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Quickstart

This guide provides a comprehensive walkthrough of the HelpingAI Python SDK, from installation to advanced usage.

Installation

Install the HelpingAI SDK using pip:

bash
pip install HelpingAI

Setup

1. Get your API key

Your API key is available on your HelpingAI Dashboard.

2. Set up your API key

We recommend using an environment variable to store your API key. This keeps your key secure and out of your codebase.

bash
export HAI_API_KEY='your-api-key-here'

3. Initialize the client

Create an instance of the HAI client. If the HAI_API_KEY environment variable is set, the client will automatically use it. Otherwise, you can pass the key directly.

python
from HelpingAI import HAI

# Initialize with environment variable {#initialize-with-environment-variable}
client = HAI()

# Or, initialize with key directly {#or-initialize-with-key-directly}
# client = HAI(api_key="your-api-key-here") {#client-haiapi_keyyour-api-key-here}

Make your first API call

You can now use the client to make API calls. For example, you can create a chat completion:

python
response = client.chat.completions.create(
    model="Dhanishtha-2.0-preview",
    messages=[
        {"role": "user", "content": "Hello, world!"}
    ]
)

print(response.choices[0].message.content)

Streaming

To stream responses, set the stream parameter to True.

python
stream = client.chat.completions.create(
    model="Dhanishtha-2.0-preview",
    messages=[
        {"role": "user", "content": "Tell me a story about a brave knight."}
    ],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Tool Calling

The HelpingAI SDK supports tool calling, allowing you to extend the capabilities of the models.

1. Define a tool

Use the @tools decorator to define a tool.

python
from HelpingAI.tools import tools

@tools
def get_weather(city: str, unit: str = "celsius") -> dict:
    """Get the current weather in a given city.

    Args:
        city (str): The city for which to get the weather.
        unit (str): The unit to use for the temperature. Can be either "celsius" or "fahrenheit".
    """
    return {"city": city, "temperature": 22, "unit": unit}

2. Use the tool

Pass the tool to the tools parameter of the client.chat.completions.create() method.

python
from HelpingAI.tools import get_tools

response = client.chat.completions.create(
    model="Dhanishtha-2.0-preview",
    messages=[{"role": "user", "content": "What's the weather in Paris?"}],
    tools=get_tools(),
    tool_choice="auto"
)

3. Handle the tool call

If the model decides to use the tool, you can execute it using client.call().

python
import json

message = response.choices[0].message

if message.tool_calls:
    tool_messages = []
    for tool_call in message.tool_calls:
        function_name = tool_call.function.name
        function_args = json.loads(tool_call.function.arguments)
        
        result = client.call(function_name, function_args)
        
        tool_messages.append({
            "role": "tool",
            "tool_call_id": tool_call.id,
            "name": function_name,
            "content": json.dumps(result)
        })

    follow_up_response = client.chat.completions.create(
        model="Dhanishtha-2.0-preview",
        messages=[
            {"role": "user", "content": "What's the weather in Paris?"},
            message,
            *tool_messages,
        ]
    )
    print(follow_up_response.choices[0].message.content)

Next steps

Now that you have the basics down, you can explore the full capabilities of the SDK: