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from crewai import Agent, Crew, Process, Task
from crewai.project import CrewBase, agent, crew, task
from newsletter_gen.tools.research import SearchAndContents, FindSimilar, GetContents
from langchain_anthropic import ChatAnthropic
from langchain_groq import ChatGroq
from datetime import datetime
import streamlit as st
from typing import Union, List, Tuple, Dict
from langchain_core.agents import AgentFinish
import json
from langchain_google_genai import ChatGoogleGenerativeAI
import os
# JB:
# https://python.langchain.com/v0.2/docs/integrations/chat/ollama/
# LangChain supports many other chat models. Here, we're using Ollama
from langchain_community.chat_models import ChatOllama
# To get rid of the telemetry error messages, try:
# Connection Timeout Error with telemetry.crewai.com #254
# https://github.com/joaomdmoura/crewAI/issues/254
# os.environ["OTEL_SDK_DISABLED"] = "true"
os.environ["OTEL_SDK_DISABLED"] = "true"
# SUCCES:
# DIT LIJKT INDERDAAD DE TELEMETRY ERROR MESSAGES IN DE VS CODE TERMINAL TE VOORKOMEN !!!!!!!!!!
# Wel in die terminal nog deze korte messages:
# 2024-06-14 02:20:17,425 - 25632 - __init__.py-__init__:1218 - WARNING: SDK is disabled.
@CrewBase
class NewsletterGenCrew:
"""NewsletterGen crew"""
agents_config = "config/agents.yaml"
tasks_config = "config/tasks.yaml"
def llm(self):
# llm = ChatAnthropic(model_name="claude-3-sonnet-20240229", max_tokens=4096) # ORIGINAL
#llm = ChatAnthropic(model_name="claude-3-sonnet-20240229",
# # max_tokens=4096,
# cache=True,
# api_key="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"
# ) # JB
# https://console.anthropic.com/dashboard
# https://console.anthropic.com/settings/keys
# jb_anthropic_key_2_13-06-2024:
# ANTHROPIC_API_KEY=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
# https://console.anthropic.com/settings/usage
# llm = ChatGroq(model="llama3-70b-8192")
# https://console.groq.com/docs/rate-limits
# llm = ChatGroq(model="mixtral-8x7b-32768") # JB 13-06-2024 - geeft af en toe rate limit errors
# llm = ChatGoogleGenerativeAI(google_api_key=os.getenv("GOOGLE_API_KEY"))
# https://python.langchain.com/v0.2/docs/integrations/chat/ollama/
# supports many more optional parameters. Hover on your `ChatOllama(...)`
# class to view the latest available supported parameters
# llm = ChatOllama(model="llama3")
llm = ChatOllama(model="mistral:latest")
# check if ollama is running and which LLMs can then be used, run this in Anaconda cmd admin window:
# ollama list
# OUTPUT EXAMPLE:
# (newsletter-gen-py3.11) (base) C:\Users\jfhmb\EXA_CREWAI\exa-crewai-master\exa-crewai-master>ollama list
# NAME ID SIZE MODIFIED
# llama3:latest 365c0bd3c000 4.7 GB 3 days ago
# nomic-embed-text:latest 0a109f422b47 274 MB 3 days ago
# crewai-llama3:latest d952d07761cd 4.7 GB 10 days ago
# llama3:8b 365c0bd3c000 4.7 GB 10 days ago
# mistral:latest 61e88e884507 4.1 GB 6 weeks ago
# mxbai-embed-large:latest 468836162de7 669 MB 6 weeks ago
#
# OLLAMA LOGS:
# C:\Users\jfhmb\AppData\Local\Ollama
print("JB: in class NewsletterGenCrew - using llm: ", llm)
return llm
def step_callback(
self,
agent_output: Union[str, List[Tuple[Dict, str]], AgentFinish],
agent_name,
*args,
):
with st.chat_message("AI"):
# Try to parse the output if it is a JSON string
if isinstance(agent_output, str):
try:
agent_output = json.loads(agent_output)
except json.JSONDecodeError:
pass
if isinstance(agent_output, list) and all(
isinstance(item, tuple) for item in agent_output
):
for action, description in agent_output:
# Print attributes based on assumed structure
st.write(f"Agent Name: {agent_name}")
st.write(f"Tool used: {getattr(action, 'tool', 'Unknown')}")
st.write(f"Tool input: {getattr(action, 'tool_input', 'Unknown')}")
st.write(f"{getattr(action, 'log', 'Unknown')}")
with st.expander("Show observation"):
st.markdown(f"Observation\n\n{description}")
# Check if the output is a dictionary as in the second case
elif isinstance(agent_output, AgentFinish):
st.write(f"Agent Name: {agent_name}")
output = agent_output.return_values
st.write(f"I finished my task:\n{output['output']}")
# Handle unexpected formats
else:
st.write(type(agent_output))
st.write(agent_output)
@agent
def researcher(self) -> Agent:
return Agent(
config=self.agents_config["researcher"],
tools=[SearchAndContents(), FindSimilar(), GetContents()],
verbose=True,
llm=self.llm(),
step_callback=lambda step: self.step_callback(step, "Research Agent"),
)
@agent
def editor(self) -> Agent:
return Agent(
config=self.agents_config["editor"],
verbose=True,
tools=[SearchAndContents(), FindSimilar(), GetContents()],
llm=self.llm(),
step_callback=lambda step: self.step_callback(step, "Chief Editor"),
)
@agent
def designer(self) -> Agent:
return Agent(
config=self.agents_config["designer"],
verbose=True,
allow_delegation=False,
llm=self.llm(),
step_callback=lambda step: self.step_callback(step, "HTML Writer"),
)
@task
def research_task(self) -> Task:
return Task(
config=self.tasks_config["research_task"],
agent=self.researcher(),
output_file=f"logs/{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}_research_task.md",
)
@task
def edit_task(self) -> Task:
return Task(
config=self.tasks_config["edit_task"],
agent=self.editor(),
output_file=f"logs/{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}_edit_task.md",
)
@task
def newsletter_task(self) -> Task:
return Task(
config=self.tasks_config["newsletter_task"],
agent=self.designer(),
output_file=f"logs/{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}_newsletter_task.html",
)
@crew
def crew(self) -> Crew:
"""Creates the NewsletterGen crew"""
return Crew(
agents=self.agents, # Automatically created by the @agent decorator
tasks=self.tasks, # Automatically created by the @task decorator
process=Process.sequential,
verbose=2,
# process=Process.hierarchical, # In case you wanna use that instead https://docs.crewai.com/how-to/Hierarchical/
)
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