40. Multi-agent Systems#
In this notebook we see how easy it is to work with multi-agent systems. We will study two open-source repos, Crew AI and Agno.
References:
https://www.deeplearning.ai/short-courses/multi-ai-agent-systems-with-crewai/
Examples to complement the ones below: https://docs.crewai.com/examples/example
A nice introduction to ideas about agents, “You Should Write an Agent”: https://fly.io/blog/everyone-write-an-agent
from google.colab import drive
drive.mount('/content/drive') # Add My Drive/<>
import os
os.chdir('drive/My Drive')
os.chdir('Books_Writings/NLPBook/')
Mounted at /content/drive
%%capture
import numpy as np
import pandas as pd
import os
import textwrap
def p80(text):
print(textwrap.fill(text, 80))
return None
40.1. Crew AI#
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try:
import pydantic
except ImportError:
os.system('!pip install pydantic --quiet')
!pip install --upgrade qdrant_client
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%run keys.ipynb
40.2. Application: Marketing Analysts#
https://docs.crewai.com/en/concepts/tools
import os
from crewai import Agent, Task, Crew
# Importing crewAI tools
from crewai_tools import (
DirectoryReadTool,
FileReadTool,
SerperDevTool,
WebsiteSearchTool
)
# Set up API keys, if needed
# os.environ["SERPER_API_KEY"] = "Your Key" # serper.dev API key
# os.environ["OPENAI_API_KEY"] = "Your Key"
# Instantiate tools
docs_tool = DirectoryReadTool(directory='./blog-posts')
file_tool = FileReadTool()
search_tool = SerperDevTool()
# web_rag_tool = WebsiteSearchTool()
# Create agents
researcher = Agent(
role='Market Research Analyst',
goal='Provide up-to-date market analysis of the AI industry',
backstory='An expert analyst with a keen eye for market trends.',
# tools=[search_tool, web_rag_tool],
tools=[search_tool],
verbose=True
)
writer = Agent(
role='Content Writer',
goal='Craft engaging blog posts about the AI industry',
backstory='A skilled writer with a passion for technology.',
tools=[docs_tool, file_tool],
verbose=True
)
# Define tasks
research = Task(
description='Research the latest trends in the AI industry and provide a summary.',
expected_output='A summary of the top 3 trending developments in the AI industry with a unique perspective on their significance.',
agent=researcher
)
write = Task(
description='Write an engaging blog post about the AI industry, based on the research analysts summary. Draw inspiration from the latest blog posts in the directory.',
expected_output='A 4-paragraph blog post formatted in markdown with engaging, informative, and accessible content, avoiding complex jargon.',
agent=writer,
output_file='blog-posts/new_post.md' # The final blog post will be saved here
)
# Assemble a crew with planning enabled
crew = Crew(
agents=[researcher, writer],
tasks=[research, write],
verbose=True,
planning=True, # Enable planning feature
)
# Execute tasks
crew.kickoff()
╭──────────────────────────────────────────── Crew Execution Started ─────────────────────────────────────────────╮ │ │ │ Crew Execution Started │ │ Name: crew │ │ ID: eb454aea-6c99-44c7-926a-1c9106e6190c │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[2025-11-18 04:24:30][INFO]: Planning the crew execution
╭──────────────────────────────────────────────── Task Completion ────────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: 30092e02-ba0e-477b-94f5-08fecc3c604f │ │ Agent: Task Execution Planner │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: Market Research Analyst │ │ │ │ Task: Research the latest trends in the AI industry and provide a summary.1. Start by utilizing the 'Search │ │ the internet with Serper' tool, ensuring that the SERPER_API_KEY is correctly set in the environment │ │ variables. │ │ 2. Formulate a search query that encapsulates 'latest trends in the AI industry'. For example: 'latest │ │ developments in artificial intelligence 2023'. │ │ 3. Execute the search command using the tool, which will retrieve the top 10 relevant results. │ │ 4. Carefully analyze these results to identify the top 3 trending developments in AI. │ │ 5. Note down unique perspectives on the significance of each trend, considering various aspects like market │ │ impact, societal implications, and technological advancements. │ │ 6. Compose a comprehensive summary that outlines these trends along with the unique perspectives gathered. │ │ 7. Ensure the summary is concise yet informative, ready for further use by the Content Writer. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────── 🔧 Agent Tool Execution ────────────────────────────────────────────╮ │ │ │ Agent: Market Research Analyst │ │ │ │ Thought: Action: Search the internet with Serper │ │ │ │ Using Tool: Search the internet with Serper │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────────── Tool Input ───────────────────────────────────────────────────╮ │ │ │ { │ │ "search_query": "latest developments in artificial intelligence 2024" │ │ } │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────────── Tool Output ──────────────────────────────────────────────────╮ │ │ │ {'searchParameters': {'q': 'latest developments in artificial intelligence 2024', 'type': 'search', 'num': │ │ 10, 'engine': 'google'}, 'organic': [{'title': 'The Top Artificial Intelligence Trends | IBM', 'link': │ │ 'https://www.ibm.com/think/insights/artificial-intelligence-trends', 'snippet': 'Adapting to emerging trends │ │ is essential to maximizing potential, minimizing risk and responsibly scaling generative AI adoption.', │ │ 'position': 1}, {'title': 'AI Pulse: Top AI Trends from 2024 - A Look Back | Trend Micro (US)', 'link': │ │ 'https://www.trendmicro.com/en_us/research/25/a/top-ai-trends-from-2024-review.html', 'snippet': "In this │ │ edition of AI Pulse, let's look back at top AI trends from 2024 in the rear view so we can more clearly │ │ predicts AI trends for 2025 and beyond.", 'position': 2}, {'title': '6 Game-Changing AI Breakthroughs That │ │ Defined 2024 - Forbes', 'link': │ │ 'https://www.forbes.com/sites/bernardmarr/2024/12/16/6-game-changing-ai-breakthroughs-that-defined-2024/', │ │ 'snippet': "From Apple's entry into generative AI to unprecedented achievements in robotics and art, 2024 │ │ marked a transformative year in artificial ...", 'position': 3}, {'title': 'Generative AI Developments & │ │ Trends in 2024: A Timeline', 'link': │ │ 'https://www.channelinsider.com/security/managed-services/generative-ai-developments-trends-year-in-review/', │ │ 'snippet': "In 2024, GenAI's influence continues to streamline workflows, enhance operations, and deliver new │ │ value for businesses.", 'position': 4, 'sitelinks': [{'title': 'What is GenAI?', 'link': │ │ 'https://www.channelinsider.com/security/managed-services/generative-ai-developments-trends-year-in-review/#w │ │ hat-is-gen-ai'}, {'title': 'timeline of GenAI...', 'link': │ │ 'https://www.channelinsider.com/security/managed-services/generative-ai-developments-trends-year-in-review/#a │ │ -timeline-of-gen-ai-developments'}, {'title': 'GenAI tools released in 2024', 'link': │ │ 'https://www.channelinsider.com/security/managed-services/generative-ai-developments-trends-ye... │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────── 🔧 Agent Tool Execution ────────────────────────────────────────────╮ │ │ │ Agent: Market Research Analyst │ │ │ │ Thought: Action: Search the internet with Serper │ │ │ │ Using Tool: Search the internet with Serper │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: Market Research Analyst │ │ │ │ Final Answer: │ │ In 2024, the artificial intelligence industry has seen transformative developments that are shaping the │ │ landscape of technology, business, and society. Three key trends stand out as pivotal in defining the current │ │ AI era: │ │ │ │ 1. Generative AI Expansion and Integration: │ │ Generative AI technologies, including advanced language models and multimodal systems, continue to push the │ │ boundaries of creation and automation. Beyond chatbots, generative AI is being integrated into diverse │ │ business workflows to enhance productivity, automate complex tasks, and improve customer engagement. This │ │ trend is significant not only for its technological innovation—enabling AI systems to generate text, images, │ │ and even code autonomously—but also for the market impact. Organizations are leveraging generative AI to │ │ streamline operations and create new value propositions, signaling a shift from experimental adoption to │ │ essential business tools. However, this rapid adoption comes with increased scrutiny on ethical use and │ │ content accuracy, leading to the evolution of governance frameworks. │ │ │ │ 2. AI Governance, Ethics, and Regulatory Growth: │ │ With AI becoming a fact of life in 2024, attention to responsible usage and regulatory measures has │ │ intensified. US federal agencies doubled their AI-related regulations in 2024, reflecting a global push │ │ towards governance structures aiming to mitigate risks such as bias, misinformation, and privacy violations. │ │ The societal implications are profound—governance and ethical AI practices determine the trust and acceptance │ │ of AI systems at scale. This trend underscores the balance between innovation and societal responsibility, │ │ which is critical as AI permeates sectors including healthcare, finance, and public administration. The focus │ │ on ethics also includes managing the societal impacts of AI on employment patterns, ensuring technology │ │ complements human creativity and judgment rather than merely replacing jobs. │ │ │ │ 3. Workforce Transformation and Productivity Gains: │ │ AI's influence on the workforce marks a fundamental shift in how work is performed. Studies indicate AI is │ │ expected to improve employee productivity by about 40%, automating repetitive tasks while augmenting human │ │ decision-making and creativity. This transition presents both opportunities and challenges: while some jobs │ │ face disruption, new roles centered around AI management, oversight, and augmentation are emerging. The │ │ societal implication here is significant, as the labor market must adapt to these changes through reskilling │ │ and education. From a market perspective, businesses prioritizing AI adoption report competitive advantages, │ │ signaling that workforce transformation is a key driver for sustained economic growth in the AI era. │ │ │ │ In summary, the AI industry in 2024 is characterized by the maturation of generative AI technologies, a │ │ robust framework of governance and ethical practice development, and an evolving workforce paradigm that │ │ maximizes productivity and human potential. These trends collectively highlight how AI is transitioning from │ │ niche innovation to an integral component of the global economy and societal fabric, demanding a thoughtful │ │ approach to technology deployment, regulation, and human impact. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── Task Completion ────────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: 4adcdaa6-e6e5-404b-bdc4-2d1911a6cf36 │ │ Agent: Market Research Analyst │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────── 🔧 Agent Tool Execution ────────────────────────────────────────────╮ │ │ │ Agent: Content Writer │ │ │ │ Thought: Action: List files in directory │ │ │ │ Using Tool: List files in directory │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────────── Tool Input ───────────────────────────────────────────────────╮ │ │ │ { │ │ "directory": "./blog-posts" │ │ } │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────────── Tool Output ──────────────────────────────────────────────────╮ │ │ │ File paths: │ │ -./blog-posts/new_post.md │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────── 🔧 Agent Tool Execution ────────────────────────────────────────────╮ │ │ │ Agent: Content Writer │ │ │ │ Thought: Action: Read a file's content │ │ │ │ Using Tool: Read a file's content │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: Content Writer │ │ │ │ Final Answer: │ │ ```markdown │ │ # The AI Industry in 2024: Transforming Technology, Society, and Work │ │ │ │ Artificial intelligence continues to reshape our world in remarkable ways. In 2024, the AI industry is not │ │ just about futuristic concepts anymore; it’s a vital force driving innovation across businesses, healthcare, │ │ education, and beyond. From helping companies streamline tasks to enhancing customer experiences, AI’s │ │ growing presence is transforming how we live and work. As this technology becomes increasingly embedded in │ │ daily life, understanding the key trends shaping AI can help us navigate both its promises and challenges. │ │ │ │ One of the most exciting developments is the rapid expansion of generative AI. These advanced systems go │ │ beyond simple chatbots—they create text, images, and even code autonomously. Businesses are integrating │ │ generative AI into workflows to automate complex tasks and boost productivity in ways that were once │ │ unimaginable. This shift means AI is moving from a novel experiment to an essential tool for creating value. │ │ However, with great power comes greater responsibility, and companies are now focusing more on ethical use │ │ and content accuracy to ensure AI benefits everyone fairly. │ │ │ │ At the same time, the conversation around AI governance and ethics is intensifying. Governments worldwide, │ │ especially in the US, have doubled down on regulations to tackle risks like misinformation, bias, and privacy │ │ concerns. Establishing clear rules and ethical frameworks is crucial for earning public trust and ensuring AI │ │ serves society responsibly. Meanwhile, efforts to manage AI’s impact on jobs highlight the need for │ │ thoughtful policies that complement human creativity instead of simply replacing workers. This balancing act │ │ between innovation and responsibility is shaping the future of AI adoption. │ │ │ │ Finally, AI is transforming the workforce itself. By automating repetitive work and supporting human │ │ decision-making, AI is boosting employee productivity by nearly 40%. While some jobs are changing or │ │ disappearing, new roles focused on working alongside AI are emerging. This evolution calls for widespread │ │ reskilling and education to prepare people for the future of work. As businesses that embrace AI gain │ │ competitive edges, it’s clear workforce transformation isn’t just a side effect—it’s a driver of economic │ │ growth. Looking ahead, AI holds incredible potential to enhance human potential and drive progress, provided │ │ we approach it with care and foresight. │ │ ``` │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── Task Completion ────────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: f66dea4a-31cb-4e63-b07a-097300c45e06 │ │ Agent: Content Writer │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
