iplayfast
commented
8 months ago This is my attempt at creating your example with Ollama instead of openai. I've defined latest_trends as a tool and imported duckduckgo_search but it still seems borked. I'm stuck as I don't know what's wrong (and the doc ai isn't helping).
import os
from crewai import Agent, Task, Crew, Process
from langchain.llms import Ollama
import duckduckgo_search
from langchain.tools import tool
import requests
from bs4 import BeautifulSoup
@tool
def latest_trends(topic: str) -> str:
"""
Search news.google.com for trends on a given topic.
This function takes a topic as a string, queries news.google.com for trends related to this topic,
and returns the trends found as a string.
"""
print(f"latest_trends tool called with topic: {topic}") # Debugging statement
# [Rest of the tool code]
# Format the topic for URL encoding
formatted_topic = topic.replace(" ", "%20")
# Construct the search URL
url = f"https://news.google.com/search?q=Trends%20on%20{formatted_topic}"
# Perform the web request
response = requests.get(url)
# Check if the request was successful
if response.status_code != 200:
return "Failed to retrieve data from news.google.com"
# Parse the HTML content
soup = BeautifulSoup(response.text, 'html.parser')
# Extract trend data
# The following is a placeholder; you'll need to adjust it based on the page structure
trends = []
for article in soup.find_all("article"):
title = article.find("h3").get_text() if article.find("h3") else "No title"
summary = article.find("p").get_text() if article.find("p") else "No summary"
trends.append(f"Title: {title}\nSummary: {summary}\n")
# Format the extracted trends
trends_output = "\n".join(trends) if trends else "No trends found for the topic."
return trends_output
ollama_mistral = Ollama(model="mistral")
# Pass Ollama Model to Agents: When creating your agents within the CrewAI framework, you can pass the Ollama model as an argument to the Agent constructor. For instance:
# Define your agents with roles and goals
researcher = Agent(
role='Researcher',
goal='Discover new insights',
backstory="You're a world class researcher working on a major data science company",
verbose=True,
allow_delegation=False,
llm=ollama_mistral, # Ollama model passed here
# llm=OpenAI(temperature=0.7, model_name="gpt-4"). It uses langchain.chat_models, default is GPT4
tools=[latest_trends,duckduckgo_search],
)
writer = Agent(
role='Writer',
goal='Create engaging content',
backstory="You're a famous technical writer, specialized on writing data related content",
verbose=True,
allow_delegation=False,
llm=ollama_mistral, # Ollama model passed here
)
# Create tasks for your agents
task1 = Task(description='Investigate the latest AI trends', agent=researcher)
task2 = Task(description='Write a blog post on AI advancements', agent=writer)
# Instantiate your crew with a sequential process
crew = Crew(
agents=[researcher, writer],
tasks=[task1, task2],
verbose=True, # Crew verbose more will let you know what tasks are being worked on
process=Process.sequential # Sequential process will have tasks executed one after the other and the outcome of the previous one is passed as extra content into this next.
)
# Get your crew to work!
result = crew.kickoff()
fxtoofaan
greysonlalonde
joaomdmoura
PiotrEsse
Adamchanadam
I set up your Readme example with Ollama and things seemed to work. But it was looking for a 'latest trends' tool which isn't available.
The example doesn't talk about this so I'm not sure where to go now.