Cleanup examples directory

examples/delegation_crewai.py → examples/old/delegation_crewai.py

@@ -10,7 +10,7 @@
 from motleycrew.common import configure_logging
 from motleycrew.tasks import SimpleTask
 
-WORKING_DIR = Path(os.path.realpath("."))
+WORKING_DIR = Path(os.path.realpath(".."))
 
 try:
     from motleycrew import MotleyCrew

examples/research_agent.py → examples/old/research_agent.py

@@ -8,7 +8,7 @@
 # This assumes you have a .env file in the examples folder, containing your OpenAI key
 load_dotenv()
 
-WORKING_DIR = Path(os.path.realpath("."))
+WORKING_DIR = Path(os.path.realpath(".."))
 
 from motleycrew import MotleyCrew
 from motleycrew.storage import MotleyKuzuGraphStore

tests/itest_golden_data/delegation_crewai.json

@@ -1 +1 @@
-"**Exploring the AI Frontier: Key Advances in 2024**\n\nWelcome to the cutting edge of technology! This year, artificial intelligence (AI) has not just stepped up; it's leaped forward, bringing exciting innovations that promise to reshape industries and enhance our daily lives. Here\u2019s a glimpse into some of the most significant AI advancements in 2024.\n\n**Generative AI: From Niche to Necessity**\nOnce a niche technology, generative AI has now gone mainstream, transforming how we create and interact with digital content. Imagine AI systems that can draft articles, create artistic images, or even compose music, all tailored to your preferences! This leap in AI capabilities is not just about enhancing creativity but also about automating routine tasks, freeing up humans to focus on complex problem-solving and innovative thinking.\n\n**The Rise of Multimodal AI**\nThis year has seen remarkable progress in multimodal AI, which combines and processes multiple types of data such as text, images, and voice. These advancements mean AI can understand context better than ever before, making interactions with AI assistants more seamless and intuitive. Whether it\u2019s helping doctors with diagnostic processes or improving customer service bots, multimodal AI is setting a new standard for how we interact with technology.\n\n**Efficiency is Key: Smaller Language Models**\nIn an impressive shift towards sustainability, the AI industry is moving towards smaller, more efficient language models. These models require less computational power, reducing the environmental impact and making advanced AI tools accessible to smaller businesses and startups. This democratization of technology is crucial for fostering innovation and competition, ensuring that the benefits of AI are not just limited to tech giants.\n\n**Ethics Take Center Stage**\nAs AI becomes more integrated into critical sectors such as healthcare, finance, and public services, the focus on ethics has never been more intense. Companies and governments are actively working to implement robust governance frameworks to ensure AI systems are fair, transparent, and accountable. This increased scrutiny is essential to build public trust and ensure that AI technologies are used responsibly and for the benefit of all.\n\n2024 is proving to be a pivotal year in AI, with technologies becoming more sophisticated, ethical, and accessible. These developments are not just transforming businesses; they are shaping the future landscape of our society. As we continue to navigate these changes, the potential of AI to improve our lives and work seems limitless. Stay tuned, and keep exploring \u2013 the future is here, and it's powered by AI!"
+"### The Dawn of Practical AI: Key Advancements in 2024\n\nAs we navigate through 2024, the landscape of artificial intelligence continues to evolve at a breathtaking pace. This year, we are witnessing a significant shift from the experimental to the practical applications of AI technologies, making them more accessible and beneficial for a broader audience. Here are some of the most notable advancements in AI this year:\n\n#### 1. **Generative AI Comes of Age**\nGenerative AI, which captured the world's attention in 2023, is now being actively integrated into business processes. According to the latest McKinsey Global Survey on AI, 65% of respondents report that their organizations are regularly using generative AI, nearly double the percentage from just ten months ago. This surge indicates a robust move towards operationalizing AI in everyday business functions, enhancing creativity, and decision-making processes.\n\n#### 2. **Open Source AI Models**\n2024 marks a significant year for open source AI models. These models have gained substantial traction, empowering businesses to merge these advanced tools with their private or real-time data. This integration is revolutionizing productivity and cost-efficiency across industries. Companies like IBM are at the forefront, contributing actively to the open source AI landscape and setting a precedent for collaboration and innovation.\n\n#### 3. **Multimodal AI**\nThe rise of multimodal AI is another exciting development this year. These systems process and integrate multiple types of data (such as text, images, and sound) to perform tasks that mimic human sensory and cognitive capabilities. This advancement is paving the way for more sophisticated and intuitive AI applications, which promise to transform user interactions and enhance the user experience significantly.\n\n#### 4. **Advancements in Small Language Models**\nWhile large language models have dominated the AI scene in recent years, 2024 is seeing a shift towards smaller, more efficient models. These models are not only easier to train and deploy but also more accessible to a wider range of users and developers. Coupled with advancements in open source, these smaller models are democratizing AI, enabling more localized and customized applications.\n\n#### 5. **Enhanced Model Optimization**\nModel optimization technology has become more accessible, allowing AI developers to streamline and enhance the performance of AI systems without extensive computational resources. This development is crucial in mitigating the ongoing GPU shortages and escalating cloud costs, making AI more sustainable and scalable.\n\n#### 6. **Customized Local Models and Data Pipelines**\nThe trend towards localized models and customized data pipelines is gaining momentum. Businesses are increasingly adopting these tailored solutions to meet specific needs, ensuring greater control over data and compliance with regulatory requirements. This approach not only enhances performance but also boosts security and privacy.\n\n### Conclusion\nThe year 2024 is shaping up to be a landmark year in the AI domain, with significant strides towards making AI technologies more practical, accessible, and integrated into our daily lives and business operations. As these technologies continue to evolve, they promise to unlock new potentials and opportunities across various sectors. The future of AI looks not only promising but also increasingly intertwined with the fabric of our societal and economic structures."

