llm_chatting
Chat with LLM models
SDK Method
async def llm_chatting(model, messages, max_tokens=4096,
temperature=0.7, top_p=0.9, top_k=0, repetition_penalty=1, presence_penalty=0,
frequency_penalty=0) -> Usage example (only text)
from VisionCraftAPI import VisionCraftClient
async def main() -> None:
api_key = "YOUR_API_KEY"
client = VisionCraftClient(api_key=api_key)
messages = [
{
"role": "user",
"content": """There are 50 books in a library.
Sam decides to read 5 of the books. How many books are there now?
If there are 45 books, say "1".
Else, if there is the same amount of books, say "2"."""
},
]
answer = await client.llm_chatting(model="gemma-7b",
messages=messages)
print(answer.role)
print(answer.content)
if __name__ == "__main__":
import asyncio
asyncio.run(main())Usage example (with image)
import base64
import aiohttp
from VisionCraftAPI import VisionCraftClient
async def main() -> None:
api_key = "YOUR_API_KEY"
client = VisionCraftClient(api_key=api_key)
async with aiohttp.ClientSession() as session:
async with session.get("https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg") as response:
base64_image = base64.b64encode(await response.read()).decode("utf-8")
messages = [{
"role": "user",
"content": [
{
"type": "text",
"text": "What’s in this image?"
},
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{base64_image}"
}
}]
}]
answer = await client.llm_chatting(model="llava-1.5-7b-hf",
messages=messages)
print(answer.role)
print(answer.content)
if __name__ == "__main__":
import asyncio
asyncio.run(main())Last updated