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articles/ai-studio/how-to/prompt-flow-tools/azure-open-ai-gpt-4v-tool.md

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# Azure OpenAI GPT-4 Turbo with Vision tool in Azure AI Studio
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Currently, access to this service is granted only by application. You can apply for access to Azure OpenAI by completing the form at <a href="https://aka.ms/oai/access" target="_blank">https://aka.ms/oai/access</a>. Open an issue on this repo to contact us if you have an issue.
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- An [Azure AI hub resource](../../how-to/create-azure-ai-resource.md) with a GPT-4 Turbo with Vision model deployed in one of the regions that support GPT-4 Turbo with Vision: Australia East, Switzerland North, Sweden Central, and West US. When you deploy from your project's **Deployments** page, select: `gpt-4` as the model name and `vision-preview` as the model version.
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- An [Azure AI hub resource](../../how-to/create-azure-ai-resource.md) with a GPT-4 Turbo with Vision model deployed in [one of the regions that support GPT-4 Turbo with Vision](../../../ai-services/openai/concepts/models.md#model-summary-table-and-region-availability). When you deploy from your project's **Deployments** page, select: `gpt-4` as the model name and `vision-preview` as the model version.
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## Build with the Azure OpenAI GPT-4 Turbo with Vision tool
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articles/ai-studio/how-to/prompt-flow-tools/prompt-flow-tools-overview.md

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ms.topic: overview
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ms.date: 4/5/2024
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The following table provides an index of tools in prompt flow.
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| Tool or tool set name | Description | Environment | Package name |
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| Tool name | Description | Package name |
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|------|-----------|-------------|--------------|
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| [Large language models](./llm-tool.md) | Use Azure OpenAI large language models for tasks such as text completion or chat. | Default | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Prompt](./prompt-tool.md) | Craft a prompt by using Jinja as the templating language. | Default | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Python](./python-tool.md) | Run Python code. | Default | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Azure OpenAI GPT-4 Turbo with Vision](./azure-open-ai-gpt-4v-tool.md) | Use AzureOpenAI GPT-4 Turbo with Vision model deployment to analyze images and provide textual responses to questions about them. | Default | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Content Safety (Text)](./content-safety-tool.md) | Use Azure AI Content Safety to detect harmful content. | Default | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Index Lookup*](./index-lookup-tool.md) | Search an Azure Machine Learning Vector Index for relevant results by using one or more text queries. | Default | [promptflow-vectordb](https://pypi.org/project/promptflow-vectordb/) |
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| [Vector Index Lookup*](./vector-index-lookup-tool.md) | Search text or a vector-based query from a vector index. | Default | [promptflow-vectordb](https://pypi.org/project/promptflow-vectordb/) |
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| [Faiss Index Lookup*](./faiss-index-lookup-tool.md) | Search a vector-based query from the Faiss index file. | Default | [promptflow-vectordb](https://pypi.org/project/promptflow-vectordb/) |
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| [Vector DB Lookup*](./vector-db-lookup-tool.md) | Search a vector-based query from an existing vector database. | Default | [promptflow-vectordb](https://pypi.org/project/promptflow-vectordb/) |
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| [Embedding](./embedding-tool.md) | Use Azure OpenAI embedding models to create an embedding vector that represents the input text. | Default | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Serp API](./serp-api-tool.md) | Use Serp API to obtain search results from a specific search engine. | Default | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Azure AI Language tools*](https://microsoft.github.io/promptflow/integrations/tools/azure-ai-language-tool.html) | This collection of tools is a wrapper for various Azure AI Language APIs, which can help effectively understand and analyze documents and conversations. The capabilities currently supported include Abstractive Summarization, Extractive Summarization, Conversation Summarization, Entity Recognition, Key Phrase Extraction, Language Detection, PII Entity Recognition, Conversational PII, Sentiment Analysis, Conversational Language Understanding, and Translator. You can learn how to use them by the [Sample flows](https://github.com/microsoft/promptflow/tree/e4542f6ff5d223d9800a3687a7cfd62531a9607c/examples/flows/integrations/azure-ai-language). Support contact: [email protected] | Custom | [promptflow-azure-ai-language](https://pypi.org/project/promptflow-azure-ai-language/) |
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| [LLM](./llm-tool.md) | Use large language models (LLM) with the Azure OpenAI Service for tasks such as text completion or chat. | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Prompt](./prompt-tool.md) | Craft a prompt by using Jinja as the templating language. | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Python](./python-tool.md) | Run Python code. | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Azure OpenAI GPT-4 Turbo with Vision](./azure-open-ai-gpt-4v-tool.md) | Use an Azure OpenAI GPT-4 Turbo with Vision model deployment to analyze images and provide textual responses to questions about them. | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Content Safety (Text)](./content-safety-tool.md) | Use Azure AI Content Safety to detect harmful content. | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Embedding](./embedding-tool.md) | Use Azure OpenAI embedding models to create an embedding vector that represents the input text. | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Serp API](./serp-api-tool.md) | Use Serp API to obtain search results from a specific search engine. | [promptflow-tools](https://pypi.org/project/promptflow-tools/) |
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| [Index Lookup](./index-lookup-tool.md) | Search a vector-based query for relevant results using one or more text queries. | [promptflow-vectordb](https://pypi.org/project/promptflow-vectordb/) |
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| [Vector Index Lookup](./vector-index-lookup-tool.md)<sup>1</sup> | Search text or a vector-based query from a vector index. | [promptflow-vectordb](https://pypi.org/project/promptflow-vectordb/) |
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| [Faiss Index Lookup](./faiss-index-lookup-tool.md)<sup>1</sup> | Search a vector-based query from the Faiss index file. | [promptflow-vectordb](https://pypi.org/project/promptflow-vectordb/) |
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| [Vector DB Lookup](./vector-db-lookup-tool.md)<sup>1</sup> For | Search a vector-based query from an existing vector database. | [promptflow-vectordb](https://pypi.org/project/promptflow-vectordb/) |
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*The asterisks indicate custom tools that the community created. Custom tools extend prompt flow's capabilities for specific use cases. The prompt flow team doesn't officially maintain or endorse these tools. When you encounter questions or issues for these tools, prioritize by using the support contact if the description provides it.
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<sup>1</sup> The Index Lookup tool replaces the three deprecated legacy index tools: Vector Index Lookup, Vector DB Lookup, and Faiss Index Lookup. If you have a flow that contains one of those tools, follow the [migration steps](./index-lookup-tool.md#how-to-migrate-from-legacy-tools-to-the-index-lookup-tool) to upgrade your flow.
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To discover more custom tools developed by the open-source community, see [More custom tools](https://microsoft.github.io/promptflow/integrations/tools/index.html).
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## Custom tools
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## Remarks
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To discover more custom tools developed by the open-source community such as [Azure AI Language tools](https://pypi.org/project/promptflow-azure-ai-language/), see [More custom tools](https://microsoft.github.io/promptflow/integrations/tools/index.html).
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- If existing tools don't meet your requirements, you can [develop your own custom tool and make a tool package](https://microsoft.github.io/promptflow/how-to-guides/develop-a-tool/create-and-use-tool-package.html).
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- To install the custom tools, if you're using the automatic runtime, you can readily install the publicly released package by adding the custom tool package name in the `requirements.txt` file in the flow folder. Then select **Save and install** to start installation. After completion, the custom tools appear in the tool list. If you want to use a local or private feed package, build an image first, and then set up the runtime based on your image. To learn more, see [How to create and manage a runtime](../create-manage-runtime.md).
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## Next steps
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- [Create a flow](../flow-develop.md)
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- [Build your own copilot by using prompt flow](../../tutorials/deploy-copilot-ai-studio.md)
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- [Build your own copilot using prompt flow](../../tutorials/deploy-copilot-ai-studio.md)