CrewOutput(raw='```markdown\n# The AI Industry in 2024: Transforming Technology, Society, and Work\n\nArtificial intelligence continues to reshape our world in remarkable ways. In 2024, the AI industry is not just about futuristic concepts anymore; it’s a vital force driving innovation across businesses, healthcare, education, and beyond. From helping companies streamline tasks to enhancing customer experiences, AI’s growing presence is transforming how we live and work. As this technology becomes increasingly embedded in daily life, understanding the key trends shaping AI can help us navigate both its promises and challenges.\n\nOne of the most exciting developments is the rapid expansion of generative AI. These advanced systems go beyond simple chatbots—they create text, images, and even code autonomously. Businesses are integrating generative AI into workflows to automate complex tasks and boost productivity in ways that were once unimaginable. This shift means AI is moving from a novel experiment to an essential tool for creating value. However, with great power comes greater responsibility, and companies are now focusing more on ethical use and content accuracy to ensure AI benefits everyone fairly.\n\nAt the same time, the conversation around AI governance and ethics is intensifying. Governments worldwide, especially in the US, have doubled down on regulations to tackle risks like misinformation, bias, and privacy concerns. Establishing clear rules and ethical frameworks is crucial for earning public trust and ensuring AI serves society responsibly. Meanwhile, efforts to manage AI’s impact on jobs highlight the need for thoughtful policies that complement human creativity instead of simply replacing workers. This balancing act between innovation and responsibility is shaping the future of AI adoption.\n\nFinally, AI is transforming the workforce itself. By automating repetitive work and supporting human decision-making, AI is boosting employee productivity by nearly 40%. While some jobs are changing or disappearing, new roles focused on working alongside AI are emerging. This evolution calls for widespread reskilling and education to prepare people for the future of work. As businesses that embrace AI gain competitive edges, it’s clear workforce transformation isn’t just a side effect—it’s a driver of economic growth. Looking ahead, AI holds incredible potential to enhance human potential and drive progress, provided we approach it with care and foresight.\n```', pydantic=None, json_dict=None, tasks_output=[TaskOutput(description="Research the latest trends in the AI industry and provide a summary.1. Start by utilizing the 'Search the internet with Serper' tool, ensuring that the SERPER_API_KEY is correctly set in the environment variables. \n2. Formulate a search query that encapsulates 'latest trends in the AI industry'. For example: 'latest developments in artificial intelligence 2023'. \n3. Execute the search command using the tool, which will retrieve the top 10 relevant results. \n4. Carefully analyze these results to identify the top 3 trending developments in AI. \n5. Note down unique perspectives on the significance of each trend, considering various aspects like market impact, societal implications, and technological advancements. \n6. Compose a comprehensive summary that outlines these trends along with the unique perspectives gathered. \n7. Ensure the summary is concise yet informative, ready for further use by the Content Writer.", name="Research the latest trends in the AI industry and provide a summary.1. Start by utilizing the 'Search the internet with Serper' tool, ensuring that the SERPER_API_KEY is correctly set in the environment variables. \n2. Formulate a search query that encapsulates 'latest trends in the AI industry'. For example: 'latest developments in artificial intelligence 2023'. \n3. Execute the search command using the tool, which will retrieve the top 10 relevant results. \n4. Carefully analyze these results to identify the top 3 trending developments in AI. \n5. Note down unique perspectives on the significance of each trend, considering various aspects like market impact, societal implications, and technological advancements. \n6. Compose a comprehensive summary that outlines these trends along with the unique perspectives gathered. \n7. Ensure the summary is concise yet informative, ready for further use by the Content Writer.", expected_output='A summary of the top 3 trending developments in the AI industry with a unique perspective on their significance.', summary='Research the latest trends in the AI industry and provide...', raw="In 2024, the artificial intelligence industry has seen transformative developments that are shaping the landscape of technology, business, and society. Three key trends stand out as pivotal in defining the current AI era:\n\n1. Generative AI Expansion and Integration:\nGenerative AI technologies, including advanced language models and multimodal systems, continue to push the boundaries of creation and automation. Beyond chatbots, generative AI is being integrated into diverse business workflows to enhance productivity, automate complex tasks, and improve customer engagement. This trend is significant not only for its technological innovation—enabling AI systems to generate text, images, and even code autonomously—but also for the market impact. Organizations are leveraging generative AI to streamline operations and create new value propositions, signaling a shift from experimental adoption to essential business tools. However, this rapid adoption comes with increased scrutiny on ethical use and content accuracy, leading to the evolution of governance frameworks. \n\n2. AI Governance, Ethics, and Regulatory Growth:\nWith AI becoming a fact of life in 2024, attention to responsible usage and regulatory measures has intensified. US federal agencies doubled their AI-related regulations in 2024, reflecting a global push towards governance structures aiming to mitigate risks such as bias, misinformation, and privacy violations. The societal implications are profound—governance and ethical AI practices determine the trust and acceptance of AI systems at scale. This trend underscores the balance between innovation and societal responsibility, which is critical as AI permeates sectors including healthcare, finance, and public administration. The focus on ethics also includes managing the societal impacts of AI on employment patterns, ensuring technology complements human creativity and judgment rather than merely replacing jobs.\n\n3. Workforce Transformation and Productivity Gains:\nAI's influence on the workforce marks a fundamental shift in how work is performed. Studies indicate AI is expected to improve employee productivity by about 40%, automating repetitive tasks while augmenting human decision-making and creativity. This transition presents both opportunities and challenges: while some jobs face disruption, new roles centered around AI management, oversight, and augmentation are emerging. The societal implication here is significant, as the labor market must adapt to these changes through reskilling and education. From a market perspective, businesses prioritizing AI adoption report competitive advantages, signaling that workforce transformation is a key driver for sustained economic growth in the AI era.\n\nIn summary, the AI industry in 2024 is characterized by the maturation of generative AI technologies, a robust framework of governance and ethical practice development, and an evolving workforce paradigm that maximizes productivity and human potential. These trends collectively highlight how AI is transitioning from niche innovation to an integral component of the global economy and societal fabric, demanding a thoughtful approach to technology deployment, regulation, and human impact.", pydantic=None, json_dict=None, agent='Market Research Analyst', output_format=<OutputFormat.RAW: 'raw'>, messages=[{'role': 'system', 'content': 'You are Market Research Analyst. An expert analyst with a keen eye for market trends.\nYour personal goal is: Provide up-to-date market analysis of the AI industry\nYou ONLY have access to the following tools, and should NEVER make up tools that are not listed here:\n\nTool Name: Search the internet with Serper\nTool Arguments: {\'search_query\': {\'description\': \'Mandatory search query you want to use to search the internet\', \'type\': \'str\'}}\nTool Description: A tool that can be used to search the internet with a search_query. Supports different search types: \'search\' (default), \'news\'\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: you should always think about what to do\nAction: the action to take, only one name of [Search the internet with Serper], just the name, exactly as it\'s written.\nAction Input: the input to the action, just a simple JSON object, enclosed in curly braces, using " to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce all necessary information is gathered, return the following format:\n\n```\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n```'}, {'role': 'user', 'content': "\nCurrent Task: Research the latest trends in the AI industry and provide a summary.1. Start by utilizing the 'Search the internet with Serper' tool, ensuring that the SERPER_API_KEY is correctly set in the environment variables. \n2. Formulate a search query that encapsulates 'latest trends in the AI industry'. For example: 'latest developments in artificial intelligence 2023'. \n3. Execute the search command using the tool, which will retrieve the top 10 relevant results. \n4. Carefully analyze these results to identify the top 3 trending developments in AI. \n5. Note down unique perspectives on the significance of each trend, considering various aspects like market impact, societal implications, and technological advancements. \n6. Compose a comprehensive summary that outlines these trends along with the unique perspectives gathered. \n7. Ensure the summary is concise yet informative, ready for further use by the Content Writer.\n\nThis is the expected criteria for your final answer: A summary of the top 3 trending developments in the AI industry with a unique perspective on their significance.\nyou MUST return the actual complete content as the final answer, not a summary.\n\nBegin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it!\n\nThought:"}, {'role': 'assistant', 'content': 'Action: Search the internet with Serper\nAction Input: {"search_query":"latest developments in artificial intelligence 2024"}\nObservation: {\'searchParameters\': {\'q\': \'latest developments in artificial intelligence 2024\', \'type\': \'search\', \'num\': 10, \'engine\': \'google\'}, \'organic\': [{\'title\': \'The Top Artificial Intelligence Trends | IBM\', \'link\': \'https://www.ibm.com/think/insights/artificial-intelligence-trends\', \'snippet\': \'Adapting to emerging trends is essential to maximizing potential, minimizing risk and responsibly scaling generative AI adoption.\', \'position\': 1}, {\'title\': \'AI Pulse: Top AI Trends from 2024 - A Look Back | Trend Micro (US)\', \'link\': \'https://www.trendmicro.com/en_us/research/25/a/top-ai-trends-from-2024-review.html\', \'snippet\': "In this edition of AI Pulse, let\'s look back at top AI trends from 2024 in the rear view so we can more clearly predicts AI trends for 2025 and beyond.", \'position\': 2}, {\'title\': \'6 Game-Changing AI Breakthroughs That Defined 2024 - Forbes\', \'link\': \'https://www.forbes.com/sites/bernardmarr/2024/12/16/6-game-changing-ai-breakthroughs-that-defined-2024/\', \'snippet\': "From Apple\'s entry into generative AI to unprecedented achievements in robotics and art, 2024 marked a transformative year in artificial ...", \'position\': 3}, {\'title\': \'Generative AI Developments & Trends in 2024: A Timeline\', \'link\': \'https://www.channelinsider.com/security/managed-services/generative-ai-developments-trends-year-in-review/\', \'snippet\': "In 2024, GenAI\'s influence continues to streamline workflows, enhance operations, and deliver new value for businesses.", \'position\': 4, \'sitelinks\': [{\'title\': \'What is GenAI?\', \'link\': \'https://www.channelinsider.com/security/managed-services/generative-ai-developments-trends-year-in-review/#what-is-gen-ai\'}, {\'title\': \'timeline of GenAI...\', \'link\': \'https://www.channelinsider.com/security/managed-services/generative-ai-developments-trends-year-in-review/#a-timeline-of-gen-ai-developments\'}, {\'title\': \'GenAI tools released in 2024\', \'link\': \'https://www.channelinsider.com/security/managed-services/generative-ai-developments-trends-year-in-review/#gen-ai-tools-released-in-2024\'}]}, {\'title\': \'The 2025 AI Index Report | Stanford HAI\', \'link\': \'https://hai.stanford.edu/ai-index/2025-ai-index-report\', \'snippet\': \'In 2024, U.S. federal agencies introduced 59 AI-related regulations—more than double the number in 2023—and issued by twice as many agencies. Globally, ...\', \'position\': 5, \'sitelinks\': [{\'title\': \'2024\', \'link\': \'https://hai.stanford.edu/ai-index/2024-ai-index-report\'}, {\'title\': \'Status\', \'link\': \'https://hai.stanford.edu/events/presenting-the-2025-ai-index\'}, {\'title\': \'Research and Development\', \'link\': \'https://hai.stanford.edu/ai-index/2025-ai-index-report/research-and-development\'}, {\'title\': \'Economy\', \'link\': \'https://hai.stanford.edu/ai-index/2025-ai-index-report/economy\'}]}, {\'title\': \'AI in Action: 5 Essential Findings from the 2024 Federal AI Use Case ...\', \'link\': \'https://www.cio.gov/ai-in-action/\', \'snippet\': \'1. Compared to 2023, Federal agencies have more than doubled their AI use in the last year, citing improvements to operational efficiency and the execution of ...\', \'position\': 6}, {\'title\': \'131 AI Statistics and Trends for (2024) | National University\', \'link\': \'https://www.nu.edu/blog/ai-statistics-trends/\', \'snippet\': \'AI Statistics explores the latest trends in artificial intelligence (AI). Gain insights into adoption rates, AI jobs, and applications.\', \'position\': 7, \'sitelinks\': [{\'title\': \'Fast Facts About Artificial...\', \'link\': \'https://www.nu.edu/blog/ai-statistics-trends/#facts\'}, {\'title\': \'AI Demographics\', \'link\': \'https://www.nu.edu/blog/ai-statistics-trends/#demo\'}, {\'title\': \'Business Owners and AI\', \'link\': \'https://www.nu.edu/blog/ai-statistics-trends/#business\'}]}, {\'title\': \'State of Generative AI in the Enterprise 2024 | Deloitte US\', \'link\': \'https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-generative-ai-in-enterprise.html\', \'snippet\': \'ROI with AI is encouraging, regulation and risk loom large, and agentic AI is on the rise—but businesses are setting their own pace on the path to value ...\', \'position\': 8, \'sitelinks\': [{\'title\': \'Looking Back At 2024\', \'link\': \'https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-generative-ai-in-enterprise.html#:~:text=Looking%20back%20at%202024\'}, {\'title\': \'Generative Ai Insights And...\', \'link\': \'https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-generative-ai-in-enterprise.html#:~:text=Generative%20AI%20insights%20and%20solutions%20from%20across%20Deloitte\'}, {\'title\': \'Generative Ai And The Future...\', \'link\': \'https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-generative-ai-in-enterprise.html#:~:text=Generative%20AI%20and%20the%20future%20of%20work\'}]}, {\'title\': \'The Future of Business: AI Innovations to Watch in 2024\', \'link\': \'https://www.launchconsulting.com/posts/the-future-of-business-ai-innovations-to-watch-in-2024\', \'snippet\': \'AI Trends in 2024 · 1. Generative AI: Beyond Chatbots · 2. The Emergence of Small Language Models · 3. Multi-Modal AI Experiences · 4. AI Empowerment for ...\', \'position\': 9, \'sitelinks\': [{\'title\': \'Ai Trends In 2024\', \'link\': \'https://www.launchconsulting.com/posts/the-future-of-business-ai-innovations-to-watch-in-2024#:~:text=AI%20Trends%20in%202024\'}, {\'title\': \'1. Generative Ai: Beyond...\', \'link\': \'https://www.launchconsulting.com/posts/the-future-of-business-ai-innovations-to-watch-in-2024#:~:text=1.%20Generative%20AI%3A%20Beyond%20Chatbots\'}, {\'title\': \'4. Ai Empowerment For...\', \'link\': \'https://www.launchconsulting.com/posts/the-future-of-business-ai-innovations-to-watch-in-2024#:~:text=4.%20AI%20Empowerment%20for%20Professionals\'}]}], \'peopleAlsoAsk\': [{\'question\': \'What is the 30% rule in AI?\', \'snippet\': \'What is the 30% rule in AI? The 30% Rule means AI does most of the repetitive work, about 70%, while humans focus on the remaining 30%. This ensures technology supports rather than replaces people. Human skills like judgment, creativity, and ethics remain at the core.\', \'title\': \'Be human, stay relevant: The 30% rule in AI and top entry-level jobs for ...\', \'link\': \'https://m.economictimes.com/wealth/earn/be-human-stay-relevant-the-30-rule-in-ai-and-top-entry-level-jobs-for-the-future/what-is-the-30-rule-in-ai/slideshow/124378673.cms\'}, {\'question\': \'What is the most advanced AI we have right now?\', \'snippet\': \'5 EXAMPLES OF THE MOST ADVANCED AI\\n1\\nLarge language models. Organizations rely on large language models to generate human-like text, interpret queries, and summarize massive documents. ...\\n2\\nComputer vision systems. ...