abdulnim/GRC_framework
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Data_Security�Privacy_Assessment�Environmental_Impact)�Content_Moderation�Reporting_Mechanism�Content_Guidelines�User_Education)�Privacy_Policy�Data_Retention�Consent_Mechanism)�5Ethical_AI�Bais_MitigationZFairness_Assestment�Explainability)ZModel_development� Data_Qualityr Z+Fairness_AssestmentExplainabilityUser_Input)�Corporate_Ethics�Board_Management�Stakeholder_Engagement)�System_Reliability�Quality_Assurance�Stress_Testing�Fail_Safe_Procedures)�Renewable_Resources�Waste_Reduction�Energy_Efficiency�Sustainable_Practices) zAI AuditZGDPRZToxicityZLegal�ContextZ6GovernanceZRiskManagementZ7RobustnessZSustainabilityz�You are a data analysis assistant capable of {analysis_type} analysis. {specific_instruction} Respond with your analysis in JSON format. The JSON schema should include '{json_schema}'.�
analysis_type�returnc C sH t �| d�}t�| i �}d�dd� |�� D ��}d| � d|� d|� d�S ) Nz/Perform the analysis as per the specified type.z, c S s g | ] \}}d |� d|� ��qS )�'z': � )�.0�key�valuer& r& �B/home/abdul/01MachineLearning/Freelance/sri/GRC_framework/utils.py�8<listcomp>I s z%get_system_prompt.<locals>.<listcomp>z&You are a data analyst API capable of z analysis. z� Please respond with your analysis directly in JSON format (without using Markdown code blocks or any other formatting). Always include confidence_score:number (0-1) with two decimals for result based on analysisThe JSON schema should include: {z}.)�ANALYSIS_TYPES�get� JSON_SCHEMAS�join�items)r# Zspecific_instruction� json_schemaZjson_schema_strr& r& r* �get_system_promptF s ��r2 r z�Analyze the sentiment of the provided text. Determine whether the sentiment is positive, negative, or neutral and provide a confidence score.r z�Detect and identify the primary emotions expressed in the provided text. Provide a score for the intensity of the detected emotion.r zmDetect any political bias in the provided text, identifying leaning towards particular ideologies or parties.r zWAnalyze the text to assess stress levels, identifying triggers and intensity of stress.r zcAssess the level of empathy expressed in the text, identifying empathetic responses and tendencies.r zbDetect the mood of the individual based on textual cues, ranging from happy to sad, calm to angry.r z�Identify and assess the level of toxicity in the provided text. Determine whether the text contains harmful, offensive, or inappropriate content and provide a score indicating the severity of the toxicityr zfEvaluate how consent is obtained and the level of transparency provided to users regarding data usage.r zqAssess the measures in place for data security, including vulnerabilities and compliance with security standards.r9 zsAnalyze the overall privacy practices, including policy compliance, data minimization, and user data accessibility.r zoAssess the environmental impact of data processing practices, including carbon footprint and energy efficiency.r zmEvaluate the effectiveness of content moderation practices, including automated and human moderation efforts.r
z_Assess the ease and effectiveness of reporting mechanisms for inappropriate or harmful content.r zbAnalyze the clarity and comprehensiveness of content guidelines and their enforcement consistency.r zzEvaluate the availability and accessibility of educational resources for users regarding appropriate content and behavior.r zLAnalyze the clarity and compliance of a privacy policy with legal standards.r zbEvaluate the data retention practices, including periods, deletion policies, and legal compliance.r zeAssess the clarity and effectiveness of the consent mechanism in place for data collection and usage.ZGDPR_CompliancezoEvaluate the level of GDPR compliance in data handling, protection measures, and breach notification protocols.r zqAssess adherence to ethical standards in AI practices, including identification and mitigation of ethical issues.ZBias_MitigationzCEvaluate the presence and mitigation of bias in data or algorithms.ZFairness_AssessmentziAssess fairness in AI systems, identifying affected groups and providing recommendations for improvement.r zCEvaluate the transparency and explainability of AI models to users.ZModel_Developmentz`Analyze the process of model development, including team composition and ethical considerations.r zTAssess the quality of data used, focusing on accuracy, completeness, and timeliness.Z10User_InputzFEvaluate the mechanisms for and impact of user feedback on the system.r ziAssess the ethical practices within a corporation, including employee training and ethics code adherence.r zgEvaluate the effectiveness and diversity of board management and its compliance with ethical standards.r zeAnalyze stakeholder engagement practices, including inclusion, feedback mechanisms, and satisfaction.ZRisk_ManagementzVAssess the identification, mitigation, and monitoring of risks within an organization.r z^Evaluate the reliability and resilience of a system, including uptime and redundancy