- Frequently asked questions:
- What is Freddy Copilot for Developers?
- Why should I use Freddy Copilot for Developers?
- How can I get started with Freddy Copilot for Developers?
- What training data was ingested by Freddy Copilot?
- How can I enable Freddy Copilot for my organization?
- Which programming languages does Freddy Copilot for Developers support?
- What guidelines should I follow to get better results from Freddy Copilot?
- Can I choose not to use the code produced by Freddy Copilot?
- What is the correctness of the code produced by Freddy Copilot?
- Are there any security vulnerabilities that I should be aware of while using Freddy Copilot?
- Which all conversational languages can I use apart from English while using Freddy Copilot for Developers?
- Is there any pricing?
- Is Freddy Copilot for Developers available across all regions?
- Will Freddy Copilot for Developers reproduce my private code?
- How can I control the sharing and use of my data in Freddy Copilot?
- Are there any data & privacy guidelines that are followed?
- What is the Use Case to app feature in Freddy Copilot for Developers?
- Why I don’t see the option for Use Case to App in my VS Code extension?
- What is the upload image option visible beside the app placeholder while using Use Case to App?
- What is the upload image option in conversation to code?
- Is there any tutorial/guide that I can use for building an app with Use Case to App?
This document details the commonly asked questions by Developers using Freddy Copilot. Kindly refer to this section whenever there arises a doubt. If no solution is available here, kindly create a community post for the same to get a faster response.
Freddy Copilot for Developers is the Generative AI-powered development experience that enables faster and more intuitive app development. Stretching across the app development journey, it integrates seamlessly with Visual Studio code and can suggest code snippets through conversational messages. It helps developers build and publish reliable apps faster through chat-based tutorials, Rapid code generation, and 1-Click actions such as 1-Click review, 1-Click Documentation, and 1-Click Publish.
With Freddy Copilot for Developers, you can forget mundane coding tasks or build apps from scratch and get started with building apps for your business needs right when you need them, and as quickly as you need it.
Through the power of generative AI, Freddy Copilot helps you ship high-quality, reliable Apps faster. Using the chat-based tutorials, Freddy Copilot empowers you to overcome upskilling challenges on a new platform. With rapid code generation, you can swiftly generate code for mundane, repetitive tasks. With 1 -Click actions you can review, document, and publish easily.
With assistance across the development journey, you can transform ideas from use cases to code deployments in a breeze. Freddy Copilot enables you with more time for value-added tasks and driving innovation across your business.
To get started refer to the getting started section from our developer community
Freddy Copilot is capable of addressing app development-related queries along with general programming paradigms as it has the context of Freshworks Developer documentation. With future releases and advancements in the platform, additional documentation will be added or updated in its knowledge base to ensure users get relevant results.
You can list your email for our beta access, and keep an eye on the email and community announcements on open launch.
Currently, the Freshworks Developer Platform supports Node JS and React-based applications. To be consistent with platform behavior Freddy Copilot support the same.
Kindly follow the standard input prompting techniques for conversational AI models. Furthermore, to get improved results kindly use Freshworks app development context-related query terms.
You can very well do that. The Freddy copilot operates as a developer assistant for code that provides chat-based code recommendations and one-click actions. The generated code output provides users explicit options to “copy code” or “insert code.” Developers can choose to include or discard the output code as deemed necessary.
The Freddy Copilot is an AI assistant and produces moderately accurate code snippets for the Freshworks app context when prompted correctly. However, since it is in its early stages of development, at times the results might not be accurate. We recommend developers provide feedback on the output response whenever met with such a situation, which will allow us to improve the code quality for such sections.
Freddy Copilot is an AI assistant that has both Freshworks and general programming context. It is possible that the generated code may at times when prompted incorrectly might result in insecure code output. We recommend that developers use the “Security Check” option within Copilot to ensure that the written/generated code is security compliant.
Which all conversational languages can I use apart from English while using Freddy Copilot for Developers?
The multi-lingual support is not there yet and English is the only supported language. When demand for a specific language increases it may be incorporated into Freddy in future versions.
Currently, there is no pricing for Freddy Copilot, we are opening gates for developers to explore Freddy Copilot and build apps for Freshworks. There will be rate limiting on API calls.**
Yes, as of 15th June 2023, Freddy Copilot is available globally in all the Freshworks regions.
No, Freddy Copilot will not be having any code base except the one you give it as input. Freddy can accept textual input as well as code-based inputs. When passed private code as input, it can analyze and suggest improvements for the code.
Freddy explicitly uses chat context to give contextual results based on user input queries. It results in higher token usage; hence, it is a configurable option that users can opt in or out of. By default, it uses five query responses as context for giving relevant results, which are maintained in the local storage of the workspace. Once the user closes the current workspace, the data is lost.
Freddy implicitly captures user data such as output feedback (upvote, downvote, and textual inputs), tokens used, and input prompts to enhance output quality in the future. It further uses chat context of last five interactions to provide relevant results. However, it doesn’t support chat persistence, so no confidential or personal information is captured or stored. Hence, the data sharing controls are not in place.
When developing applications that deal with sensitive data, we recommend complying with local data and privacy guidelines with local regulations for app building while using Freddy. For example, EU-GDPR when dealing with customer data for the European region.
The Use Case to App is a new feature we added to enable developers to build an app for their use case by simply defining what the app should do. For instance if you are trying to build an app for Freshdesk, which should be visible for every ticket in its sidebar and should accept the order ID as input and fetch data for that order ID from Shopify orders. You can simply provide the information as an input prompt and generate the app for it.
The Use Case to App feature is available as part of Freddy Copilot for Developers v2.0.2 onwards. If you don’t see this option, kindly update your copilot extension.
The Use Case to Code capability of Freddy Copilot for Developers generates UI for the given app using Freshworks Crayons UI components. If in case you have a specific layout planned or a pre-defined way of how the final solution must look, you can provide a wireframe/image of the same as input, along with the Use Case definition.
With Freddy Copilot for Developers v2.0.2 onwards, you can pass images as input to the conversation to code option, where you can generate the equivalent Crayons code for UI elements available in the input image.
Here is a hands-on tutorial for the same, which covers everything from installation to usage.