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Change Query Assist sample template to use Claude model (#629)
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* Change Query Assist sample template to use Claude model

Signed-off-by: Daniel Widdis <[email protected]>

* Add guardrail type

Signed-off-by: Daniel Widdis <[email protected]>

* Add session_token

Signed-off-by: Daniel Widdis <[email protected]>

* Rename model files to identify LLM and testing status

Signed-off-by: Daniel Widdis <[email protected]>

---------

Signed-off-by: Daniel Widdis <[email protected]>
@dbwiddis
dbwiddis authored Mar 29, 2024
1 parent 42f53da commit b86ea9c
Showing 4 changed files with 150 additions and 278 deletions.
0 ...e-templates/observability-chat-agent.json → ...rvability-chat-agent-openai-untested.json
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File renamed without changes.
0 ...le-templates/observability-chat-agent.yml → ...ervability-chat-agent-openai-untested.yml
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File renamed without changes.
213 changes: 68 additions & 145 deletions sample-templates/query-assist-agent.json → ...tes/query-assist-agent-claude-tested.json
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Original file line number Diff line number Diff line change
@@ -1,90 +1,109 @@
{
"name": "Query Assist Agent",
"description": "Create a Query Assist Agent using Bedrock and Sagemaker models",
"description": "Create a Query Assist Agent using Claude on BedRock",
"use_case": "REGISTER_AGENT",
"version": {
"template": "1.0.0",
"compatibility": [
"2.12.0",
"3.0.0"
]
"compatibility": ["2.13.0", "3.0.0"]
},
"workflows": {
"provision": {
"user_params": {},
"nodes": [
{
"id": "create_openai_connector",
"id": "create_claude_connector",
"type": "create_connector",
"previous_node_inputs": {},
"user_inputs": {
"name": "OpenAI Chat Connector",
"description": "The connector to public OpenAI model service for GPT 3.5",
"version": "1",
"protocol": "http",
"parameters": {
"endpoint": "api.openai.com",
"model": "gpt-3.5-turbo"
},
"credential": {
"openAI_key": "PUT_YOUR_API_KEY_HERE"
},
"name": "Claude instant runtime Connector",
"protocol": "aws_sigv4",
"description": "The connector to BedRock service for Claude model",
"actions": [
{
"action_type": "predict",
"headers": {
"x-amz-content-sha256": "required",
"content-type": "application/json"
},
"method": "POST",
"url": "https://${parameters.endpoint}/v1/chat/completions"
"request_body": "{\"prompt\":\"${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_openai_model",
"id": "register_claude_model",
"type": "register_remote_model",
"previous_node_inputs": {
"create_openai_connector": "connector_id"
"create_claude_connector": "connector_id"
},
"user_inputs": {
"name": "openAI-gpt-3.5-turbo",
"deploy": true
"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_openai_model": "model_id"
"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,
"model_type": "openai"
"execute": false
},
"include_output_in_agent_response": true
}
},
{
"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"
}
},
{
"id": "summarize_success_tool",
"type": "create_tool",
"previous_node_inputs": {
"register_openai_model": "model_id"
"register_claude_model": "model_id"
},
"user_inputs": {
"type": "MLModelTool",
@@ -96,26 +115,11 @@
}
}
},
{
"id": "response_summary_agent",
"type": "register_agent",
"previous_node_inputs": {
"summarize_success_tool": "tools"
},
"user_inputs": {
"parameters": {
},
"app_type": "query_assist",
"name": "Response summary agent",
"description": "this is the summarize success PPL response agent",
"type": "flow"
}
},
{
"id": "summarize_error_tool",
"type": "create_tool",
"previous_node_inputs": {
"register_openai_model": "model_id"
"register_claude_model": "model_id"
},
"user_inputs": {
"type": "MLModelTool",
@@ -132,7 +136,7 @@
"id": "suggestions_tool",
"type": "create_tool",
"previous_node_inputs": {
"register_openai_model": "model_id"
"register_claude_model": "model_id"
},
"user_inputs": {
"type": "MLModelTool",
@@ -146,97 +150,16 @@
}
},
{
"id": "error_summary_agent",
"id": "ppl_agent",
"type": "register_agent",
"previous_node_inputs": {
"summarize_error_tool": "tools",
"suggestions_tool": "tools"
"TransferQuestionToPPLAndExecuteTool": "tools"
},
"user_inputs": {
"parameters": {
},
"parameters": {},
"app_type": "query_assist",
"name": "Error summary agent",
"description": "this is the agent for summarizing PPL error and give suggested questions",
"tools_order": [
"summarize_error_tool",
"suggestions_tool"
],
"type": "flow"
}
},
{
"id": "ppl_agent_tool",
"type": "create_tool",
