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Added conversation search default use case with RAG tool (opensearch-…
…project#732) Added conversation search use case with RAG tool Signed-off-by: owaiskazi19 <[email protected]>
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35 changes: 35 additions & 0 deletions
35
src/main/resources/defaults/conversational-search-rag-tool-defaults.json
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,35 @@ | ||
| { | ||
| "template.name": "deploy-bedrock-chat-model", | ||
| "template.description": "A template to deploy a Bedrock chat model", | ||
| "create_bedrock_connector.name": "Amazon Bedrock Connector: Claude Instant V1", | ||
| "create_bedrock_connector.description": "The connector to bedrock Claude model", | ||
| "create_bedrock_connector.protocol": "aws_sigv4", | ||
| "create_bedrock_connector.actions.url": "https://bedrock-runtime.us-west-2.amazonaws.com/model/anthropic.claude-instant-v1/invoke", | ||
| "create_bedrock_connector.actions.request_body": "{\"prompt\":\"${parameters.prompt}\", \"max_tokens_to_sample\":${parameters.max_tokens_to_sample}, \"temperature\":${parameters.temperature}, \"anthropic_version\":\"${parameters.anthropic_version}\" }", | ||
| "create_bedrock_connector.credential.access_key": "", | ||
| "create_bedrock_connector.credential.secret_key": "", | ||
| "create_bedrock_connector.credential.session_token": "", | ||
| "create_bedrock_connector.region": "us-west-2", | ||
| "create_embedding_connector.name": "Amazon Bedrock Connector: embedding", | ||
| "create_embedding_connector.description": "The connector to bedrock Titan embedding model", | ||
| "create_embedding_connector.protocol": "aws_sigv4", | ||
| "create_embedding_connector.actions.url": "https://bedrock-runtime.us-west-2.amazonaws.com/model/amazon.titan-embed-text-v2:0/invoke", | ||
| "create_embedding_connector.actions.request_body": "{ \"inputText\": \"${parameters.inputText}\" }", | ||
| "register_bedrock_model.name": "anthropic.claude-v2", | ||
| "register_bedrock_model.description": "bedrock-chat-model", | ||
| "register_bedrock_embedding_model.name": "Bedrock embedding model v2", | ||
| "register_bedrock_embedding_model.description": "Bedrock embedding model v2", | ||
| "create_ingest_pipeline.pipeline_id": "nlp-ingest-pipeline", | ||
| "create_ingest_pipeline.description": "A neural ingest pipeline", | ||
| "text_embedding.field_map.input": "passage_text", | ||
| "text_embedding.field_map.output": "passage_embedding", | ||
| "create_index.name": "my-nlp-index", | ||
| "create_index.mappings.method.engine": "lucene", | ||
| "create_index.mappings.method.space_type": "l2", | ||
| "create_index.mappings.method.name": "hnsw", | ||
| "text_embedding.field_map.output.dimension": "1024", | ||
| "rag_tool.parameters.prompt": "\n\nHuman:You are a professional data analysist. You will always answer question based on the given context first. If the answer is not directly shown in the context, you will analyze the data and find the answer. If you don't know the answer, just say don't know. \n\n Context:\n${parameters.output_field:-}\n\n\nHuman:${parameters.question}\n\nAssistant:", | ||
| "root_agent.parameters.parameters": "Answer the question as best you can.", | ||
| "root_agent.name": "Root agent", | ||
| "root_agent.description": "this is the root agent" | ||
| } |
218 changes: 218 additions & 0 deletions
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...resources/substitutionTemplates/conversational-search-with-bedrock-rag-tool-template.json
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| { | ||
| "name": "${{template.name}}", | ||
| "description": "${{template.description}}", | ||
| "use_case": "CONVERSATION_SEARCH", | ||
| "version": { | ||
| "template": "1.0.0", | ||
| "compatibility": [ | ||
| "2.12.0", | ||
| "3.0.0" | ||
| ] | ||
| }, | ||
| "workflows": { | ||
| "provision": { | ||
| "nodes": [ | ||
| { | ||
| "id": "create_bedrock_connector", | ||
| "type": "create_connector", | ||
| "user_inputs": { | ||
| "name": "${{create_bedrock_connector.name}}", | ||
| "description": "Test connector for Amazon Bedrock", | ||
| "version": "1", | ||
| "protocol": "${{create_bedrock_connector.protocol}}", | ||
| "credential": { | ||
| "access_key": "${{create_bedrock_connector.credential.access_key}}", | ||
| "secret_key": "${{create_bedrock_connector.credential.secret_key}}", | ||
| "session_token": "${{create_bedrock_connector.credential.session_token}}" | ||
| }, | ||
| "parameters": { | ||
| "max_tokens_to_sample": "8000", | ||
| "service_name": "bedrock", | ||
| "temperature": "1.0E-4", | ||
| "response_filter": "$.completion", | ||
| "region": "${{create_bedrock_connector.region}}", | ||
| "anthropic_version": "bedrock-2023-05-31" | ||
| }, | ||
| "actions": [ | ||
| { | ||
| "action_type": "PREDICT", | ||
| "method": "POST", | ||
| "url": "${{create_bedrock_connector.actions.url}}", | ||
| "headers": { | ||
| "x-amz-content-sha256": "required", | ||
| "content-type": "application/json" | ||
| }, | ||
| "request_body": "${{create_bedrock_connector.actions.request_body}}" | ||
| } | ||
| ] | ||
| } | ||
| }, | ||
| { | ||
| "id": "create_embedding_connector", | ||
| "type": "create_connector", | ||
