gistfile1.py

import os
from langchain.agents import Tool
from langchain.tools.retriever import create_retriever_tool
from langchain_openai import OpenAIEmbeddings
from indexclient import IndexChroma
from crewai import Agent, Task, Crew, Process


# TODO
# I had to install langchain_chroma seperately. It should be included in the requirements
# I had to find how to import `indexclient` instead of `indexnetwork-sdk`, we need to update docs
# Sources parameter should be mandatory

os.environ["OPENAI_MODEL_NAME"]="gpt-4o"
os.environ['OPENAI_API_KEY'] = 'YOUR_OPENAI_KEY'

embeddings = OpenAIEmbeddings(model="text-embedding-ada-002")

vectorstore = IndexChroma(embedding_function=embeddings, network="mainnet")

tool = create_retriever_tool(
    vectorstore.as_retriever( search_kwargs={'filter': {'indexId':'kjzl6kcym7w8y806zfnn4zymjuk1acvljrjc9qnwpfaqvfkwi4yyw071h7pb0wv'}}),
    "index_retriever",
    "Searches and returns documents.",
)

# Creating a senior researcher agent with memory and verbose mode
researcher = Agent(
  role='Senior Researcher',
  goal='Provide comperhensive and complete responses in {topic}',
  verbose=True,
  memory=True,
  backstory=(
    "An expert analyst with a keen eye."
  ),
  tools=[tool],
  allow_delegation=True
)

# Creating a writer agent with custom tools and delegation capability
writer = Agent(
  role='Writer',
  goal='Narrate the research about {topic}',
  verbose=True,
  memory=True,
  backstory=(
    "With a flair for simplifying complex topics, you craft"
    "engaging narratives that captivate and educate, bringing new"
    "discoveries to light in an accessible manner."
  ),
  tools=[tool],
  allow_delegation=False
)

# Research task
research_task = Task(
  description=(
    "Identify the elements of {topic}."
    "Focus on identifying pros and cons and the overall narrative."
    "Your final report should clearly articulate the key points."
  ),
  expected_output='A comprehensive 3 paragraphs long report ',
  tools=[tool],
  agent=researcher,
)

# Writing task with language model configuration
write_task = Task(
  description=(
    "Compose an insightful article on {topic}."
    "This article should be easy to understand, engaging, and positive."
  ),
  expected_output='A 4 paragraph article on {topic} formatted as markdown.',
  tools=[tool],
  agent=writer,
  async_execution=False,
  output_file='new-blog-post.md'  # Example of output customization
)



# Forming the tech-focused crew with some enhanced configurations
crew = Crew(
  agents=[researcher, writer],
  tasks=[research_task, write_task],
  process=Process.sequential,  # Optional: Sequential task execution is default
  memory=True,
  cache=True,
  max_rpm=100,
  share_crew=True
)

result = crew.kickoff(inputs={'topic': 'Differences between the cross-chain solutions'})
print(result)