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doc: add document for dashboards assistant (opensearch-project#8622)
* doc: add document for dashboards assistant text to visualization Signed-off-by: Yulong Ruan <[email protected]> * Add documentation for suggest anomaly detector feature (#1) Signed-off-by: gaobinlong <[email protected]> * doc: Add document for dashboard assistant alert insight (opensearch-project#2) * doc: Add document for dashboard assistant alert insight * fix title Signed-off-by: qianheng <[email protected]> * Add data summary documentation (opensearch-project#3) Signed-off-by: Liyun Xiu <[email protected]> * add doc for alert insight agent (opensearch-project#4) * add doc for alert insight agent Signed-off-by: yuye-aws <[email protected]> * add example request for alert insight API Signed-off-by: yuye-aws <[email protected]> * correct default value for question parameter for alert insight API Signed-off-by: yuye-aws <[email protected]> * add pics for alert insight UI Signed-off-by: yuye-aws <[email protected]> --------- Signed-off-by: yuye-aws <[email protected]> * Doc review Signed-off-by: Fanit Kolchina <[email protected]> * minor rewording Signed-off-by: Fanit Kolchina <[email protected]> * Apply suggestions from code review Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> * Change to data summary feature Signed-off-by: Fanit Kolchina <[email protected]> * add instruction on how to create t2viz agents with flow template Signed-off-by: Yulong Ruan <[email protected]> * fix doc for alert summary and insight (opensearch-project#5) * fix doc for alert summary and insight Signed-off-by: yuye-aws <[email protected]> * fix doc Signed-off-by: yuye-aws <[email protected]> * change main branch to 2.x branch Signed-off-by: yuye-aws <[email protected]> * small fix Signed-off-by: yuye-aws <[email protected]> --------- Signed-off-by: yuye-aws <[email protected]> * Rewording agent creation steps Signed-off-by: Fanit Kolchina <[email protected]> * Editorial comment and rewording Signed-off-by: Fanit Kolchina <[email protected]> * Image sizes Signed-off-by: Fanit Kolchina <[email protected]> --------- Signed-off-by: Yulong Ruan <[email protected]> Signed-off-by: gaobinlong <[email protected]> Signed-off-by: qianheng <[email protected]> Signed-off-by: Liyun Xiu <[email protected]> Signed-off-by: yuye-aws <[email protected]> Signed-off-by: Fanit Kolchina <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> Co-authored-by: gaobinlong <[email protected]> Co-authored-by: qianheng <[email protected]> Co-authored-by: Liyun Xiu <[email protected]> Co-authored-by: yuye-aws <[email protected]> Co-authored-by: Fanit Kolchina <[email protected]> Co-authored-by: kolchfa-aws <[email protected]> Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: Eric Pugh <[email protected]>
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| --- | ||
| layout: default | ||
| title: Data summary | ||
| parent: OpenSearch Assistant for OpenSearch Dashboards | ||
| nav_order: 1 | ||
| has_children: false | ||
| --- | ||
|
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| # Data summary | ||
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| This is an experimental feature and is not recommended for use in a production environment. 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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| The OpenSearch Dashboards Assistant data summary feature uses large language models (LLMs) to help you generate summaries for data stored in OpenSearch indexes. This tool provides an efficient way to gain insights from large datasets, making it easier to understand and act on the information contained in your OpenSearch indexes. | ||
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| ## Configuration | ||
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| To configure the data summary feature, use the following steps. | ||
|
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| ### Prerequisite | ||
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| Before using the data summary feature, enable query enhancements in OpenSearch Dashboards as follows: | ||
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| 1. On the top menu bar, go to **Management > Dashboards Management**. | ||
| 1. In the left navigation pane, select **Advanced settings**. | ||
| 1. On the settings page, toggle **Enable query enhancements** to **On**. | ||
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| ### Step 1: Enable the data summary feature | ||
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| To enable the data summary feature, configure the following `opensearch_dashboards.yml` setting: | ||