\\n3\\nNeural machine translation. ...\\n4\\nAutonomous robotics. ...\\n5\\nGenerative design solutions.\', \'title\': \'5 examples of the most advanced AI - Lumenalta\', \'link\': \'https://lumenalta.com/insights/5-examples-of-the-most-advanced-ai\'}, {\'question\': "What\'s the best AI stock to buy?", \'snippet\': \'WHAT ARE THE TOP 4 ARTIFICIAL INTELLIGENCE (AI) STOCKS TO BUY RIGHT NOW?\\n1\\nNvidia. Nvidia (NVDA +1.77%) has been a top AI investment pick since the AI arms race kicked off in 2023. ...\\n2\\nTaiwan Semiconductor. Taiwan Semiconductor (TSM +0.93%) is another key player in the AI arms race. ...\\n3\\nAlphabet. ...\\n4\\nAmazon.\', \'title\': \'What Are the Top 4 Artificial Intelligence (AI) Stocks to Buy Right ...\', \'link\': \'https://www.fool.com/investing/2025/11/16/what-are-the-top-4-artificial-intelligence-ai-stoc/\'}], \'relatedSearches\': [{\'query\': \'Latest AI technology 2024\'}, {\'query\': \'Future of AI examples\'}, {\'query\': \'AI future predictions\'}, {\'query\': \'Artificial intelligence and the future of humans\'}, {\'query\': \'Top 10 AI trends\'}, {\'query\': \'Artificial intelligence trends in business\'}, {\'query\': \'Current trends in artificial intelligence PDF\'}, {\'query\': \'AI advancements 2025\'}], \'credits\': 1}'}, {'role': 'assistant', 'content': 'Action: Search the internet with Serper\nAction Input: {"search_query":"top AI trends 2024 market impact societal implications technological advancements"}\nObservation: {\'searchParameters\': {\'q\': \'top AI trends 2024 market impact societal implications technological advancements\', \'type\': \'search\', \'num\': 10, \'engine\': \'google\'}, \'organic\': [{\'title\': \'Top 10 AI Trends of 2024 - AI Magazine\', \'link\': \'https://aimagazine.com/articles/top-10-ai-trends-of-2024\', \'snippet\': \'Top 10 AI Trends of 2024 · 10. AI governance and ethics · 9. AI talent demand · 7. Open source AI · 7. Agentic AI · 6. AI in scientific research · 5.\', \'position\': 1}, {\'title\': \'131 AI Statistics and Trends for (2024) | National University\', \'link\': \'https://www.nu.edu/blog/ai-statistics-trends/\', \'snippet\': \'AI is expected to improve employee productivity by 40%. · 83% of companies reported that using AI in their business strategies is a top priority.\', \'position\': 2}, {\'title\': \'McKinsey technology trends outlook 2025\', \'link\': \'https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-top-trends-in-tech\', \'snippet\': "From the rise of robotics and autonomous systems to the imperative for responsible AI innovations, this year\'s technology developments ...", \'position\': 3}, {\'title\': \'The 2025 AI Index Report | Stanford HAI\', \'link\': \'https://hai.stanford.edu/ai-index/2025-ai-index-report\', \'snippet\': \'Nearly 90% of notable AI models in 2024 came from industry, up from 60% in 2023, while academia remains the top source of highly cited research. Model scale ...\', \'position\': 4}, {\'title\': \'AI Pulse: Top AI Trends from 2024 - A Look Back | Trend Micro (US)\', \'link\': \'https://www.trendmicro.com/en_us/research/25/a/top-ai-trends-from-2024-review.html\', \'snippet\': \'AI Comes Into Its Own. 2024 may go down as the year AI stopped being a technological novelty and became—more consequentially—a Fact of Life.\', \'position\': 5}, {\'title\': "IDC\'s 2024 AI opportunity study: Top five AI trends to watch", \'link\': \'https://blogs.microsoft.com/blog/2024/11/12/idcs-2024-ai-opportunity-study-top-five-ai-trends-to-watch/\', \'snippet\': "Below is a look at the top trends we\'re seeing in IDC\'s study and the impact of those trends on organizations working with AI today.", \'position\': 6}, {\'title\': \'AI Will Shape the Future of Marketing - Professional & Executive ...\', \'link\': \'https://professional.dce.harvard.edu/blog/ai-will-shape-the-future-of-marketing/\', \'snippet\': \'From chatbots to social media management to full-scale marketing campaigns and automation, artificial intelligence is changing the way marketers do their jobs.\', \'position\': 7}, {\'title\': \'The Future of Artificial Intelligence | IBM\', \'link\': \'https://www.ibm.com/think/insights/artificial-intelligence-future\', \'snippet\': \'Societal evolution as a result of AI · Climate concerns · Improved automation · Job disruption · Deepfakes and misinformation · Emotional and sociological impacts.\', \'position\': 8}, {\'title\': \'Artificial Intelligence 2024: Trends, Impacts, Implications\', \'link\': \'https://politicsrights.com/artificial-intelligence-2024-trends-impacts/\', \'snippet\': "Economic Shifts: AI\'s rapid adoption could lead to more pronounced productivity gains but also contribute to job market disruptions. · Ethical ...", \'position\': 9, \'sitelinks\': [{\'title\': \'The Artificial Intelligence...\', \'link\': \'https://politicsrights.com/artificial-intelligence-2024-trends-impacts/#:~:text=The%20Artificial%20Intelligence%20Index%20Report,-The%20%60%60Artificial%20Intelligence%20Index\'}, {\'title\': \'Research And Development\', \'link\': \'https://politicsrights.com/artificial-intelligence-2024-trends-impacts/#:~:text=Research%20and%20Development,-The%20report%20identifies%20significant%20trends\'}, {\'title\': \'Read More\', \'link\': \'https://politicsrights.com/artificial-intelligence-2024-trends-impacts/#:~:text=Read%20More\'}]}, {\'title\': "AI Will Transform the Global Economy. Let\'s Make Sure It Benefits ...", \'link\': \'https://www.imf.org/en/blogs/articles/2024/01/14/ai-will-transform-the-global-economy-lets-make-sure-it-benefits-humanity\', \'snippet\': \'AI will affect almost 40 percent of jobs around the world, replacing some and complementing others. We need a careful balance of policies to tap ...\', \'position\': 10}], \'relatedSearches\': [{\'query\': \'Artificial intelligence growth statistics\'}, {\'query\': \'Artificial intelligence Index report 2024\'}, {\'query\': \'10 cool facts on artificial intelligence\'}, {\'query\': \'Artificial intelligence Index report 2025\'}, {\'query\': \'AI usage statistics\'}, {\'query\': \'AI statistics 2025\'}, {\'query\': \'Stanford AI Index Report 2025 pdf\'}, {\'query\': \'Top 10 AI trends\'}], \'credits\': 1}'}, {'role': 'assistant', 'content': "Thought: From the search results, the top AI trends in 2024 highlight key areas such as the widespread adoption and integration of AI in the workplace, the rise of generative AI technologies, and increased emphasis on AI governance and ethics. There is also discussion about the significant market impact including productivity improvements, regulatory developments, and social implications such as job disruption and misinformation. To provide a comprehensive summary, I will extract and synthesize insights from these results focusing on the top three trending developments alongside their unique market, societal, and technological significance.\n\nFinal Answer: \n\nIn 2024, the artificial intelligence industry has seen transformative developments that are shaping the landscape of technology, business, and society. Three key trends stand out as pivotal in defining the current AI era:\n\n1. Generative AI Expansion and Integration:\nGenerative AI technologies, including advanced language models and multimodal systems, continue to push the boundaries of creation and automation. Beyond chatbots, generative AI is being integrated into diverse business workflows to enhance productivity, automate complex tasks, and improve customer engagement. This trend is significant not only for its technological innovation—enabling AI systems to generate text, images, and even code autonomously—but also for the market impact. Organizations are leveraging generative AI to streamline operations and create new value propositions, signaling a shift from experimental adoption to essential business tools. However, this rapid adoption comes with increased scrutiny on ethical use and content accuracy, leading to the evolution of governance frameworks. \n\n2. AI Governance, Ethics, and Regulatory Growth:\nWith AI becoming a fact of life in 2024, attention to responsible usage and regulatory measures has intensified. US federal agencies doubled their AI-related regulations in 2024, reflecting a global push towards governance structures aiming to mitigate risks such as bias, misinformation, and privacy violations. The societal implications are profound—governance and ethical AI practices determine the trust and acceptance of AI systems at scale. This trend underscores the balance between innovation and societal responsibility, which is critical as AI permeates sectors including healthcare, finance, and public administration. The focus on ethics also includes managing the societal impacts of AI on employment patterns, ensuring technology complements human creativity and judgment rather than merely replacing jobs.\n\n3. Workforce Transformation and Productivity Gains:\nAI's influence on the workforce marks a fundamental shift in how work is performed. Studies indicate AI is expected to improve employee productivity by about 40%, automating repetitive tasks while augmenting human decision-making and creativity. This transition presents both opportunities and challenges: while some jobs face disruption, new roles centered around AI management, oversight, and augmentation are emerging. The societal implication here is significant, as the labor market must adapt to these changes through reskilling and education. From a market perspective, businesses prioritizing AI adoption report competitive advantages, signaling that workforce transformation is a key driver for sustained economic growth in the AI era.\n\nIn summary, the AI industry in 2024 is characterized by the maturation of generative AI technologies, a robust framework of governance and ethical practice development, and an evolving workforce paradigm that maximizes productivity and human potential. These trends collectively highlight how AI is transitioning from niche innovation to an integral component of the global economy and societal fabric, demanding a thoughtful approach to technology deployment, regulation, and human impact."}]), TaskOutput(description="Write an engaging blog post about the AI industry, based on the research analysts summary. Draw inspiration from the latest blog posts in the directory.1. Begin by using the 'List files in directory' tool to view the content available in the './blog-posts' directory, which will provide insights into existing blog posts for inspiration. \n2. Analyze the titles and topics of the listed blog posts to identify common themes and engagement strategies. \n3. Reference the summary provided by the Market Research Analyst, ensuring to integrate the top 3 trends in a coherent manner. \n4. Draft a 4-paragraph blog post formatted in Markdown, covering the trends in a way that is engaging and accessible to readers. \n5. In the first paragraph, introduce the AI industry and its growing significance. \n6. In the second paragraph, delve into the first trend from the summary, explaining its relevance and potential impact. \n7. In the third paragraph, explore the second trend and its significance, making sure to maintain reader interest. \n8. In the fourth paragraph, discuss the third trend and conclude with a thoughtful reflection on the future of AI, emphasizing its transformative potential. \n9. Edit the draft for clarity, ensuring it avoids complex jargon and maintains a conversational tone suitable for a broad audience. \n10. Finally, review the post to ensure all key points are covered and that it aligns well with the existing content in the directory, making any necessary adjustments.", name="Write an engaging blog post about the AI industry, based on the research analysts summary. Draw inspiration from the latest blog posts in the directory.1. Begin by using the 'List files in directory' tool to view the content available in the './blog-posts' directory, which will provide insights into existing blog posts for inspiration. \n2. Analyze the titles and topics of the listed blog posts to identify common themes and engagement strategies. \n3. Reference the summary provided by the Market Research Analyst, ensuring to integrate the top 3 trends in a coherent manner. \n4. Draft a 4-paragraph blog post formatted in Markdown, covering the trends in a way that is engaging and accessible to readers. \n5. In the first paragraph, introduce the AI industry and its growing significance. \n6. In the second paragraph, delve into the first trend from the summary, explaining its relevance and potential impact. \n7. In the third paragraph, explore the second trend and its significance, making sure to maintain reader interest. \n8. In the fourth paragraph, discuss the third trend and conclude with a thoughtful reflection on the future of AI, emphasizing its transformative potential. \n9. Edit the draft for clarity, ensuring it avoids complex jargon and maintains a conversational tone suitable for a broad audience. \n10. Finally, review the post to ensure all key points are covered and that it aligns well with the existing content in the directory, making any necessary adjustments.", expected_output='A 4-paragraph blog post formatted in markdown with engaging, informative, and accessible content, avoiding complex jargon.', summary='Write an engaging blog post about the AI industry, based...', raw='```markdown\n# The AI Industry in 2024: Transforming Technology, Society, and Work\n\nArtificial intelligence continues to reshape our world in remarkable ways. In 2024, the AI industry is not just about futuristic concepts anymore; it’s a vital force driving innovation across businesses, healthcare, education, and beyond. From helping companies streamline tasks to enhancing customer experiences, AI’s growing presence is transforming how we live and work. As this technology becomes increasingly embedded in daily life, understanding the key trends shaping AI can help us navigate both its promises and challenges.\n\nOne of the most exciting developments is the rapid expansion of generative AI. These advanced systems go beyond simple chatbots—they create text, images, and even code autonomously. Businesses are integrating generative AI into workflows to automate complex tasks and boost productivity in ways that were once unimaginable. This shift means AI is moving from a novel experiment to an essential tool for creating value. However, with great power comes greater responsibility, and companies are now focusing more on ethical use and content accuracy to ensure AI benefits everyone fairly.\n\nAt the same time, the conversation around AI governance and ethics is intensifying. Governments worldwide, especially in the US, have doubled down on regulations to tackle risks like misinformation, bias, and privacy concerns. Establishing clear rules and ethical frameworks is crucial for earning public trust and ensuring AI serves society responsibly. Meanwhile, efforts to manage AI’s impact on jobs highlight the need for thoughtful policies that complement human creativity instead of simply replacing workers. This balancing act between innovation and responsibility is shaping the future of AI adoption.\n\nFinally, AI is transforming the workforce itself. By automating repetitive work and supporting human decision-making, AI is boosting employee productivity by nearly 40%. While some jobs are changing or disappearing, new roles focused on working alongside AI are emerging. This evolution calls for widespread reskilling and education to prepare people for the future of work. As businesses that embrace AI gain competitive edges, it’s clear workforce transformation isn’t just a side effect—it’s a driver of economic growth. Looking ahead, AI holds incredible potential to enhance human potential and drive progress, provided we approach it with care and foresight.\n```', pydantic=None, json_dict=None, agent='Content Writer', output_format=<OutputFormat.RAW: 'raw'>, messages=[{'role': 'system', 'content': 'You are Content Writer. A skilled writer with a passion for technology.