From 6aed1b3fd66be0baa1bff1c930e1931f50808e60 Mon Sep 17 00:00:00 2001 From: Paul Cornell Date: Mon, 15 Sep 2025 15:12:29 -0700 Subject: [PATCH 1/4] IBM watsonx Orchestrate tool example --- examplecode/tools/ibm-orchestrate.mdx | 74 +++++++++++++++++++++++++++ 1 file changed, 74 insertions(+) create mode 100644 examplecode/tools/ibm-orchestrate.mdx diff --git a/examplecode/tools/ibm-orchestrate.mdx b/examplecode/tools/ibm-orchestrate.mdx new file mode 100644 index 00000000..b822c268 --- /dev/null +++ b/examplecode/tools/ibm-orchestrate.mdx @@ -0,0 +1,74 @@ + +## Requirements + +To use this example, you will need the following: + +- Within your IBM Cloud account, an IBM watsonx.data subscription that contains a Milvus service instance. + + - Create an [IBM Cloud account](https://cloud.ibm.com/registration). + - Create an [IBM watsonx.data subscription](https://cloud.ibm.com/watsonxdata) in your IBM Cloud account. + - Create a [Milvus service instance](/ui/destinations/milvus) within your IBM watsonx.data subscription plan. + +- Within your Unstructured account, a workflow that contains a Milvus destination connector. + + - Create an [Unstructured account](https://unstructured.io/signup). + - Create a [Milvus destination connector](/ui/destinations/milvus) in your Unstructured account. + - Create a [workflow]() that contains the Milvus destination connector in your Unstructured account. + + The workflow must generate [embeddings](/ui/embedding). The workflow's **Embedder** node's selected embedding model provider must be "IBM". The + node's selected embedding model must be one of the following models that are offered by IBM watsonx Orchestrate: + + - `all-minilm6-v2`, with 384 dimensions. Per IBM, this model is good for tasks such as information retrieval, clustering, and for detecting sentence similarity. + - `granite-embedding-107m-multilingual`, with 384 dimensions. Per IBM, this model is good for tasks such as text similarity, retrieval, and search. + - `granite-embedding-278m-multilingual`, with 768 dimensions. + - `multilingual-e5-large`, with 1024 dimensions. Per IBM, this model is good for generating text embeddings for text in a language other than English. + - `slate-125m-english-retrvr`, with 768 dimensions. Per IBM, the `slate-125m-*` models are good for generating embeddings for various inputs such as queries, passages, or documents. Per IBM, the `slate-125m-*` models are two to three times slower but perform slightly better than the `slate-30m-*` models. + - `slate-125m-english-retrvr-v2`, with 768 dimensions. + - `slate-30m-english-retrvr`, with 384 dimensions. Per IBM, the `slate-30m-*` models are trained to maximize the cosine similarity between two text inputs so that embeddings can be evaluated based on similarity later. Per IBM, the `slate-30m-*` models are two to three times faster and have slightly lower performance scores than the `slate-125m-*` models. + - `slate-30m-english-retrvr-v2`, with 384 dimensions. + + Be sure to [run the workflow](/ui/workflows#edit%2C-delete%2C-or-run-a-workflow) to have Unstructured generate the embeddings and store them—along with + Unstructured's processed data representing your organization's source documents and semi-structured data—in the database + that is accessed through the Milvus service instance within your IBM watsonx.data subscription. + +## Step 1: ... + +In this step, you add an IBM watsonx Orchestrate subscription to your IBM Cloud account. + +If you already have an IBM watsonx Orchestrate subscription, then skip ahead to **Step 2**. + +1. [Log in to your IBM Cloud account](https://cloud.ibm.com/login). +2. On the sidebar, click the **Resource list** icon. If the sidebar is not visible, click the **Navigation Menu** icon to the far left of the + top navigation bar. +3. Click **Create resource**. +4. With **IBM Cloud catalog** selected, search for and select **watsonx Orchestrate**. +5. Complete the on-screen instructions to finish creating the IBM watsonx Orchestrate subscription. + +## Step 2: ... + +In this step, ... + +1. Open your IBM watsonx Orchestrate subscription, if it is not already open. To do this: + + a. [Log in to your IBM Cloud account](https://cloud.ibm.com/login).