"previous_node_inputs": {
"ppl_agent": "agent_id"
},
"user_inputs": {
"description": "PPL Agent Tool",
"include_output_in_agent_response": true,
"type": "AgentTool",
"parameters": {
"max_iteration": "5"
},
"name": "PPLAgentTool"
}
},
{
"id": "response_summary_agent_tool",
"type": "create_tool",
"previous_node_inputs": {
"response_summary_agent": "agent_id"
},
"user_inputs": {
"description": "Response Summary Agent Tool",
"include_output_in_agent_response": true,
"type": "AgentTool",
"parameters": {
"max_iteration": "5"
},
"name": "ResponseSummaryPPLAgentTool"
}
},
{
"id": "error_summary_agent_tool",
"type": "create_tool",
"previous_node_inputs": {
"error_summary_agent": "agent_id"
},
"user_inputs": {
"description": "Error Summary Agent Tool",
"include_output_in_agent_response": true,
"type": "AgentTool",
"parameters": {
"max_iteration": "5"
},
"name": "ErrorSummaryAgentTool"
}
},
{
"id": "root_agent",
"type": "register_agent",
"previous_node_inputs": {
"ppl_agent_tool": "tools",
"response_summary_agent_tool": "tools",
"error_summary_agent_tool": "tools",
"register_openai_model": "model_id"
},
"user_inputs": {
"parameters": {
"prompt": "Answer the question as best you can."
},
"app_type": "chatbot",
"name": "Root agent",
"description": "this is the root agent",
"tools_order": [
"ppl_agent_tool",
"response_summary_agent_tool",
"error_summary_agent_tool"
],
"memory": {
"type": "conversation_index"
},
"name": "PPL agent",
"description": "this is the PPL agent",
"type": "flow"
}
}
215 changes: 82 additions & 133 deletions sample-templates/query-assist-agent.yml → ...ates/query-assist-agent-claude-tested.yml
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Original file line number Diff line number Diff line change
@@ -1,64 +1,98 @@
# This template creates connectors to OpenAI GPT model.
# This template creates a connectors to Claude v1 model on Bedrock
#
# It then creates tools in the Agent Framework to create a query assist agent.
#
# To use:
# - update the "credential" fields under the create_openai_connector node.
# - if needed, update region
# - update the "credential" fields under the create_claude_connector node.
# - if needed, update region and endpoint
#
# After provisioning:
# - returns a workflow ID
# - use the status API to get the deployed model IDs and agent IDs
# - use those models and agents to create a chat experience
---
name: Query Assist Agent
description: Create a Query Assist Agent using Bedrock and Sagemaker models
description: Create a Query Assist Agent using Claude on BedRock
use_case: REGISTER_AGENT
version:
template: 1.0.0
compatibility:
- 2.12.0
- 2.13.0
- 3.0.0
# This section defines the provision workflow. Nodes are connected in a graph.
# Either previous_node_inputs or explicit edges can be used to enforce ordering.
workflows:
provision:
user_params: {}
nodes:
#
# SETUP EXTERNAL MODEL
#
# Create a connector to an OpenAI model and deploy the model
- id: create_openai_connector
# This node (workflow step) creates the connector to the Claude model on Bedrock.
# To use a different model, you can update this node.
# Be sure to enter your keys/token in the credentials section, and change the region and endpoint if applicable.
- id: create_claude_connector
type: create_connector
previous_node_inputs: {}
user_inputs:
name: OpenAI Chat Connector
description: The connector to public OpenAI model service for GPT 3.5
version: '1'
protocol: http
parameters:
endpoint: api.openai.com
model: gpt-3.5-turbo
credential:
openAI_key: 'PUT_YOUR_API_KEY_HERE'
name: Claude instant runtime Connector
protocol: aws_sigv4
description: The connector to BedRock service for Claude model
actions:
- action_type: predict
- headers:
x-amz-content-sha256: required
content-type: application/json
method: POST
url: https://${parameters.endpoint}/v1/chat/completions
- id: register_openai_model
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: "$.completion"
anthropic_version: bedrock-2023-05-31
# This node registers the connector in the previous step and loads it into memory.
# The resulting model_id can be used later when configuring the agents to use this model.
- id: register_claude_model
type: register_remote_model
previous_node_inputs:
create_openai_connector: connector_id
create_claude_connector: connector_id
user_inputs:
name: openAI-gpt-3.5-turbo
description: Claude model
deploy: true
#
# SETUP PPL AGENT
#
# Create a PPLTool
name: claude-instant
# Guardrails can filter the input and output to the model.
guardrails:
# The type is presently unused but required. Any string works here.
type: local_regex
input_guardrail:
stop_words:
- index_name: words0
