updated agents

This commit is contained in:
jad2121 2024-03-04 17:09:25 -05:00
parent 54406181b4
commit 295d8d53f6
3 changed files with 10 additions and 98 deletions

View File

@ -1 +0,0 @@
3.10

View File

@ -1,81 +0,0 @@
from langchain_community.tools import DuckDuckGoSearchRun
import os
from crewai import Agent, Task, Crew, Process
from dotenv import load_dotenv
import os
current_directory = os.path.dirname(os.path.realpath(__file__))
config_directory = os.path.expanduser("~/.config/fabric")
env_file = os.path.join(config_directory, ".env")
load_dotenv(env_file)
os.environ['OPENAI_MODEL_NAME'] = 'gpt-4-0125-preview'
# You can choose to use a local model through Ollama for example. See https://docs.crewai.com/how-to/LLM-Connections/ for more information.
# osOPENAI_API_BASE='http://localhost:11434/v1'
# OPENAI_MODEL_NAME='openhermes' # Adjust based on available model
# OPENAI_API_KEY=''
# Install duckduckgo-search for this example:
# !pip install -U duckduckgo-search
search_tool = DuckDuckGoSearchRun()
# Define your agents with roles and goals
researcher = Agent(
role='Senior Research Analyst',
goal='Uncover cutting-edge developments in AI and data science',
backstory="""You work at a leading tech think tank.
Your expertise lies in identifying emerging trends.
You have a knack for dissecting complex data and presenting actionable insights.""",
verbose=True,
allow_delegation=False,
tools=[search_tool]
# You can pass an optional llm attribute specifying what mode you wanna use.
# It can be a local model through Ollama / LM Studio or a remote
# model like OpenAI, Mistral, Antrophic or others (https://docs.crewai.com/how-to/LLM-Connections/)
#
# import os
#
# OR
#
# from langchain_openai import ChatOpenAI
# llm=ChatOpenAI(model_name="gpt-3.5", temperature=0.7)
)
writer = Agent(
role='Tech Content Strategist',
goal='Craft compelling content on tech advancements',
backstory="""You are a renowned Content Strategist, known for your insightful and engaging articles.
You transform complex concepts into compelling narratives.""",
verbose=True,
allow_delegation=True
)
# Create tasks for your agents
task1 = Task(
description="""Conduct a comprehensive analysis of the latest advancements in AI in 2024.
Identify key trends, breakthrough technologies, and potential industry impacts.""",
expected_output="Full analysis report in bullet points",
agent=researcher
)
task2 = Task(
description="""Using the insights provided, develop an engaging blog
post that highlights the most significant AI advancements.
Your post should be informative yet accessible, catering to a tech-savvy audience.
Make it sound cool, avoid complex words so it doesn't sound like AI.""",
expected_output="Full blog post of at least 4 paragraphs",
agent=writer
)
# Instantiate your crew with a sequential process
crew = Crew(
agents=[researcher, writer],
tasks=[task1, task2],
verbose=2, # You can set it to 1 or 2 to different logging levels
)
# Get your crew to work!
result = crew.kickoff()
print("######################")
print(result)

View File

@ -1,4 +1,5 @@
from .utils import Standalone, Update, Setup, Alias, AgentSetup
from .agents.trip_planner.main import planner_cli
import argparse
import sys
import time
@ -16,12 +17,11 @@ def main():
parser.add_argument(
"--copy", "-C", help="Copy the response to the clipboard", action="store_true"
)
subparsers = parser.add_subparsers(dest='command', help='Sub-command help')
agents_parser = subparsers.add_parser('agents', help='Crew command help')
agents_parser.add_argument(
"trip_planner", help="The origin city for the trip")
agents_parser.add_argument(
'ApiKeys', help="enter API keys for tools", action="store_true")
parser.add_argument(
'--agents', '-a', choices=['trip_planner', 'ApiKeys'],
help="Use an AI agent to help you with a task. Acceptable values are 'trip_planner' or 'ApiKeys'. This option cannot be used with any other flag."
)
parser.add_argument(
"--output",
"-o",
@ -73,19 +73,13 @@ def main():
Update()
Alias()
sys.exit()
if args.command == "agents":
from .agents.trip_planner.main import planner_cli
if not args.trip_planner:
print("Please provide an agent")
print(f"Available Agents:")
for agent in tripcrew.agents:
print(agent)
sys.exit
elif args.trip_planner:
if args.agents:
# Handle the agents logic
if args.agents == 'trip_planner':
tripcrew = planner_cli()
tripcrew.ask()
sys.exit()
if args.ApiKeys:
elif args.agents == 'ApiKeys':
AgentSetup().run()
sys.exit()
if args.update: