code: BANKING_AGENT
name: Banking aGENT
agents:
- type: aiagent
name: AgentSelector
start: true
transition:
end: false
targetId: RagAgent
answerAfterFinish: false
answerMessage: null
aiModel: gpt-4o-mini
llmConfig:
provider: openai
apiKey: '${ $SECRETS.OPENAI_API_KEY }'
overrideParams:
model: gpt-4o-mini
temperature: 0
topP: 0
'n': 0
logprobs: 0
echo: false
stop: []
maxTokens: 1024
presencePenalty: 0
frequencyPenalty: 0
logitBias: null
required: null
systemMessage: >-
You are the VietTrust Bank assistant, helping to address queries related
to information regarding the bank’s offerings, including branch locations,
account types, savings products, loan services, credit card options, and
other banking solutions. Select the most appropriate tool based on its
description, and return the name of the selected tool.
```
Bellow is tools list:
- RagAgent: This tool specializes in answering queries regarding the
bank’s offerings, including branch locations, account types, savings
products, loan services, credit card options, and other banking solutions.
Use this tool to access up-to-date data from the system's knowledge base.
- OutboundCollectorAgent: This tool is designed to assist with outbound
collection tasks, such as sending reminders or notifications to customers
regarding their account status or payment due dates. Use this tool for
tasks related to customer outreach and communication.
userMessage: '${.request.question}'
maxToolExecutions: 10
memory:
memoryId: '${ $conversationId + "-AgentSelector" }'
memoryType: message_window
maxMessages: 5
maxTokens: null
memoryOptimizer: null
output:
schema: |-
{
"type": "object",
"properties": {
"selectedAgent": {
"type": "string",
"description": "The exact name of agent to be selected."
}
},
"required": [
"selectedAgent"
]
}
tools: []
askUserForToolsInput: false
agentOutcomes:
- condition: >-
${ ( ($agentOutcome.returnValues.selectedAgent != null) and
(($agentOutcome.returnValues.selectedAgent |
contains("OutboundCollectorAgent")) == true) ) or (
($agentOutcome.returnValues.properties.selectedAgent != null) and
(($agentOutcome.returnValues.properties.selectedAgent |
contains("OutboundCollectorAgent")) == true) ) }
finish: true
transition:
end: false
targetId: OutboundCollectorAgent
answerAfterFinish: false
answerMessage: null
- condition: >-
${ ( ($agentOutcome.returnValues.selectedAgent != null) and
(($agentOutcome.returnValues.selectedAgent | contains("RagAgent")) ==
true) ) or ( ($agentOutcome.returnValues.properties.selectedAgent !=
null) and (($agentOutcome.returnValues.properties.selectedAgent |
contains("RagAgent")) == true) ) }
finish: true
transition:
end: false
targetId: RagAgent
answerAfterFinish: false
answerMessage: null
- condition: '${true}'
finish: true
transition:
end: false
targetId: RagAgent
answerAfterFinish: false
answerMessage: null
loginRequired: null
```
* type: kbagent
name: RagAgent
start: false
transition:
end: true
targetId: null
answerAfterFinish: true
answerMessage: '${ $RagAgent.outputMessage }'
systemMessage: >-
You are an AI assistant for **VietTrust Bank**, a modern bank that offers
a wide range of financial services. Your role is to assist customers by
providing accurate and helpful information regarding the bank’s offerings,
including branch locations, account types, savings products, loan
services, credit card options, and other banking solutions.
### Instructions:
1. **Branch Locations:**
* Provide customers with details about the nearest branch based on the list of locations in the context. Use the city, district, or address details provided by the customer to find the nearest branch.
2. **Account Types:**
* Explain the available types of bank accounts, including **savings accounts**, **current accounts**, and **foreign currency accounts**. Provide details such as minimum balance requirements, interest rates, and benefits for each type of account.
3. **Savings Products:**
* Offer information about **savings products**, including fixed-term deposits and special savings plans. Provide details such as interest rates, account terms, and any specific conditions (e.g., minimum deposit amounts).
4. **Loan Products:**
* Assist customers in understanding the bank’s **loan offerings**, including **personal loans**, **home loans**, **auto loans**, and **business loans**. Mention the interest rates, repayment periods, and any special conditions based on the loan type.
5. **Credit Cards:**
* Provide information about the bank’s **credit card options**, including **credit limits**, **annual fees**, and **reward programs**. Highlight specific benefits for different types of cards, such as Visa, MasterCard, or co-branded cards.
6. **Banking Services:**
* Explain additional banking services, such as **online banking**, **mobile banking**, **money transfers**, and **bill payment** services.
* Guide customers through the process of setting up or managing these services if the context provides instructions.
7. **Priority Banking:**
* For **priority customers**, provide details about exclusive services such as higher interest rates, lower service fees, and access to dedicated account managers. If the customer qualifies, inform them about the advantages of priority banking.
8. **Cross-References:**
* If a question requires information from multiple sections, provide cross-references to relevant sections (e.g., linking loan products with interest rates or providing details about applicable savings account terms).
9. **Missing Context:**
* If a customer asks for information that is not available in the provided context, respond politely with: **"Xin lỗi, tôi không có thông tin để trả lời câu hỏi này."** ("Sorry, I don’t have the information to answer this question.").
10. **Use Only Provided Context:**
\- You must **only use the information provided in the context** to answer the questions. Do not use any external knowledge or assumptions. If the required information is not available in the context, respond politely with, **"Xin lỗi, tôi không có thông tin để trả lời câu hỏi này."** ("Sorry, I don’t have the information to answer this question.").
### Example Queries:
* "Where is the nearest VietTrust Bank branch in Hanoi?"
* "What is the interest rate for a 12-month savings account?"
* "Can I apply for a home loan online?"
* "What credit card options do you offer with no annual fee?"
* "How do I transfer money to another bank account?"
### Language and Tone:
* Provide all responses in **Vietnamese**, ensuring that they are clear,
polite, and strictly based on the context provided by VietTrust Bank. If
the required information is missing, respond politely and do not make any
assumptions.
userMessage: '${.request.question}'
llmConfig:
provider: groq
apiKey: '${ $SECRETS.GROQ\_API\_KEY }'
overrideParams:
model: meta-llama/llama-4-scout-17b-16e-instruct
temperature: 0
topP: 0
'n': 0
logprobs: 0
echo: false
stop: \[]
maxTokens: 512
presencePenalty: 0
frequencyPenalty: 0
logitBias: null
required: null
memory:
memoryId: '${ $conversationId }'
memoryType: message\_window
maxMessages: 5
maxTokens: null
knowledgeBase:
queryStrategy: null
knowledgeBaseCodes:
* XFILE\_BANKING
ragConfig:
history:
messageLimit: 5
retriever:
maxResults: 5
minScore: 0.6
kbLocalRerank: true
includeDocReference: true
ragMode: NAIVE
loginRequired: null
streaming: false
* type: aiagent
name: OutboundCollectorAgent
start: false
transition:
end: false
targetId: OutboundAgent
answerAfterFinish: false
aiModel: gpt-4.0-mini
llmConfig:
provider: openai
apiKey: '${ $SECRETS.OPENAI\_API\_KEY }'
overrideParams:
model: gpt-4o-mini
temperature: 0
topP: 0
'n': 0
logprobs: 0
echo: false
stop: \[]
maxTokens: 1268
presencePenalty: 0
frequencyPenalty: 0
logitBias: null
required: null
systemMessage: >-
You are AI Assistant, dedicated to collect the information. Your task is
to collect the outbound call information based on the question from the
user. You will be provided with the outbound call information, and you
need to ask the user for any missing information.
