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Merge pull request Azure#91 from Azure/jhgpt4vimage
Added image processing and converted to use azd for deployments
2 parents 8e0b7e6 + 71be6f2 commit fe194a4

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‎AI-in-a-Box.sln‎

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Microsoft Visual Studio Solution File, Format Version 12.00
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# Visual Studio Version 17
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VisualStudioVersion = 17.5.002.0
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MinimumVisualStudioVersion = 10.0.40219.1
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Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "gen-ai", "gen-ai", "{5A9632E5-F638-42BF-BF07-3B35E2BE0605}"
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EndProject
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Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "semantic-kernel-bot-in-a-box", "semantic-kernel-bot-in-a-box", "{3E61D800-B120-46E9-B7EE-332ED8488CC9}"
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "SemanticKernelBot", "gen-ai\semantic-kernel-bot-in-a-box\src\SemanticKernelBot.csproj", "{189DDAAC-CE3B-4488-BD53-C71F802E3395}"
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EndProject
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Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Assistants", "Assistants", "{176DEFFB-5FDF-4308-84B3-C685641CFA0B}"
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EndProject
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Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "bot-in-a-box", "bot-in-a-box", "{83389DF2-DAC5-4172-A0DF-017F511DBD8A}"
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AssistantBot", "gen-ai\Assistants\bot-in-a-box\src\AssistantBot.csproj", "{BD9D160A-49C7-4BD7-9559-7C0185C76122}"
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EndProject
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Global
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
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Debug|Any CPU = Debug|Any CPU
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Release|Any CPU = Release|Any CPU
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GlobalSection(ProjectConfigurationPlatforms) = postSolution
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{189DDAAC-CE3B-4488-BD53-C71F802E3395}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{189DDAAC-CE3B-4488-BD53-C71F802E3395}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{189DDAAC-CE3B-4488-BD53-C71F802E3395}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{189DDAAC-CE3B-4488-BD53-C71F802E3395}.Release|Any CPU.Build.0 = Release|Any CPU
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{BD9D160A-49C7-4BD7-9559-7C0185C76122}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{BD9D160A-49C7-4BD7-9559-7C0185C76122}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{BD9D160A-49C7-4BD7-9559-7C0185C76122}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{BD9D160A-49C7-4BD7-9559-7C0185C76122}.Release|Any CPU.Build.0 = Release|Any CPU
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GlobalSection(NestedProjects) = preSolution
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{3E61D800-B120-46E9-B7EE-332ED8488CC9} = {5A9632E5-F638-42BF-BF07-3B35E2BE0605}
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{189DDAAC-CE3B-4488-BD53-C71F802E3395} = {3E61D800-B120-46E9-B7EE-332ED8488CC9}
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{176DEFFB-5FDF-4308-84B3-C685641CFA0B} = {5A9632E5-F638-42BF-BF07-3B35E2BE0605}
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{83389DF2-DAC5-4172-A0DF-017F511DBD8A} = {176DEFFB-5FDF-4308-84B3-C685641CFA0B}
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{BD9D160A-49C7-4BD7-9559-7C0185C76122} = {83389DF2-DAC5-4172-A0DF-017F511DBD8A}
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EndGlobalSection
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GlobalSection(ExtensibilityGlobals) = postSolution
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SolutionGuid = {DB39B9D2-8859-49C2-9636-C4E4D345C9A7}
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EndGlobal

‎README.md‎

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|[Azure ML Operationalization in-a-box](./machine-learning/ml-ops-in-a-box)|Boilerplate Data Science project from model development to deployment and monitoring|<li>End-to-end MLOps project template <li>Outer Loop (infrastructure setup) <br> <li>Inner Loop (model creation and deployment lifecycle)|
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|[Edge AI in-a-box](./edge-ai/)|Edge AI from model creation to deployment on Edge Device(s) |<li>Create a model and deploy to Edge Device <li>Outer Loop Infrastructure Setup (IoT Hub, IoT Edge, Edge VM, Container Registry, Azure ML) <br> <li>Inner Loop (model creation and deployment)|
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|[Doc Intelligence in-a-box](./ai-services/doc-intelligence-in-a-box) | This accelerator enables companies to automate PDF form processing, modernize operations, save time, and cut costs as part of their digital transformation journey. |<li>Receive PDF Forms<br> <li>Function App and Logic App for Orchestration<br> <li>Document Intelligence Model creation for form processing and content extraction <br> <li> Saves PDF data in Azure Cosmos DB |
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|[Video Analysis-Azure Open AI in-a-box](./ai-services/gpt-video-analysis-in-a-box/) | Extracts information about videos by ingesting them into an Azure Computer Vision Video Retrieval index and sending the index to Azure GPT-4 Turbo with Vision along with the prompt and system message. |<li>Orchestration through Azure Data Factory<br> <li>Low code solution, easily extensible for your own use cases through ADF parameters<br> <li> Reuse same solution and deployed resources for many different scenarios<br> <li> Saves GPT4-V results to Azure CosmosDB|
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|[Image and Video Analysis in-a-box](./ai-services/gpt-video-analysis-in-a-box/) | Extracts information from images and videos with Azure AI Vision and sends the results along with the prompt and system message to Azure GPT-4 Turbo with Vision. |<li>Orchestration through Azure Data Factory<br> <li>Low code solution, easily extensible for your own use cases through ADF parameters<br> <li> Reuse same solution and deployed resources for many different scenarios<br> <li> Saves GPT4-V results to Azure CosmosDB|
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|[Cognitive Services Landing Zone in-a-box](./ai-services/ai-landing-zone)|Minimal enterprise-ready networking and AI Services setup to support most Cognitive Services scenarios in a secure environment|<li>Hub-and-Spoke Vnet setup and peering <br> <li>Cognitive Service deployment <br> <li>Private Endpoint setup <br> <li>Private DNS integration with PaaS DNS resolver|
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|[Semantic Kernel Bot in-a-box](./gen-ai/semantic-kernel-bot-in-a-box)|Extendable solution accelerator for advanced Azure OpenAI Bots|<li>Deploy Azure OpenAI bot to multiple channels (Web, Teams, Slack, etc) <br> <li>Built-in Retrieval-Augmented Generation (RAG) support <br> <li>Implement custom AI Plugins|
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[NLP to SQL in-a-box](./gen-ai/nlp-sql-in-a-box)|Unleash the power of a cutting-edge speech-enabled SQL query system with Azure Open AI, Semantic Kernel, and Azure Speech Services. Simply speak your data requests in natural language, and let the magic happen.|<li>Allows users to verbally express natural language queries <br> <li>Translate into SQL statements using Azure Speech & AOAI <br> <li> Execute on an Azure SQL DB |

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