[Docs] Add example for building Personal AI Assistant using Mem0 (mem0ai#1486)

Author: deshraj

Diff for: .gitignore

@@ -182,4 +182,5 @@ notebooks/*.yaml
 
 # local directories for testing
 eval/
-qdrant_storage/
+qdrant_storage/
+.crossnote

Diff for: README.md

@@ -18,6 +18,7 @@
 
 Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.
 
+> Note: The Mem0 repository now also includes the Embedchain project. We continue to maintain and support Embedchain ❤️. You can find the Embedchain codebase in the [embedchain](https://github.com/mem0ai/mem0/tree/main/embedchain) directory.
 ## 🚀 Quick Start
 
 ### Installation

Diff for: docs/examples/customer-support-agent.mdx

@@ -24,6 +24,9 @@ Below is the simplified code to create and interact with a Customer Support AI A
 from openai import OpenAI
 from mem0 import Memory
 
+# Set the OpenAI API key
+os.environ['OPENAI_API_KEY'] = 'sk-xxx'
+
 class CustomerSupportAIAgent:
     def __init__(self):
         """

Diff for: docs/examples/overview.mdx

@@ -17,12 +17,16 @@ Here are some examples of how Mem0 can be integrated into various applications:
 ## Example Use Cases
 
 <CardGroup cols={1}>
-  <Card title="Personalized AI Tutor" icon="square-2" href="/examples/personal-ai-tutor">
+  <Card title="Personal AI Tutor" icon="square-1" href="/examples/personal-ai-tutor">
     <img width="100%" src="/images/ai-tutor.png" />
-    Build a Personalized AI Tutor that adapts to student progress and learning preferences. This tutor can offer tailored lessons, remember past interactions, and provide a more effective and engaging educational experience.
+    Create a Personalized AI Tutor that adapts to student progress and learning preferences.
   </Card>
-  <Card title="Customer Support Agent" icon="square-1" href="/examples/customer-support-agent">
+  <Card title="Personal Travel Assistant" icon="square-2" href="/examples/personal-travel-assistant">
+    <img src="/images/personal-travel-agent.png" />
+    Build a Personalized AI Travel Assistant that understands your travel preferences and past itineraries.
+  </Card>
+  <Card title="Customer Support Agent" icon="square-3" href="/examples/customer-support-agent">
     <img width="100%" src="/images/customer-support-agent.png" />
-    Develop a Personal AI Assistant that can remember user preferences, past interactions, and context to provide personalized and efficient assistance. This assistant can manage tasks, provide reminders, and adapt to individual user needs, enhancing productivity and user experience.
+    Develop a Personal AI Assistant that remembers user preferences, past interactions, and context to provide personalized and efficient assistance.
   </Card>
 </CardGroup>

Diff for: docs/examples/personal-ai-tutor.mdx

@@ -23,6 +23,9 @@ Below is the complete code to create and interact with a Personalized AI Tutor u
 from openai import OpenAI
 from mem0 import Memory
 
+# Set the OpenAI API key
+os.environ['OPENAI_API_KEY'] = 'sk-xxx'
+
 # Initialize the OpenAI client
 client = OpenAI()
 

Diff for: docs/examples/personal-travel-assistant.mdx

@@ -0,0 +1,101 @@
+---
+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.

Diff for: docs/images/personal-travel-agent.png

@@ -1,5 +1,5 @@
 ---
-title: 🤖 Large language models (LLMs)
+title: 🤖 LLMs
 ---
 
 ## Overview

Diff for: docs/llms.mdx

@@ -54,7 +54,7 @@
       ]
     },
     {
-      "group": "LLMs",
+      "group": "Integrations",
       "pages": [
         "llms"
       ]
@@ -64,7 +64,8 @@
       "pages": [
         "examples/overview",
         "examples/personal-ai-tutor",
-        "examples/customer-support-agent"
+        "examples/customer-support-agent",
+        "examples/personal-travel-assistant"
       ]
     }
   ],