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| ```yaml | ||
| queryEnhancements.queryAssist.summary.enabled: true | ||
| ``` | ||
| {% include copy.html %} | ||
| ### Step 2: Create a data summary agent | ||
| To orchestrate data summarization, create a data summary [agent]({{site.url}}{{site.baseurl}}/ml-commons-plugin/agents-tools/index/#agents). To create an agent, send a `POST /_plugins/_ml/agents/_register` request and provide the agent template as a payload: | ||
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| <details markdown="block"> | ||
| <summary> | ||
| Request | ||
| </summary> | ||
| {: .text-delta} | ||
|
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| ```json | ||
| POST /_plugins/_ml/agents/_register | ||
| { | ||
| "name": "Query Assist Agent", | ||
| "description": "Create a Query Assist Agent using Claude on BedRock", | ||
| "use_case": "REGISTER_AGENT", | ||
| "version": { | ||
| "template": "1.0.0", | ||
| "compatibility": ["2.13.0", "3.0.0"] | ||
| }, | ||
| "workflows": { | ||
| "provision": { | ||
| "user_params": {}, | ||
| "nodes": [ | ||
| { | ||
| "id": "create_claude_connector", | ||
| "type": "create_connector", | ||
| "previous_node_inputs": {}, | ||
| "user_inputs": { | ||
| "version": "1", | ||
| "name": "Claude instant runtime Connector", | ||
| "protocol": "aws_sigv4", | ||
| "description": "The connector to BedRock service for Claude model", | ||
| "actions": [ | ||
| { | ||
| "headers": { | ||
| "x-amz-content-sha256": "required", | ||
| "content-type": "application/json" | ||
| }, | ||
| "method": "POST", | ||
| "request_body": "{\"prompt\":\"${parameters.prompt}\", \"max_tokens_to_sample\":${parameters.max_tokens_to_sample}, \"temperature\":${parameters.temperature}, \"anthropic_version\":\"${parameters.anthropic_version}\" }", | ||
| "action_type": "predict", | ||
| "url": "https://bedrock-runtime.us-west-2.amazonaws.com/model/anthropic.claude-instant-v1/invoke" | ||
| } | ||
| ], | ||
| "credential": { | ||
| "access_key": "<YOUR_ACCESS_KEY>", | ||
| "secret_key": "<YOUR_SECRET_KEY>", | ||
| "session_token": "<YOUR_SESSION_TOKEN>" | ||
| }, | ||
| "parameters": { | ||
| "region": "us-west-2", | ||
| "endpoint": "bedrock-runtime.us-west-2.amazonaws.com", | ||
| "content_type": "application/json", | ||
| "auth": "Sig_V4", | ||
| "max_tokens_to_sample": "8000", | ||
| "service_name": "bedrock", | ||
| "temperature": "0.0001", | ||
| "response_filter": "$.completion", | ||
| "anthropic_version": "bedrock-2023-05-31" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "id": "register_claude_model", | ||
| "type": "register_remote_model", | ||
| "previous_node_inputs": { | ||
| "create_claude_connector": "connector_id" | ||
| }, | ||
| "user_inputs": { | ||
| "description": "Claude model", | ||
| "deploy": true, | ||
| "name": "claude-instant", | ||
| "guardrails": { | ||
| "type": "local_regex", | ||
| "input_guardrail": { | ||
| "stop_words": [ | ||
| { | ||
| "index_name": "words0", | ||
| "source_fields": ["title"] | ||
| } | ||
| ], | ||
| "regex": ["regex1", "regex2"] | ||
| }, | ||
| "output_guardrail": { | ||
| "stop_words": [ | ||
| { | ||
| "index_name": "words0", | ||
| "source_fields": ["title"] | ||
| } | ||
| ], | ||
| "regex": ["regex1", "regex2"] | ||
| } | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "id": "TransferQuestionToPPLAndExecuteTool", | ||
| "type": "create_tool", | ||
| "previous_node_inputs": { | ||
| "register_claude_model": "model_id" | ||
| }, | ||
| "user_inputs": { | ||
| "type": "PPLTool", | ||
| "name": "TransferQuestionToPPLAndExecuteTool", | ||
| "description": "Use this tool to transfer natural language to generate PPL and execute PPL to query inside. Use this tool after you know the index name, otherwise, call IndexRoutingTool first. The input parameters are: {index:IndexName, question:UserQuestion}", | ||
| "parameters": { | ||
| "response_filter": "$.completion", | ||
| "execute": false | ||
| }, | ||
| "include_output_in_agent_response": true | ||
| } | ||
| }, | ||
| { | ||
| "id": "summarize_success_tool", | ||
| "type": "create_tool", | ||
| "previous_node_inputs": { | ||
| "register_claude_model": "model_id" | ||
| }, | ||
| "user_inputs": { | ||
| "type": "MLModelTool", | ||
| "Name": "SummarizeSuccessTool", | ||
| "description": "Use this tool to summarize a PPL success response in query assist", | ||
| "parameters": { | ||