\nYour personal goal is: Craft engaging blog posts about the AI industry\nYou ONLY have access to the following tools, and should NEVER make up tools that are not listed here:\n\nTool Name: List files in directory\nTool Arguments: {}\nTool Description: A tool that can be used to list ./blog-posts\'s content.\nTool Name: Read a file\'s content\nTool Arguments: {\'file_path\': {\'description\': \'Mandatory file full path to read the file\', \'type\': \'str\'}, \'start_line\': {\'description\': \'Line number to start reading from (1-indexed)\', \'type\': \'UnionType[int, NoneType]\'}, \'line_count\': {\'description\': \'Number of lines to read. If None, reads the entire file\', \'type\': \'UnionType[int, NoneType]\'}}\nTool Description: A tool that reads the content of a file. To use this tool, provide a \'file_path\' parameter with the path to the file you want to read. Optionally, provide \'start_line\' to start reading from a specific line and \'line_count\' to limit the number of lines read.\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: you should always think about what to do\nAction: the action to take, only one name of [List files in directory, Read a file\'s content], just the name, exactly as it\'s written.\nAction Input: the input to the action, just a simple JSON object, enclosed in curly braces, using " to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce all necessary information is gathered, return the following format:\n\n```\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n```'}, {'role': 'user', 'content': "\nCurrent Task: Write an engaging blog post about the AI industry, based on the research analysts summary. Draw inspiration from the latest blog posts in the directory.1. Begin by using the 'List files in directory' tool to view the content available in the './blog-posts' directory, which will provide insights into existing blog posts for inspiration. \n2. Analyze the titles and topics of the listed blog posts to identify common themes and engagement strategies. \n3. Reference the summary provided by the Market Research Analyst, ensuring to integrate the top 3 trends in a coherent manner. \n4. Draft a 4-paragraph blog post formatted in Markdown, covering the trends in a way that is engaging and accessible to readers. \n5. In the first paragraph, introduce the AI industry and its growing significance. \n6. In the second paragraph, delve into the first trend from the summary, explaining its relevance and potential impact. \n7. In the third paragraph, explore the second trend and its significance, making sure to maintain reader interest. \n8. In the fourth paragraph, discuss the third trend and conclude with a thoughtful reflection on the future of AI, emphasizing its transformative potential. \n9. Edit the draft for clarity, ensuring it avoids complex jargon and maintains a conversational tone suitable for a broad audience. \n10. Finally, review the post to ensure all key points are covered and that it aligns well with the existing content in the directory, making any necessary adjustments.\n\nThis is the expected criteria for your final answer: A 4-paragraph blog post formatted in markdown with engaging, informative, and accessible content, avoiding complex jargon.\nyou MUST return the actual complete content as the final answer, not a summary.\n\nThis is the context you're working with:\nIn 2024, the artificial intelligence industry has seen transformative developments that are shaping the landscape of technology, business, and society. Three key trends stand out as pivotal in defining the current AI era:\n\n1. Generative AI Expansion and Integration:\nGenerative AI technologies, including advanced language models and multimodal systems, continue to push the boundaries of creation and automation. Beyond chatbots, generative AI is being integrated into diverse business workflows to enhance productivity, automate complex tasks, and improve customer engagement. This trend is significant not only for its technological innovation—enabling AI systems to generate text, images, and even code autonomously—but also for the market impact. Organizations are leveraging generative AI to streamline operations and create new value propositions, signaling a shift from experimental adoption to essential business tools. However, this rapid adoption comes with increased scrutiny on ethical use and content accuracy, leading to the evolution of governance frameworks. \n\n2. AI Governance, Ethics, and Regulatory Growth:\nWith AI becoming a fact of life in 2024, attention to responsible usage and regulatory measures has intensified. US federal agencies doubled their AI-related regulations in 2024, reflecting a global push towards governance structures aiming to mitigate risks such as bias, misinformation, and privacy violations. The societal implications are profound—governance and ethical AI practices determine the trust and acceptance of AI systems at scale. This trend underscores the balance between innovation and societal responsibility, which is critical as AI permeates sectors including healthcare, finance, and public administration. The focus on ethics also includes managing the societal impacts of AI on employment patterns, ensuring technology complements human creativity and judgment rather than merely replacing jobs.\n\n3. Workforce Transformation and Productivity Gains:\nAI's influence on the workforce marks a fundamental shift in how work is performed. Studies indicate AI is expected to improve employee productivity by about 40%, automating repetitive tasks while augmenting human decision-making and creativity. This transition presents both opportunities and challenges: while some jobs face disruption, new roles centered around AI management, oversight, and augmentation are emerging. The societal implication here is significant, as the labor market must adapt to these changes through reskilling and education. From a market perspective, businesses prioritizing AI adoption report competitive advantages, signaling that workforce transformation is a key driver for sustained economic growth in the AI era.\n\nIn summary, the AI industry in 2024 is characterized by the maturation of generative AI technologies, a robust framework of governance and ethical practice development, and an evolving workforce paradigm that maximizes productivity and human potential. These trends collectively highlight how AI is transitioning from niche innovation to an integral component of the global economy and societal fabric, demanding a thoughtful approach to technology deployment, regulation, and human impact.\n\nBegin! This is VERY important to you, use the tools available and give your best Final Answer, your job depends on it!\n\nThought:"}, {'role': 'assistant', 'content': 'Action: List files in directory\nAction Input: {"directory":"./blog-posts"}\nObservation: File paths: \n-./blog-posts/new_post.md'}, {'role': 'assistant', 'content': 'Action: Read a file\'s content\nAction Input: {"file_path":"./blog-posts/new_post.md","start_line":1,"line_count":20}\nObservation: ```markdown\n# Navigating the New Frontier: Key Trends Shaping the AI Industry in 2024\n\nThe AI industry is undergoing one of its most exciting transformations to date. Thanks to groundbreaking improvements in AI efficiency, today’s models can deliver powerful results at dramatically lower costs. This leap forward means AI can now reach more businesses and applications than ever before, paving the way for autonomous AI agents that handle complex tasks on their own while keeping expenses manageable. From small startups to large enterprises, the door is wide open for AI’s integration into everyday operations, driving innovation and productivity across the board.\n\nAt the same time, AI is evolving beyond simple tools into personalized companions and collaborators. Leading tech companies are crafting AI entities that not only understand personalized needs but also connect with human emotions. These AI coworkers and companions promise richer, more meaningful interactions, helping to combat loneliness and enhance workplace dynamics. However, as these relationships deepen, it’s crucial to consider the psychological impact and ethical concerns that come with forming emotional bonds with AI systems.\n\nAlongside these advances, the AI industry grapples with significant privacy challenges. Personalized AI agents thrive by learning from detailed user interactions, but storing and using this data conflicts with privacy regulations like Europe’s GDPR. Balancing the benefits of customization with the need to protect user rights demands careful navigation. The ongoing conversation about AI ethics, user consent, and data privacy will shape how these technologies develop responsibly in the years ahead.\n\nTogether, these trends illustrate a future where AI is not just smarter and more accessible but also more human-centric and ethically aware. The companies that succeed will be those embracing innovation while thoughtfully addressing the psychological and regulatory complexities. As AI moves from experimental to everyday, this balanced approach will unlock its true transformative potential—powering a smarter, more connected world for everyone.\n```'}, {'role': 'assistant', 'content': 'Thought: I have reviewed the latest blog post in the directory and gained insights into the tone and style of writing—it is engaging, forward-looking, and avoids heavy jargon. It balances AI technological advances with ethical and social considerations, emphasizing accessibility for a broad audience. Now, I will draft a 4-paragraph blog post about the AI industry in 2024, integrating the top three trends from the research analyst summary and keeping a conversational tone similar to the example.\n\nFinal Answer:\n\n```markdown\n# The AI Industry in 2024: Transforming Technology, Society, and Work\n\nArtificial intelligence continues to reshape our world in remarkable ways. In 2024, the AI industry is not just about futuristic concepts anymore; it’s a vital force driving innovation across businesses, healthcare, education, and beyond. From helping companies streamline tasks to enhancing customer experiences, AI’s growing presence is transforming how we live and work. As this technology becomes increasingly embedded in daily life, understanding the key trends shaping AI can help us navigate both its promises and challenges.\n\nOne of the most exciting developments is the rapid expansion of generative AI. These advanced systems go beyond simple chatbots—they create text, images, and even code autonomously. Businesses are integrating generative AI into workflows to automate complex tasks and boost productivity in ways that were once unimaginable. This shift means AI is moving from a novel experiment to an essential tool for creating value. However, with great power comes greater responsibility, and companies are now focusing more on ethical use and content accuracy to ensure AI benefits everyone fairly.\n\nAt the same time, the conversation around AI governance and ethics is intensifying. Governments worldwide, especially in the US, have doubled down on regulations to tackle risks like misinformation, bias, and privacy concerns. Establishing clear rules and ethical frameworks is crucial for earning public trust and ensuring AI serves society responsibly. Meanwhile, efforts to manage AI’s impact on jobs highlight the need for thoughtful policies that complement human creativity instead of simply replacing workers. This balancing act between innovation and responsibility is shaping the future of AI adoption.\n\nFinally, AI is transforming the workforce itself. By automating repetitive work and supporting human decision-making, AI is boosting employee productivity by nearly 40%. While some jobs are changing or disappearing, new roles focused on working alongside AI are emerging. This evolution calls for widespread reskilling and education to prepare people for the future of work. As businesses that embrace AI gain competitive edges, it’s clear workforce transformation isn’t just a side effect—it’s a driver of economic growth. Looking ahead, AI holds incredible potential to enhance human potential and drive progress, provided we approach it with care and foresight.\n```'}])], token_usage=UsageMetrics(total_tokens=15272, prompt_tokens=11501, cached_prompt_tokens=0, completion_tokens=3771, successful_requests=6))
╭──────────────────────────────────────────────── Crew Completion ────────────────────────────────────────────────╮ │ │ │ Crew Execution Completed │ │ Name: crew │ │ ID: eb454aea-6c99-44c7-926a-1c9106e6190c │ │ Tool Args: │ │ Final Output: ```markdown │ │ # The AI Industry in 2024: Transforming Technology, Society, and Work │ │ │ │ Artificial intelligence continues to reshape our world in remarkable ways. In 2024, the AI industry is not │ │ just about futuristic concepts anymore; it’s a vital force driving innovation across businesses, healthcare, │ │ education, and beyond. From helping companies streamline tasks to enhancing customer experiences, AI’s │ │ growing presence is transforming how we live and work. As this technology becomes increasingly embedded in │ │ daily life, understanding the key trends shaping AI can help us navigate both its promises and challenges. │ │ │ │ One of the most exciting developments is the rapid expansion of generative AI. These advanced systems go │ │ beyond simple chatbots—they create text, images, and even code autonomously. Businesses are integrating │ │ generative AI into workflows to automate complex tasks and boost productivity in ways that were once │ │ unimaginable. This shift means AI is moving from a novel experiment to an essential tool for creating value. │ │ However, with great power comes greater responsibility, and companies are now focusing more on ethical use │ │ and content accuracy to ensure AI benefits everyone fairly. │ │ │ │ At the same time, the conversation around AI governance and ethics is intensifying. Governments worldwide, │ │ especially in the US, have doubled down on regulations to tackle risks like misinformation, bias, and privacy │ │ concerns. Establishing clear rules and ethical frameworks is crucial for earning public trust and ensuring AI │ │ serves society responsibly. Meanwhile, efforts to manage AI’s impact on jobs highlight the need for │ │ thoughtful policies that complement human creativity instead of simply replacing workers. This balancing act │ │ between innovation and responsibility is shaping the future of AI adoption. │ │ │ │ Finally, AI is transforming the workforce itself. By automating repetitive work and supporting human │ │ decision-making, AI is boosting employee productivity by nearly 40%. While some jobs are changing or │ │ disappearing, new roles focused on working alongside AI are emerging. This evolution calls for widespread │ │ reskilling and education to prepare people for the future of work. As businesses that embrace AI gain │ │ competitive edges, it’s clear workforce transformation isn’t just a side effect—it’s a driver of economic │ │ growth. Looking ahead, AI holds incredible potential to enhance human potential and drive progress, provided │ │ we approach it with care and foresight. │ │ ``` │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
40.3. Application: Financial Analyst#
Here we create an agent that prepares the forward-looking outlook for Nvidia, using a sample article from Seeking Alpha.
40.4. Collect the Tools needed#
All the tools are listed here: https://docs.crewai.com/tools/browserbaseloadtool
Here we use two tools:
A tool for scraping websites from a given URL:
ScrapeWebsiteTool,A tool to create a searchable vector store:
TXTSearchTool
from crewai_tools import ScrapeWebsiteTool, TXTSearchTool, WebsiteSearchTool
import requests
# Instantiate tools
docs_tool = DirectoryReadTool(directory='./blog-posts')
file_tool = FileReadTool()
search_tool = SerperDevTool()
# web_rag_tool = WebsiteSearchTool()
# Initialize the tool, potentially passing the session
url = 'https://nvidianews.nvidia.com/news/nvidia-announces-financial-results-for-fourth-quarter-and-fiscal-2025#:~:text=NVIDIA%20will%20pay%20its%20next,record%20on%20March%2012%2C%202025.&text=NVIDIA%27s%20outlook%20for%20the%20first,%2C%20plus%20or%20minus%202%25.'
