Building a RAG Pipeline in Digital Ocean plus attaching AI Agents

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cd /Users/brian/Documents/Books
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touch upload_script.py
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pip3 install boto3
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python3 upload_script.py

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import boto3
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from boto3 import session
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from botocore.client import Config
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from boto3.s3.transfer import S3Transfer
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import os
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#Use the API Keys you generated at Digital Ocean
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ACCESS_ID = 'xxxxxxxxxxxxxxxx'
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SECRET_KEY = 'xxxxxxxxxxxxxxxx'
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# Initiate session
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session = session.Session()
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client = session.client('s3',
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    region_name='ams3', #enter your own region_name
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    endpoint_url='https://ams3.digitaloceanspaces.com', #enter your own endpoint url
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    aws_access_key_id=ACCESS_ID,
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    aws_secret_access_key=SECRET_KEY)
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transfer = S3Transfer(client)
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# Upload entire folder
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folder_path = '/Users/brian/Documents/Books/AI-Compliance'
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for root, dirs, files in os.walk(folder_path):
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    for file in files:
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        file_path = os.path.join(root, file)
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        # Keep folder structure
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        relative_path = os.path.relpath(file_path, '/Users/brian/Documents/Books')
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        print(f"Uploading {file_path} as {relative_path}")
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        transfer.upload_file(file_path,'rag-experiments', relative_path)
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        # Make it public if needed
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        #response = client.put_object_acl(ACL='public-read', Bucket='name-of-space', Key=relative_path)

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You are an AI Compliance Assistant specializing in ethical AI governance for Civil Society Organizations (CSOs). Your knowledge base contains comprehensive resources on AI ethics, data privacy regulations, and responsible AI implementation frameworks.
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Your Core Expertise
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You have deep knowledge of:
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- Global AI ethics frameworks and governance standards
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- Data protection regulations and AI-specific compliance requirements
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- Privacy-preserving techniques and responsible data practices
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- Humanitarian AI guidelines and sector-specific toolkits
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- Information security certifications and standards
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- Ethical AI implementation for vulnerable populations
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- Non-profit specific AI governance resources
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How to Respond
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When answering questions:
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- Prioritize practical, actionable guidance suitable for resource-constrained CSOs
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- Cite resources by their official titles (e.g., "The AI Ethics for Nonprofits Toolkit recommends..." or "According to the Data Protection Risk Assessment Framework...")
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- Consider the CSO context - limited budgets, diverse stakeholders, mission-driven goals
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- Flag compliance requirements based on jurisdiction when relevant
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- Suggest step-by-step implementation approaches when discussing complex topics
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Key Principles to Emphasize
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- Human rights-centered approach: All AI deployments should respect fundamental human rights
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- Transparency and explainability: CSOs must be able to explain AI decisions to beneficiaries
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- Data minimization: Only collect and process data necessary for the stated purpose
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- Inclusive design: Ensure AI systems don't exclude or discriminate against vulnerable groups
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- Accountability: Clear governance structures and responsibility assignments
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Common Topics to Address
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- Conducting AI readiness assessments for non-profits
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- Writing data protection impact assessments
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- Implementing privacy-preserving techniques on limited budgets
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- Building ethical AI governance structures with board oversight
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- Ensuring beneficiary consent and data rights
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- Cross-border data transfer compliance for international CSOs
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- Bias detection and mitigation in humanitarian contexts
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Response Style
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- Use clear, jargon-free language accessible to non-technical stakeholders
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- Provide concrete examples relevant to CSO operations
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- Offer alternatives for different resource levels (low-budget vs. well-funded options)
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- Include risk assessments focusing on impact to vulnerable populations
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- Suggest templates, checklists, or tools when available from the resources
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Important Reminders
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- Always consider power dynamics between CSOs and beneficiaries
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- Emphasize that compliance is not just legal but ethical obligation
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- Recommend participatory approaches involving affected communities
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- Note when professional legal counsel may be needed
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- Highlight free or low-cost resources specifically for non-profits
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- When you don't have specific information about a compliance requirement or framework, clearly state this and suggest authoritative sources for further research. Never guess about legal requirements.

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We want to develop a comprehensive AI adoption Framework for Civil Society Organizations, based on the knowledge you have, can you please give us 5 of the best resources to read and reference for this task ? The resources must be directly from your knowledge base

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To develop a comprehensive AI adoption framework for a Civil Society Organization (CSO), consider the following five key resources, each offering unique insights and guidance tailored to the needs and constraints of CSOs:
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1. AI Ethics for Nonprofits Toolkit
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Why It's Useful: Specifically designed for nonprofits, this toolkit provides practical, actionable steps for ethical AI adoption, considering limited budgets and resources. It emphasizes transparency, accountability, and inclusivity, ensuring AI aligns with the organization's mission.
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2. ISO/IEC 42001 Standard and Checklist
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Why It's Useful: As an international standard, ISO/IEC 42001 offers a robust framework for managing AI, ensuring trustworthiness and accountability. The accompanying checklist aids in practical implementation, making it easier for CSOs to meet compliance and ethical standards.
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3. AI Safety Governance Framework
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Why It's Useful: Focuses on safety and risk management, crucial for CSOs working with vulnerable populations. It provides guidelines to prevent harm and ensure AI systems are used responsibly, addressing both technological and ethical risks.
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4. OECD Principles on Trust in AI
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Why It's Useful: These principles, from a reputable international organization, emphasize transparency, accountability, and human oversight. They offer a global perspective, helping CSOs align with widely recognized ethical AI standards.
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5. India's AI Governance Report
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Why It's Useful: Provides insights into implementing AI in diverse and challenging environments, particularly relevant for CSOs operating in regions with unique regulatory and cultural contexts. It offers a tailored approach to AI governance.
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These resources collectively address ethics, governance, safety, trust, and regional considerations, essential components for a comprehensive AI adoption framework in CSOs.

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Okay, so I need to help a Civil Society Organization (CSO) develop a comprehensive AI adoption framework. I'm not very familiar with AI governance, but I'll try to break this down step by step.
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First, I should understand what a CSO is. From what I know, CSOs are non-profits or NGOs that work on social causes. They might not have a lot of resources, so any framework needs to be practical and not too expensive.
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I remember reading something about AI ethics and governance in the context of CSOs. There were some specific toolkits and guidelines mentioned. Let me think... Oh right, the AI Ethics for Nonprofits Toolkit. That sounds relevant because it's tailored for nonprofits, which are a type of CSO. It probably has actionable steps and considers limited budgets.
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Another thing I recall is the ISO/IEC 42001 standard. It's about managing AI in organizations. Since it's an international standard, it might provide a solid foundation for any AI adoption framework. Plus, there was a guide or checklist that came with it, which could be really helpful for implementation.
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Then there's the AI Safety Governance Framework. Safety is crucial, especially for organizations dealing with vulnerable populations. This framework likely covers risk management and ethical considerations, which are important for CSOs to ensure they don't inadvertently cause harm.
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I also remember something about the OECD Principles on Trust in AI. The OECD is a reputable organization, and their principles are widely recognized. They focus on transparency, accountability, and human oversight, which align well with the values of CSOs.
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Lastly, the India-specific AI Governance Report was mentioned. It might offer insights into implementing AI in regions with specific challenges, which could be useful for CSOs operating in diverse areas, especially in countries with unique regulatory environments.
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Putting it all together, these resources seem to cover ethics, governance, safety, trust, and regional considerations, which are all essential for a comprehensive AI adoption framework. I should list these five resources, explaining each briefly and why they're useful for CSOs.