Add into README.md info about target platform #294
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RLKRo
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Dec 3, 2023
README.md
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| @@ -12,6 +12,8 @@ The Dialog Flow Framework (DFF) allows you to develop conversational services. | |||
| DFF offers a specialized domain-specific language (DSL) for quickly writing dialogs in pure Python. The service is created by defining a special dialog graph that determines the behavior of the dialog agent. The latter is then leveraged in the DFF pipeline. | |||
| You can use the framework in various services such as social networks, call centers, websites, personal assistants, etc. | |||
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| DFF, a versatile Python-based conversational service framework, can be deployed across a spectrum of platforms, ensuring flexibility for both novice and seasoned developers. Cloud platforms like AWS, Azure, and GCP offer scalable environments for DFF, with options such as AWS Lambda and Azure Functions providing serverless execution. For containerized deployment, Docker and Kubernetes streamline the orchestration of DFF applications. Furthermore, the framework's adaptability extends to IoT ecosystems, making it suitable for integration with edge devices in scenarios like smart homes or industrial automation. Whether deployed on cloud platforms, containerized environments, or directly on IoT devices, DFF's accessibility and customization options make it a robust choice for developing conversational services in the evolving landscape of Python applications and IoT connectivity. | |||
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I feel like this has the same issue as Amazon Alexa. Maybe we shouldn't mention AWS, Azure without having anything to do with them (no user guides / tutorials, e.t.c.). I think that instead we could simply mention that DFF can be used on cloud platforms.
README.md
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| @@ -12,6 +12,8 @@ The Dialog Flow Framework (DFF) allows you to develop conversational services. | |||
| DFF offers a specialized domain-specific language (DSL) for quickly writing dialogs in pure Python. The service is created by defining a special dialog graph that determines the behavior of the dialog agent. The latter is then leveraged in the DFF pipeline. | |||
| You can use the framework in various services such as social networks, call centers, websites, personal assistants, etc. | |||
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| DFF, a versatile Python-based conversational service framework, can be deployed across a spectrum of platforms, ensuring flexibility for both novice and seasoned developers. Cloud platforms like AWS, Azure, and GCP offer scalable environments for DFF, with options such as AWS Lambda and Azure Functions providing serverless execution. For containerized deployment, Docker and Kubernetes streamline the orchestration of DFF applications. Furthermore, the framework's adaptability extends to IoT ecosystems, making it suitable for integration with edge devices in scenarios like smart homes or industrial automation. Whether deployed on cloud platforms, containerized environments, or directly on IoT devices, DFF's accessibility and customization options make it a robust choice for developing conversational services in the evolving landscape of Python applications and IoT connectivity. | |||
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This feels like too much text (most of which is meaningless).
It was difficult for me to read that but I'm not sure if it's because of the amount of filler words or because it's late.
The essence of the text is rather short:
DFF can be deployed on various platforms:
- Cloud
- Containers
- IoT devices
If I was a user that was reading this I would give up after the first sentence and just skim the text looking for keywords such as Docker, AWS, IoT. We could save users some trouble by replacing this with a shorter version.
RLKRo
pushed a commit
that referenced
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Dec 27, 2023
* Add into README.md info about target platform * restructure markdown --------- Co-authored-by: Roman Zlobin <[email protected]> (cherry picked from commit 7652451)
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Description
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