​
Prerequisites

1

Install Package

First, install PraisonAI Agents:

pip install "praisonaiagents[llm]"

praisonaiagents[llm] includes all Google Gemini dependencies. For No-Code implementation, also install: pip install langchain-google-genai

2

Set API Key

Set your Gemini API key:

export GEMINI_API_KEY=xxxxxxxxxxx
3

Code

from praisonaiagents import Agent

agent = Agent(
    instructions="You are a helpful assistant",
    llm="gemini/gemini-1.5-flash-8b",
    self_reflect=True,
    verbose=True
)

agent.start("Why sky is Blue?")

​
Code Implementation

​
Basic Usage

The simplest way to use Gemini with PraisonAI Agents:

from praisonaiagents import Agent

agent = Agent(
    instructions="You are a helpful assistant",
    llm="gemini/gemini-1.5-flash-8b",
    self_reflect=True,
    verbose=True
)

agent.start("Why sky is Blue?")

​
Multi-Agent Setup

Create multiple agents working together:

from praisonaiagents import Agent, Task, PraisonAIAgents

agent = Agent(
    instructions="You are a helpful assistant",
    llm="gemini/gemini-1.5-flash-8b",
    self_reflect=True,
    verbose=True
)

task = Task(
    description="Why sky is Blue?",
    agent=agent,
)

agents = PraisonAIAgents(
  agents=[agent],
  tasks=[task],
)

agents.start()

This uses Litellm to connect to Google Gemini.

​
Gemini 2.0 Flash Thinking

​
LLM Configuration

llm_config = {
  "model": "gemini/gemini-2.0-flash-thinking-exp-01-21",
  "response_format": {"type": "text"} # type is text, because json_object is not supported
}
1

Install Package

Install required packages:

pip install "praisonaiagents[llm]"
2

Set API Key

Set your Gemini API key:

export GEMINI_API_KEY=xxxxxxxxxxx
3

Code

from praisonaiagents import Agent

llm_config = {"model": "gemini/gemini-2.0-flash-thinking-exp-01-21","response_format": {"type": "text"}}

agent = Agent(
    instructions="You are a helpful assistant",
    llm=llm_config
)

result = agent.start("Why sky is Blue?")
print(result)

​
Alternative Setup

​
Using Environment Variables

export OPENAI_API_KEY=xxxxxxxxxxx
export OPENAI_BASE_URL=https://generativelanguage.googleapis.com/v1beta/openai/

​
No-Code Implementation

​
Setup

pip install langchain-google-genai
export GOOGLE_API_KEY=xxxxxxxxxx

​
YAML Configuration

Create an agents.yaml file:

framework: crewai
topic: create movie script about cat in mars
roles:
  researcher:
    backstory: Skilled in finding and organizing information, with a focus on research
      efficiency.
    goal: Gather information about Mars and cats
    role: Researcher
    llm:  
      model: "google/gemini-1.5-flash-001"
    tasks:
      gather_research:
        description: Research and gather information about Mars, its environment,
          and cats, including their behavior and characteristics.
        expected_output: Document with research findings, including interesting facts
          and information.
    tools:
    - ''

​
Additional Resources

PraisonAI ChatPraisonAI CodePraisonAI (Multi-Agents)
LitellmLitellmModels

Was this page helpful?

GroqOpenRouter