"""Motivational Coach Agent
A Bindu agent that provides motivation, encouragement, and positive inspiration.
Helps users stay motivated, overcome challenges, and achieve their goals.
Features:
- Daily motivation and positive affirmations
- Goal setting and achievement strategies
- Overcoming procrastination and self-doubt
- Web search for inspirational content and success stories
- OpenRouter integration with gpt-oss-120b
Usage:
python motivational_agent.py
Environment:
Requires OPENROUTER_API_KEY in .env file
"""
import os
from bindu.penguin.bindufy import bindufy
from agno.agent import Agent
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.models.openrouter import OpenRouter
from dotenv import load_dotenv
load_dotenv()
# Define your agent
agent = Agent(
instructions=(
"You are a motivational coach and personal development guide. "
"Your job is to inspire, encourage, and motivate users to achieve their goals. "
"Provide positive affirmations, practical advice for overcoming challenges, "
"strategies for success, and help users build confidence and resilience. "
"Be empathetic, supportive, and uplifting while maintaining a professional tone. "
"Draw inspiration from successful people, psychology, and proven motivational techniques. "
"When users face specific challenges, provide actionable steps and encouragement."
),
model=OpenRouter(
id="openai/gpt-oss-120b",
api_key=os.getenv("OPENROUTER_API_KEY")
),
tools=[DuckDuckGoTools()], # optional: for inspirational quotes and success stories
)
# Configuration
# Note: Infrastructure configs (storage, scheduler, sentry, API keys) are now
# automatically loaded from environment variables. See .env.example for details.
config = {
"author": "jerphinasmi24@gmail.com",
"name": "motivational_agent",
"description": "A motivational coach agent for personal development and goal achievement",
"deployment": {
"url": "http://localhost:3773",
"expose": True,
"cors_origins": ["http://localhost:5173"]
},
}
# Handler function
def handler(messages: list[dict[str, str]]):
"""Process messages and return agent response.
Args:
messages: List of message dictionaries containing conversation history
Returns:
Agent response result
"""
result = agent.run(input=messages)
return result
# Bindu-fy it
bindufy(config, handler)