+ b. On the sidebar, click the **Resource list** icon. If the sidebar is not visible, click the **Navigation Menu** icon to the far left of the + top navigation bar.
+ c. In the list of resources, expand **AI / Machine Learning**, and then click the target watsonx Orchestrate subscription.
+ d. Click **Launch watsonx Orchestrate**.
+ +2. If the **Chat** page is not already open, click the **Open the main menu** icon to the far left of the + top navigation bar, and then click **Chat**. +3. Toward the bottom of the sidebar, click **Create new agent**. +4. On the **Create an agent** page, with **Create from scratch** already selected, enter some **Name** and **Description**for the agent, and then click **Create**. +5. Under **Knowledge source**, in the **Start by adding knowledge** tile, click **Choose knowledge**. +6. On the **Select source** page, click **Milvus**, and then click **Next**. +7. On the **Connect Milvus** page, specify the following settings: + + a. For **GRPC host**, enter the GRPC host value for the Milvus service instance within your IBM watsonx.data subscription.
+ b. For **GRPC port**, enter the GRPC port value for the Milvus service instance.
+ c. For **Choose an authentication type**, select **Basic authentication**.
+ d. For **Username**, enter `ibmlhapikey`.
+ e. For **Password**, enter the API key for your IBM Cloud account.
+ f. Click **Next**.
+ +8. ... \ No newline at end of file From a1163fd692123aedb63bab60ba9f159518b2159f Mon Sep 17 00:00:00 2001 From: Paul Cornell Date: Mon, 15 Sep 2025 16:03:18 -0700 Subject: [PATCH 2/4] Added more initial content --- examplecode/tools/ibm-orchestrate.mdx | 45 ++++++++++++++++++++++++--- 1 file changed, 41 insertions(+), 4 deletions(-) diff --git a/examplecode/tools/ibm-orchestrate.mdx b/examplecode/tools/ibm-orchestrate.mdx index b822c268..76d90ef6 100644 --- a/examplecode/tools/ibm-orchestrate.mdx +++ b/examplecode/tools/ibm-orchestrate.mdx @@ -6,16 +6,27 @@ To use this example, you will need the following: - Within your IBM Cloud account, an IBM watsonx.data subscription that contains a Milvus service instance. - Create an [IBM Cloud account](https://cloud.ibm.com/registration). + + To complete this example, you will to [create an API key](https://www.ibm.com/docs/en/masv-and-l/cd?topic=cli-creating-your-cloud-api-key) for your IBM Cloud account. + - Create an [IBM watsonx.data subscription](https://cloud.ibm.com/watsonxdata) in your IBM Cloud account. - Create a [Milvus service instance](/ui/destinations/milvus) within your IBM watsonx.data subscription plan. + To complete this example, you will need the following settings for the Milvus service instance: + + - The instance's GRPC host value. + - The instance's GRPC port value. + - The name of the target database on the instance. + - The name of the target collection in the database. + - The name of the target index in the collection. + - Within your Unstructured account, a workflow that contains a Milvus destination connector. - Create an [Unstructured account](https://unstructured.io/signup). - Create a [Milvus destination connector](/ui/destinations/milvus) in your Unstructured account. - - Create a [workflow]() that contains the Milvus destination connector in your Unstructured account. + - Create a [custom workflow](/ui/workflows#create-a-custom-workflow) that contains the Milvus destination connector in your Unstructured account. - The workflow must generate [embeddings](/ui/embedding). The workflow's **Embedder** node's selected embedding model provider must be "IBM". The + The workflow must generate [embeddings](/ui/embedding). The workflow's **Embedder** node's selected embedding model provider must be **IBM watson.ai**. The node's selected embedding model must be one of the following models that are offered by IBM watsonx Orchestrate: - `all-minilm6-v2`, with 384 dimensions. Per IBM, this model is good for tasks such as information retrieval, clustering, and for detecting sentence similarity. @@ -65,10 +76,36 @@ In this step, ... 7. On the **Connect Milvus** page, specify the following settings: a. For **GRPC host**, enter the GRPC host value for the Milvus service instance within your IBM watsonx.data subscription.