| "prompt": "\n\nHuman: You will be given a search response, summarize it as a concise paragraph while considering the following:\nUser's question on index '${parameters.index}': ${parameters.question}\nPPL (Piped Processing Language) query used: ${parameters.query}\n\nGive some documents to support your point.\nNote that the output could be truncated, summarize what you see. Don't mention about total items returned and don't mention about the fact that output is truncated if you see 'Output is too long, truncated' in the response.\n\nSkip the introduction; go straight into the summarization.\n\nUse the following pieces of context to answer the users question.\nIf you don't know the answer, just say that you don't know, don't try to make up an answer.\n----------------\n${parameters.response}\n\nAssistant:", | ||
| "response_filter": "$.completion" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "id": "summarize_error_tool", | ||
| "type": "create_tool", | ||
| "previous_node_inputs": { | ||
| "register_claude_model": "model_id" | ||
| }, | ||
| "user_inputs": { | ||
| "type": "MLModelTool", | ||
| "name": "SummarizeErrorTool", | ||
| "description": "Use this tool to summarize a PPL error response in query assist", | ||
| "include_output_in_agent_response": true, | ||
| "parameters": { | ||
| "prompt": "\n\nHuman: You will be given an API response with errors, summarize it as a concise paragraph. Do not try to answer the user's question.\nIf the error cannot be fixed, eg. no such field or function not supported, then give suggestions to rephrase the question.\nIt is imperative that you must not give suggestions on how to fix the error or alternative PPL query, or answers to the question.\n\nConsider the following:\nUser's question on index '${parameters.index}': ${parameters.question}\nPPL (Piped Processing Language) query used: ${parameters.query}\n\nSkip the introduction; go straight into the summarization.\n\nUse the following pieces of context to answer the users question.\nIf you don't know the answer, just say that you don't know, don't try to make up an answer.\n----------------\n${parameters.response}\n\nAssistant:", | ||
| "response_filter": "$.completion" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "id": "suggestions_tool", | ||
| "type": "create_tool", | ||
| "previous_node_inputs": { | ||
| "register_claude_model": "model_id" | ||
| }, | ||
| "user_inputs": { | ||
| "type": "MLModelTool", | ||
| "name": "SuggestionsTool", | ||
| "description": "Use this tool to generate possible questions for an index in query assist", | ||
| "include_output_in_agent_response": true, | ||
| "parameters": { | ||
| "prompt": "\n\nHuman: OpenSearch index: ${parameters.index}\n\nRecommend 2 or 3 possible questions on this index given the fields below. Only give the questions, do not give descriptions of questions and do not give PPL queries.\n\nThe format for a field is\n```\n- field_name: field_type (sample field value)\n```\n\nFields:\n${parameters.fields}\n\nPut each question in a <question> tag.\n\nAssistant:", | ||
| "response_filter": "$.completion" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "id": "ppl_agent", | ||
| "type": "register_agent", | ||
| "previous_node_inputs": { | ||
| "TransferQuestionToPPLAndExecuteTool": "tools" | ||
| }, | ||
| "user_inputs": { | ||
| "parameters": {}, | ||
| "app_type": "query_assist", | ||
| "name": "PPL agent", | ||
| "description": "this is the PPL agent", | ||
| "type": "flow" | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
|
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| </details> | ||
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| For sample agent templates, see [Flow Framework sample templates](https://github.com/opensearch-project/flow-framework/tree/2.x/sample-templates). Note the agent ID; you'll use it in the following step. | ||
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| ### Step 3: Create a root agent | ||
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| Next, create a [root agent]({{site.url}}{{site.baseurl}}/automating-configurations/workflow-tutorial/#root_agent) for the data summary agent created in the previous step: | ||
|
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| ```json | ||
| POST /.plugins-ml-config/_doc/os_data2summary | ||
| { | ||
| "type": "os_root_agent", | ||
| "configuration": { | ||
| "agent_id": "<DATA_SUMMARY_AGENT_ID>" | ||
| } | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
|
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| ### Step 4: Test the agent | ||
|
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| You can verify that the data summary agent was created successfully by calling the agent with an example payload: | ||
|
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| ```json | ||
| POST /_plugins/_ml/agents/<DATA_SUMMARY_AGENT_ID>/_execute | ||
| { | ||
| "parameters": { | ||