source_fields:
- title
regex:
- regex1
- regex2
output_guardrail:
stop_words:
- index_name: words0
source_fields:
- title
regex:
- regex1
- regex2
# The next node uses the model_id generated from the previous node in tools for the Agent Framework
- id: TransferQuestionToPPLAndExecuteTool
type: create_tool
previous_node_inputs:
register_openai_model: model_id
register_claude_model: model_id
user_inputs:
type: PPLTool
name: TransferQuestionToPPLAndExecuteTool
@@ -69,27 +103,12 @@ workflows:
parameters:
response_filter: "$.completion"
execute: false
model_type: openai
include_output_in_agent_response: true
# Create a flow agent to use the PPLTool
- 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
#
# SETUP RESPONPSE SUMMARY AGENT
#
# Create a tool to summarize successful results in natural language
# This tool is presently unused in this template. Add it to the Agent to be used.
- id: summarize_success_tool
type: create_tool
previous_node_inputs:
register_openai_model: model_id
register_claude_model: model_id
user_inputs:
type: MLModelTool
Name: SummarizeSuccessTool
@@ -114,25 +133,11 @@ workflows:
Assistant:
response_filter: "$.completion"
# Create a flow agent to use the PPLTool
- id: response_summary_agent
type: register_agent
previous_node_inputs:
summarize_success_tool: tools
user_inputs:
parameters: {}
app_type: query_assist
name: Response summary agent
description: this is the summarize success PPL response agent
type: flow
#
# SETUP ERROR AND SUGGESTIONS AGENT
#
# Create a tool to summarize error results in natural language
# This tool is presently unused in this template. Add it to the Agent to be used.
- id: summarize_error_tool
type: create_tool
previous_node_inputs:
register_openai_model: model_id
register_claude_model: model_id
user_inputs:
type: MLModelTool
name: SummarizeErrorTool
@@ -159,16 +164,16 @@ workflows:
Assistant:
response_filter: "$.completion"
# Create a tool to give suggestions for future questions
# This tool is presently unused in this template. Add it to the Agent to be used.
- id: suggestions_tool
type: create_tool
previous_node_inputs:
register_openai_model: model_id
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
description: Use this tool to generate possible questions for an index in
query assist
include_output_in_agent_response: true
parameters:
prompt: |2-
@@ -190,75 +195,19 @@ workflows:
Assistant:
response_filter: "$.completion"
# Create a flow agent to summarize the errors and suggest possible questions
- id: error_summary_agent
# This is the Flow Agent that uses the TransferQuestionToPPLAndExecuteTool
# To use more tools, add them in a new tools_order field under user_inputs
- id: ppl_agent
type: register_agent
previous_node_inputs:
summarize_error_tool: tools
suggestions_tool: tools
TransferQuestionToPPLAndExecuteTool: tools
user_inputs:
parameters: {}
app_type: query_assist
name: Error summary agent
description: this is the agent for summarizing PPL error and give suggested questions
tools_order:
- summarize_error_tool
- suggestions_tool
type: flow
#
# WRAP AGENTS IN AGENT TOOLS FOR ROOT AGENT
#
- id: ppl_agent_tool
type: create_tool
previous_node_inputs:
ppl_agent: agent_id
user_inputs:
description: PPL Agent Tool
include_output_in_agent_response: true
type: AgentTool
parameters:
max_iteration: '5'
name: PPLAgentTool
- id: response_summary_agent_tool
type: create_tool
previous_node_inputs:
response_summary_agent: agent_id
user_inputs:
description: Response Summary Agent Tool
include_output_in_agent_response: true
type: AgentTool
parameters:
max_iteration: '5'
name: ResponseSummaryPPLAgentTool
- id: error_summary_agent_tool
type: create_tool
previous_node_inputs:
error_summary_agent: agent_id
user_inputs:
description: Error Summary Agent Tool
include_output_in_agent_response: true
type: AgentTool
parameters:
max_iteration: '5'
name: ErrorSummaryAgentTool
# The root agent will use the agent tools
- id: root_agent
type: register_agent
previous_node_inputs:
ppl_agent_tool: tools
response_summary_agent_tool: tools
error_summary_agent_tool: tools
register_openai_model: model_id
user_inputs:
parameters:
prompt: Answer the question as best you can.
app_type: chatbot
name: Root agent
description: this is the root agent
tools_order:
- ppl_agent_tool
- response_summary_agent_tool
- error_summary_agent_tool
memory:
type: conversation_index
name: PPL agent
description: this is the PPL agent
type: flow
# Uncomment if you want to add more tools. Order matters for flow agent.
# tools_order:
# - TransferQuestionToPPLAndExecuteTool
# - add other tools here in order

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