[Agentic Search]Documentation with all the features #11138
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Great work on the documentation @rithin-pullela-aws! Few comments
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| ## End-to-end example | ||
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| ### Prerequisites: Register Models |
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this should be moved up under prereq
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I have mentioned the prerequisites at the beginning as well.
Here I want the end to end example to have all the details at the risk of duplicating.
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| ### Step 3: Create a model for Query Planning tool | ||
| ```json | ||
| POST /_plugins/_ml/models/_register |
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@rithin-pullela-aws Should this have ?deploy=true to deploy the model (here and in the next step)?
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| ### Step 4(b): Register an agent with search templates | ||
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| Register an agent with the Query Planning tool configured to use your search templates: |
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| Register an agent with the Query Planning tool configured to use your search templates: | |
| Register an agent with the `QueryPlanningTool` configured to use your search templates: |
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| </details> | ||
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| However, with search templates, the agent can handle sophisticated queries by selecting the appropriate template and filling in the parameters. The LLM correctly identifies and uses the `store_sum_skus` template, fills the template parameters (such as `city: "Seattle"` and `sku1: "iphone_17_air"`), and generates a valid query with nested aggregations and bucket selectors. The response contains stores (`S-SEA-002` and `S-SEA-003`) with combined inventory ≥ 30 units: |
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| However, with search templates, the agent can handle sophisticated queries by selecting the appropriate template and filling in the parameters. The LLM correctly identifies and uses the `store_sum_skus` template, fills the template parameters (such as `city: "Seattle"` and `sku1: "iphone_17_air"`), and generates a valid query with nested aggregations and bucket selectors. The response contains stores (`S-SEA-002` and `S-SEA-003`) with combined inventory ≥ 30 units: | |
| However, with search templates, the agent can handle sophisticated queries by selecting the appropriate template and filling in the parameters. The LLM correctly identifies and uses the `store_sum_skus` template, fills the template parameters (such as `city: "Seattle"` and `sku1: "iphone_17_air"`), and generates a valid query with nested aggregations and bucket selectors. The response contains stores (`S-SEA-002` and `S-SEA-003`) with a combined inventory of ≥ 30 units: |
| } | ||
| ``` | ||
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| ## Related articles |
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| ## Related articles | |
| ## Related documentation |
| This is an experimental UI feature. For updates on the progress of the feature or if you want to leave feedback, join the discussion on the [OpenSearch forum](https://forum.opensearch.org/). | ||
| {: .warning} | ||
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| [Agentic search]({{site.url}}{{site.baseurl}}/vector-search/ai-search/agentic-search/) lets you ask questions in natural language and have OpenSearch agents plan and execute the retrieval automatically. OpenSearch Dashboards offers an intuitive user interface for configuring agents, equipping agents with different tools, and executing agentic searches. |
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| [Agentic search]({{site.url}}{{site.baseurl}}/vector-search/ai-search/agentic-search/) lets you ask questions in natural language and have OpenSearch agents plan and execute the retrieval automatically. OpenSearch Dashboards offers an intuitive user interface for configuring agents, equipping agents with different tools, and executing agentic searches. | |
| [Agentic search]({{site.url}}{{site.baseurl}}/vector-search/ai-search/agentic-search/) lets you ask questions in natural language and have OpenSearch agents plan and execute the retrieval automatically. OpenSearch Dashboards offers an intuitive UI for configuring agents, equipping agents with different tools, and executing agentic searches. |
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| 1. Under **Test flow** > **Index**, select the index you'd like to search, as shown in the following image. Under **Test flow** > **Query**, enter a natural language query. Optionally, specify query fields for the agent to search in your selected index. To edit the full `agentic` search query directly, toggle to the `JSON` view. Then select **Search**. The agent may take several seconds to execute. | ||
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| 1. Under **Generated query**, view the query DSL that the agent generated and ran against your cluster. |
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| 1. Under **Generated query**, view the query DSL that the agent generated and ran against your cluster. | |
| 1. Under **Generated query**, view the query domain-specific language (DSL) that the agent generated and ran against your cluster. |
Signed-off-by: Nathan Bower <nbower@amazon.com>
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Description
Describe what this change achieves.
Issues Resolved
Closes #11026
Version
List the OpenSearch version to which this PR applies, e.g. 2.14, 2.12--2.14, or all.
Frontend features
If you're submitting documentation for an OpenSearch Dashboards feature, add a video that shows how a user will interact with the UI step by step. A voiceover is optional.
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