101 lines
3.4 KiB
Plaintext
101 lines
3.4 KiB
Plaintext
---
|
|
title: Personal AI Travel Assistant
|
|
---
|
|
Create a personalized AI Travel Assistant using Mem0. This guide provides step-by-step instructions and the complete code to get you started.
|
|
|
|
## Overview
|
|
|
|
The Personalized AI Travel Assistant uses Mem0 to store and retrieve information across interactions, enabling a tailored travel planning experience. It integrates with OpenAI's GPT-4 model to provide detailed and context-aware responses to user queries.
|
|
|
|
## Setup
|
|
|
|
Install the required dependencies using pip:
|
|
|
|
```bash
|
|
pip install openai mem0ai
|
|
```
|
|
|
|
## Full Code Example
|
|
|
|
Here's the complete code to create and interact with a Personalized AI Travel Assistant using Mem0:
|
|
|
|
```python
|
|
import os
|
|
from openai import OpenAI
|
|
from mem0 import Memory
|
|
|
|
# Set the OpenAI API key
|
|
os.environ['OPENAI_API_KEY'] = 'sk-xxx'
|
|
|
|
class PersonalTravelAssistant:
|
|
def __init__(self):
|
|
self.client = OpenAI()
|
|
self.memory = Memory()
|
|
self.messages = [{"role": "system", "content": "You are a personal AI Assistant."}]
|
|
|
|
def ask_question(self, question, user_id):
|
|
# Fetch previous related memories
|
|
previous_memories = self.search_memories(question, user_id=user_id)
|
|
prompt = question
|
|
if previous_memories:
|
|
prompt = f"User input: {question}\n Previous memories: {previous_memories}"
|
|
self.messages.append({"role": "user", "content": prompt})
|
|
|
|
# Generate response using GPT-4o
|
|
response = self.client.chat.completions.create(
|
|
model="gpt-4o",
|
|
messages=self.messages
|
|
)
|
|
answer = response.choices[0].message.content
|
|
self.messages.append({"role": "assistant", "content": answer})
|
|
|
|
# Store the question in memory
|
|
self.memory.add(question, user_id=user_id)
|
|
return answer
|
|
|
|
def get_memories(self, user_id):
|
|
memories = self.memory.get_all(user_id=user_id)
|
|
return [m['text'] for m in memories]
|
|
|
|
def search_memories(self, query, user_id):
|
|
memories = self.memory.search(query, user_id=user_id)
|
|
return [m['text'] for m in memories]
|
|
|
|
# Usage example
|
|
user_id = "traveler_123"
|
|
ai_assistant = PersonalTravelAssistant()
|
|
|
|
def main():
|
|
while True:
|
|
question = input("Question: ")
|
|
if question.lower() in ['q', 'exit']:
|
|
print("Exiting...")
|
|
break
|
|
|
|
answer = ai_assistant.ask_question(question, user_id=user_id)
|
|
print(f"Answer: {answer}")
|
|
memories = ai_assistant.get_memories(user_id=user_id)
|
|
print("Memories:")
|
|
for memory in memories:
|
|
print(f"- {memory}")
|
|
print("-----")
|
|
|
|
if __name__ == "__main__":
|
|
main()
|
|
```
|
|
|
|
## Key Components
|
|
|
|
- **Initialization**: The `PersonalTravelAssistant` class is initialized with the OpenAI client and Mem0 memory setup.
|
|
- **Asking Questions**: The `ask_question` method sends a question to the AI, incorporates previous memories, and stores new information.
|
|
- **Memory Management**: The `get_memories` and search_memories methods handle retrieval and searching of stored memories.
|
|
|
|
## Usage
|
|
|
|
1. Set your OpenAI API key in the environment variable.
|
|
2. Instantiate the `PersonalTravelAssistant`.
|
|
3. Use the `main()` function to interact with the assistant in a loop.
|
|
|
|
## Conclusion
|
|
|
|
This Personalized AI Travel Assistant leverages Mem0's memory capabilities to provide context-aware responses. As you interact with it, the assistant learns and improves, offering increasingly personalized travel advice and information. |