- b. For **GRPC port**, enter the GRPC port value for the Milvus service instance.
+ b. For **GRPC port**, enter the GRPC port value for the instance.
c. For **Choose an authentication type**, select **Basic authentication**.
d. For **Username**, enter `ibmlhapikey`.
e. For **Password**, enter the API key for your IBM Cloud account.
f. Click **Next**.
-8. ... \ No newline at end of file +8. On the **Select index** page, specify the following settings: + + a. For **Database**, select the name of the target database on the Milvus service instance within your IBM watsonx.data subscription.
+ b. For **Use Collection or Alias**, select **Collection**.
+ c. For **Collection**, select the name of the target collection in the database.
+ d. For **Index**, select the name of the target index in the collection.
+ e. For **Embedding model**, select the name of the embedding model that matches the one that you specified in your Unstructured workflow.
+ f. for **Title**, select **element_id**.
+ g. For **Body**, select **text**.
+ h. Click **Next**.
+ +9. On the **Description** page, enter some description for the agent, and then click **Save**. +10. In the list of pages, click **Behavior**. +11. Switch on **Chat with documents**. +10. Click **Deploy**. +11. On the **Pre-deployment summary** page, click **Deploy**. + +## Step 3: ... + +In this step, ... + +1. If the **Chat** page is not already open in IBM watsonxOrchestrate, click the **Open the main menu** icon to the far left of the + top navigation bar, and then click **Chat**. +2. In the sidebar, in the **Agents** list, select the name of the agent that you created in the previous step. +3. In the **Type something** box, enter a question, and then press `Enter`. +4. The agent will provide an answer. +5. Keep asking as many questions as you want to. \ No newline at end of file From 5ff7d682257d35dc38b62646b1424e14b9e089a1 Mon Sep 17 00:00:00 2001 From: Paul Cornell Date: Mon, 29 Sep 2025 08:41:05 -0700 Subject: [PATCH 3/4] Finished adding initial content --- docs.json | 1 + examplecode/tools/ibm-orchestrate.mdx | 55 ++++++++++++++------------- 2 files changed, 30 insertions(+), 26 deletions(-) diff --git a/docs.json b/docs.json index 9f5b6286..bfa6b27a 100644 --- a/docs.json +++ b/docs.json @@ -294,6 +294,7 @@ "examplecode/tools/vectorshift", "examplecode/tools/mcp", "examplecode/tools/mcp-partition", + "examplecode/tools/ibm-orchestrate", "examplecode/tools/snowflake-streamlit", "examplecode/tools/crewai", "examplecode/tools/neo4j-chatbot" diff --git a/examplecode/tools/ibm-orchestrate.mdx b/examplecode/tools/ibm-orchestrate.mdx index 76d90ef6..df65272c 100644 --- a/examplecode/tools/ibm-orchestrate.mdx +++ b/examplecode/tools/ibm-orchestrate.mdx @@ -1,3 +1,13 @@ +--- +title: IBM watsonx Orchestrate +--- + +[IBM watsonx Orchestrate](https://www.ibm.com/products/watsonx-orchestrate) helps you build, deploy and manage powerful +AI assistants and agents that automate workflows and processes with generative AI. + +This article provides a hands-on, step-by-step walkthrough that uses IBM watsonx Orchestrate to +build a simple AI chat app. This chat app relies on data that is stored in a Milvus vector database. This data +is generated by Unstructured and is based on your organization's source documents and semi-structured data. ## Requirements @@ -7,10 +17,11 @@ To use this example, you will need the following: - Create an [IBM Cloud account](https://cloud.ibm.com/registration). - To complete this example, you will to [create an API key](https://www.ibm.com/docs/en/masv-and-l/cd?topic=cli-creating-your-cloud-api-key) for your IBM Cloud account. + To complete this example, you must [create an API key](https://www.ibm.com/docs/en/masv-and-l/cd?topic=cli-creating-your-cloud-api-key) for your IBM Cloud account. - Create an [IBM watsonx.data subscription](https://cloud.ibm.com/watsonxdata) in your IBM Cloud account. - - Create a [Milvus service instance](/ui/destinations/milvus) within your IBM watsonx.data subscription plan. + - Create a [Milvus service instance](/ui/destinations/milvus) within your IBM watsonx.data subscription plan. This instance + must contain a database, a collection, and an index to store and manage the data that is generated by Unstructured. To complete this example, you will need the following settings for the Milvus service instance: @@ -20,6 +31,8 @@ To use this example, you will need the following: - The name of the target collection in the database. - The name of the target index in the collection. + To get these settings, see the [Milvus destination connector](/ui/destinations/milvus) documentation. + - Within your Unstructured account, a workflow that contains a Milvus destination connector. - Create an [Unstructured account](https://unstructured.io/signup). @@ -27,24 +40,11 @@ To use this example, you will need the following: - Create a [custom workflow](/ui/workflows#create-a-custom-workflow) that contains the Milvus destination connector in your Unstructured account. The workflow must generate [embeddings](/ui/embedding). The workflow's **Embedder** node's selected embedding model provider must be **IBM watson.ai**. The - node's selected embedding model must be one of the following models that are offered by IBM watsonx Orchestrate: - - - `all-minilm6-v2`, with 384 dimensions. Per IBM, this model is good for tasks such as information retrieval, clustering, and for detecting sentence similarity. - - `granite-embedding-107m-multilingual`, with 384 dimensions. Per IBM, this model is good for tasks such as text similarity, retrieval, and search. - - `granite-embedding-278m-multilingual`, with 768 dimensions. - - `multilingual-e5-large`, with 1024 dimensions. Per IBM, this model is good for generating text embeddings for text in a language other than English. - - `slate-125m-english-retrvr`, with 768 dimensions. Per IBM, the `slate-125m-*` models are good for generating embeddings for various inputs such as queries, passages, or documents. Per IBM, the `slate-125m-*` models are two to three times slower but perform slightly better than the `slate-30m-*` models. - - `slate-125m-english-retrvr-v2`, with 768 dimensions. - - `slate-30m-english-retrvr`, with 384 dimensions. Per IBM, the `slate-30m-*` models are trained to maximize the cosine similarity between two text inputs so that embeddings can be evaluated based on similarity later. Per IBM, the `slate-30m-*` models are two to three times faster and have slightly lower performance scores than the `slate-125m-*` models. - - `slate-30m-english-retrvr-v2`, with 384 dimensions. - - Be sure to [run the workflow](/ui/workflows#edit%2C-delete%2C-or-run-a-workflow) to have Unstructured generate the embeddings and store them—along with - Unstructured's processed data representing your organization's source documents and semi-structured data—in the database - that is accessed through the Milvus service instance within your IBM watsonx.data subscription. + node's selected embedding model must match the embedding model that you will specify later in **Step 2**. -## Step 1: ... + Be sure to [run the workflow](/ui/workflows#edit%2C-delete%2C-or-run-a-workflow) to have Unstructured generate the data and store it in your Milvus instance's database. -In this step, you add an IBM watsonx Orchestrate subscription to your IBM Cloud account. +## Step 1: Add an IBM watsonx Orchestrate subscription to your IBM Cloud account If you already have an IBM watsonx Orchestrate subscription, then skip ahead to **Step 2**. @@ -55,9 +55,11 @@ If you already have an IBM watsonx Orchestrate subscription, then skip ahead to 4. With **IBM Cloud catalog** selected, search for and select **watsonx Orchestrate**. 5. Complete the on-screen instructions to finish creating the IBM watsonx Orchestrate subscription. -## Step 2: ... +## Step 2: Create the chat app in IBM watsonx Orchestrate -In this step, ... +In this step, you use IBM watsonx Orchestrate to create a chat app. This chat app allows you to ask questions about +your organization's documents and semi-structured data. This data is stored in your Milvus instance's database and was +generated by Unstructured in a format that is well-suited for your chat app. 1. Open your IBM watsonx Orchestrate subscription, if it is not already open. To do this: @@ -70,7 +72,7 @@ In this step, ... 2. If the **Chat** page is not already open, click the **Open the main menu** icon to the far left of the top navigation bar, and then click **Chat**. 