Quick Examples

from agentmind import Memory

memory = Memory(api_key="YOUR_API_KEY")

# Real conversation with memory
def support_agent(user_id, message):
    # Agent searches its memory naturally
    context = memory.recall(message, user_id=user_id)
    
    # Agent remembers this conversation
    memory.remember(message, user_id=user_id)
    
    # Generate response with full context
    return generate_response(message, context)

# Actual conversation
user: "My app keeps crashing"
agent: memory.remember("User experiencing app crashes", user_id="user_123")
agent: "I'll help you with the crashes. What device are you using?"

user: "iPhone 13"
agent: memory.remember("Using iPhone 13", user_id="user_123")
agent: "Let me check for iPhone 13 specific issues..."

# Days later - agent remembers everything
user: "Still having that problem"
agent: memory.recall("previous issues", user_id="user_123")
agent: "I see you were having crashes on your iPhone 13. Let's try a different solution..."

# Agent learns your project naturally through conversation
user: "I'm building a React app with TypeScript"
agent: memory.remember("Project: React with TypeScript")

user: "We use Tailwind for styling"
agent: memory.remember("Styling: Tailwind CSS")

user: "Create a button component"
agent: memory.recall("project tech stack")
# Agent knows: React, TypeScript, Tailwind
agent: "Here's a TypeScript React component with Tailwind styling..."

# Generated code matches your stack perfectly

# Natural conversation with persistent memory
user: "I'm allergic to shellfish"
agent: memory.remember("Allergic to shellfish")

user: "I have a meeting every Monday at 9am"
agent: memory.remember("Weekly meeting: Monday 9am")

user: "My wife's birthday is March 15"
agent: memory.remember("Wife's birthday: March 15")

# Agent uses memory contextually
user: "Find me a restaurant for dinner"
agent: memory.recall("dietary restrictions allergies")
agent: "I'll find restaurants without shellfish on the menu"

user: "When's my next meeting?"
agent: memory.recall("meetings schedule")
agent: "Your weekly meeting is Monday at 9am"

user: "I need gift ideas"
agent: memory.recall("family birthdays important dates")
agent: "Your wife's birthday is coming up on March 15. Should I suggest some gift ideas?"

# Track entire customer journey naturally
def sales_agent(lead_id, message):
    # Remember everything
    memory.remember(
        {"message": message, "timestamp": datetime.now()},
        user_id=lead_id
    )
    
    # Search memory with natural language
    context = memory.recall(message, user_id=lead_id)
    return respond_with_context(message, context)

# Natural sales conversation
lead: "What's your pricing?"
agent: "Our starter plan is $99/month. What size is your team?"

lead: "We have 50 employees"
agent: memory.remember("Team size: 50 employees")
agent: "For 50 users, I'd recommend our Business plan at $999/month"

# Follow-up conversation
lead: "Can we get a discount?"
agent: memory.recall("pricing discussions team size")
agent: "Since you have 50 employees, I can offer a 20% volume discount"

# Adaptive learning through conversation
student: "I'm learning Python"
tutor: memory.remember("Learning Python", user_id="student_1")

student: "Loops are confusing"
tutor: memory.remember("Struggles with loops", user_id="student_1")
tutor: "Let's start with simple for loops..."

# Next session - tutor adapts
student: "Ready for the next lesson"
tutor: memory.recall("learning progress struggles", user_id="student_1")
tutor: "Since you found loops challenging, let's practice more before moving to functions"

# No complex queries needed
memory.recall("what did the user say about pricing?")
memory.recall("previous error messages")
memory.recall("user preferences")
memory.recall("all conversations from last week")

# Memory understands context
memory.remember("User wants refund")
memory.recall("refund requests")  # Finds all refund-related memories

memory.remember("Bug in checkout flow")
memory.recall("checkout issues")  # Finds all checkout problems

# Each user has their own memory space
memory.remember("Prefers email", user_id="alice")
memory.remember("Prefers phone", user_id="bob")

memory.recall("contact preference", user_id="alice")  # Returns: "email"
memory.recall("contact preference", user_id="bob")    # Returns: "phone"