from anthropic import Anthropic
 
client = Anthropic()
MODEL_NAME = "claude-sonnet-4-5"

def web_search(topic):
    print(f"pretending to search the web for {topic}")
 
 
web_search_tool = {
    "name": "web_search",
    "description": "A tool to retrieve up to date information on a given topic by searching the web",
    "input_schema": {
        "type": "object",
        "properties": {
            "topic": {"type": "string", "description": "The topic to search the web for"},
        },
        "required": ["topic"],
    },
}

from datetime import date
 
 
def chat_with_web_search(user_query):
    messages = [{"role": "user", "content": user_query}]
 
    system_prompt = f"""
    Answer as many questions as you can using your existing knowledge.
    Only search the web for queries that you can not confidently answer.
    Today's date is {date.today().strftime("%B %d %Y")}
    If you think a user's question involves something in the future that hasn't happened yet, use the search tool.
    """
 
    response = client.messages.create(
        system=system_prompt,
        model=MODEL_NAME,
        messages=messages,
        max_tokens=1000,
        tool_choice={"type": "auto"},
        tools=[web_search_tool],
    )
    last_content_block = response.content[-1]
    if last_content_block.type == "text":
        print("Claude did NOT call a tool")
        print(f"Assistant: {last_content_block.text}")
    elif last_content_block.type == "tool_use":
        print("Claude wants to use a tool")
        print(last_content_block)

chat_with_web_search("What color is the sky?")

chat_with_web_search("Who won the 2024 Miami Grand Prix?")

# Claude should NOT need to use the tool for this:
chat_with_web_search("Who won the superbowl in 2022?")

# Claude SHOULD use the tool for this:
chat_with_web_search("Who won the superbowl in 2024?")

tools = [
    {
        "name": "print_sentiment_scores",
        "description": "Prints the sentiment scores of a given tweet or piece of text.",
        "input_schema": {
            "type": "object",
            "properties": {
                "positive_score": {
                    "type": "number",
                    "description": "The positive sentiment score, ranging from 0.0 to 1.0.",
                },
                "negative_score": {
                    "type": "number",
                    "description": "The negative sentiment score, ranging from 0.0 to 1.0.",
                },
                "neutral_score": {
                    "type": "number",
                    "description": "The neutral sentiment score, ranging from 0.0 to 1.0.",
                },
            },
            "required": ["positive_score", "negative_score", "neutral_score"],
        },
    },
    {
        "name": "calculator",
        "description": "Adds two number",
        "input_schema": {
            "type": "object",
            "properties": {
                "num1": {"type": "number", "description": "first number to add"},
                "num2": {"type": "number", "description": "second number to add"},
            },
            "required": ["num1", "num2"],
        },
    },
]

def analyze_tweet_sentiment(query):
    response = client.messages.create(
        model=MODEL_NAME,
        max_tokens=4096,
        tools=tools,
        tool_choice={"type": "auto"},
        messages=[{"role": "user", "content": query}],
    )
    print(response)

analyze_tweet_sentiment("Holy cow, I just made the most incredible meal!")

analyze_tweet_sentiment(
    "I love my cats! I had four and just adopted 2 more! Guess how many I have now?"
)

def analyze_tweet_sentiment(query):
    response = client.messages.create(
        model=MODEL_NAME,
        max_tokens=4096,
        tools=tools,
        tool_choice={"type": "tool", "name": "print_sentiment_scores"},
        messages=[{"role": "user", "content": query}],
    )
    print(response)

analyze_tweet_sentiment("Holy cow, I just made the most incredible meal!")

analyze_tweet_sentiment(
    "I love my cats! I had four and just adopted 2 more! Guess how many I have now?"
)

def analyze_tweet_sentiment(query):
    prompt = f"""
    Analyze the sentiment in the following tweet:
    <tweet>{query}</tweet>
    """
 
    response = client.messages.create(
        model=MODEL_NAME,
        max_tokens=4096,
        tools=tools,
        tool_choice={"type": "auto"},
        messages=[{"role": "user", "content": prompt}],
    )
    print(response)

def send_text_to_user(text):
    # Sends a text to the user
    # We'll just print out the text to keep things simple:
    print(f"TEXT MESSAGE SENT: {text}")
 
 
def get_customer_info(username):
    return {
        "username": username,
        "email": f"{username}@email.com",
        "purchases": [
            {"id": 1, "product": "computer mouse"},
            {"id": 2, "product": "screen protector"},
            {"id": 3, "product": "usb charging cable"},
        ],
    }
 
 
tools = [
    {
        "name": "send_text_to_user",
        "description": "Sends a text message to a user",
        "input_schema": {
            "type": "object",
            "properties": {
                "text": {
                    "type": "string",
                    "description": "The piece of text to be sent to the user via text message",
                },
            },
            "required": ["text"],
        },
    },
    {
        "name": "get_customer_info",
        "description": "gets information on a customer based on the customer's username.  Response includes email, username, and previous purchases. Only call this tool once a user has provided you with their username",
        "input_schema": {
            "type": "object",
            "properties": {
                "username": {
                    "type": "string",
                    "description": "The username of the user in question. ",
                },
            },
            "required": ["username"],
        },
    },
]
 
system_prompt = """
All your communication with a user is done via text message.
Only call tools when you have enough information to accurately call them.
Do not call the get_customer_info tool until a user has provided you with their username. This is important.
If you do not know a user's username, simply ask a user for their username.
"""
 
 
def sms_chatbot(user_message):
    messages = [{"role": "user", "content": user_message}]
 
    response = client.messages.create(
        system=system_prompt,
        model=MODEL_NAME,
        max_tokens=4096,
        tools=tools,
        tool_choice={"type": "any"},
        messages=messages,
    )
    if response.stop_reason == "tool_use":
        last_content_block = response.content[-1]
        if last_content_block.type == "tool_use":
            tool_name = last_content_block.name
            tool_inputs = last_content_block.input
            print(f"=======Claude Wants To Call The {tool_name} Tool=======")
            if tool_name == "send_text_to_user":
                send_text_to_user(tool_inputs["text"])
            elif tool_name == "get_customer_info":
                print(get_customer_info(tool_inputs["username"]))
            else:
                print("Oh dear, that tool doesn't exist!")
 
    else:
        print("No tool was called. This shouldn't happen!")

sms_chatbot("Hey there! How are you?")

sms_chatbot("I need help looking up an order")

sms_chatbot("I need help looking up an order.  My username is jenny76")

sms_chatbot("askdj aksjdh asjkdbhas kjdhas 1+1 ajsdh")