spiceai 0.1.8

A Python library for building AI-powered applications.

Spice

Usage Examples

All examples can be found in scripts/run.py

from spice import Spice

client = Spice()

messages: List[SpiceMessage] = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "list 5 random words"},
]
response = await client.get_response(messages=messages, model="gpt-4-0125-preview")

print(response.text)

Streaming

# You can set a default model for the client instead of passing it with each call
client = Spice(default_text_model="claude-3-opus-20240229")

messages: List[SpiceMessage] = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "list 5 random words"},
]
stream = await client.stream_response(messages=messages)

async for text in stream:
    print(text, end="", flush=True)
# Retrieve the complete response from the stream
response = await stream.complete_response()

# Response always includes the final text, no need build it from the stream yourself
print(response.text)

# Response also includes helpful stats
print(f"Took {response.total_time:.2f}s")
print(f"Input/Output tokens: {response.input_tokens}/{response.output_tokens}")

Mixing Providers

# Commonly used models and providers have premade constants
from spice.models import GPT_4_0125_PREVIEW

# Alias models for easy configuration, even mixing providers
model_aliases = {
    "task1_model": GPT_4_0125_PREVIEW,
    "task2_model": "claude-3-opus-20240229",
    "task3_model": "claude-3-haiku-20240307",
}

client = Spice(model_aliases=model_aliases)

messages: List[SpiceMessage] = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "list 5 random words"},
]
responses = await asyncio.gather(
    client.get_response(messages=messages, model="task1_model"),
    client.get_response(messages=messages, model="task2_model"),
    client.get_response(messages=messages, model="task3_model"),
)

for i, response in enumerate(responses, 1):
    print(f"\nModel {i} response:")
    print(response.text)
    print(f"Characters per second: {response.characters_per_second:.2f}")

Using unknown models

client = Spice()

messages: List[SpiceMessage] = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "list 5 random words"},
]

# To use Azure, specify the provider and the deployment model name
response = await client.get_response(messages=messages, model="first-gpt35", provider="azure")
print(response.text)

# Alternatively, to make a model and it's provider known to Spice, create a custom Model object
from spice.models import TextModel
from spice.providers import AZURE

AZURE_GPT = TextModel("first-gpt35", AZURE, context_length=16385)
response = await client.get_response(messages=messages, model=AZURE_GPT)
print(response.text)

# Creating the model automatically registers it in Spice's model list, so listing the provider is no longer needed
response = await client.get_response(messages=messages, model="first-gpt35")
print(response.text)