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XTM Cloud integrates with OpenAI GPT models through the so-called OpenAI connector. Since the this integration provides the functionality of machine translation functionality, OpenAI is therefore treated as an MT engine.
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For now, OpenAI GPT MT only works on a segment-to-segment basis, which means that, to obtain an MT translation, you need to enter XTM Workbench and a particular segment in the edit mode, to obtain an MT translation. XTM Cloud only sends the text for MT matching only during an active XTM Workbench session. For this reason, in the Send text for matching parameter, in the XTM Cloud UI global configuration, when it comes to the Send text for matching parameter, the After analysis and After analysis and in XTM Workbench options are permanently inactive.
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In XTM Workbench, OpenAI GPT MT matches are labeled as OpenAI GPT MT.
Target languages
When OpenAI GPT MT allows for deciding is used, the user can decide which target languages will are to be matched against MT within the framework of in a single XTM Cloud project. You can enable or disable it matching for a specific language pair in the project’s settings (or project template’s) , in settings (Project Editor → General info → Machine translation → Matching for language pair → Choose….)
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ChatGPT Plus
Sometimes you You might mistakenly consider ChatGPT Plus as yet to be just another OpenAI GPT MT engine variant that is available to purchase. Quite On the contrary, ChatGPT Plus and OpenAI API are two distinct different platforms, and purchasing one does not affect the quota or access for the other.
ChatGPT Plus is just an enhanced subscription plan for using ChatGPT on OpenAI's chat platform, ChatGPT, which utilizes OpenAI models. It provides enhanced performance for interacting with ChatGPT directly, such as faster response times and priority access during peak usage, for interacting with ChatGPT directly. However, it ChatGPT Plus does not include access to the OpenAI API.
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Global settings
In general, all the configuration is performed settings are configured in the XTM Cloud UI. In Select Configuration → Settings → Translation → Machine translation → MT engines , select → OpenAI.
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The OpenAI GPT section will appear belowbe displayed below the list of MT engines.
Default setting → Select this option to specify whether this MT engine should automatically be enabled at XTM Cloud customer and/or project level. At each of these levels, Project Managers need to must clear the checkbox in the customer’s and project’s settings , to disable this MT engine at customer and project level respectively.
Connection way → Select this option to specify how your XTM Cloud instance should be connected connect to the OpenAI GPT MT engine:
OpenAI | Azure OpenAI | ||||
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If you select this option, the API Key option is displayed.  It allows you to type in You can then enter a unique API key for your OpenAI GPT integration, which means that you will need to get . To do so, you must obtain an appropriate key that will allow enable you to use OpenAI GPT via API. To use the OpenAI API, you need to must sign up and obtain that API key at on the OpenAI Platform. You can also monitor your usage and billing information there.
| If you select this option, it means that you are going to your XTM Cloud instance will connect to the OpenAI GPT MT engine via Microsoft Azure. Then, the The following settings are then displayed.: 
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Send text for matching → This setting specifies the stage at which content is to be sent to the MT engine. As was mentioned beforeearlier, the After analysis and After analysis and in XTM Workbench options are permanently inactive since XTM Cloud only sends the text for MT matching only during an active XTM Workbench session.
Use auto inline tag placement → This feature uses the XTM NLP framework for the automatic placement of inline tags for in machine-translated text. After receiving translation is received from the MT system, the auto-insert mechanism works for is applied to all matches received from the MT engine. Similarly to the Send text for matching setting, inline tags are not processed by GPT, so the Use auto inline tag placement option is always enabled and cannot be changed.
Customer settings
XTM Cloud offers setting up In addition to the OpenAI access credentials that are configured in the global configuration, different OpenAI access credentials can also be configured for different XTM Cloud customers than those set up in global configuration. For example, take a look at the following . Example global configuration:
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Now, take a look at Contrast this to the configuration for one of a particular XTM Cloud customers [customer (Customers → Customer list → (select a relevant customer) → Settings → Machine translation].):
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One example of how way that this can be beneficial is in gaining to provide better control over costs. By using When separate API keys aer used, translations created for different XTM Cloud customers will be are billed separately on the OpenAI side. This approach allows for keeping makes it possible to keep track of which customer is utilizing more translationsuse the OpenAI translation service more, which helps to manage expenses more effectively.
Similarly, to achieve different translation effects depending on the XTM Cloud customer involved, you can also set up configure different credentials for Azure OpenAI that, as you know, will allow you to utilize , enabling different OpenAI GPT models to be used, if you would like to achieve different translation effects depending on the XTM Cloud customerrequired.
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Does XTM Cloud allow for training translation models?
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