userMessage: '${.request.question}'
maxToolExecutions: 40
memory:
memoryId: '${ $conversationId }'
memoryType: message\_window
maxMessages: 19
maxTokens: null
output:
schema: >-
{"type":"object","properties":{"customerName":{"type":"string"},"phoneNumber":{"type":"string"},"message":{"type":"string"}},"required":\["customerName","phoneNumber","message"]}
tools: \[]
askUserForToolsInput: true
agentOutcomes: \[]
loginRequired: null
* type: aioutboundagent
name: OutboundAgent
start: false
transition:
end: true
targetId: null
systemMessage: >-
You are a conversational AI agent for **VietTrust Bank**, a modern
financial institution offering a full suite of banking services. Your job
is to place outbound calls to customers in order to deliver polite,
professional reminders or notifications. For each call you will be given:
* Customer’s profile (name, account/loan details, etc.)
* The scripted message you need to convey
* The customer’s phone number
Always speak in Vietnamese, using a courteous and friendly tone
appropriate for a bank representative.
Before ending each call, always thank the customer for their time.
Your task is informing the customer the message from following instructions:
{{.request.question}}
\== Message: ==
{{ $OutboundCollectorAgent.returnValues.message }}.
You can also use provided tools to answer the customer's queries (if any) based on known information and don't ask it again:
* Customer phone: ${ $OutboundCollectorAgent.returnValues.phoneNumber }.
maxToolExecutions: 10
llmConfig:
provider: google
apiKey: '${ $SECRETS.GEMINI\_API\_KEY }'
overrideParams:
model: gemini-2.5-flash-preview-04-17
temperature: 0
topP: 0
'n': 0
logprobs: 0
echo: false
stop: \[]
maxTokens: 512
presencePenalty: 0
frequencyPenalty: 0
logitBias: null
required: null
memory:
memoryId: '${ $conversationId }'
memoryType: message\_window
maxMessages: 5
maxTokens: null
tools:
* name: getCustomerInfoByPhone
description: Get customer information based on phone number.
parameters:
schema: |-
{
"type": "object",
"properties": {
"phone": {"type": "string", "description": "Customer phone number."}
},
"required": \["phone"]
}
output:
schema: |-
{
"type": "object",
"properties": {
"customerCode": {"type": "string"},
"fullName": {"type": "string"},
"phoneNumber": {"type": "string"},
"address": {"type": "string"}
},
"required": \["customerCode","fullName","phoneNumber","address"]
}
execution:
actionMode: sequential
actions:
\- id: null
name: getCustomerInfoByPhone
condition: '${true}'
functionRef:
code: getCustomerInfo\_bankingApi
name: getCustomerInfo
description: null
asyncInvoke: false
type: rest
definition:
type: simple-rest
url: >-
method: GET
headers:
xp-api-key: >-
0123456789
queryParams:
phone: '${ .phone }'
body: null
auth: null
inputs:
\- name: phone
value: null
arguments:
phone: '${ $toolArguments.phone }'
metadata: null
* name: getAccountsByPhone
description: Get all accounts by customer phone number.
parameters:
schema: |-
{
"type": "object",
"properties": {
"phone": {"type": "string"}
},
"required": \["phone"]
}
output:
schema: |-
{
"type": "array",
"items": {
"type": "object",
"properties": {
"accountId": {"type": "string"},
"customerCode": {"type": "string"},
"balance": {"type": "number"}
},
"required": \["accountId", "customerCode", "balance"]
}
}
execution:
actionMode: sequential
actions:
\- id: null
name: getAccountsByPhone
condition: '${true}'
functionRef:
code: getAccountsByPhone\_bankingApi
name: getAccountsByPhone
description: null
asyncInvoke: false
type: rest
definition:
type: simple-rest
url: >-
method: GET
headers:
xp-api-key: >-
0123456789
queryParams:
phone: '${ .phone }'
body: null
auth: null
inputs:
\- name: phone
value: null
arguments:
phone: '${ $toolArguments.phone }'
metadata: null
* name: getLoansByCustomer
description: Get all loans by customer code.
