Commit
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d8661f4
1
Parent(s):
c75efd8
Add initial code
Browse files- .gitignore +1 -0
- app.py +71 -0
- old-app.py +119 -0
.gitignore
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app.py
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import streamlit as st
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import requests
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from azure.storage.blob import BlobServiceClient
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from azure.core.credentials import AzureKeyCredential
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from azure.ai.translation.document import DocumentTranslationClient
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# Translator AI
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AZURE_AI_TRANSLATOR_KEY = "26JrNtz5HvXYJ7zTL1MkmuRjTkAJ4EXx2gsHp6rj8pV9VIb4Q6TTJQQJ99AKACqBBLyXJ3w3AAAbACOGFu5N"
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AZURE_AI_ENDPOINT_URL = "https://cbd-translation.cognitiveservices.azure.com/"
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AZURE_AI_API_VERSION = "2024-05-01"
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# Streamlit UI
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st.title("Azure Translation Tools")
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uploaded_file = st.file_uploader("Upload a file to start the process")
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# Language options
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langs = (
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'id - Indonesian',
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'en - English',
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'es - Spanish',
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'zh - Chinese',
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'ar - Arabic',
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'fr - French',
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'ru - Russian',
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'hi - Hindi',
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'pt - Portuguese',
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'de - German',
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'ms - Malay',
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'ta - Tamil',
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'ko - Korean',
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'th - Thai',
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)
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lang = st.selectbox('Target language selection:', langs, key='lang')
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lang_id = lang.split()[0]
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lang_name = lang.split()[-1]
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if uploaded_file:
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submit = st.button("Get Result", key='submit')
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if uploaded_file and submit:
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file_name = uploaded_file.name
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file_content = uploaded_file.read()
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#TODO: filter which type of files that need batch translation, otherwise just use synchronous translation directly
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# Define headers and files
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headers = {
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"Ocp-Apim-Subscription-Key": AZURE_AI_TRANSLATOR_KEY,
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}
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files = {
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"document": (file_name, file_content, "ContentType/file-extension"),
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}
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# Make the POST request
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url = f"{AZURE_AI_ENDPOINT_URL}/translator/document:translate?targetLanguage={lang_id}&api-version={AZURE_AI_API_VERSION}"
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response = requests.post(url, headers=headers, files=files)
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if response.status_code == 200:
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st.success("Translation completed successfully.")
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else:
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st.error(f"Failed with status code {response.status_code}: {response.text}")
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# Allow user to download the file
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st.download_button(
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label="Download the Processed File",
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data=response.content,
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file_name=f"{lang_name}-translated-{file_name}",
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mime="application/octet-stream"
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)
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old-app.py
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import streamlit as st
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from azure.storage.blob import BlobServiceClient
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from azure.core.credentials import AzureKeyCredential
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from azure.ai.translation.document import DocumentTranslationClient
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# Azure Blob Storage connection strings
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STORAGE_CONNECTION_STRING = 'DefaultEndpointsProtocol=https;AccountName=cbdtranslation;AccountKey=V4CBDnn6UH8PlybYGAbLUxejErCnDdxJWWcbMeM+HJB8S/zYDof/8EWAtG6latsG12fR2Q9NVf4l+ASt4ohA4g==;EndpointSuffix=core.windows.net'
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# Container names
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FIRST_CONTAINER_NAME = "source"
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SECOND_CONTAINER_NAME = "target"
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# Translator AI
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AZURE_AI_TRANSLATOR_KEY = "26JrNtz5HvXYJ7zTL1MkmuRjTkAJ4EXx2gsHp6rj8pV9VIb4Q6TTJQQJ99AKACqBBLyXJ3w3AAAbACOGFu5N"
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AZURE_AI_ENDPOINT_URL = "https://cbd-translation.cognitiveservices.azure.com/"
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# Initialize Azure Blob Service Clients
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blob_service_client = BlobServiceClient.from_connection_string(STORAGE_CONNECTION_STRING)
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# Function to upload file to Azure Storage
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def upload_to_azure(blob_service_client, container_name, file, file_name):
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container_client = blob_service_client.get_container_client(container_name)
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container_client.upload_blob(name=file_name, data=file, overwrite=True)
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# Function to download file from Azure Storage
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def download_from_azure(blob_service_client, container_name, file_name):
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container_client = blob_service_client.get_container_client(container_name)
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blob_client = container_client.get_blob_client(blob=file_name)
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file_content = blob_client.download_blob().readall()
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return file_content
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# Function to delete file from Azure Storage
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def delete_from_azure(blob_service_client, container_name, file_name):
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container_client = blob_service_client.get_container_client(container_name)
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blob_client = container_client.get_blob_client(blob=file_name)
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blob_client.delete_blob()
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key = AZURE_AI_TRANSLATOR_KEY
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endpoint = AZURE_AI_ENDPOINT_URL
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sourceUri = "https://cbdtranslation.blob.core.windows.net/source"
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targetUri = "https://cbdtranslation.blob.core.windows.net/target"
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# Initialize a new instance of the DocumentTranslationClient
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client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
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def translate(lang_id, lang_name):
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poller = client.begin_translation(sourceUri, targetUri, lang_id)
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result = poller.result()
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st.write(
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'Total documents: {}'.format(
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poller.details.documents_total_count
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)
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)
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for document in result:
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if document.status == 'Succeeded':
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st.success('Translated to language: {}\n'.format(lang_name))
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else:
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st.error(
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'Error Code: {}, Message: {}\n'.format(
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document.error.code, document.error.message
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)
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)
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# Streamlit UI
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st.title("Azure Translation Tools")
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# Step 1: Upload File
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uploaded_file = st.file_uploader("Upload a file to start the process")
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langs = (
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'id - Indonesian',
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'en - English',
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'es - Spanish',
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'zh - Chinese',
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'ar - Arabic',
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'fr - French',
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'ru - Russian',
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'hi - Hindi',
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'pt - Portuguese',
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'de - German',
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'ms - Malay',
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'ta - Tamil',
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'ko - Korean',
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'th - Thai',
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)
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lang = st.selectbox('Target language selection:', langs, key='lang')
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lang_id = lang.split()[0]
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lang_name = lang.split()[-1]
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if uploaded_file:
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submit = st.button("Get Result", key='submit')
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if uploaded_file and submit:
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file_name = uploaded_file.name
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file_content = uploaded_file.read()
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upload_to_azure(blob_service_client, FIRST_CONTAINER_NAME, file_content, file_name)
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st.info("Performing translations on the file...")
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translate(lang_id, lang_name)
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# Upload file to second storage for simulation
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downloaded_file_content = download_from_azure(blob_service_client, SECOND_CONTAINER_NAME, file_name)
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# Step 5: Delete both files
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delete_from_azure(blob_service_client, FIRST_CONTAINER_NAME, file_name)
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delete_from_azure(blob_service_client, SECOND_CONTAINER_NAME, file_name)
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# Allow user to download the file
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st.download_button(
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label="Download the Processed File",
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data=downloaded_file_content,
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file_name=f"{lang_name}-translated-{file_name}",
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mime="application/octet-stream"
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)
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