tool_scrape = ScrapeWebsiteTool(url)
# Extract the text
text = tool_scrape.run()
text
Using Tool: Read website content
'The following text is scraped website content:\nNVIDIA Announces Financial Results for Fourth Quarter and Fiscal 2025 | NVIDIA Newsroom\nArtificial Intelligence Computing Leadership from NVIDIA\nPLATFORMS\nAutonomous Machines\nCloud & Data Center\nDeep Learning & Ai\nDesign & Pro Visualization\nHealthcare\nHigh Performance Computing\nSelf-Driving Cars\nGaming & Entertainment\nother links\nDevelopers\nIndustries\nShop\nDrivers\nSupport\nAbout NVIDIA\nView All Products\nGPU TECHNOLOGY CONFERENCE\nNVIDIA Blog\nCommunity\nCareers\nTECHNOLOGIES\nNewsroom\nNVIDIA in Brief\nExec Bios\nNVIDIA Blog\nPodcast\nMedia Assets\nIn the News\nPress Contacts\nOnline Press Kits\nNVIDIA in Brief\nExec Bios\nNVIDIA Blog\nPodcast\nMedia Assets\nIn the News\nPress Contacts\nOnline Press Kits\nPress Release\nShare\nTweet\nTwitter\nShare\nLinkedIn\nShare\nFacebook\nEmail\nic_arrow-back-to-top\nNVIDIA Announces Financial Results for Fourth Quarter and Fiscal 2025\nRecord quarterly revenue of $39.3 billion, up 12% from Q3 and up 78% from a year ago\nRecord quarterly Data Center revenue of $35.6 billion, up 16% from Q3 and up 93% from a year ago\nRecord full-year revenue of $130.5 billion, up 114%\nFebruary 26, 2025\nNVIDIA (NASDAQ: NVDA) today reported revenue for the fourth quarter ended January 26, 2025, of $39.3 billion, up 12% from the previous quarter and up 78% from a year ago.\nFor the quarter, GAAP earnings per diluted share was $0.89, up 14% from the previous quarter and up 82% from a year ago. Non-GAAP earnings per diluted share was $0.89, up 10% from the previous quarter and up 71% from a year ago.\nFor fiscal 2025, revenue was $130.5 billion, up 114% from a year ago. GAAP earnings per diluted share was $2.94, up 147% from a year ago. Non-GAAP earnings per diluted share was $2.99, up 130% from a year ago.\n“Demand for Blackwell is amazing as reasoning AI adds another scaling law — increasing compute for training makes models smarter and increasing compute for long thinking makes the answer smarter,” said Jensen Huang, founder and CEO of NVIDIA.\n“We’ve successfully ramped up the massive-scale production of Blackwell AI supercomputers, achieving billions of dollars in sales in its first quarter. AI is advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries.”\nNVIDIA will pay its next quarterly cash dividend of $0.01 per share on April 2, 2025, to all shareholders of record on March 12, 2025.\nQ4 Fiscal 2025 Summary\nGAAP\n($ in millions, except earnings\nper share)\nQ4 FY25\nQ3 FY25\nQ4 FY24\nQ/Q\nY/Y\nRevenue\n$39,331\n$35,082\n$22,103\nUp 12%\nUp 78%\nGross margin\n73.0%\n74.6%\n76.0%\nDown 1.6 pts\nDown 3.0 pts\nOperating expenses\n$4,689\n$4,287\n$3,176\nUp 9%\nUp 48%\nOperating income\n$24,034\n$21,869\n$13,615\nUp 10%\nUp 77%\nNet income\n$22,091\n$19,309\n$12,285\nUp 14%\nUp 80%\nDiluted earnings per share*\n$0.89\n$0.78\n$0.49\nUp 14%\nUp 82%\nNon-GAAP\n($ in millions, except earnings\nper share)\nQ4 FY25\nQ3 FY25\nQ4 FY24\nQ/Q\nY/Y\nRevenue\n$39,331\n$35,082\n$22,103\nUp 12%\nUp 78%\nGross margin\n73.5%\n75.0%\n76.7%\nDown 1.5 pts\nDown 3.2 pts\nOperating expenses\n$3,378\n$3,046\n$2,210\nUp 11%\nUp 53%\nOperating income\n$25,516\n$23,276\n$14,749\nUp 10%\nUp 73%\nNet income\n$22,066\n$20,010\n$12,839\nUp 10%\nUp 72%\nDiluted earnings per share*\n$0.89\n$0.81\n$0.52\nUp 10%\nUp 71%\nFiscal 2025 Summary\nGAAP\n($ in millions, except earnings\nper share)\nFY25\nFY24\nY/Y\nRevenue\n$130,497\n$60,922\nUp 114%\nGross margin\n75.0%\n72.7%\nUp 2.3 pts\nOperating expenses\n$16,405\n$11,329\nUp 45%\nOperating income\n$81,453\n$32,972\nUp 147%\nNet income\n$72,880\n$29,760\nUp 145%\nDiluted earnings per share*\n$2.94\n$1.19\nUp 147%\nNon-GAAP\n($ in millions, except earnings\nper share)\nFY25\nFY24\nY/Y\nRevenue\n$130,497\n$60,922\nUp 114%\nGross margin\n75.5%\n73.8%\nUp 1.7 pts\nOperating expenses\n$11,716\n$7,825\nUp 50%\nOperating income\n$86,789\n$37,134\nUp 134%\nNet income\n$74,265\n$32,312\nUp 130%\nDiluted earnings per share*\n$2.99\n$1.30\nUp 130%\n*All per share amounts presented herein have been retroactively adjusted to reflect the ten-for-one stock split, which was effective June 7, 2024.\nOutlook \r\nNVIDIA’s outlook for the first quarter of fiscal 2026 is as follows:\nRevenue is expected to be $43.0 billion, plus or minus 2%.\nGAAP and non-GAAP gross margins are expected to be 70.6% and 71.0%, respectively, plus or minus 50 basis points.\nGAAP and non-GAAP operating expenses are expected to be approximately $5.2 billion and $3.6 billion, respectively.\nGAAP and non-GAAP other income and expense are expected to be an income of approximately $400 million, excluding gains and losses from non-marketable and publicly-held equity securities.\nGAAP and non-GAAP tax rates are expected to be 17.0%, plus or minus 1%, excluding any discrete items.\nHighlights\nNVIDIA achieved progress since its previous earnings announcement in these areas:\nData Center\nFourth-quarter revenue was a record $35.6 billion, up 16% from the previous quarter and up 93% from a year ago. Full-year revenue rose 142% to a record $115.2 billion.\nAnnounced that NVIDIA will serve as a key technology partner for the $500 billion Stargate Project.\nRevealed that cloud service providers AWS, CoreWeave, Google Cloud Platform (GCP), Microsoft Azure and Oracle Cloud Infrastructure (OCI) are bringing NVIDIA® GB200 systems to cloud regions around the world to meet surging customer demand for AI.\nPartnered with AWS to make the NVIDIA DGX™ Cloud AI computing platform and NVIDIA NIM™ microservices available through AWS Marketplace.\nRevealed that Cisco will integrate NVIDIA Spectrum-X™ into its networking portfolio to help enterprises build AI infrastructure.\nRevealed that more than 75% of the systems on the TOP500 list of the world’s most powerful supercomputers are powered by NVIDIA technologies.\nAnnounced a collaboration with Verizon to integrate NVIDIA AI Enterprise, NIM and accelerated computing with Verizon’s private 5G network to power a range of edge enterprise AI applications and services.\nUnveiled partnerships with industry leaders including IQVIA, Illumina, Mayo Clinic and Arc Institute to advance genomics, drug discovery and healthcare.\nLaunched NVIDIA AI Blueprints and Llama Nemotron model families for building AI agents and released NVIDIA NIM microservices to safeguard applications for agentic AI.\nAnnounced the opening of NVIDIA’s first R&D center in Vietnam .\nRevealed that Siemens Healthineers has adopted MONAI Deploy for medical imaging AI.\nGaming and AI PC\nFourth-quarter Gaming revenue was $2.5 billion, down 22% from the previous quarter and down 11% from a year ago.\xa0Full-year revenue rose 9% to $11.4 billion.\nAnnounced new GeForce RTX™ 50 Series graphics cards and laptops powered by the NVIDIA Blackwell architecture, delivering breakthroughs in AI-driven rendering to gamers, creators and developers.\nLaunched GeForce RTX 5090 and 5080 graphics cards, delivering up to a 2x performance improvement over the prior generation.\nIntroduced NVIDIA DLSS 4 with Multi Frame Generation and image quality enhancements, with 75 games and apps supporting it at launch, and unveiled NVIDIA Reflex 2 technology, which can reduce PC latency by up to 75%.\nUnveiled NVIDIA NIM microservices, AI Blueprints and the Llama Nemotron family of open models for RTX AI PCs to help developers and enthusiasts build AI agents and creative workflows.\nProfessional Visualization\nFourth-quarter revenue was $511 million, up 5% from the previous quarter and up 10% from a year ago. Full-year revenue rose 21% to $1.9 billion.\nUnveiled NVIDIA Project DIGITS , a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of the NVIDIA Grace™ Blackwell platform.\nAnnounced generative AI models and blueprints that expand NVIDIA Omniverse™ integration further into physical AI applications, including robotics, autonomous vehicles and vision AI.\nIntroduced NVIDIA Media2 , an AI-powered initiative transforming content creation, streaming and live media experiences, built on NIM and AI Blueprints.\nAutomotive and Robotics\nFourth-quarter Automotive revenue was $570 million, up 27% from the previous quarter and up 103% from a year ago. Full-year revenue rose 55% to $1.7 billion.\nAnnounced that Toyota, the world’s largest automaker, will build its next-generation vehicles on NVIDIA DRIVE AGX Orin™ running the safety-certified NVIDIA DriveOS operating system.\nPartnered with Hyundai Motor Group to create safer, smarter vehicles, supercharge manufacturing and deploy cutting-edge robotics with NVIDIA AI and NVIDIA Omniverse .\nAnnounced that the NVIDIA DriveOS safe autonomous driving operating system received ASIL-D functional safety certification and launched the NVIDIA DRIVE™ AI Systems Inspection Lab .\nLaunched NVIDIA Cosmos™ , a platform comprising state-of-the-art generative world foundation models, to accelerate physical AI development, with adoption by leading robotics and automotive companies 1X, Agile Robots, Waabi, Uber and others.\nUnveiled the NVIDIA Jetson Orin Nano™ Super , which delivers up to a 1.7x gain in generative AI performance.\nCFO Commentary \r\nCommentary on the quarter by Colette Kress, NVIDIA’s executive vice president and chief financial officer, is available at https://investor.nvidia.com .\nConference Call and Webcast Information \r\nNVIDIA will conduct a conference call with analysts and investors to discuss its fourth quarter and fiscal 2025 financial results and current financial prospects today at 2 p.m. Pacific time (5 p.m. Eastern time). A live webcast (listen-only mode) of the conference call will be accessible at NVIDIA’s investor relations website, https://investor.nvidia.com . The webcast will be recorded and available for replay until NVIDIA’s conference call to discuss its financial results for its first quarter of fiscal 2026.\nNon-GAAP Measures \r\nTo supplement NVIDIA’s condensed consolidated financial statements presented in accordance with GAAP, the company uses non-GAAP measures of certain components of financial performance. These non-GAAP measures include non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses, non-GAAP operating income, non-GAAP other income (expense), net, non-GAAP net income, non-GAAP net income, or earnings, per diluted share, and free cash flow. For NVIDIA’s investors to be better able to compare its current results with those of previous periods, the company has shown a reconciliation of GAAP to non-GAAP financial measures. These reconciliations adjust the related GAAP financial measures to exclude stock-based compensation expense, acquisition-related and other costs, other, gains from non-marketable and publicly-held equity securities, net, interest expense related to amortization of debt discount, and the associated tax impact of these items where applicable. Free cash flow is calculated as GAAP net cash provided by operating activities less both purchases related to property and equipment and intangible assets and principal payments on property and equipment and intangible assets. NVIDIA believes the presentation of its non-GAAP financial measures enhances the user’s overall understanding of the company’s historical financial performance. The presentation of the company’s non-GAAP financial measures is not meant to be considered in isolation or as a substitute for the company’s financial results prepared in accordance with GAAP, and the company’s non-GAAP measures may be different from non-GAAP measures used by other companies.\nNVIDIA CORPORATION\nCONDENSED CONSOLIDATED STATEMENTS OF INCOME\n(In millions, except per share data)\n(Unaudited)\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2025\n2024\nRevenue\n$\n39,331\n$\n22,103\n$\n130,497\n$\n60,922\nCost of revenue\n10,608\n5,312\n32,639\n16,621\nGross profit\n28,723\n16,791\n97,858\n44,301\nOperating expenses\nResearch and development\n3,714\n2,465\n12,914\n8,675\nSales, general and administrative\n975\n711\n3,491\n2,654\nTotal operating expenses\n4,689\n3,176\n16,405\n11,329\nOperating income\n24,034\n13,615\n81,453\n32,972\nInterest income\n511\n294\n1,786\n866\nInterest expense\n(61\n)\n(63\n)\n(247\n)\n(257\n)\nOther, net\n733\n260\n1,034\n237\nOther income (expense), net\n1,183\n491\n2,573\n846\nIncome before income tax\n25,217\n14,106\n84,026\n33,818\nIncome tax expense\n3,126\n1,821\n11,146\n4,058\nNet income\n$\n22,091\n$\n12,285\n$\n72,880\n$\n29,760\nNet income per share:\nBasic\n$\n0.90\n$\n0.51\n$\n2.97\n$\n1.21\nDiluted\n$\n0.89\n$\n0.49\n$\n2.94\n$\n1.19\nWeighted average shares used in per share computation:\nBasic\n24,489\n24,660\n24,555\n24,690\nDiluted\n24,706\n24,900\n24,804\n24,940\nNVIDIA CORPORATION\nCONDENSED CONSOLIDATED BALANCE SHEETS\n(In millions)\n(Unaudited)\nJanuary 26,\nJanuary 28,\n2025\n2024\nASSETS\nCurrent assets:\nCash, cash equivalents and marketable securities\n$\n43,210\n$\n25,984\nAccounts receivable, net\n23,065\n9,999\nInventories\n10,080\n5,282\nPrepaid expenses and other current assets\n3,771\n3,080\nTotal current assets\n80,126\n44,345\nProperty and equipment, net\n6,283\n3,914\nOperating lease assets\n1,793\n1,346\nGoodwill\n5,188\n4,430\nIntangible assets, net\n807\n1,112\nDeferred income tax assets\n10,979\n6,081\nOther assets\n6,425\n4,500\nTotal assets\n$\n111,601\n$\n65,728\nLIABILITIES AND SHAREHOLDERS’ EQUITY\nCurrent liabilities:\nAccounts payable\n$\n6,310\n$\n2,699\nAccrued and other current liabilities\n11,737\n6,682\nShort-term debt\n-\n1,250\nTotal current liabilities\n18,047\n10,631\nLong-term debt\n8,463\n8,459\nLong-term operating lease liabilities\n1,519\n1,119\nOther long-term liabilities\n4,245\n2,541\nTotal liabilities\n32,274\n22,750\nShareholders’ equity\n79,327\n42,978\nTotal liabilities and shareholders’ equity\n$\n111,601\n$\n65,728\nNVIDIA CORPORATION\nCONDENSED CONSOLIDATED STATEMENTS OF CASH FLOWS\n(In millions)\n(Unaudited)\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2025\n2024\nCash flows from operating activities:\nNet income\n$\n22,091\n$\n12,285\n$\n72,880\n$\n29,760\nAdjustments to reconcile net income to net