| "sample_data":"'[{\"_index\":\"90943e30-9a47-11e8-b64d-95841ca0b247\",\"_source\":{\"referer\":\"http://twitter.com/success/gemini-9a\",\"request\":\"/beats/metricbeat/metricbeat-6.3.2-amd64.deb\",\"agent\":\"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 1.1.4322)\",\"extension\":\"deb\",\"memory\":null,\"ip\":\"239.67.210.53\",\"index\":\"opensearch_dashboards_sample_data_logs\",\"message\":\"239.67.210.53 - - [2018-08-30T15:29:01.686Z] \\\"GET /beats/metricbeat/metricbeat-6.3.2-amd64.deb HTTP/1.1\\\" 404 2633 \\\"-\\\" \\\"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 1.1.4322)\\\"\",\"url\":\"https://artifacts.opensearch.org/downloads/beats/metricbeat/metricbeat-6.3.2-amd64.deb\",\"tags\":\"success\",\"geo\":{\"srcdest\":\"CN:PL\",\"src\":\"CN\",\"coordinates\":{\"lat\":44.91167028,\"lon\":-108.4455092},\"dest\":\"PL\"},\"utc_time\":\"2024-09-05 15:29:01.686\",\"bytes\":2633,\"machine\":{\"os\":\"win xp\",\"ram\":21474836480},\"response\":\"404\",\"clientip\":\"239.67.210.53\",\"host\":\"artifacts.opensearch.org\",\"event\":{\"dataset\":\"sample_web_logs\"},\"phpmemory\":null,\"timestamp\":\"2024-09-05 15:29:01.686\"}}]'", | ||
| "sample_count":1, | ||
| "total_count":383, | ||
| "question":"Are there any errors in my logs?", | ||
| "ppl":"source=opensearch_dashboards_sample_data_logs| where QUERY_STRING(['response'], '4* OR 5*')"} | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
|
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| ## Generating a data summary | ||
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| You can generate a data summary by calling the `/api/assistant/data2summary` API endpoint. The `sample_count`, `total_count`, `question`, and `ppl` parameters are optional: | ||
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| ```json | ||
| POST /api/assistant/data2summary | ||
| { | ||
| "sample_data":"'[{\"_index\":\"90943e30-9a47-11e8-b64d-95841ca0b247\",\"_source\":{\"referer\":\"http://twitter.com/success/gemini-9a\",\"request\":\"/beats/metricbeat/metricbeat-6.3.2-amd64.deb\",\"agent\":\"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 1.1.4322)\",\"extension\":\"deb\",\"memory\":null,\"ip\":\"239.67.210.53\",\"index\":\"opensearch_dashboards_sample_data_logs\",\"message\":\"239.67.210.53 - - [2018-08-30T15:29:01.686Z] \\\"GET /beats/metricbeat/metricbeat-6.3.2-amd64.deb HTTP/1.1\\\" 404 2633 \\\"-\\\" \\\"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 1.1.4322)\\\"\",\"url\":\"https://artifacts.opensearch.org/downloads/beats/metricbeat/metricbeat-6.3.2-amd64.deb\",\"tags\":\"success\",\"geo\":{\"srcdest\":\"CN:PL\",\"src\":\"CN\",\"coordinates\":{\"lat\":44.91167028,\"lon\":-108.4455092},\"dest\":\"PL\"},\"utc_time\":\"2024-09-05 15:29:01.686\",\"bytes\":2633,\"machine\":{\"os\":\"win xp\",\"ram\":21474836480},\"response\":\"404\",\"clientip\":\"239.67.210.53\",\"host\":\"artifacts.opensearch.org\",\"event\":{\"dataset\":\"sample_web_logs\"},\"phpmemory\":null,\"timestamp\":\"2024-09-05 15:29:01.686\"}}]'", | ||
| "sample_count":1, | ||
| "total_count":383, | ||
| "question":"Are there any errors in my logs?", | ||
| "ppl":"source=opensearch_dashboards_sample_data_logs| where QUERY_STRING(['response'], '4* OR 5*')" | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| The following table describes the Assistant Data Summary API parameters. | ||
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| Parameter | Required/Optional | Description | ||
| :--- | :--- | :--- | ||
| `sample_data` | Required | A sample of data returned by the specified query and used as input for summarization. | ||
| `question` | Optional | The user's natural language question about the data, which guides the summary generation. | ||
| `ppl` | Optional | The Piped Processing Language (PPL) query used to retrieve data; in query assistance, this is generated by the LLM using the user's natural language question. | ||
| `sample_count` | Optional | The number of entries included in sample_data. | ||
| `total_count` | Optional | The total number of entries in the full query result set. | ||
|
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| ## Viewing data summaries in OpenSearch Dashboards | ||
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| To view alert insights in OpenSearch Dashboards, use the following steps: | ||
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| 1. On the top menu bar, go to **OpenSearch Dashboards > Discover**. | ||
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| 1. From the query language dropdown list, select **PPL**. You will see the generated data summary after the query text, as shown in the following image. | ||
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| <img src="{{site.url}}{{site.baseurl}}/images/dashboards-assistant/data-summary.png" alt="data summary"> |
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