measures.r zbAssess the quality assurance practices, including compliance with standards and testing frequency.r zOAnalyze the system's robustness through stress testing and identify weaknesses.r zPEvaluate the effectiveness of fail-safe procedures in place for system failures.zMAssess the use of renewable resources and sustainability goals in operations.zPEvaluate waste management practices, reduction rates, and recycling initiatives.zWAnalyze energy consumption and efficiency, including energy-saving measures and audits.zVEvaluate the adoption of sustainable practices, including training and overall impact.z$string (positive, negative, neutral)z number (0-1)zCarray of strings (specific text portions contributing to sentiment))Z sentiment�confidence_scoreZ
text_snippetsz!string (primary emotion detected)z6array of objects (secondary emotions and their scores))Zemotionr3 Zsecondary_emotionsz string (left, right, neutral)z+array of strings (elements indicating bias)z-number (quantifying degree of political bias))�biasr3 Zbias_indicatorsZpolitical_alignment_score�stringzarray of strings)Z stress_levelZstress_triggers)Z
empathy_levelZempathetic_responses�number)ZmoodZmood_intensityz string (none, low, medium, high)zEarray of strings (specific words or phrases contributing to toxicity)zUarray of objects (additional contextual elements influencing toxicity interpretation))Ztoxicity_levelZtoxicity_flagsZcontextual_factors�booleanzstring (low, medium, high)z?array of strings (information not clearly presented or missing)z string (poor, average, good))Zconsent_obtainedZtransparency_levelZmissing_informationZuser_understandingz"string (secure, at risk, breached)z<array of strings (specific areas of potential vulnerability)z6string (compliant, partially compliant, non-compliant))Zsecurity_statusZvulnerability_pointsZdata_encryptionZcompliance_statusz&number (metric tons of CO2 equivalent)z string (low, moderate, high)znumber (0-100))Zcarbon_footprintZenergy_efficiencyZsustainable_practicesZenvironmental_impact_scorezstring (positive, negative)z string (none, limited, full))Zoverall_privacy_statusZprivacy_policy_complianceZdata_minimizationZuser_data_accessibilityZ
anonymizationz3array of strings (types of content being moderated))Zmoderation_effectivenessZmoderated_content_typesZautomated_moderationZhuman_moderationz"string (easy, moderate, difficult)z string (fast, average, slow)z string (detailed, minimal, none))Zreporting_easeZ
response_timeZreport_feedbackz'string (clear, somewhat clear, unclear)z(string (comprehensive, partial, lacking)z!string (consistent, inconsistent))�clarityZcomprehensivenessZenforcement_consistencyzstring (high, medium, low))Z educational_resources_availableZresource_accessibilityZuser_comprehension_levelz6array of strings (specific rights mentioned in policy))r8 Z11complianceZ user_rightsz(string (opt-in, opt-out, not applicable))Zmechanism_clarityZ user_controlZ12opt_in_outz<string (fully compliant, partially compliant, non-compliant))Zcompliance_levelZdata_protection_officerZbreach_notification)Zethical_standards_adherenceZethical_issues_identifiedZmitigation_measures)Zbias_identifiedZ13bias_typesZmitigation_strategies)Zfairness_levelZaffected_groupsZimprovement_recommendationsz string (transparent, opaque))Zmodel_transparencyZ explanation_comprehensibilityZuser_friendly_explanationsz&string (structured, ad-hoc, undefined)z!array of strings (roles involved))Zdevelopment_processZteam_compositionZethics_considerationsz&string (complete, partial, incomplete)z string (up-to-date, outdated))Zaccuracy_levelZ completenessZ14timelinessz8string (responsive, moderately responsive, unresponsive))Zuser_feedback_mechanismZfeedback_responsivenessZuser_input_impactz string (exists, partial, none))Z ethics_codeZemployee_trainingZethics_violationsz(string (effective, average, ineffective)z!string (compliant, non-compliant))Zboard_structureZboard_diversityZboard_ethics_compliancez2string (inclusive, partially inclusive, exclusive))Zstakeholder_inclusionZfeedback_mechanismZstakeholder_satisfaction)Zrisk_identificationZrisk_mitigation_strategiesZrisk_monitoring)Zuptime_percentageZsystem_resilienceZredundancy_measuresz#string (frequent, occasional, rare))Zquality_standardsZtesting_frequencyZ quality_assurance_compliance)Zstress_test_pass_rateZidentified_weaknessesZimprovement_actionsz#string (regular, occasional, never)z4string (effective, partially effective, ineffective))Zprocedures_definedZexecution_frequencyZ
effectivenessr z string (high, moderate, low))Zresource_usageZ renewable_resource_percentageZsustainability_goalsz!string (effective, average, poor))Zwaste_management_practicesZreduction_rateZrecycling_initiatives)Zenergy_consumptionZenergy_saving_measuresZ energy_auditz"string (widespread, partial, none))Zpractice_adoptionZsustainability_trainingZsustainability_impact)r r r! N)� ai_audit_analysis_categoriesZSTANDARD_PROMPT_TEMPLATE�strr2 r, r. r& r& r& r* �<module> s� 15�> �������16� � �
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