3. Toward the bottom of the sidebar, click **Create new agent**. -4. On the **Create an agent** page, with **Create from scratch** already selected, enter some **Name** and **Description**for the agent, and then click **Create**. +4. On the **Create an agent** page, with **Create from scratch** already selected, enter some **Name** and **Description** for the agent, and then click **Create**. 5. Under **Knowledge source**, in the **Start by adding knowledge** tile, click **Choose knowledge**. 6. On the **Select source** page, click **Milvus**, and then click **Next**. 7. On the **Connect Milvus** page, specify the following settings: @@ -88,8 +90,8 @@ In this step, ... b. For **Use Collection or Alias**, select **Collection**.
c. For **Collection**, select the name of the target collection in the database.
d. For **Index**, select the name of the target index in the collection.
- e. For **Embedding model**, select the name of the embedding model that matches the one that you specified in your Unstructured workflow.
- f. for **Title**, select **element_id**.
+ e. For **Embedding model**, select the name of the embedding model that matches the one that you specified earlier in your Unstructured workflow.
+ f. For **Title**, select **element_id**.
g. For **Body**, select **text**.
h. Click **Next**.
@@ -99,11 +101,12 @@ In this step, ... 10. Click **Deploy**. 11. On the **Pre-deployment summary** page, click **Deploy**. -## Step 3: ... +## Step 3: Run the chat app -In this step, ... +In this step, you ask questions about your organization's source documents and semi-structured data. The chat app then +attempts to answer your questions by searching the related data that Unstructured generated and stored in your Milvus instance's database. -1. If the **Chat** page is not already open in IBM watsonxOrchestrate, click the **Open the main menu** icon to the far left of the +1. If the **Chat** page is not already open in IBM watsonx Orchestrate, click the **Open the main menu** icon to the far left of the top navigation bar, and then click **Chat**. 2. In the sidebar, in the **Agents** list, select the name of the agent that you created in the previous step. 3. In the **Type something** box, enter a question, and then press `Enter`. From 629785224df5e9ae3522ed0d79ad1f3ec4e86b21 Mon Sep 17 00:00:00 2001 From: Paul Cornell Date: Wed, 22 Oct 2025 11:34:58 -0700 Subject: [PATCH 4/4] Add Astra DB steps --- examplecode/tools/ibm-orchestrate.mdx | 87 +++++++++++++++++++++++---- 1 file changed, 74 insertions(+), 13 deletions(-) diff --git a/examplecode/tools/ibm-orchestrate.mdx b/examplecode/tools/ibm-orchestrate.mdx index df65272c..1af13cb7 100644 --- a/examplecode/tools/ibm-orchestrate.mdx +++ b/examplecode/tools/ibm-orchestrate.mdx @@ -6,13 +6,41 @@ title: IBM watsonx Orchestrate AI assistants and agents that automate workflows and processes with generative AI. This article provides a hands-on, step-by-step walkthrough that uses IBM watsonx Orchestrate to -build a simple AI chat app. This chat app relies on data that is stored in a Milvus vector database. This data +build a simple AI chat app. This chat app relies on data that is stored in an Astra DB or Milvus vector database. This data is generated by Unstructured and is based on your organization's source documents and semi-structured data. ## Requirements To use this example, you will need the following: +If you want to connect Unstructured to Astra DB for providing the source data to IBM watsonx Orchestrate, you will need the following: + +- An [IBM Cloud account](https://cloud.ibm.com/registration) or [DataStax account](https://astra.datastax.com/signup) account. +- An [Astra DB database](https://accounts.datastax.com/session-service/v1/login). +- To complete this example, you will need the following settings for the Astra DB database: + + - The database's API endpoint. + - An application token for the database. + - The name of the target keyspace in the database. + - The name of the target collection in the keyspace. + + To get these settings, see the [Astra DB destination connector](/ui/destinations/astradb) documentation. + +- Within your Unstructured account, a workflow that contains an Astra DB destination connector. + + - Create an [Unstructured account](https://unstructured.io/?modal=try-for-free). + - Create an [Astra DB destination connector](/ui/destinations/astradb) in your Unstructured account. + - Create a [custom workflow](/ui/workflows#create-a-custom-workflow) that contains the Astra DB destination connector in your Unstructured account. + + The workflow must generate [embeddings](/ui/embedding). The workflow's **Embedder** node's selected embedding model provider must be **IBM**. The + node's selected embedding model must match the embedding model that you will specify later in **Step 2**. + + Be sure to [run the workflow](/ui/workflows#edit%2C-delete%2C-or-run-a-workflow) to have Unstructured generate the data and store it in your Astra DB database. + +After you meet the preceding requirements, skip ahead to [Step 1](#step-1%3A-add-an-ibm-watsonx-orchestrate-subscription-to-your-ibm-cloud-account). + +If, however, you want to connect Unstructured to Milvus on IBM watsonx.data for providing the source data to IBM watsonx Orchestrate, you will need the following: + - Within your IBM Cloud account, an IBM watsonx.data subscription that contains a Milvus service instance. - Create an [IBM Cloud account](https://cloud.ibm.com/registration). @@ -39,14 +67,14 @@ To use this example, you will need the following: - Create a [Milvus destination connector](/ui/destinations/milvus) in your Unstructured account. - Create a [custom workflow](/ui/workflows#create-a-custom-workflow) that contains the Milvus destination connector in your Unstructured account. - The workflow must generate [embeddings](/ui/embedding). The workflow's **Embedder** node's selected embedding model provider must be **IBM watson.ai**. The + The workflow must generate [embeddings](/ui/embedding). The workflow's **Embedder** node's selected embedding model provider must be **IBM**. The node's selected embedding model must match the embedding model that you will specify later in **Step 2**. Be sure to [run the workflow](/ui/workflows#edit%2C-delete%2C-or-run-a-workflow) to have Unstructured generate the data and store it in your Milvus instance's database. ## Step 1: Add an IBM watsonx Orchestrate subscription to your IBM Cloud account -If you already have an IBM watsonx Orchestrate subscription, then skip ahead to **Step 2**. +If you already have an IBM watsonx Orchestrate subscription, then skip ahead to [Step 2](#step-2%3A-create-the-chat-app-in-ibm-watsonx-orchestrate) 1. [Log in to your IBM Cloud account](https://cloud.ibm.com/login). 2. On the sidebar, click the **Resource list** icon. If the sidebar is not visible, click the **Navigation Menu** icon to the far left of the @@ -58,7 +86,7 @@ If you already have an IBM watsonx Orchestrate subscription, then skip ahead to ## Step 2: Create the chat app in IBM watsonx Orchestrate In this step, you use IBM watsonx Orchestrate to create a chat app. This chat app allows you to ask questions about -your organization's documents and semi-structured data. This data is stored in your Milvus instance's database and was +your organization's documents and semi-structured data. This data is stored in your Astra DB or Milvus vector database and was generated by Unstructured in a format that is well-suited for your chat app. 1. Open your IBM watsonx Orchestrate subscription, if it is not already open. To do this: @@ -74,8 +102,42 @@ generated by Unstructured in a format that is well-suited for your chat app. 3. Toward the bottom of the sidebar, click **Create new agent**. 4. On the **Create an agent** page, with **Create from scratch** already selected, enter some **Name** and **Description** for the agent, and then click **Create**. 5. Under **Knowledge source**, in the **Start by adding knowledge** tile, click **Choose knowledge**. -6. On the **Select source** page, click **Milvus**, and then click **Next**. -7. On the **Connect Milvus** page, specify the following settings: + +If you are using Astra DB for providing the source data to IBM watsonx Orchestrate, then do the following: + +1. On the **Select source** page, click **Astra DB**, and then click **Next**. +2. On the **Connect Astra DB** page, specify the following settings: + + a. For **URL**, enter the API endpoint for the Astra DB database.