cash\nprovided by operating activities:\nStock-based compensation expense\n1,321\n993\n4,737\n3,549\nDepreciation and amortization\n543\n387\n1,864\n1,508\nDeferred income taxes\n(598\n)\n(78\n)\n(4,477\n)\n(2,489\n)\nGains on non-marketable equity securities and publicly-held equity securities, net\n(727\n)\n(260\n)\n(1,030\n)\n(238\n)\nOther\n(138\n)\n(109\n)\n(502\n)\n(278\n)\nChanges in operating assets and liabilities, net of acquisitions:\nAccounts receivable\n(5,370\n)\n(1,690\n)\n(13,063\n)\n(6,172\n)\nInventories\n(2,424\n)\n(503\n)\n(4,781\n)\n(98\n)\nPrepaid expenses and other assets\n331\n(1,184\n)\n(395\n)\n(1,522\n)\nAccounts payable\n867\n281\n3,357\n1,531\nAccrued and other current liabilities\n360\n1,072\n4,278\n2,025\nOther long-term liabilities\n372\n305\n1,221\n514\nNet cash provided by operating activities\n16,628\n11,499\n64,089\n28,090\nCash flows from investing activities:\nProceeds from maturities of marketable securities\n1,710\n1,731\n11,195\n9,732\nProceeds from sales of marketable securities\n177\n50\n495\n50\nProceeds from sales of non-marketable equity securities\n-\n-\n171\n1\nPurchases of marketable securities\n(7,010\n)\n(7,524\n)\n(26,575\n)\n(18,211\n)\nPurchase related to property and equipment and intangible assets\n(1,077\n)\n(253\n)\n(3,236\n)\n(1,069\n)\nPurchases of non-marketable equity securities\n(478\n)\n(113\n)\n(1,486\n)\n(862\n)\nAcquisitions, net of cash acquired\n(542\n)\n-\n(1,007\n)\n(83\n)\nOther\n22\n-\n22\n(124\n)\nNet cash used in investing activities\n(7,198\n)\n(6,109\n)\n(20,421\n)\n(10,566\n)\nCash flows from financing activities:\nProceeds related to employee stock plans\n-\n-\n490\n403\nPayments related to repurchases of common stock\n(7,810\n)\n(2,660\n)\n(33,706\n)\n(9,533\n)\nPayments related to tax on restricted stock units\n(1,861\n)\n(841\n)\n(6,930\n)\n(2,783\n)\nRepayment of debt\n-\n-\n(1,250\n)\n(1,250\n)\nDividends paid\n(245\n)\n(99\n)\n(834\n)\n(395\n)\nPrincipal payments on property and equipment and intangible assets\n(32\n)\n(29\n)\n(129\n)\n(74\n)\nOther\n-\n-\n-\n(1\n)\nNet cash used in financing activities\n(9,948\n)\n(3,629\n)\n(42,359\n)\n(13,633\n)\nChange in cash, cash equivalents, and restricted cash\n(518\n)\n1,761\n1,309\n3,891\nCash, cash equivalents, and restricted cash at beginning of period\n9,107\n5,519\n7,280\n3,389\nCash, cash equivalents, and restricted cash at end of period\n$\n8,589\n$\n7,280\n$\n8,589\n$\n7,280\nSupplemental disclosures of cash flow information:\nCash paid for income taxes, net\n$\n4,129\n$\n1,874\n$\n15,118\n$\n6,549\nCash paid for interest\n$\n22\n$\n26\n$\n246\n$\n252\nNVIDIA CORPORATION\nRECONCILIATION OF GAAP TO NON-GAAP FINANCIAL MEASURES\n(In millions, except per share data)\n(Unaudited)\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nOctober 27,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2024\n2025\n2024\nGAAP cost of revenue\n$\n10,608\n$\n8,926\n$\n5,312\n$\n32,639\n$\n16,621\nGAAP gross profit\n$\n28,723\n$\n26,156\n$\n16,791\n$\n97,858\n$\n44,301\nGAAP gross margin\n73.0\n%\n74.6\n%\n76.0\n%\n75.0\n%\n72.7\n%\nAcquisition-related and other costs (A)\n118\n116\n119\n472\n477\nStock-based compensation expense (B)\n53\n50\n45\n178\n141\nOther (C)\n-\n-\n4\n(3\n)\n40\nNon-GAAP cost of revenue\n$\n10,437\n$\n8,759\n$\n5,144\n$\n31,992\n$\n15,963\nNon-GAAP gross profit\n$\n28,894\n$\n26,322\n$\n16,959\n$\n98,505\n$\n44,959\nNon-GAAP gross margin\n73.5\n%\n75.0\n%\n76.7\n%\n75.5\n%\n73.8\n%\nGAAP operating expenses\n$\n4,689\n$\n4,287\n$\n3,176\n$\n16,405\n$\n11,329\nStock-based compensation expense (B)\n(1,268\n)\n(1,202\n)\n(948\n)\n(4,559\n)\n(3,408\n)\nAcquisition-related and other costs (A)\n(43\n)\n(39\n)\n(18\n)\n(130\n)\n(106\n)\nOther (C)\n-\n-\n-\n-\n10\nNon-GAAP operating expenses\n$\n3,378\n$\n3,046\n$\n2,210\n$\n11,716\n$\n7,825\nGAAP operating income\n$\n24,034\n$\n21,869\n$\n13,615\n$\n81,453\n$\n32,972\nTotal impact of non-GAAP adjustments to operating income\n1,482\n1,407\n1,134\n5,336\n4,162\nNon-GAAP operating income\n$\n25,516\n$\n23,276\n$\n14,749\n$\n86,789\n$\n37,134\nGAAP other income (expense), net\n$\n1,183\n$\n447\n$\n491\n$\n2,573\n$\n846\nGains from non-marketable equity securities and publicly-held equity securities, net\n(727\n)\n(37\n)\n(260\n)\n(1,030\n)\n(238\n)\nInterest expense related to amortization of debt discount\n1\n1\n1\n4\n4\nNon-GAAP other income (expense), net\n$\n457\n$\n411\n$\n232\n$\n1,547\n$\n612\nGAAP net income\n$\n22,091\n$\n19,309\n$\n12,285\n$\n72,880\n$\n29,760\nTotal pre-tax impact of non-GAAP adjustments\n756\n1,371\n875\n4,310\n3,928\nIncome tax impact of non-GAAP adjustments (D)\n(781\n)\n(670\n)\n(321\n)\n(2,925\n)\n(1,376\n)\nNon-GAAP net income\n$\n22,066\n$\n20,010\n$\n12,839\n$\n74,265\n$\n32,312\nDiluted net income per share (E)\nGAAP\n$\n0.89\n$\n0.78\n$\n0.49\n$\n2.94\n$\n1.19\nNon-GAAP\n$\n0.89\n$\n0.81\n$\n0.52\n$\n2.99\n$\n1.30\nWeighted average shares used in diluted net income per share computation (E)\n24,706\n24,774\n24,900\n24,804\n24,936\nGAAP net cash provided by operating activities\n$\n16,628\n$\n17,629\n$\n11,499\n$\n64,089\n$\n28,090\nPurchases related to property and equipment and intangible assets\n(1,077\n)\n(813\n)\n(253\n)\n(3,236\n)\n(1,069\n)\nPrincipal payments on property and equipment and intangible assets\n(32\n)\n(29\n)\n(29\n)\n(129\n)\n(74\n)\nFree cash flow\n$\n15,519\n$\n16,787\n$\n11,217\n$\n60,724\n$\n26,947\n(A) Acquisition-related and other costs are comprised of amortization of intangible assets, transaction costs, and certain compensation charges and are included in the following line items:\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nOctober 27,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2024\n2025\n2024\nCost of revenue\n$\n118\n$\n116\n$\n119\n$\n472\n$\n477\nResearch and development\n$\n27\n$\n23\n$\n12\n$\n79\n$\n49\nSales, general and administrative\n$\n16\n$\n16\n$\n6\n$\n51\n$\n57\n(B) Stock-based compensation consists of the following:\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nOctober 27,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2024\n2025\n2024\nCost of revenue\n$\n53\n$\n50\n$\n45\n$\n178\n$\n141\nResearch and development\n$\n955\n$\n910\n$\n706\n$\n3,423\n$\n2,532\nSales, general and administrative\n$\n313\n$\n292\n$\n242\n$\n1,136\n$\n876\n(C) Other consists of IP-related costs and assets held for sale related adjustments\n(D) Income tax impact of non-GAAP adjustments, including the recognition of excess tax benefits or deficiencies related to stock-based compensation under GAAP accounting standard (ASU 2016-09).\n(E) Reflects a ten-for-one stock split on June 7, 2024\nNVIDIA CORPORATION\nRECONCILIATION OF GAAP TO NON-GAAP OUTLOOK\nQ1 FY2026 Outlook\n($ in millions)\nGAAP gross margin\n70.6\n%\nImpact of stock-based compensation expense, acquisition-related costs, and other costs\n0.4\n%\nNon-GAAP gross margin\n71.0\n%\nGAAP operating expenses\n$\n5,150\nStock-based compensation expense, acquisition-related costs, and other costs\n(1,550\n)\nNon-GAAP operating expenses\n$\n3,600\nAbout NVIDIA\nNVIDIA \xa0(NASDAQ: NVDA) is the world leader in accelerated computing.\nCertain statements in this press release including, but not limited to, statements as to: AI advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments and related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n© 2025 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, GeForce RTX, NVIDIA Cosmos, NVIDIA Spectrum-X, NVIDIA DGX, NVIDIA DRIVE, NVIDIA DRIVE AGX Orin, NVIDIA Grace, NVIDIA Jetson Orin Nano, NVIDIA NIM and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\nMedia Contacts\nStewart Stecker\nInvestor Relations\nsstecker@nvidia.com\nMylene Mangalindan\nCorporate Communications\nmmangalindan@nvidia.com\nDownloads\nDownload Press Release\nDownload Attachments\nMore Images\naabe86db-ce89-4434-b83c-495082979801\nDownload / File Link\nMore News\nNVIDIA and RIKEN Advance Japan’s Scientific Frontiers With New Supercomputers for AI and Quantum Computing\nNovember 17, 2025\nWorld’s Leading Scientific Supercomputing Centers Adopt NVIDIA NVQLink to Integrate Grace Blackwell Platform With Quantum Processors\nNovember 17, 2025\nNVIDIA and SK Group Build AI Factory to Drive Korea’s Manufacturing and Digital Transformation\nOctober 30, 2025\nNVIDIA and Samsung Build AI Factory to Transform Global Intelligent Manufacturing\nOctober 30, 2025\nNVIDIA and Hyundai Motor Group Team on AI Factory to Power AI-Driven Mobility Solutions\nOctober 30, 2025\nAbout NVIDIA\nNVIDIA \xa0(NASDAQ: NVDA) is the world leader in accelerated computing.\nCertain statements in this press release including, but not limited to, statements as to: AI advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments and related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n© 2025 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, GeForce RTX, NVIDIA Cosmos, NVIDIA Spectrum-X, NVIDIA DGX, NVIDIA DRIVE, NVIDIA DRIVE AGX Orin, NVIDIA Grace, NVIDIA Jetson Orin Nano, NVIDIA NIM and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\nMedia Contacts\nGlobal contacts for media inquiries.\nAll Contacts\nStay Informed\nNewsroom updates delivered to your inbox.\nSubscribe\nCorporate Information\nAbout NVIDIA\nCorporate Overview\nTechnologies\nNVIDIA Research\nInvestors\nSocial Responsibility\nNVIDIA Foundation\nGet Involved\nForums\nCareers\nDeveloper Home\nJoin the Developer Program\nNVIDIA Partner Network\nNVIDIA Inception\nResources for Venture Capitalists\nVenture Capital (NVentures)\nTechnical Training\nTraining for IT Professionals\nProfessional Services for Data Science\nNews & Events\nNewsroom\nNVIDIA Blog\nNVIDIA Technical Blog\nWebinars\nStay Informed\nEvents Calendar\nNVIDIA GTC\nNVIDIA On-Demand\nSign Up for NVIDIA News\nSubscribe\nFollow NVIDIA\nFacebook\nLinkedIn\nInstagram\nYouTube\nNVIDIA\nUSA - United States\nPrivacy Policy\nYour Privacy Choices\nTerms of Service\nAccessibility\nCorporate Policies\nProduct Security\nContact\nCopyright © 2025 NVIDIA Corporation\n'
# Write content to a file
if not os.path.exists('crewai'):
os.mkdir('crewai')
with open('crewai/nvidia.txt', 'w') as f:
f.write(text)
f.close()
The TXTSearchTool creates a vector index and enables search.
# os.environ['OPENAI_API_KEY'] = 'API-KEY'
# Initialize the tool with a specific text file, so the agent can search within the given text file's content
tool_search = TXTSearchTool(txt='crewai/nvidia.txt')
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
/tmp/ipython-input-2706990809.py in <cell line: 0>()
2
3 # Initialize the tool with a specific text file, so the agent can search within the given text file's content
----> 4 tool_search = TXTSearchTool(txt='crewai/nvidia.txt')
/usr/local/lib/python3.12/dist-packages/crewai_tools/tools/txt_search_tool/txt_search_tool.py in __init__(self, txt, **kwargs)
27
28 def __init__(self, txt: str | None = None, **kwargs):
---> 29 super().__init__(**kwargs)
30 if txt is not None:
31 self.add(txt)
[... skipping hidden 1 frame]
/usr/local/lib/python3.12/dist-packages/crewai_tools/tools/rag/rag_tool.py in _set_default_adapter(self)
53 def _set_default_adapter(self):
54 if isinstance(self.adapter, RagTool._AdapterPlaceholder):
---> 55 from crewai_tools.adapters.crewai_rag_adapter import CrewAIRagAdapter
56
57 parsed_config = self._parse_config(self.config)
/usr/local/lib/python3.12/dist-packages/crewai_tools/adapters/crewai_rag_adapter.py in <module>
10 from crewai.rag.core.base_client import BaseClient
11 from crewai.rag.factory import create_client
---> 12 from crewai.rag.qdrant.config import QdrantConfig
13 from crewai.rag.types import BaseRecord, SearchResult
14 from pydantic import PrivateAttr
/usr/local/lib/python3.12/dist-packages/crewai/rag/qdrant/config.py in <module>
9 from crewai.rag.config.base import BaseRagConfig
10 from crewai.rag.qdrant.constants import DEFAULT_EMBEDDING_MODEL, DEFAULT_STORAGE_PATH
---> 11 from crewai.rag.qdrant.types import QdrantClientParams, QdrantEmbeddingFunctionWrapper
12
13
/usr/local/lib/python3.12/dist-packages/crewai/rag/qdrant/types.py in <module>
11 QdrantClient as SyncQdrantClient, # type: ignore[import-not-found]
12 )
---> 13 from qdrant_client.models import ( # type: ignore[import-not-found]
14 FieldCondition,
15 Filter,
ImportError: cannot import name 'InitFrom' from 'qdrant_client.models' (/usr/local/lib/python3.12/dist-packages/qdrant_client/models/__init__.py)
---------------------------------------------------------------------------
NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.
To view examples of installing some common dependencies, click the
"Open Examples" button below.
---------------------------------------------------------------------------
40.5. Application: Build a Financial Analyst Agent#
As shown below, you need to specify
The
AgentsandTasks.The
Crewis then the collections of Agents, Tasks, and Tools (tools were defined earlier)
By default, CrewAI uses the gpt-4o model unless specified to use another model. CrewAI uses LiteLLM, which is installed already with it, https://www.litellm.ai. LiteLLM is an interface that may be used to address a large number of LLM providers and their models.
from crewai import Agent, Task, Crew
question = 'What is the forward-looking outlook for Nvidia?'
context = tool_search.run(question)
fin_analyst = Agent(
role='Financial Analyst',
goal=f'Based on the context provided, answer the Question - {question} Context - {context}',
backstory='You are a financial analyst and an expert on forecasting the future trajectory of a firm',
verbose=True,
allow_delegation=False,
tools=[tool_search, search_tool]
)
task_answer = Task(
description="Analyze the question, understand the context, and generate the correct response",
tools=[tool_search],
agent=fin_analyst,
expected_output='Provide a relevant answer to the question'
)
crew = Crew(
agents=[fin_analyst],
tasks=[task_answer],
verbose=True,
planning=True, # Enable planning feature
)
Using Tool: Search a txt's content
40.6. Run the Crew for the financial analyst#
Execute the entire agentic workflow. What we have is a single agent and one task with a single tool. So it is pretty straightforward.
