`rvr8rrrr<postraise_for_statusrbrwarningr Exception exception)rArMrrrr$r+r,rre input_textrfrQrrsrresponserwr is_flaggedes r_run_qualifire_checkz'QualifireGuardrail._run_qualifire_check/s( .11/BXdFXFX *..|<O *..|<O $(#9#9#?R.  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Args: inputs: Dictionary containing: - texts: List of texts to check - structured_messages: Structured messages from the request (pre-call only) - tool_calls: Tool calls if present request_data: The original request data input_type: "request" for pre-call, "response" for post-call logging_obj: Optional logging object Returns: GenericGuardrailAPIInputs - unchanged if allowed through Raises: HTTPException: If content is blocked )rstructured_messagesrMNtextsr assistantrRrVrPz9Qualifire Guardrail: No messages or texts found, skippingro)rMrrr))get_guardrail_dynamic_request_body_paramsr6r]r>r`rrr) rArrrrrrMrrrs rapply_guardrailz"QualifireGuardrail.apply_guardrails <!% N N\h N i39**=R2S#'' 3H"zz'2.  #&0&=r3u:%0V\rJK%+Ub PRST$**+fg ".!1!1'!:'')+ (     sCCCCrcddlm}|S)NrQualifireGuardrailConfigModel)8litellm.types.proxy.guardrails.guardrail_hooks.qualifirerrs rget_config_modelz#QualifireGuardrail.get_config_models -,r!) NNNNNNNNNNr0r)__name__ __module__ __qualname__ classmethodr>rr r`boolr@r9rrIr:rr^rrnrvrrrr rrLiteLLMLoggingObjr staticmethodrSr __classcell__)rCs@rrr"s $/B*C  ##$()-,0'+!%0448'+!(9#t9#*9#Tz 9#  $; 9# #Tk 9#9#$;9##'+9#'+Tk9#I$9#$J9#v s t  Om OPT O    @=M8N@SWX\]`be]eXfSg@D%0$s)d2B%0tDQTVYQYNG[^bGb%0NS#X4$$4S>*$d $I$ $ d38n-4 $ c3h $V-1 u'(ud uS#X u cT) u  un 15 E)EE12 E '- E # EEN-d#9:TA--r!r)"rbr4typingrrrfastapirlitellm._loggingr%litellm.integrations.custom_guardrailrr *litellm.litellm_core_utils.litellm_loggingr r&litellm.llms.custom_httpx.http_handlerr r litellm.secret_managers.mainr litellm.types.guardrailsrrlitellm.types.llms.openair3litellm.types.proxy.guardrails.guardrail_hooks.baserlitellm.types.utilsrr__annotations__rrr3r!rrs] &&!1T8G6T9##$@E@R-R-r!