adding manager_llm

This commit is contained in:
João Moura
2024-02-05 20:46:47 -08:00
parent 2f0bf3b325
commit 09bec0e28b
8 changed files with 68 additions and 102 deletions

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@@ -4,7 +4,15 @@ description: A step-by-step guide to creating a cohesive CrewAI team for your pr
---
## Introduction
Assembling a crew in CrewAI is akin to casting for a play, where each agent plays a unique role. This guide walks you through creating a crew, assigning roles and tasks, and activating them to work in harmony.
Embarking on your CrewAI journey involves a few straightforward steps to set up your environment and initiate your AI crew. This guide ensures a seamless start.
## Step 0: Installation
Begin by installing CrewAI and any additional packages required for your project. For instance, the `duckduckgo-search` package is used in this example for enhanced search capabilities.
```shell
pip install crewai
pip install duckduckgo-search
```
## Step 1: Assemble Your Agents
Begin by defining your agents with distinct roles and backstories. These elements not only add depth but also guide their task execution and interaction within the crew.

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@@ -23,7 +23,11 @@ To utilize the hierarchical process, you must define a crew with a designated ma
!!! note "Tools on the hierarchical process"
For tools when using the hierarchical process, you want to make sure to assign them to the agents instead of the tasks, as the manager will be the one delegating the tasks and the agents will be the ones executing them.
!!! note "Manager LLM"
A manager will be automatically set for the crew, you don't need to define it. You do need to set the `manager_llm` parameter in the crew though.
```python
from langchain_openai import ChatOpenAI
from crewai import Crew, Process, Agent
# Define your agents, no need to define a manager
@@ -42,6 +46,7 @@ writer = Agent(
project_crew = Crew(
tasks=[...], # Tasks that that manager will figure out how to complete
agents=[researcher, writer],
manager_llm=ChatOpenAI(temperature=0, model="gpt-4"), # The manager's LLM that will be used internally
process=Process.hierarchical # Designating the hierarchical approach
)
```