tests/itest_golden_data/single_llama_index.json

@@ -1 +1 @@
-"**Comprehensive Analysis of AI Advancements in 2024**\n\n**1. Introduction**\n2024 marks a significant year in the evolution of artificial intelligence (AI), with technologies reaching new heights of utility and integration into everyday life. This analysis explores the latest advancements, key trends, breakthrough technologies, and their potential impacts on various industries.\n\n**2. Key Trends in AI**\n- **Generative AI**: This technology has matured significantly, becoming more accessible and useful for the general public, not just technology experts. Generative AI's capabilities in creating content, whether text, images, or even code, have reached new levels of sophistication and utility.\n- **Integration of AI in Daily Life**: AI technologies are increasingly being woven into the fabric of daily life, affecting how individuals interact with technology on a fundamental level.\n\n**3. Breakthrough Technologies**\n- **Advanced Generative Models**: Following the trend set by earlier models like ChatGPT, newer generative models in 2024 are expected to be even more powerful and versatile, enabling users to perform more complex tasks with ease.\n\n**4. Industry Impacts**\n- **Shift in Leadership Roles**: There is a noticeable trend of organizations reducing the number of specialized 'chiefs', such as chief data officers and chief AI officers. This suggests a shift towards more integrated roles where AI and data analytics capabilities are becoming essential skills for various managerial positions.\n- **Economic and Social Implications**: As AI becomes more embedded in various sectors, its impact on job roles, productivity, and even societal norms continues to evolve. The democratization of AI tools allows for a broader base of users to innovate and create, potentially leading to significant economic shifts.\n\n**5. Conclusion**\nThe advancements in AI in 2024 are poised to transform industries and societies in profound ways. As generative AI reaches new heights, its accessibility and integration into everyday applications are making it a pivotal year for AI's role in shaping future technologies.\n\nThis report provides a snapshot of the transformative changes expected in 2024, driven by AI advancements. The ongoing evolution of AI continues to offer both challenges and opportunities across the technological landscape."
+"**Comprehensive Analysis Report on AI Advancements in 2024**\n\n**Introduction**\nIn 2024, the field of artificial intelligence (AI) continues to evolve rapidly, with significant advancements and shifts that promise to redefine the interaction between humans and technology. The year has seen a surge in the practical application and integration of AI across various sectors, driven by both technological breakthroughs and increased adoption.\n\n**Key Trends in AI for 2024**\n1. **Generative AI Becomes Mainstream**: Generative AI has transitioned from experimental to mainstream applications, with a notable increase in usage across industries. Organizations are leveraging these technologies to enhance creativity, automate content generation, and drive innovation.\n2. **Realistic Expectations**: There is a growing trend towards setting more realistic expectations for AI deployments, focusing on achievable outcomes and value-driven applications.\n3. **Multimodal AI**: Advancements in multimodal AI, which integrates multiple forms of data such as text, images, and sound, are enhancing the AI's ability to understand and interact in more complex ways.\n4. **Smaller Language Models and Open Source**: There is a shift towards smaller, more efficient language models that are easier to deploy and maintain. Additionally, open-source contributions continue to accelerate the democratization of AI technology.\n5. **GPU Shortages and Cloud Costs**: The industry faces challenges such as GPU shortages and rising cloud costs, which could impact the speed of AI research and deployment.\n6. **Model Optimization and Accessibility**: Tools and techniques for optimizing AI models are becoming more accessible, allowing for more efficient and cost-effective AI solutions.\n7. **Customized Local Models and Data Pipelines**: There is an increasing focus on developing customized AI models and data pipelines tailored to specific organizational needs and contexts.\n\n**Breakthrough Technologies**\n1. **Quantum AI**: Quantum computing is beginning to intersect with AI, leading to potential breakthroughs that could dramatically accelerate problem-solving and data processing capabilities.\n2. **Next-Generation Generative AI**: New generations of generative AI models are emerging, which promise to further enhance the capabilities and applications of AI in creative and analytical tasks.\n\n**Industry Impacts**\n1. **Business Value Realization**: Organizations are increasingly realizing tangible business value from AI, particularly in areas such as automation, customer experience, and decision-making.\n2. **Widespread Adoption Across Sectors**: AI adoption is becoming more widespread across different sectors, including healthcare, finance, retail, and manufacturing, driving significant transformations in these industries.\n3. **Ethical and Regulatory Considerations**: As AI becomes more integrated into societal functions, ethical and regulatory issues are gaining prominence, necessitating frameworks to ensure responsible AI deployment.\n\n**Conclusion**\nThe year 2024 marks a pivotal moment in the evolution of AI, characterized by significant advancements and a shift towards more practical and value-driven applications. As organizations continue to explore and integrate AI technologies, the landscape of human-AI collaboration is set to evolve, offering new opportunities and challenges.\n\nThis report highlights the dynamic nature of AI development and its potential to impact various aspects of modern life and business. As we move forward, continuous monitoring and adaptation will be crucial to harness the full potential of AI advancements."