SemanticQuestion10K | Ask questions to a 10K report
kandi X-RAY | SemanticQuestion10K Summary
kandi X-RAY | SemanticQuestion10K Summary
SemanticQuestion10K is a C# library. SemanticQuestion10K has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
Ask the Microsoft 2022 10K questions and get answers using Microsoft Semantic Kernel and Azure OpenAI Service. This is a sample project that shows the basics of how to ask questions to a document using the Semantic Kernel project (For this sample I have used Microsoft's 10K statement for 2022. Embeddings are used to create a semantic database. When you ask a question, the database is searched for similar sentences. A prompt is crafted from these sentences and sent to an OpenAI GPT-3 model in Azure OpenAI Service to create an answer.
Ask the Microsoft 2022 10K questions and get answers using Microsoft Semantic Kernel and Azure OpenAI Service. This is a sample project that shows the basics of how to ask questions to a document using the Semantic Kernel project (For this sample I have used Microsoft's 10K statement for 2022. Embeddings are used to create a semantic database. When you ask a question, the database is searched for similar sentences. A prompt is crafted from these sentences and sent to an OpenAI GPT-3 model in Azure OpenAI Service to create an answer.
Support
Quality
Security
License
Reuse
Support
SemanticQuestion10K has a low active ecosystem.
It has 5 star(s) with 4 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
SemanticQuestion10K has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of SemanticQuestion10K is current.
Quality
SemanticQuestion10K has no bugs reported.
Security
SemanticQuestion10K has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
SemanticQuestion10K is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
SemanticQuestion10K releases are not available. You will need to build from source code and install.
Installation instructions are available. Examples and code snippets are not available.
Top functions reviewed by kandi - BETA
kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of SemanticQuestion10K
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of SemanticQuestion10K
SemanticQuestion10K Key Features
No Key Features are available at this moment for SemanticQuestion10K.
SemanticQuestion10K Examples and Code Snippets
No Code Snippets are available at this moment for SemanticQuestion10K.
Community Discussions
No Community Discussions are available at this moment for SemanticQuestion10K.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install SemanticQuestion10K
An Azure OpenAI Service is required to run this project. https://azure.microsoft.com/en-us/services/openai-service/. A Qdrant vector database (https://github.com/qdrant/qdrant) is used to store the embeddings. You can easily run the Qdrant database in a container and map a volume from your drive to the container. https://qdrant.tech/documentation/quick_start/. There are two assembly references in this project that refer to the Semantic Kernel project. https://github.com/microsoft/semantic-kernel You will need to download the project from the Semantic Kernel repo, build it, and add the references to the project. I have included a text file in the docs folder which is just the 10K document saved as text - you will need this to create the smemantic database.
An Azure OpenAI Service is required to run this project. https://azure.microsoft.com/en-us/services/openai-service/
A Qdrant vector database (https://github.com/qdrant/qdrant) is used to store the embeddings. You can easily run the Qdrant database in a container and map a volume from your drive to the container. https://qdrant.tech/documentation/quick_start/
There are two assembly references in this project that refer to the Semantic Kernel project. https://github.com/microsoft/semantic-kernel You will need to download the project from the Semantic Kernel repo, build it, and add the references to the project.
I have included a text file in the docs folder which is just the 10K document saved as text - you will need this to create the smemantic database.
Provide the following variables through user secrets:
An Azure OpenAI Service is required to run this project. https://azure.microsoft.com/en-us/services/openai-service/
A Qdrant vector database (https://github.com/qdrant/qdrant) is used to store the embeddings. You can easily run the Qdrant database in a container and map a volume from your drive to the container. https://qdrant.tech/documentation/quick_start/
There are two assembly references in this project that refer to the Semantic Kernel project. https://github.com/microsoft/semantic-kernel You will need to download the project from the Semantic Kernel repo, build it, and add the references to the project.
I have included a text file in the docs folder which is just the 10K document saved as text - you will need this to create the smemantic database.
Provide the following variables through user secrets:
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
Find more information at:
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
