CrewAI

pip install crewai 'crewai[tools]' exa_py

from crewai_tools import tool
from exa_py import Exa
import os

exa_api_key = os.getenv("EXA_API_KEY")

@tool("Exa search and get contents")
def search_and_get_contents_tool(question: str) -> str:
    """Tool using Exa's Python SDK to run semantic search and return result highlights."""

    exa = Exa(api_key=exa_api_key)

    response = exa.search(
        question,
        type="auto",
        num_results=10,
        contents={"highlights": True}
    )

    parsedResult = ''.join([
      f'<Title id={idx}>{eachResult.title}</Title>'
      f'<URL id={idx}>{eachResult.url}</URL>'
      f'<Highlight id={idx}>{"".join(eachResult.highlights)}</Highlight>'
      for (idx, eachResult) in enumerate(response.results)
    ])

    return parsedResult

from crewai import Task, Crew, Agent

exa_tools = search_and_get_contents_tool

# Creating a senior researcher agent with memory and verbose mode
researcher = Agent(
  role='Researcher',
  goal='Get the latest research on {topic}',
  verbose=True,
  memory=True,
  backstory=(
    "Driven by curiosity, you're at the forefront of"
    "innovation, eager to explore and share knowledge that could change"
    "the world."
  ),
  tools=[exa_tools],
  allow_delegation=False
)

article_writer = Agent(
  role='Writer',
  goal='Write a great newsletter article on {topic}',
  verbose=True,
  memory=True,
  backstory=(
    "Driven by a love of writing and passion for"
    "innovation, you are eager to share knowledge with"
    "the world."
  ),
  tools=[exa_tools],
  allow_delegation=False
)

research_task = Task(
  description=(
    "Identify the latest research in {topic}."
    "Your final report should clearly articulate the key points,"
  ),
  expected_output='A comprehensive 3 paragraphs long report on the {topic}.',
  tools=[exa_tools],
  agent=researcher,
)

write_article = Task(
  description=(
    "Write a newsletter article on the latest research in {topic}."
    "Your article should be engaging, informative, and accurate."
    "The article should address the audience with a greeting to the newsletter audience \"Hi readers!\", plus a similar signoff"
  ),
  expected_output='A comprehensive 3 paragraphs long newsletter article on the {topic}.',
  agent=article_writer,
)

crew = Crew(
  agents=[researcher, article_writer],
  tasks=[research_task, write_article],
  memory=True,
  cache=True,
  max_rpm=100,
  share_crew=True
)

response = crew.kickoff(inputs={'topic': 'Latest AI research'})

print(response)

[... Prior output truncated ...]

> Finished chain.
Hi readers!

As we step into the promising arena of 2024, we bring you some of the most significant advancements in the field of AI research. The year witnessed a considerable focus on the development of AI agents and LLMs (Large Language Models). Adept, a frontrunner in the space, showcased an agent that can find apartments on Redfin, input information into Salesforce, and interact with spreadsheets using natural language. While there is no clear winner on the commercial front yet, this development promises a future where AI can perform tasks for us.

The year also saw a continued focus on LLMs, with efforts directed towards matching the text performance of GPT-4 with smaller models. An interesting outcome of these efforts was the Falcon 7B model, which matches the performance of the 8B PaLM model. This model, interestingly, uses 100% web data for pretraining. It's worth mentioning that LLMs were also used to generate imitation models, which mimic the style of upstream LLMs. One study found that these models are highly rated by crowd workers.

In the field of computer vision, there were numerous developments. One noteworthy mention is the ASSET paper that introduced an architecture capable of modifying an input high-resolution image according to a user's edits on its semantic segmentation map. This advancement points to the possibility of synthesizing interesting phenomena in scenes, which has the potential to revolutionize the way we interact with digital imagery.

As we continue to explore the ever-evolving landscape of AI, we hope to bring you more such exciting updates. Stay tuned and until next time, keep exploring!

Best,
[Your Name]