+ b. Leave **Astra DB port** blank.
+ c. For **API key**, enter the application token for your Astra DB database.
+ d. Click **Next**.
+ +3. On the **Settings details** page, specify the following settings: + + a. For **Keyspace**, select the name of the target keyspace in the Astra DB database.
+ b. For **Data type**, select **Collection**.
+ c. For **Collection**, select the name of the target collection in the database.
+ d. For **Embedding mode**, select **Client**.
+ e. For **Embedding model**, select the name of the embedding model that matches the one that you specified earlier in your Unstructured workflow.
+ f. For **Search mode**, select **Vector**.
+ g. For **Title**, enter `record_id`.
+ h. For **Body**, enter `content`.
+ i. Leave **URL** and **Advanced settings** blank.
+ j. Click **Next**.
+ +4. On the **Description** page, enter some description for the agent, and then click **Save**. +5. In the list of pages, click **Behavior**. +6. At the bottom of the **Behavior** section, turn on **Chat with documents**. +7. In the upper-right corner of the page, click **Deploy**. +8. On the **Pre-deployment summary** page, click **Deploy**. + +Skip ahead to [Step 3](#step-3%3A-run-the-chat-app). + +If, however, you are using Milvus on IBM watsonx.data for providing the source data to IBM watsonx Orchestrate, then do the following: + +1. On the **Select source** page, click **Milvus**, and then click **Next**. +2. On the **Connect Milvus** page, specify the following settings: a. For **GRPC host**, enter the GRPC host value for the Milvus service instance within your IBM watsonx.data subscription.
b. For **GRPC port**, enter the GRPC port value for the instance.
@@ -84,7 +146,7 @@ generated by Unstructured in a format that is well-suited for your chat app. e. For **Password**, enter the API key for your IBM Cloud account.
f. Click **Next**.
-8. On the **Select index** page, specify the following settings: +3. On the **Select index** page, specify the following settings: a. For **Database**, select the name of the target database on the Milvus service instance within your IBM watsonx.data subscription.
b. For **Use Collection or Alias**, select **Collection**.
@@ -95,16 +157,15 @@ generated by Unstructured in a format that is well-suited for your chat app. g. For **Body**, select **text**.
h. Click **Next**.
-9. On the **Description** page, enter some description for the agent, and then click **Save**. -10. In the list of pages, click **Behavior**. -11. Switch on **Chat with documents**. -10. Click **Deploy**. -11. On the **Pre-deployment summary** page, click **Deploy**. +4. On the **Description** page, enter some description for the agent, and then click **Save**. +5. At the bottom of the **Behavior** section, turn on **Chat with documents**. +6. In the upper-right corner of the page, click **Deploy**. +7. On the **Pre-deployment summary** page, click **Deploy**. ## Step 3: Run the chat app In this step, you ask questions about your organization's source documents and semi-structured data. The chat app then -attempts to answer your questions by searching the related data that Unstructured generated and stored in your Milvus instance's database. +attempts to answer your questions by searching the related data that Unstructured generated and stored in your Astra DB or Milvus vector database. 1. If the **Chat** page is not already open in IBM watsonx Orchestrate, click the **Open the main menu** icon to the far left of the top navigation bar, and then click **Chat**.