Chat
import base64
from aibrary import AiBrary
aibrary = AiBrary()
# Function to encode the image
def encode_file(path):
with open(path, "rb") as file:
return base64.b64encode(file.read()).decode("utf-8")
# Getting the base64 string
english_audio_base64 = encode_file("tests/assets/file.mp3")
return aibrary.chat.completions.create(
model="gpt-4o-audio-preview-2024-10-01@openai",
modalities=["text", "audio"],
audio={"voice": "alloy", "format": "wav"},
messages=[
{"role": "system", "content": "translate to persian"},
{
"role": "user",
"content": [
{
"type": "input_audio",
"input_audio": {"data": english_audio_base64, "format": "mp3"},
}
],
},
],
)from aibrary import AiBrary
aibrary = AiBrary()
# Function to encode the image
def encode_file(path):
with open(path, "rb") as file:
return base64.b64encode(file.read()).decode("utf-8")
# Getting the base64 string
base64_image = encode_file("tests/assets/test-image.jpg")
return aibrary.chat.completions.create(
model="claude-3-haiku@anthropic",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is in this image?",
},
{
"type": "image_url",
"image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
},
],
}
],
)aibrary = AiBrary()
aibrary.chat.completions.create(
model="Llama-3.1-Nemotron-70B-Instruct",
messages=[
{"role": "user", "content": "How are you today?"},
{"role": "assistant", "content": "I'm doing great, thank you!"},
],
stream=True,
)aibrary = AiBrary()
aibrary.chat.completions.create(
model="Llama-3.1-Nemotron-70B-Instruct",
messages=[
{"role": "user", "content": "How are you today?"},
{"role": "assistant", "content": "I'm doing great, thank you!"},
]
)Last updated