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How to Use Claude API Python in 2023: The Comprehensive Guide

    The Claude API by Anthropic allows developers to seamlessly integrate cutting-edge AI into their applications with just a few lines of code. Whether you want to build intelligent chatbots, power semantic search, automatically summarize long-form text, or categorize content, the Claude API makes it possible through simple API calls.

    In this in-depth guide, we‘ll walk through everything you need to know to start using the Claude API in Python. We‘ll cover how to get your API key, install the Python library, and initialize the client. Then we‘ll dive into code examples for Claude‘s most powerful capabilities including chat, search, summarization, classification, question-answering, and translation. Finally, we‘ll share best practices to keep in mind when deploying your Claude-powered app to production.

    By the end of this guide, you‘ll be fully equipped to start taking advantage of Claude‘s AI in your own projects. Let‘s jump in!

    Overview of Claude API

    At a high level, the Claude API allows you to send text or documents to Claude and receive AI-generated results through HTTP requests. Some of the key capabilities include:

    • Chat: Engage in multi-turn conversations with Claude to chat, answer questions, and get helpful information on any topic
    • Search: Query Claude‘s vast knowledge using natural language and quickly find relevant information
    • Summarization: Submit long articles or documents and get back concise summaries that capture the key points
    • Classification: Categorize text into predefined classes like sentiment, topic, and more
    • Question Answering: Ask questions based on a given context and have Claude locate and extract the answers
    • Translation: Translate between English and 100+ languages

    The API exposes HTTP endpoints that accept JSON payloads containing your text/document and any additional parameters. It then returns Claude‘s output in the response.

    Anthropic also provides a convenient Python client library that abstracts away the raw HTTP requests, making it even easier to integrate Claude into your applications. Let‘s see how to set that up now.

    Getting Started with the Claude Python Library

    Before you can start making requests to the Claude API, there are a few setup steps:

    Sign Up for an API Key

    First, you‘ll need to sign up for a free Claude account in order to get your API key.

    1. Go to and click "Sign Up"
    2. Follow the prompts to create your account
    3. Once logged in, navigate to the "Account Settings" page
    4. Click "Create new API key"
    5. Copy this API key to use in your code

    Install the Python Library

    Next, you need to install Anthropic‘s official claude-python library. The easiest way is through PyPI using pip:

    pip install claude-python

    This will install the latest version of the library along with its dependencies.

    Initialize the Claude Client

    Now in your Python code, you can import the client and initialize it with your API key:

    from claude import ClaudeClient
    client = ClaudeClient(api_key=‘YOUR_API_KEY‘)

    Be sure to replace ‘YOUR_API_KEY‘ with the API key you generated in your account settings.

    And with that, you‘re ready to start using Claude in your Python code! Let‘s explore some of the most common use cases.

    Core Claude API Use Cases

    The Claude API offers a wide range of capabilities accessible through a few core endpoints. Here we‘ll provide example code for some of the most popular use cases in Python.


    Claude really shines in its ability to engage in freeform conversation. Using the method, you can have multi-turn dialogues:

    response =[
      {‘role‘: ‘user‘, ‘content‘: ‘What is the capital of France?‘},
      {‘role‘: ‘assistant‘, ‘content‘: ‘The capital of France is Paris.‘},  
      {‘role‘: ‘user‘, ‘content‘: ‘What is Paris known for?‘}

    Simply provide a list of messages, alternating between ‘user‘ and ‘assistant‘ roles. Claude will respond to the latest message and the full conversation will be returned.

    Some tips for the Chat endpoint:

    • Have longer conversations by appending additional messages to the list
    • Use stream=True to receive responses in real-time as they are generated
    • Customize Claude‘s persona by setting voice=‘professional‘ or style=‘concise‘


    To tap into Claude‘s encyclopedic knowledge on any subject, use the method:

    response =‘When was the Eiffel Tower built?‘)
    # The Eiffel Tower was built in 1887-1889.

    In addition to natural language questions, you can use special search operators for more targeted queries:

    • capital of France – Keyword based lookup
    • tallest building in the world ELI5 – Explain a topic as you would to a 5 year old
    • 1.75 cups to tbsp – Unit conversions

    Refer to the search documentation for the full syntax.


    Provide a longer document to the client.summary() method and get back a concise synopsis:

    document = """
    Machine learning is a rapidly growing field at the intersection of computer 
    science and statistics concerned with finding patterns in data. It is responsible
    for tremendous advances in technology, from personalized recommendations to 
    self-driving cars, that have impacted billions of people across sectors...
    response = client.summary(document)
    # Machine learning is a field combining computer science and statistics to find
    # patterns in data. It has driven major technological advances in areas like 
    # recommendations and autonomous vehicles that have transformed multiple industries
    # and impacted billions of lives.

    You can customize the summarization by providing additional parameters:

    • length – Controls the number of sentences in the summary
    • max_input_length – Truncate the input to this length if needed
    • voice – The summarization writing style (‘short‘, ‘professional‘, etc.)