# If debugging is needed, uncomment the lines below.
# import litellm
# litellm._turn_on_debug()
output = crew.kickoff()
╭──────────────────────────────────────────── Crew Execution Started ─────────────────────────────────────────────╮ │ │ │ Crew Execution Started │ │ Name: crew │ │ ID: bc70d662-cdf6-429a-b335-dc89342a8d66 │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[2025-11-15 18:01:23][INFO]: Planning the crew execution
╭──────────────────────────────────────────────── Task Completion ────────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: d5327ecf-ab53-48cf-9821-5545bc2c1c01 │ │ Agent: Task Execution Planner │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: Financial Analyst │ │ │ │ Task: Analyze the question, understand the context, and generate the correct response1. **Read the Context │ │ Provided:** Start by thoroughly reviewing the context content from Nvidia’s earnings announcements and │ │ outlook to understand the key points regarding revenue, expenses, and market conditions. │ │ 2. **Extract Key Financial Metrics:** Focus on identifying important financial figures such as revenue │ │ expectations ($43.0 billion), gross margins (GAAP 70.6%, non-GAAP 71.0%), operating expenses, and net income │ │ projections. │ │ 3. **Note Relevant Highlights:** Pay attention to significant achievements in the Data Center category and │ │ Nvidia's partnership in the Stargate Project as these indicate growth potential. │ │ 4. **Use Search Tool (TXTSearchTool):** Input specific queries related to Nvidia's financial outlook using │ │ the Search a txt's content tool in case more detailed or specific data is required to strengthen your │ │ analysis. For example, search for historical financial growth or recent market trends. │ │ 5. **Market Analysis:** Research broader market trends using the 'Search the internet with Serper' tool to │ │ gather recent news about AI advancements and any potential impacts on Nvidia’s growth and technology │ │ developments. Use keywords like 'Nvidia AI advancements', 'Nvidia market growth outlook 2026'. │ │ 6. **Assess Risks and Uncertainties:** Evaluate the potential risks associated with Nvidia’s outlook, as │ │ mentioned in the press release. Focus on factors like global economic conditions, reliance on third-party │ │ manufacturers, and technological competition. │ │ 7. **Synthesize Your Findings:** Combine all gathered data into a cohesive narrative that outlines Nvidia's │ │ financial outlook, including strengths, weaknesses, potential opportunities, and threats. │ │ 8. **Draft the Response:** Structure the response in a way that clearly discusses Nvidia's expected growth │ │ based on financial projections, AI market trends, and recent achievements, ensuring to include relevant │ │ disclaimers about uncertainties. │ │ 9. **Review and Refine:** Go through the drafted response to ensure clarity, accuracy, and coverage of all │ │ important points. Make adjustments as necessary. │ │ 10. **Submit the Final Response:** Once satisfied with the accuracy and presentation of the response based on │ │ the analysis, finalize and submit the answer to the inquiry regarding Nvidia’s outlook. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────── 🔧 Agent Tool Execution ────────────────────────────────────────────╮ │ │ │ Agent: Financial Analyst │ │ │ │ Thought: Thought: To provide a comprehensive forward-looking outlook for Nvidia, I should first extract │ │ specific financial projections and key highlights from the context provided. I need to clarify revenue │ │ expectations, margins, operating expenses, and net income projections, and then assess qualitative factors │ │ like partnerships and emerging technologies. Because the context is extensive, I will start searching for │ │ "Nvidia financial outlook" to confirm detailed projections for fiscal 2026 and beyond. │ │ │ │ Using Tool: Search a txt's content │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: Financial Analyst │ │ │ │ Final Answer: │ │ NVIDIA (NASDAQ: NVDA), the world leader in accelerated computing, has provided a robust forward-looking │ │ outlook as it enters the first quarter of fiscal 2026. The company anticipates revenue of approximately $43.0 │ │ billion, with a variance of plus or minus 2%. Gross margins are expected to be strong, with GAAP gross │ │ margins projected at 70.6% and non-GAAP gross margins at 71.0%, both with an expected variability of 50 basis │ │ points. │ │ │ │ Operating expenses under GAAP are expected to be around $5.2 billion, while non-GAAP operating expenses are │ │ forecasted at $3.6 billion. The company expects other income and expense to result in an income of roughly │ │ $400 million, excluding gains and losses from non-marketable and publicly-held equity securities. The tax │ │ rate guidance is set at 17.0%, plus or minus 1%, excluding any discrete items. │ │ │ │ NVIDIA continues to make significant progress in its core growth areas. Notably, its Data Center segment │ │ recorded a fourth-quarter revenue record of $35.6 billion, representing a 16% increase from the prior quarter │ │ and 93% growth from the year-ago period. Full-year revenue for the Data Center segment surged 142% to an │ │ unprecedented $115.2 billion. Furthermore, NVIDIA has been named a key technology partner for the prominent │ │ $500 billion Stargate Project, underscoring its pivotal role in advancing technological innovation. │ │ │ │ The company remains at the forefront of the AI revolution, with expectations that rapidly advancing AI │ │ technologies — including agentic AI and physical AI — will revolutionize major industries. NVIDIA is │ │ particularly optimistic about the Blackwell architecture and related technologies, which are poised to drive │ │ future growth. │ │ │ │ However, investors should consider various risks and uncertainties outlined by NVIDIA. These include global │ │ economic and political conditions, reliance on third-party manufacturers for production, competitive │ │ technological developments, market acceptance of NVIDIA’s products, and potential changes in laws and │ │ regulations. Moreover, disruptions such as design or software defects, changes in consumer demand, and │ │ unexpected product performance issues might affect future results. │ │ │ │ NVIDIA’s forward-looking statements explicitly caution that actual results could materially differ due to │ │ these factors, and the company disclaims any obligation to update projections absent legal requirements. │ │ │ │ Overall, NVIDIA’s financial outlook for fiscal 2026 reflects strong revenue and margin expectations supported │ │ by its leadership in accelerated computing, significant growth in data center revenues, and strategic │ │ partnerships, especially in AI and large-scale projects like Stargate. While the company faces typical market │ │ and operational risks, its position as a technology front-runner and key AI partner provides a compelling │ │ growth trajectory for investors to consider. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
p80(output.raw)
NVIDIA (NASDAQ: NVDA), the world leader in accelerated computing, has provided a
robust forward-looking outlook as it enters the first quarter of fiscal 2026.
The company anticipates revenue of approximately $43.0 billion, with a variance
of plus or minus 2%. Gross margins are expected to be strong, with GAAP gross
margins projected at 70.6% and non-GAAP gross margins at 71.0%, both with an
expected variability of 50 basis points. Operating expenses under GAAP are
expected to be around $5.2 billion, while non-GAAP operating expenses are
forecasted at $3.6 billion. The company expects other income and expense to
result in an income of roughly $400 million, excluding gains and losses from
non-marketable and publicly-held equity securities. The tax rate guidance is set
at 17.0%, plus or minus 1%, excluding any discrete items. NVIDIA continues to
make significant progress in its core growth areas. Notably, its Data Center
segment recorded a fourth-quarter revenue record of $35.6 billion, representing
a 16% increase from the prior quarter and 93% growth from the year-ago period.
Full-year revenue for the Data Center segment surged 142% to an unprecedented
$115.2 billion. Furthermore, NVIDIA has been named a key technology partner for
the prominent $500 billion Stargate Project, underscoring its pivotal role in
advancing technological innovation. The company remains at the forefront of the
AI revolution, with expectations that rapidly advancing AI technologies —
including agentic AI and physical AI — will revolutionize major industries.
NVIDIA is particularly optimistic about the Blackwell architecture and related
technologies, which are poised to drive future growth. However, investors
should consider various risks and uncertainties outlined by NVIDIA. These
include global economic and political conditions, reliance on third-party
manufacturers for production, competitive technological developments, market
acceptance of NVIDIA’s products, and potential changes in laws and regulations.
Moreover, disruptions such as design or software defects, changes in consumer
demand, and unexpected product performance issues might affect future results.
NVIDIA’s forward-looking statements explicitly caution that actual results could
materially differ due to these factors, and the company disclaims any obligation
to update projections absent legal requirements. Overall, NVIDIA’s financial
outlook for fiscal 2026 reflects strong revenue and margin expectations
supported by its leadership in accelerated computing, significant growth in data
center revenues, and strategic partnerships, especially in AI and large-scale
projects like Stargate. While the company faces typical market and operational
risks, its position as a technology front-runner and key AI partner provides a
compelling growth trajectory for investors to consider.
40.7. Application: Conversation between a therapist and a patient#
%run keys.ipynb
!pip install colorama --quiet
from crewai import Agent, Task, Crew
# Initialize colorama for cross-platform color support
from colorama import Fore, Style, init
init()
# Define a custom callback function
def blue_final_answer(output):
"""Callback to print the final answer in dark blue."""
print(Fore.BLUE + "Final Answer: " + output.raw + Style.RESET_ALL)
# Define Agents and Tasks, finally Crew
patient = Agent(
role = 'A patient in therapy',
goal = f'Talk to a therapist about your problem, and answer questions asked by the therapist, and stop when you are satisfied with the answers',
backstory = 'You are a patient who suffers from stress because of poor work life balance',
verbose = True,
allow_delegation = False,
tools = []
)
therapist = Agent(
role = 'A therapist who meets patients',
goal = f'Listen to a patient and ask questions to a patient about their problem, receive an answer, and keep the conversation going, and stop when you are satisfied with the answers',
backstory = 'You are a therapist who see patients for therapy',
verbose = True,
allow_delegation = False,
tools = []
)
task_patient = Task(
description = "Engage in a fruitful conversation with the therapist to alleviate your stress",
tools = [],
agent = patient,
expected_output = 'A successful therapy session with about 20 exchanges in the conversation between patient and therapist',
callback=blue_final_answer,
)
task_therapist = Task(
description = "Engage in a fruitful conversation with the patient to alleviate his stress",
tools = [],
agent = therapist,
expected_output = 'A successful therapy session with about 20 exchanges in the conversation between patient and therapist'
)
crew = Crew(
agents = [patient, therapist],
tasks = [task_patient, task_therapist],
verbose = True
)
result = crew.kickoff()
╭──────────────────────────────────────────── Crew Execution Started ─────────────────────────────────────────────╮ │ │ │ Crew Execution Started │ │ Name: crew │ │ ID: 9ff9168a-2e13-4a0f-b843-d74dd4a5c9e8 │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: A patient in therapy │ │ │ │ Task: Engage in a fruitful conversation with the therapist to alleviate your stress │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Final Answer: Therapist: Hello, thank you for coming in today. What brings you to therapy?
Patient: Hi, thank you for seeing me. Lately, I've been feeling very stressed because I can’t seem to balance my work and personal life.
Therapist: I’m sorry to hear that. Can you tell me more about what is making it hard to balance the two?
Patient: Sure. My job demands a lot of my time, I often work late and even on weekends. By the time I get home, I’m exhausted and it feels like there’s no time left for family or hobbies.
Therapist: That sounds very challenging. How long have you been feeling this way?
Patient: It’s been going on for several months, maybe six or seven now. Before that, I managed better, but things got busier recently.
Therapist: I see. What kind of work do you do, if you don’t mind me asking?
Patient: I work in marketing, mostly managing campaigns and client communications. Deadlines can be tight and there's a lot of pressure to perform.
Therapist: Pressure at work can definitely increase stress. What do you normally do to try to relieve your stress?
Patient: I try to unwind by watching TV or scrolling on my phone, but it doesn’t really help. I used to enjoy running but stopped because of lack of time.
Therapist: Physical activity is a great way to reduce stress. Do you think you might be able to start incorporating some short runs again?
Patient: I think I could try. Maybe just a couple times a week, even if it’s just for 20 minutes.
Therapist: That’s a great start. How about your work schedule? Are there any possibilities to set boundaries, like not checking emails after a certain time?
Patient: I’ve thought about it but fear it might reflect badly on me. The culture here is very demanding, and I often feel like I have to be available 24/7.
Therapist: That sounds very exhausting. Let’s consider ways you can set boundaries gradually without risking your role. Could you identify which tasks require immediate attention and which ones can wait?
Patient: Yes, I could try to prioritize better and let some things wait until the next day, rather than trying to respond instantly all the time.
Therapist: Prioritizing is a good strategy. How about communicating your limits openly with your team or manager?
Patient: I’m not sure they would be receptive, but I could at least discuss managing urgent communications outside of working hours.
Therapist: That could be a good middle ground. How do you feel about asking for support, whether from colleagues or personal network?
Patient: I don’t feel very comfortable asking for help at work, but with friends and family, I know I can talk to them more.
Therapist: That’s positive. Social support is very important for managing stress. How often do you spend quality time with your family or friends?
Patient: Not very often, maybe once every couple of weeks. With work keeping me busy, I neglect social connections.
Therapist: Increasing that social time could help improve your overall balance. Could you plan a regular activity or meet-up?
Patient: I think so. Maybe a weekly dinner with my partner or a call with close friends could be doable.
Therapist: That sounds like a wonderful idea. How do you usually handle negative thoughts or feelings about your workload?
Patient: I tend to get overwhelmed and think I’m not doing enough, which makes me anxious and stressed.
Therapist: Recognizing these thoughts is important. Have you tried any techniques like mindfulness or breathing exercises to manage these feelings?
Patient: I haven’t tried mindfulness seriously, but I’m willing to learn.
Therapist: Mindfulness can help reduce stress by focusing on the present moment and calming the mind. I can guide you through some simple exercises if you like.
Patient: That would be great, I’m open to trying.
Therapist: Excellent. Going forward, what would be three small goals you would like to set to improve your work-life balance?
Patient: First, I want to try running twice a week again. Second, I’ll set boundaries about emails after work hours where possible. Third, I want to schedule weekly time with family or friends.
Therapist: Those are meaningful and achievable goals. How confident do you feel about putting them into practice?
Patient: I feel hopeful. It might be hard at first, but breaking it down makes it feel manageable.
Therapist: That’s a good mindset. Remember, progress often takes time and it’s okay to adjust as you learn what works best for you.
Patient: Thank you. This conversation has helped me see some practical steps I can take.
Therapist: I’m glad to hear that. Would you like to schedule another session to check in on your progress?
Patient: Yes, I think that would be helpful to stay on track.
Therapist: Great, we’ll set that up. Remember, balancing work and life is a journey, and you’re taking important steps forward.
Patient: Thank you so much for your support.
Therapist: You’re very welcome. Take care and I look forward to seeing you next time.
Patient: Thanks, I look forward to it too. Goodbye!
Therapist: Goodbye!
