Anthropic

from anthropic import Anthropic
from agentmind import Memory

# Initialize
client = Anthropic()
memory = Memory(api_key="YOUR_API_KEY")

# Define memory tools for Claude
tools = [
    {
        "name": "remember",
        "description": "Store important information from the conversation",
        "input_schema": {
            "type": "object",
            "properties": {
                "content": {"type": "string", "description": "What to remember"}
            },
            "required": ["content"]
        }
    },
    {
        "name": "recall",
        "description": "Search memories to find relevant information",
        "input_schema": {
            "type": "object",
            "properties": {
                "query": {"type": "string", "description": "Natural language search query"}
            },
            "required": ["query"]
        }
    }
]

# Chat with Claude + Memory
message = client.messages.create(
    model="claude-3-opus-20240229",
    max_tokens=1000,
    tools=tools,
    messages=[
        {"role": "user", "content": "I prefer Python and I'm building a Django app"}
    ]
)

# Claude uses tools to remember
if message.stop_reason == "tool_use":
    for tool_use in message.content:
        if tool_use.type == "tool_use":
            if tool_use.name == "remember":
                memory.remember(tool_use.input["content"])
            elif tool_use.name == "recall":
                results = memory.recall(tool_use.input["query"])

from anthropic import Anthropic
from agentmind import Memory

class ClaudeWithMemory:
    def __init__(self, api_key, memory_key):
        self.client = Anthropic(api_key=api_key)
        self.memory = Memory(api_key=memory_key)
        self.tools = [
            {
                "name": "remember",
                "description": "Store important information",
                "input_schema": {
                    "type": "object",
                    "properties": {
                        "content": {"type": "string"}
                    },
                    "required": ["content"]
                }
            },
            {
                "name": "recall",
                "description": "Search stored memories",
                "input_schema": {
                    "type": "object",
                    "properties": {
                        "query": {"type": "string"}
                    },
                    "required": ["query"]
                }
            }
        ]
    
    def chat(self, user_message, user_id=None):
        # Let Claude decide what to remember/recall
        response = self.client.messages.create(
            model="claude-3-opus-20240229",
            max_tokens=1000,
            tools=self.tools,
            messages=[{"role": "user", "content": user_message}]
        )
        
        # Process tool calls
        if response.stop_reason == "tool_use":
            for content in response.content:
                if content.type == "tool_use":
                    if content.name == "remember":
                        self.memory.remember(
                            content.input["content"],
                            user_id=user_id
                        )
                    elif content.name == "recall":
                        memories = self.memory.recall(
                            content.input["query"],
                            user_id=user_id
                        )
                        # Continue conversation with retrieved memories
                        return self.chat_with_context(user_message, memories)
        
        return response.content[0].text

# Usage
assistant = ClaudeWithMemory(
    api_key="your_anthropic_key",
    memory_key="YOUR_API_KEY"
)

# First conversation
response = assistant.chat("I'm learning Rust and love systems programming")
# Claude remembers this preference

# Later conversation
response = assistant.chat("What programming language should I use for my OS project?")
# Claude recalls your Rust interest and systems programming preference