Merge pull request #267080 from likebupt/update-pf-tool-20240223

update pf tool articles

Author: v-ccolin

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

@@ -74,7 +74,7 @@ The following are available input parameters:
 | ---- | ---- | ----------- | -------- |
 | connection             | AzureOpenAI | The Azure OpenAI connection to be used in the tool.                                              | Yes      |
 | deployment\_name       | string      | The language model to use.                                                                      | Yes      |
-| prompt                 | string      | Text prompt that the language model uses to generate its response.                    | Yes      |
+| prompt                 | string      | Text prompt that the language model uses to generate its response. The Jinja template for composing prompts in this tool follows a similar structure to the chat API in the LLM tool. To represent an image input within your prompt, you can use the syntax `![image]({{INPUT NAME}})`. Image input can be passed in the `user`, `system` and `assistant` messages.                 | Yes      |
 | max\_tokens            | integer     | Maximum number of tokens to generate in the response. Default is 512.                      | No       |
 | temperature            | float       | Randomness of the generated text. Default is 1.                                            | No       |
 | stop                   | list        | Stopping sequence for the generated text. Default is null.                                 | No       |
@@ -90,7 +90,7 @@ The following are available output parameters:
 |-------------|------------------------------------------|
 | string      | The text of one response of conversation |
 
-## Next steps
-
-- [Learn more about how to create a flow](../flow-develop.md)
+## Next step
 
+- Learn more about [how to process images in prompt flow](../flow-process-image.md).
+- [Learn more about how to create a flow](../flow-develop.md).

articles/ai-studio/how-to/prompt-flow-tools/python-tool.md

@@ -111,13 +111,15 @@ If you're developing a python tool that requires calling external services with
 
 Create a custom connection that stores all your LLM API KEY or other required credentials.
 
-1. Go to Prompt flow in your workspace, then go to **connections** tab.
-1. Select **Create** and select **Custom**.
-1. In the right panel, you can define your connection name, and you can add multiple *Key-value pairs* to store your credentials and keys by selecting **Add key-value pairs**. 
+1. Go to **AI project settings**, then select **New Connection**.
+1. Select **Custom** service. You can define your connection name, and you can add multiple *Key-value pairs* to store your credentials and keys by selecting **Add key-value pairs**. 
 
     > [!NOTE]
     > Make sure at least one key-value pair is set as secret, otherwise the connection will not be created successfully. You can set one Key-Value pair as secret by **is secret** checked, which will be encrypted and stored in your key value.
 
+    :::image type="content" source="../../media/prompt-flow/create-connection.png" alt-text="Screenshot that shows create connection in AI Studio." lightbox = "../../media/prompt-flow/create-connection.png"::: 
+
+
 1. Add the following custom keys to the connection:
     - `azureml.flow.connection_type`: `Custom`
     - `azureml.flow.module`: `promptflow.connections`

articles/ai-studio/media/prompt-flow/create-connection.png

@@ -34,7 +34,7 @@ Azure OpenAI GPT-4 Turbo with Vision tool enables you to leverage your AzureOpen
 
 ## Connection
 
-Setup connections to provisioned resources in prompt flow.
+Set up connections to provisioned resources in prompt flow.
 
 | Type        | Name     | API KEY  | API Type | API Version |
 |-------------|----------|----------|----------|-------------|
@@ -46,7 +46,7 @@ Setup connections to provisioned resources in prompt flow.
 |------------------------|-------------|------------------------------------------------------------------------------------------------|----------|
 | connection             | AzureOpenAI | the AzureOpenAI connection to be used in the tool                                              | Yes      |
 | deployment\_name       | string      | the language model to use                                                                      | Yes      |
-| prompt                 | string      | The text prompt that the language model will use to generate its response.                    | Yes      |
+| prompt                 | string      | Text prompt that the language model uses to generate its response. The Jinja template for composing prompts in this tool follows a similar structure to the chat API in the LLM tool. To represent an image input within your prompt, you can use the syntax `![image]({{INPUT NAME}})`. Image input can be passed in the `user`, `system` and `assistant` messages.                 | Yes      |
 | max\_tokens            | integer     | the maximum number of tokens to generate in the response. Default is 512.                      | No       |
 | temperature            | float       | the randomness of the generated text. Default is 1.                                            | No       |
 | stop                   | list        | the stopping sequence for the generated text. Default is null.                                 | No       |
@@ -59,3 +59,7 @@ Setup connections to provisioned resources in prompt flow.
 | Return Type | Description                              |
 |-------------|------------------------------------------|
 | string      | The text of one response of conversation |
+
+## Next step
+
+Learn more about [how to process images in prompt flow](../how-to-process-image.md).

articles/machine-learning/prompt-flow/tools-reference/azure-open-ai-gpt-4v-tool.md

@@ -44,7 +44,7 @@ Set up connections to provisioned resources in prompt flow.
 |------------------------|-------------|------------------------------------------------------------------------------------------------|----------|
 | connection             | OpenAI      | The OpenAI connection to be used in the tool.                                                  | Yes      |
 | model                  | string      | The language model to use, currently only support gpt-4-vision-preview.                        | Yes      |
-| prompt                 | string      | The text prompt that the language model uses to generate its response.                         | Yes      |
+| prompt                 | string      | Text prompt that the language model uses to generate its response. The Jinja template for composing prompts in this tool follows a similar structure to the chat API in the LLM tool. To represent an image input within your prompt, you can use the syntax `![image]({{INPUT NAME}})`. Image input can be passed in the `user`, `system` and `assistant` messages.                 | Yes      |
 | max\_tokens            | integer     | The maximum number of tokens to generate in the response. Default is a low value decided by [OpenAI API](https://platform.openai.com/docs/guides/vision).                      | No       |
 | temperature            | float       | The randomness of the generated text. Default is 1.                                            | No       |
 | stop                   | list        | The stopping sequence for the generated text. Default is null.                                 | No       |
@@ -56,4 +56,8 @@ Set up connections to provisioned resources in prompt flow.
 
 | Return Type | Description                              |
 |-------------|------------------------------------------|
-| string      | The text of one response of conversation |
+| string      | The text of one response of conversation |
+
+## Next step
+
+Learn more about [how to process images in prompt flow](../how-to-process-image.md).