articles/ai-studio/quickstarts/multimodal-vision.md

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Currently, access to this service is granted only by application. You can apply for access to Azure OpenAI by completing the form at <a href="https://aka.ms/oai/access" target="_blank">https://aka.ms/oai/access</a>. Open an issue on this repo to contact us if you have an issue.
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- An [Azure AI hub resource](../how-to/create-azure-ai-resource.md) with a GPT-4 Turbo with Vision model deployed in one of the [regions that support GPT-4 Turbo with Vision](../../ai-services/openai/concepts/models.md#gpt-4-and-gpt-4-turbo-preview-model-availability): Australia East, Switzerland North, Sweden Central, and West US. When you deploy from your Azure AI project's **Deployments** page, select: `gpt-4` as the model name and `vision-preview` as the model version.
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- An [Azure AI hub resource](../how-to/create-azure-ai-resource.md) with a GPT-4 Turbo with Vision model deployed in one of the [regions that support GPT-4 Turbo with Vision](../../ai-services/openai/concepts/models.md#gpt-4-and-gpt-4-turbo-preview-model-availability). When you deploy from your Azure AI project's **Deployments** page, select: `gpt-4` as the model name and `vision-preview` as the model version.
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- An [Azure AI project](../how-to/create-projects.md) in Azure AI Studio.
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## Start a chat session to analyze images or video

articles/ai-studio/tutorials/deploy-chat-web-app.md

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# Tutorial: Deploy a web app for chat on your data

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