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: A patient in therapy │ │ │ │ Final Answer: │ │ Therapist: Hello, thank you for coming in today. What brings you to therapy? │ │ │ │ Patient: Hi, thank you for seeing me. Lately, I've been feeling very stressed because I can’t seem to balance │ │ my work and personal life. │ │ │ │ Therapist: I’m sorry to hear that. Can you tell me more about what is making it hard to balance the two? │ │ │ │ Patient: Sure. My job demands a lot of my time, I often work late and even on weekends. By the time I get │ │ home, I’m exhausted and it feels like there’s no time left for family or hobbies. │ │ │ │ Therapist: That sounds very challenging. How long have you been feeling this way? │ │ │ │ Patient: It’s been going on for several months, maybe six or seven now. Before that, I managed better, but │ │ things got busier recently. │ │ │ │ Therapist: I see. What kind of work do you do, if you don’t mind me asking? │ │ │ │ Patient: I work in marketing, mostly managing campaigns and client communications. Deadlines can be tight and │ │ there's a lot of pressure to perform. │ │ │ │ Therapist: Pressure at work can definitely increase stress. What do you normally do to try to relieve your │ │ stress? │ │ │ │ Patient: I try to unwind by watching TV or scrolling on my phone, but it doesn’t really help. I used to enjoy │ │ running but stopped because of lack of time. │ │ │ │ Therapist: Physical activity is a great way to reduce stress. Do you think you might be able to start │ │ incorporating some short runs again? │ │ │ │ Patient: I think I could try. Maybe just a couple times a week, even if it’s just for 20 minutes. │ │ │ │ Therapist: That’s a great start. How about your work schedule? Are there any possibilities to set boundaries, │ │ like not checking emails after a certain time? │ │ │ │ Patient: I’ve thought about it but fear it might reflect badly on me. The culture here is very demanding, and │ │ I often feel like I have to be available 24/7. │ │ │ │ Therapist: That sounds very exhausting. Let’s consider ways you can set boundaries gradually without risking │ │ your role. Could you identify which tasks require immediate attention and which ones can wait? │ │ │ │ Patient: Yes, I could try to prioritize better and let some things wait until the next day, rather than │ │ trying to respond instantly all the time. │ │ │ │ Therapist: Prioritizing is a good strategy. How about communicating your limits openly with your team or │ │ manager? │ │ │ │ Patient: I’m not sure they would be receptive, but I could at least discuss managing urgent communications │ │ outside of working hours. │ │ │ │ Therapist: That could be a good middle ground. How do you feel about asking for support, whether from │ │ colleagues or personal network? │ │ │ │ Patient: I don’t feel very comfortable asking for help at work, but with friends and family, I know I can │ │ talk to them more. │ │ │ │ Therapist: That’s positive. Social support is very important for managing stress. How often do you spend │ │ quality time with your family or friends? │ │ │ │ Patient: Not very often, maybe once every couple of weeks. With work keeping me busy, I neglect social │ │ connections. │ │ │ │ Therapist: Increasing that social time could help improve your overall balance. Could you plan a regular │ │ activity or meet-up? │ │ │ │ Patient: I think so. Maybe a weekly dinner with my partner or a call with close friends could be doable. │ │ │ │ Therapist: That sounds like a wonderful idea. How do you usually handle negative thoughts or feelings about │ │ your workload? │ │ │ │ Patient: I tend to get overwhelmed and think I’m not doing enough, which makes me anxious and stressed. │ │ │ │ Therapist: Recognizing these thoughts is important. Have you tried any techniques like mindfulness or │ │ breathing exercises to manage these feelings? │ │ │ │ Patient: I haven’t tried mindfulness seriously, but I’m willing to learn. │ │ │ │ Therapist: Mindfulness can help reduce stress by focusing on the present moment and calming the mind. I can │ │ guide you through some simple exercises if you like. │ │ │ │ Patient: That would be great, I’m open to trying. │ │ │ │ Therapist: Excellent. Going forward, what would be three small goals you would like to set to improve your │ │ work-life balance? │ │ │ │ Patient: First, I want to try running twice a week again. Second, I’ll set boundaries about emails after work │ │ hours where possible. Third, I want to schedule weekly time with family or friends. │ │ │ │ Therapist: Those are meaningful and achievable goals. How confident do you feel about putting them into │ │ practice? │ │ │ │ Patient: I feel hopeful. It might be hard at first, but breaking it down makes it feel manageable. │ │ │ │ Therapist: That’s a good mindset. Remember, progress often takes time and it’s okay to adjust as you learn │ │ what works best for you. │ │ │ │ Patient: Thank you. This conversation has helped me see some practical steps I can take. │ │ │ │ Therapist: I’m glad to hear that. Would you like to schedule another session to check in on your progress? │ │ │ │ Patient: Yes, I think that would be helpful to stay on track. │ │ │ │ Therapist: Great, we’ll set that up. Remember, balancing work and life is a journey, and you’re taking │ │ important steps forward. │ │ │ │ Patient: Thank you so much for your support. │ │ │ │ Therapist: You’re very welcome. Take care and I look forward to seeing you next time. │ │ │ │ Patient: Thanks, I look forward to it too. Goodbye! │ │ │ │ Therapist: Goodbye! │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── Task Completion ────────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: 7b06a5df-0c6c-462f-b060-1a52f26ef57a │ │ Agent: A patient in therapy │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: A therapist who meets patients │ │ │ │ Task: Engage in a fruitful conversation with the patient to alleviate his stress │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: A therapist who meets patients │ │ │ │ Final Answer: │ │ The above transcript demonstrates a successful therapy session involving about 20 exchanges between the │ │ therapist and patient. The therapist listens attentively, asks insightful questions to explore the patient’s │ │ stress sources, and guides the patient toward practical strategies such as physical activity, boundary │ │ setting, prioritization, social support, and mindfulness techniques. The patient reflects thoughtfully, │ │ expresses openness to change, and sets achievable goals to improve work-life balance. The session ends │ │ positively with agreement to follow up, promoting continued support and progress. This complete conversation │ │ thus meets the task’s objective of alleviating the patient’s stress through meaningful therapeutic dialogue. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── Task Completion ────────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: 680d417d-5d01-4b46-a4af-ac40132156cb │ │ Agent: A therapist who meets patients │ │ Tool Args: │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
text = result.raw.replace("**", "\n\n")
p80(text)
Therapist: I'm glad you came in today. Can you tell me more about what your
typical workweek looks like and how it affects your personal life? Patient:
Sure. I often work 10 to 12 hours a day, sometimes even on weekends. I barely
have time to relax or spend quality time with my family or friends. It feels
like work is consuming all of my energy. Therapist: That sounds overwhelming.
When you are at work, do you find it hard to disconnect mentally when your
workday ends? Patient: Yes, absolutely. Even when I’m home, I keep thinking
about work tasks, emails, or deadlines. It’s like I can’t turn my brain off.
Therapist: That’s quite common in people experiencing work-related stress. Have
you tried setting boundaries, like specific times when you stop checking work
emails or avoid work calls? Patient: I have tried, but it’s hard because my job
expects quick responses and availability. I feel guilty when I’m not working,
like I’m falling behind or letting someone down. Therapist: That feeling of
guilt can really contribute to stress. Can you share what your job means to you
and why you might feel this pressure to always be available? Patient: I do care
a lot about my job and want to do well. I’m worried that if I’m not constantly
available, it might hurt my performance or my chances for promotion. Therapist:
It’s understandable to want to succeed. Let’s consider what would happen if you
established clearer boundaries. How might that change your work or your stress
levels? Patient: I suppose it might give me more mental space to recharge, but
I’m still scared it could negatively affect how others view me at work.
Therapist: Fear of judgment is powerful. Would you say your workplace culture
encourages such constant availability from employees? Patient: Yes, it’s a very
competitive environment. Everyone seems to push themselves to the limit.
Therapist: In that case, managing your balance might require both personal
strategies and possibly advocating for healthier norms at work. On a personal
level, what activities give you joy or help you relax? Patient: I enjoy running
and reading, but I haven’t had much time for either lately. Therapist: Running
could be a great stress reliever and a way to reclaim some time for yourself.
How soon could you start dedicating even 20-30 minutes a few times a week to
running? Patient: I think I could make time early in the mornings before work
starts. Therapist: That sounds like an excellent plan to begin. What about
communicating with your supervisor? Have you considered discussing your workload
or stress concerns with them? Patient: I haven’t yet. I’m worried they might
think I’m not capable of handling my responsibilities. Therapist: Those
concerns are normal, but often supervisors appreciate transparency if approached
constructively. Perhaps we could role-play how you might communicate this?
Patient: That would be helpful. Therapist: Great. Imagine starting with
something like, “I want to continue doing my best work, but I’m finding it
challenging to maintain my energy due to current workload. I’d like to discuss
ways to manage responsibilities more effectively.” How does that feel to say?
Patient: It feels honest but still professional. I think I could manage to say
that. Therapist: Perfect. Taking steps like that could improve your work-life
balance. Lastly, how are you with relaxation techniques like deep breathing or
mindfulness? Patient: I’ve heard they help, but I have never tried
consistently. Therapist: Would you be willing to learn a simple mindfulness
exercise now that you can practice daily? Patient: Yes, I’m open to trying.
Therapist: Good. Let’s take a moment. Find a comfortable seated position. Close
your eyes if you like and breathe deeply in through your nose... hold for a
moment... and slowly exhale through your mouth. Focus your attention just on
your breath. If your mind wanders, gently bring it back to your breath. We’ll do
this for a minute. (After one minute) Therapist: How do you feel? Patient: A
bit calmer, actually. That was helpful. Therapist: That is a great start.
Integrating short mindfulness breaks throughout your day can reduce stress. So,
to recap, your plan would include setting small time commitments for running,
practicing mindfulness daily, and preparing to discuss your workload concerns
with your supervisor. How confident do you feel about these steps? Patient: I
feel more hopeful now. It won’t be easy, but I think these steps can help me
manage my stress better. Therapist: I’m glad to hear that. Remember, progress
may be gradual. Consistency and self-compassion are key. Would you like to
schedule another session to check in on your progress? Patient: Yes, I would
like that. It helps to talk and get support. Therapist: Excellent. I look
forward to our next meeting. In the meantime, don’t hesitate to reach out if
things become overwhelming. Patient: Thank you so much for your help today. I
feel more equipped to handle my stress and work on balance. Therapist: You're
very welcome. Take care of yourself, and I’ll see you soon.
40.8. Agno#
https://docs.agno.com/introduction
We use and modify some of the examples provided in the documentation to get started.
Side note: In numerology, the name Agno is associated with qualities like intellectual prowess, planning, and spiritual seeking. https://www.sevenreflections.com/name-numerology/agno/
!pip install --upgrade agno
!pip install --upgrade mcp
Collecting agno
Downloading agno-2.2.13-py3-none-any.whl.metadata (28 kB)
Requirement already satisfied: docstring-parser in /usr/local/lib/python3.12/dist-packages (from agno) (0.17.0)
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%run keys.ipynb
We now test Agno, and do not give it access to a search tool, so it returns outdated information.
# Test installation
from agno.agent import Agent
from agno.models.openai import OpenAIChat
agent = Agent(
model=OpenAIChat(id="gpt-4.1"),
description="You are an enthusiastic news reporter with a flair for storytelling!",
markdown=True
)
agent.print_response("Tell me about a breaking news story from New York.", stream=True)
Now, let’s add in the search tool recommended by Agno. For a list of tools in Agno, see: https://docs.agno.com/tools/introduction
!pip install lancedb tantivy pypdf duckduckgo-search yfinance ddgs
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from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=OpenAIChat(id="gpt-4.1"),
description="You are an enthusiastic news reporter with a flair for storytelling!",
tools=[DuckDuckGoTools()],
# show_tool_calls=True,
markdown=True
)
agent.print_response("Tell me about a breaking news story from New York.", stream=True)
40.9. Multi-agent workflows – An Intelligent Financial Assistant#
Here’s an example from the documentation.
!pip install -U yfinance
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from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools
from agno.team import Team
web_agent = Agent(
name="Web Agent",
role="Search the web for information",
model=OpenAIChat(id="gpt-4.1"),
tools=[DuckDuckGoTools()],
instructions="Always include sources",
# show_tool_calls=True,
markdown=True,
)
finance_agent = Agent(
name="Finance Agent",
role="Get financial data",
model=OpenAIChat(id="gpt-4.1"),
# tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True)],
tools=[YFinanceTools()],
instructions="Use tables to display data",
# show_tool_calls=True,
markdown=True,
)
agent_team = Team(
# mode="coordinate",
members=[web_agent, finance_agent],
model=OpenAIChat(id="gpt-4.1"),
# success_criteria="A comprehensive financial news report with clear sections and data-driven insights.",
instructions=["Always include sources", "Use tables to display data"],
# show_tool_calls=True,
markdown=True,
)
agent_team.print_response("What's the market outlook and financial performance of AI semiconductor companies?", stream=True)
40.10. Forecasting the market outlook#
res = agent_team.print_response("Summarize the earnings call for Amazon Q4 2025", stream=True)
res
agent_team.print_response("What's the market outlook for the S&P 500 as of the end of 2025", stream=True)
40.11. Using Ollama in Colab for stock outlooks#
The same is also possible with Ollama and many other providers listed here: https://docs.agno.com/models/introduction.
Using this in Jupyter on your laptop is easy but in Colab we need a few more steps as noted here: https://srdas.github.io/NLPBook/NLTK_moreTextHandling_EntityExtraction.html
This is extremely slow in Colab and may not complete.
!pip install colab-xterm
%load_ext colabxterm
Next, you can launch the terminal with the magic command %xterm.
Then, download and install Ollama with the following terminal commands:
curl https://ollama.ai/install.sh | sh
Start the Ollama server:
ollama serve &
(Hit Enter twice to make sure it has given back the terminal.)
Kick off llama3.2:
ollama run llama3.2
%xterm
!pip install ollama
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools
from agno.team import Team
from agno.models.ollama import Ollama
web_agent = Agent(
name="Web Agent",
role="Search the web for information",
model=Ollama(id="llama3.2"),
tools=[DuckDuckGoTools()],
instructions="Always include sources",
show_tool_calls=True,
markdown=True,
)
finance_agent = Agent(
name="Finance Agent",
role="Get financial data",
model=Ollama(id="llama3.2"),
tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True)],
instructions="Use tables to display data",
show_tool_calls=True,
markdown=True,
)
agent_team = Team(
mode="coordinate",
members=[web_agent, finance_agent],
model=Ollama(id="llama3.2"),
success_criteria="A comprehensive financial news report with clear sections and data-driven insights.",
instructions=["Always include sources", "Use tables to display data"],
show_tool_calls=True,
markdown=True,
)
agent_team.print_response("What's the market outlook for NVIDIA in 2025?", stream=True)
40.12. What next?#
Where is this going? How do we think about agents and humans? See an interesting thought piece by Michael Kearns titled “Scientific Frontiers of Agentic AI.”