Integrating ChatGPT with Microsoft Teams: Efficiency and Security with Power Automate
The definitive guide to this integration step by step.
ChatGPT is a powerful language model that can generate responses based on the context of the conversation, which can include sensitive information that should not be shared outside of the organization. Improper use of the data can lead to privacy breaches and violations of company policies and regulations.
To mitigate these risks, it is important for companies to establish clear policies and guidelines for the use of ChatGPT in chat platforms. This can include restrictions on the types of information that can be shared with ChatGPT and guidelines for how the generated responses can be used and shared within the organization.
Additionally, implementing security measures such as encryption and access controls can help protect sensitive information from unauthorized access. Regular audits and monitoring can also help ensure that ChatGPT is being used appropriately and in compliance with company policies and regulations.
Integrating ChatGPT with Microsoft Team and Power Automate can be a good option for companies that want to ensure privacy and auditability in their chat interactions. Power Automate provides a range of automation capabilities that can be used to streamline workflows and automate auditing processes, while ChatGPT can provide intelligent chat capabilities that can help companies to handle complex conversations and provide better customer service.
With PowerAutomate we can create workflows that ensure that only authorized personnel have access to sensitive information, while also logging all chat interactions for auditing purposes.
Furthermore, the integration can also help companies to ensure compliance with regulatory requirements such as GDPR, by providing a centralized and auditable platform for handling chat interactions that may contain personal or sensitive information.
Basic integration of Microsoft Team and ChatGpt, using PowerAutomate and OpenAI API
For learning purposes, the following flow represents a minimal integration, that allow us to write a sentence or question using Microsoft Team, send it to ChatGpt using OpenAI API, receive the answer again in the Microsoft Team , and finally record it in the audit log, the date, time, text sent and response received.
Here we can see the chat with the question and the answer generated by ChatGpt, in Microsoft Team.
This is the basic audit trail that is generated. We could save any variable or parameter that user Team or ChatGpt.
Implementation Flow.
Now I will explain step by step the elements (box) of the flow and its parameterization. For privacy reasons the fields with personal information are framed in gray.
- The flow is activated when a keyword arrives in the team chat, in this case teamchat, and initializes the var_text.
Remember that our Microsoft Team chat can be accessed only by people that we as administrators give access to.
2. Retrieve the body of the message written in team, in json format, in the PlainTextContent field, that store in the variable var_text (defined in the point 1).
4. We will use the predefined HTTP connector, which will make it easier for us to call the OpenAI API, with the necessary parameters. The information about the use of the API can be seen at https://platform.openai.com/, and specifically the token generation for our example at https://platform.openai.com/account/api-keys.
5. The response that ChatGpt arrives in the body of the message, and we retrieve it in json format, specifically in the choice.text field, in the first position first(body(‘Json_Analysis_ChatGpt’)?[‘choices’])[‘text ‘]
5. Now we notify ChatGpt’s response in our Team Chat, and finally we save the audit record, with the time, date, text sent and received from ChatGpt
As I have already commented, it is a very basic flow but it clearly represents the expected functionality. From this base we can incorporate the necessary functionalities that allow us to ensure compliance with the policies of our organization.
It is important to take into account that the use of connectors that make calls to public Internet sites, such as https:/api.openai.com, must be authorized by the companies or educational centers where we use it.
TO BE: In my next article I will explain how to use a Custom Connector (https://learn.microsoft.com/en-us/connectors/custom-connectors/) instead of the HTTP connector explained in step 4. The custom connector allows us, among other things, to extend the security of the connection using our own tokens.
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