vision.py

######################################################################################################
# In this section, we set the user authentication, user and app ID, model details, and the URL of 
# the text we want as an input. Change these strings to run your own example.
######################################################################################################

# Your PAT (Personal Access Token) can be found in the portal under Authentification
PAT = 'a90021e0adb7490c95e36f65f6d0974d'
# Specify the correct user_id/app_id pairings
# Since you're making inferences outside your app's scope
USER_ID = 'openai'
APP_ID = 'chat-completion'
# Change these to whatever model and text URL you want to use
MODEL_ID = 'gpt-4-vision-alternative'
MODEL_VERSION_ID = '12b67ac2b5894fb9af9c06ebf8dc02fb'
RAW_TEXT = 'I love your product very much'
# To use a hosted text file, assign the url variable
# TEXT_FILE_URL = 'https://samples.clarifai.com/negative_sentence_12.txt'
# Or, to use a local text file, assign the url variable
# TEXT_FILE_LOCATION = 'YOUR_TEXT_FILE_LOCATION_HERE'

############################################################################
# YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
############################################################################

from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc
from clarifai_grpc.grpc.api.status import status_code_pb2
from clarifai.client.model import Model
prompt = "What’s in this image?"

image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"

openai_api_key = PAT

inference_params = dict(temperature=0.2, max_tokens=100, image_url=image_url)

# Model Predict
model_prediction = Model("https://clarifai.com/openai/chat-completion/models/gpt-4-vision").predict_by_bytes(prompt.encode(), input_type="text", inference_params=inference_params)
print(model_prediction.outputs[0].data.text.raw)