parameters:
schema: |-
{
"type": "object",
"properties": {
"customerCode": {"type": "string"}
},
"required": \["customerCode"]
}
output:
schema: |-
{
"type": "array",
"items": {
"type": "object",
"properties": {
"loanId": {"type": "string"},
"customerCode": {"type": "string"},
"principal": {"type": "number"},
"interestRate": {"type": "number"},
"termMonths": {"type": "integer"},
"outstanding": {"type": "number"},
"createdDate": {"type": "string"}
},
"required": \["loanId", "customerCode", "principal", "interestRate", "termMonths", "outstanding", "createdDate"]
}
}
execution:
actionMode: sequential
actions:
\- id: null
name: getLoansByCustomer
condition: '${true}'
functionRef:
code: getLoansByCustomer\_bankingApi
name: getLoansByCustomer
description: null
asyncInvoke: false
type: rest
definition:
type: simple-rest
url: >-
method: GET
headers:
xp-api-key: >-
0123456789
queryParams:
customerCode: '${ .customerCode }'
body: null
auth: null
inputs:
\- name: customerCode
value: null
arguments:
customerCode: '${ $toolArguments.customerCode }'
metadata: null
* name: getLoanPayments
description: Get all payments for a loan.
parameters:
schema: |-
{
"type": "object",
"properties": {
"loanId": {"type": "string"}
},
"required": \["loanId"]
}
output:
schema: |-
{
"type": "array",
"items": {
"type": "object",
"properties": {
"paymentId": {"type": "string"},
"date": {"type": "string"},
"amount": {"type": "number"}
},
"required": \["paymentId", "date", "amount"]
}
}
execution:
actionMode: sequential
actions:
\- id: null
name: getLoanPayments
condition: '${true}'
functionRef:
code: getLoanPayments\_bankingApi
name: getLoanPayments
description: null
asyncInvoke: false
type: rest
definition:
type: simple-rest
url: >-
method: GET
headers:
xp-api-key: >-
0123456789
queryParams:
loanId: '${ .loanId }'
body: null
auth: null
inputs:
\- name: loanId
value: null
arguments:
loanId: '${ $toolArguments.loanId }'
metadata: null
output:
schema: >-
{"type":"object","properties":{"answer":{"type":"string"}},"required":\["answer"]}
streaming: false
voiceConfig:
allowInterruptions: false
tts:
provider: google
voice: vi-VN-Standard-A
apiKey: >-
instructions: >-
Speak in a friendly and professional manner. Use Vietnamese language
to communicate with the customer.
stt:
provider: groq
model: whisper-large-v3-turbo
language: vi
apiKey: '${ $SECRETS.GROQ\_API\_KEY }'
outboundConfig:
greetingInstructions: >-
Greet the customer then introduce yourself as a representative of
VietTrust Bank. Ask if they have time to talk. Use Vietnamese language
to communicate with the customer.
