Getting Started#
Qualcomm has developed a Python package known as Imagine SDK. Its purpose is to simplify the process of creating GenAI applications. It achieves this by merging our Imagine APIs with sophisticated Python AI frameworks like LangChain. This amalgamation facilitates the creation of applications such as chatbots, Generative Question-Answering (GQA), summarization, and workflow automation.
The most basic example of using a Large Language Model (LLM) to generate text.
How get the Imagine SDK working on your system.
Examples showcasing many typical use cases of how to use the Imagine SDK. The code snippets are designed so that you can copy-paste and run them on your environment.
Documentation about every single class, method and function that Imagine SDK offers. Great to have next to your IDE when developing code using the SDK.
How to use it#
Start with installing the Imagine SDK. Installation is a straight forward process like installing a any python package from a wheel file. Please refer to the installation section for steps and complete.
Before running any example from this documentation, two parameters have to be configured.
You must set the environment variable
IMAGINE_API_KEYto your personal Imagine API key. Alternatively, you can pass your API key directly to the client withImagineClient(api_key="my-api-key").You must set the environment variable
IMAGINE_ENDPOINT_URLpointing to the endpoint you are using. Alternatively, you can pass your endpoint directly to the client withImagineClient(endpoint="https://my-endpoint/api/v2").
Danger
You should never share your personal Imagine API keys with anyone!
Likewise, you should never commit your personal Imagine API keys to any git repository!
How to get an API key
If you don’t have yet an Imagine API key, get it here.
How to get the endpoint URL
If you don’t know your endpoint URL, you can get it here.
The following is the most basic example of using a Large Language Model (LLM) to
generate text.
It instantiates the client ImagineClient and starts a
new conversation by asking a
question.
from imagine import ChatMessage, ImagineClient
client = ImagineClient()
chat_response = client.chat(
messages=[ChatMessage(role="user", content="What is the best Spanish cheese?")],
model="Llama-3.1-8B",
)
print(chat_response.first_content)
This will print something similar to:
Spain is renowned for its rich variety of cheeses, each with its unique flavor profile
and texture. The "best" Spanish cheese is subjective and often depends on personal
taste preferences. However, here are some of the most popular and highly-regarded
Spanish cheeses:
1. Manchego: A firm, crumbly cheese made from sheep's milk, Manchego is a classic
Spanish cheese with a nutty, slightly sweet flavor.
2. Mahon: A semi-soft cheese from the island of Minorca, Mahon has a mild,
creamy flavor and a smooth texture.
3. Idiazabal: A smoked cheese from the Basque region, Idiazabal has a strong, savory
flavor and a firm texture.
4. Garrotxa: A soft, creamy cheese from Catalonia, Garrotxa has a mild, buttery flavor
and a delicate aroma.
...
The Imagine SDK exposes two clients, each with a different programming paradigm: synchronous and asynchronous.
ImagineClient is the synchronous Imagine client. If you don’t need
asynchronous programming on your Python code, or simply you are not familiar with
asynchronous programming, this is the client you want to use.
Otherwise, if you are leveraging asyncio on your codebase,
ImagineAsyncClient might be a better choice.
Support#
Please reach out to your Imagine service provider for support.