    To categorize text into pre-defined classes, use the client.classify() method:

    text = "The dinner was superb and the wait staff was extraordinarily attentive!"
    response = client.classify(text, model=‘sentiment‘)
    # positive

    Some of the built-in classification models:

    • sentiment – Is the text positive, neutral, or negative?
    • toxicity – Does the text contain profanity, hate speech, etc.?
    • topics – High-level topic categorization
    • spam – Is the text considered spam/junk?

    Check the classification reference for the full list of models. You can also train your own custom classifiers!

    Question Answering

    Have Claude locate answers to questions from a provided context using

    context = """
    Claude is an AI assistant created by Anthropic to be helpful, harmless, and honest.
    response =, question=‘Who created Claude?‘)
    # According to the context, Claude was created by Anthropic.

    Provide the background information as context and the question you want answered. Claude will do its best to extract the relevant snippet from the context.

    The length of the context can range from a short paragraph to pages of content.


    Translate between languages using the client.translate() method:

    response = client.translate(
      text=‘Hello my friend, how are you?‘,
    # Hola mi amigo, ¿cómo estás?

    Specify the source_language and target_language using standard locale codes like ‘en‘, ‘es‘, ‘fr‘, ‘de‘, ‘ko‘, ‘hi‘, etc. Claude supports translating between English and over 100 other languages.

    Best Practices for Production Apps

    Once you‘ve prototyped your app using the Claude Python library, there are a few best practices to keep in mind when deploying it to production:

    Increase Request Timeout

    By default, the client times out API calls after 10 seconds. For longer requests like big summarizations, increase the timeout:

    client = ClaudeClient(timeout=30)
    response = client.summary(very_long_text)  

    Retry Logic

    Occasionally, API requests may fail due to network issues or backend instability. Implement retry logic to gracefully recover:

      response = 
    except APIError as e:
      if e.status == 503:
        response =

    Retry the request after a short exponential backoff period if the error code indicates a transient failure.


    For applications that make repeated requests with the same prompts, cache the responses:

    import redis
    redis = redis.Redis()
    prompt = ‘...‘
    cache_key = f‘claude_response_{hash(prompt)}‘
    if redis.exists(cache_key):
      response = json.loads(redis.get(cache_key)) 
      response =
      redis.set(cache_key, json.dumps(response))

    By storing responses in a fast in-memory cache, you can reduce load on the API and return results to users quicker.

    Async Processing

    For longer tasks like summarization, offload the requests to a background queue:

    import dramatiq 
    def generate_summary(text):
      response = client.summary(text)
    # Enqueue the job

    Return immediately to the user and process the request asynchronously. You can use a task queue like Dramatiq, Celery, or Cloud Tasks.


    Keep your API key secret and never expose it in client-side code or check it into version control. Instead, store it securely on your server using environment variables or a secrets manager.

    Additionally, implement appropriate user authentication and authorization before allowing requests to the Claude API. Anthropic allows you to create separate API keys for development and production environments.

    Monitor Usage

    Keep an eye on your API usage from the Anthropic dashboard to avoid unexpected overages. You can set up alerts to notify you when usage reaches predefined thresholds.

    As your app scales, you can upgrade your plan for higher rate limits and support.


    The Claude API is a powerful tool for incorporating world-class AI into your applications. Using the claude-python library, you can start building with Claude in just a few lines of code.

    In this guide, we covered:

    • Getting started with API keys and the Python client library
    • Code examples for Claude‘s core capabilities like chat, search, summarization, classification, question answering, and translation
    • Best practices for deploying Claude-powered apps to production

    To continue learning, check out the full Claude documentation, Python client reference, and Anthropic blog for the latest guides and tutorials. You can also join the Anthropic developer community to get help from other developers.

    By taking advantage of the Claude API, you can create applications that engage users in natural conversation, find information in an instant, understand and summarize text, and much more. We can‘t wait to see what you build!

    Thanks for reading! Let us know what cool projects you‘re working on with Claude in the comments below.

    Frequently Asked Questions

    What is the difference between the /search and /qa endpoints?

    The /search endpoint allows you to query Claude‘s internal knowledge using keywords and operators. The /qa endpoint instead takes a context you provide and then answers a question based on that specific context.

    What are tokens and how are they measured?

    API requests are metered based on the number of "tokens" consumed. A token is approximately 4 characters or 0.75 words. Your logs will show the number of tokens used by each request.

    How do I view my API usage?

    The Anthropic dashboard shows your current API usage including total requests, tokens, and spend for the current period. You can also view graphs of past usage.

    Is there a rate limit on requests?

    Yes, the free tier is limited to 50 requests per minute. Paid plans have higher limits. If you exceed the rate limit, requests will return a 429 error code until the limit resets.

    Can I use Claude in non-English languages?

    Yes! You can translate to/from English and 100+ languages using the /translate endpoint. However, the core models like search and QA are English-only for now.

    Where can I get help if I have questions?

    If you have technical issues or product feedback, please file an issue on our GitHub. For general discussion with other developers, check out the Anthropic community forums. You can also reach out to [email protected].