| "user_inputs": { | ||
| "name": "${{create_embedding_connector.name}}", | ||
| "description": "${{create_embedding_connector.description}}", | ||
| "version": "1", | ||
| "protocol": "${{create_embedding_connector.protocol}}", | ||
| "credential": { | ||
| "access_key": "${{create_bedrock_connector.credential.access_key}}", | ||
| "secret_key": "${{create_bedrock_connector.credential.secret_key}}", | ||
| "session_token": "${{create_bedrock_connector.credential.session_token}}" | ||
| }, | ||
| "parameters": { | ||
| "service_name": "bedrock", | ||
| "model": "amazon.titan-embed-text-v2:0", | ||
| "region": "us-west-2", | ||
| "anthropic_version": "bedrock-2023-05-31" | ||
| }, | ||
| "actions": [ | ||
| { | ||
| "action_type": "PREDICT", | ||
| "method": "POST", | ||
| "url": "${{create_embedding_connector.actions.url}}", | ||
| "headers": { | ||
| "x-amz-content-sha256": "required", | ||
| "content-type": "application/json" | ||
| }, | ||
| "request_body": "${{create_embedding_connector.actions.request_body}}", | ||
| "pre_process_function": "connector.pre_process.bedrock.embedding", | ||
| "post_process_function": "connector.post_process.bedrock.embedding" | ||
| } | ||
| ] | ||
| } | ||
| }, | ||
|
|
||
| { | ||
| "id": "register_bedrock_model", | ||
| "type": "register_remote_model", | ||
| "previous_node_inputs": { | ||
| "create_bedrock_connector": "connector_id" | ||
| }, | ||
| "user_inputs": { | ||
| "name": "${{register_bedrock_model.name}}", | ||
| "function_name": "remote", | ||
| "description": "${{register_bedrock_model.description}}", | ||
| "deploy": true | ||
| } | ||
| }, | ||
| { | ||
| "id": "register_bedrock_embedding_model", | ||
| "type": "register_remote_model", | ||
| "previous_node_inputs": { | ||
| "create_embedding_connector": "connector_id" | ||
| }, | ||
| "user_inputs": { | ||
| "name": "${{register_bedrock_embedding_model.name}}", | ||
| "description": "${{register_bedrock_embedding_model.description}}", | ||
| "function_name": "remote", | ||
| "deploy": true | ||
| } | ||
| }, | ||
| { | ||
| "id": "create_ingest_pipeline", | ||
| "type": "create_ingest_pipeline", | ||
| "previous_node_inputs": { | ||
| "register_bedrock_embedding_model": "model_id" | ||
| }, | ||
| "user_inputs": { | ||
| "pipeline_id": "${{create_ingest_pipeline.pipeline_id}}", | ||
| "configurations": { | ||
| "description": "${{create_ingest_pipeline.description}}", | ||
| "processors": [ | ||
| { | ||
| "text_embedding": { | ||
| "model_id": "${{register_bedrock_embedding_model.model_id}}", | ||
| "field_map": { | ||
| "${{text_embedding.field_map.input}}": "${{text_embedding.field_map.output}}" | ||
| } | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "id": "create_index", | ||
| "type": "create_index", | ||
| "previous_node_inputs": { | ||
| "create_ingest_pipeline": "pipeline_id" | ||
| }, | ||
| "user_inputs": { | ||
| "index_name": "${{create_index.name}}", | ||
| "configurations": { | ||
| "settings": { | ||
| "index": { | ||
| "default_pipeline": "${{create_ingest_pipeline.pipeline_id}}", | ||
| "knn": "true" | ||
| } | ||
| }, | ||
| "mappings": { | ||
| "properties": { | ||
| "${{text_embedding.field_map.input}}": { | ||
| "type": "text" | ||
| }, | ||
| "${{text_embedding.field_map.output}}": { | ||
| "type": "knn_vector", | ||
| "method": { | ||
| "engine": "${{create_index.mappings.method.engine}}", | ||
| "space_type": "${{create_index.mappings.method.space_type}}", | ||
| "name": "${{create_index.mappings.method.name}}", | ||
| "parameters": {} | ||
| }, | ||
| "dimension": "${{text_embedding.field_map.output.dimension}}" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "id": "rag_tool", | ||
| "type": "create_tool", | ||
| "previous_node_inputs": { | ||
| "register_bedrock_model": "model_id", | ||
| "register_bedrock_embedding_model": "model_id" | ||
| }, | ||
| "user_inputs": { | ||
| "type": "RAGTool", | ||
| "name": "RAGTool", | ||
| "parameters": { | ||
| "inference_model_id": "${{register_bedrock_model.model_id}}", | ||
| "embedding_model_id": "${{register_bedrock_embedding_model.model_id}}", | ||
| "index": "${{create_index.name}}", | ||
| "embedding_field": "${{text_embedding.field_map.output}}", | ||
| "source_field": "[\"${{text_embedding.field_map.input}}\"]", | ||
| "query_type": "neural", | ||
| "input": "${parameters.question}", | ||
| "prompt": "${{rag_tool.parameters.prompt}}", | ||
| "include_output_in_agent_response": true | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "id": "root_agent", | ||
| "type": "register_agent", | ||
| "previous_node_inputs": { | ||
| "rag_tool": "tools" | ||
| }, | ||
| "user_inputs": { | ||
| "parameters": { | ||
| "prompt": "${{root_agent.parameters.parameters}}" | ||
| }, | ||
| "app_type": "chatbot", | ||
| "name": "${{root_agent.name}}", | ||
| "description": "${{root_agent.description}}", | ||
| "tools_order": [ | ||
| "rag_tool" | ||
| ], | ||
| "memory": { | ||
| "type": "conversation_index" | ||
| }, | ||
| "type": "flow" | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| } |
2 changes: 1 addition & 1 deletion
2
...ain/resources/substitutionTemplates/conversational-search-with-cohere-model-template.json
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