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import streamlit as st
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
# Set your Clarifai credentials and model details
PAT = '3ca5bd8b0f2244eb8d0e4b2838fc3cf1'
USER_ID = 'openai'
APP_ID = 'dall-e'
MODEL_ID = 'dall-e-3'
MODEL_VERSION_ID = 'dc9dcb6ee67543cebc0b9a025861b868'
RAW_TEXT = 'ocr check mistake with image base with python opencv computer vision help out to know people'
channel = ClarifaiChannel.get_grpc_channel()
stub = service_pb2_grpc.V2Stub(channel)
metadata = (('authorization', 'Key ' + PAT),)
userDataObject = resources_pb2.UserAppIDSet(user_id=USER_ID, app_id=APP_ID)
post_model_outputs_response = stub.PostModelOutputs(
service_pb2.PostModelOutputsRequest(
user_app_id=userDataObject,
model_id=MODEL_ID,
version_id=MODEL_VERSION_ID,
inputs=[
resources_pb2.Input(
data=resources_pb2.Data(
text=resources_pb2.Text(
raw=RAW_TEXT
)
)
)
]
),
metadata=metadata
)
if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
st.error(f"Clarifai API request failed: {post_model_outputs_response.status.description}")
else:
output = post_model_outputs_response.outputs[0].data.image.base64
st.image(output, caption='Generated Image', use_column_width=True)
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