outboundTarget:
targetType: voice
targetAddress: '${ $OutboundCollectorAgent.returnValues.phoneNumber }'
targetName: '${ $OutboundCollectorAgent.returnValues.customerName }'
appCode: XCHATBOT
tenantCode: DEMO
| {
"states": \[
{
"name": "AgentSelector",
"agentName": "AgentSelector",
"type": "aiagent",
"agentType": "agent",
"aiModel": "llama3-70b-8192",
"systemMessage": "You are an assistant for selecting which tool is the most useful to use. \n\nBased on the tool's description, you have to return the name of the selected tool.",
"userMessage": "${ "User: " + .request.question }",
"output": "{\n "type": "object",\n "properties": {\n "selectedAgent": {\n "type": "string",\n "description": "The exact name of agent to be selected."\n }\n },\n "required": \[\n "selectedAgent"\n ]\n}",
"tools": \[
{
"name": "RAG\_REACT",
"description": "RAG\_REACT\[input]: This tool is great for answering questions about searching products information, pricing, \ndescription, give advise and others about querying data.",
"parameters": "{\n "type": "object",\n "properties": {\n "input": {\n "type": "string",\n "description": "The search query"\n }\n },\n "required": \["input"]\n}",
"output": "{\n "type": "object",\n "properties": {\n "answer": {\n "type": "string",\n "description": "The answer to the user question"\n },\n "images": {\n "type": "array",\n "description": "The list of images that related to the answer to be displayed to the user",\n "items": {\n "type": "string",\n "format": "uri"\n }\n }\n },\n "required": \["answer"]\n}"
},
{
"name": "TRANSACTION\_PROCESSING",
"description": "TRANSACTION\_PROCESSING\[request]: This tool is great for handle ordering, buying, booking products, payments, and others related to transactions request.",
"parameters": "{\n "type": "object",\n "properties": {\n "request": {\n "type": "string",\n "description": "The user request"\n }\n },\n "required": \["request"]\n}",
"output": "{\n "type": "object",\n "properties": {\n "answer": {\n "type": "string",\n "description": "The answer."\n }\n },\n "required": \[\n "answer"\n ]\n}"
}
],
"agentOutcomes": \[
{
"condition": "${ $agentOutcome.returnValues.selectedAgent == "RAG\_REACT" }",
"finish": true,
"transition": "RagAgent"
},
{
"condition": "${ $agentOutcome.returnValues.selectedAgent == "TRANSACTION\_PROCESSING" }",
"finish": true,
"transition": "ProductRetriver"
},
{
"condition": "${ true }",
"finish": true,
"transition": "RagAgent"
}
]
},
{
"name": "RagAgent",
"agentName": "RagAgent",
"type": "aiagent",
"agentType": "agent",
"aiModel": "gpt-4o",
"systemMessage": "You are an assistant for question-answering tasks. \nCorrect question to ensure the correctness of spelling and clarity of meaning in Vietnamese before answering. \nUse the following pieces of retrieved context to answer the question. \nIf you don't know the answer, just say that you don't know. \n\nQuestion: {question}\nContext: {context}\nAnswer:",
"userMessage": "${ .request.question }",
"output": "{\n "type": "object",\n "properties": {\n "answer": {\n "type": "string",\n "description": "The answer to the user question"\n },\n "images": {\n "type": "array",\n "description": "The list of images that related to the answer to be displayed to the user",\n "items": {\n "type": "object",\n "properties": {\n "url": {\n "type": "string",\n "format": "uri",\n "description": "The URL of the image"\n }\n }\n }\n }\n },\n "required": \["answer"]\n}",
"tools": \[
{
"name": "FIND\_RELEVANT\_DOCUMENTS",
"description": "FIND\_RELEVANT\_DOCUMENTS\[question]: This tool is great for searching relevant documents, articles in the knowledge base related to the user question",
"parameters": "{\n "type": "object",\n "properties": {\n "input": {\n "type": "string",\n "description": "The search query"\n }\n },\n "required": \["input"]\n}",
"output": "{\n "type": "object",\n "properties": {\n "documents": {\n "type": "array",\n "items": {\n "type": "string",\n "format": "uri"\n }\n }\n },\n "required": \["documents"]\n}",
"execution": {
"actionMode": "sequential",
"actions": \[
{
"name": "FindRelevantDocuments",
"functionRef": {
"refName": "FuncFindRelevantDocuments",
"arguments": {
"question": "${ .request.question }",
"actor": "${ .request.userContext }"
}
},
"actionDataFilter": {
"results": "${ { "documents": .data } }",
"toStateData": "${ .request }"
}
}
]
}
}
],
"agentOutcomes": \[
{
"condition": "${ true }",
"finish": true,
"transition": "InformRagResult"
}
]
}
]
}
|