Quick Start for Communication Intelligence Engine

Request a number

Before connecting to the Communication Intelligence Engine, you must complete applications for voice qualifications and number resources. Voice number qualification applications, resource requests, and bill viewing are all managed in Voice Service.

1. Apply for voice qualifications: Go to the Voice Service console. In the navigation bar, choose Qualification and Script Management > Qualification Management and click Add New Qualification. Follow the instructions in Enterprise Qualification Management to fill in the required information and submit your application.

2. Apply for voice scripts: After your qualification is approved, in the navigation bar, choose Qualification and Script Management > Scenario & Script Management and click Add Script. Fill in the requested information and script content as prompted. Select Dedicated Mode for the business mode.

3. Apply for number resources: After your script is approved, in the navigation bar, choose Voice Numbers > Real Number Application and click Apply for Number. Request fixed-line and mobile phone numbers for the required regions based on your business needs.

   Note

   The monthly rental fee for a standard number is CNY 35 per month. Charges start in the month the number is activated. Partial months are billed as full months. You can also contact your account manager for fully managed service: Fully managed is a Voice Service feature that automatically applies for and replaces numbers based on your call volume to maintain high answer rates.

Configure an LLM

Create an LLM gateway

1. Go to the Artificial Intelligence Cloud Call Service console. In the navigation bar, choose LLM Communication > Communication Intelligence Engine > LLM Gateway Configuration and click Create LLM Gateway.

2. In the dialog box, enter model details. For example, if using Alibaba Cloud Model Studio:

   Note

   You can use Qwen-series models, open source models, or commercially mature third-party models. If building your own LLM, fine-tune it for your business scenario and configure prompts before connecting to the Communication Intelligence Engine. Your custom LLM must comply with the LLM Gateway Integration Parameter Protocol to connect.

   Configuration item	Description	Best practice setting
   Model name	Enter a custom name to distinguish this LLM gateway.	Test Gateway
   Model endpoint	Enter the LLM invocation endpoint. If using an Alibaba Cloud Model Studio model: https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions If using an Alibaba Cloud Model Studio application: Replace YOUR_APP_ID in https://dashscope.aliyuncs.com/api/v1/apps/YOUR_APP_ID/completion with your application ID	http://****
   Authorization code	API key for the LLM service. If using Alibaba Cloud Model Studio, go to the Alibaba Cloud Model Studio console to get your API key. If you don’t have one, click Create My API_KEY in the upper-right corner.	s*********************************1
   Model temperature	Sampling temperature that controls the diversity of generated text.	0.7 Note This is a recommended value.
   Model topP	Nucleus sampling probability threshold that controls the diversity of generated text.	0.9 Note This is a recommended value.
   Model topK	Size of the candidate set during generation.	50 Note This is a recommended value.
   Base model version	Model version passed as a parameter to the LLM. For Qwen models, versions include qwen-plus, qwen-turbo, and qwen-max. For more information, see Select a model. Note When using a Model Studio application, do not configure the base model version to avoid test errors.	qwen-plus

Test and publish the LLM gateway

After creating the gateway, test it before publishing for use by LLM applications.

1. Go to the Artificial Intelligence Cloud Call Service console. In the navigation bar, choose Communication Intelligence Engine > LLM Gateway Configuration. Find your gateway and click Test in the Actions column.

2. In the dialog box, enter test content and click Test to view results.

   Results appear in a table with three columns: Base Model Version, Connectivity Test Result, and Test Result, showing the model version used, whether connectivity passed, and the model’s response.

3. After a successful test, click Publish in the Actions column.

Create an LLM application

1. Go to the Artificial Intelligence Cloud Call Service console. In the navigation bar, choose LLM Communication > Communication Intelligence Engine > LLM Application Management and click Create LLM Application.

   Configuration item	Description	Example
   Application name	Enter a custom name.	Test Application
   Model name	Select a published LLM gateway.	-
   Base template	Select a base template.	-
   Maximum concurrency	Default is 10. Contact operations staff to adjust.	-
   Qualification	Select an approved qualification. View qualification details in Voice Service Qualification Management.	-
   Script	Select an approved script. View script details in Voice Service Script Management.	-
   Greeting	Text: Enter custom greeting text. Use variables in the format ${param}. Recording: Upload a greeting audio file in WAV format, up to 10 MB. Note To ensure natural-sounding voice, if you use a recording for the greeting, select a cloned voice matching that recording when choosing voice tone.	Text: Hello, are you ${param}?
   Prompt	Enter custom prompt text. Use variables in the format ${param}. Note A prompt is an instruction given to the LLM to tell it what you want it to do.	You are Xiao Mei, a professional Alibaba Cloud customer service agent handling pre-sales inquiries. Strictly follow these rules: 1. If the customer asks about ${problem}, direct them to view details in ${document}. 2. If the customer asks about ${other}, direct them to view details in ${answer}.
   Call voice tone	Choose a preset or custom voice tone. Adjust voice style, speed, and volume. Enter sample text to preview online.	-

2. Click Submit to finish adding the application.

Configure LLM application properties

1. Select your LLM application and click Conversation Properties in the Actions column.

2. In the dialog box, configure the following parameters:

   Configuration option	Description	Best practice setting
   Silence duration	Set the wait time before triggering the silence model when neither party speaks. Range: 3–15 seconds.	5
   Silence-triggered model	When the customer does not speak, the model application sends a fixed script to the LLM: User did not speak. Contact technical support for custom content. Values: Yes: Enable silence-triggered model. The model generates content when both parties are silent and pushes the silence event to your LLM. No: Disable silence-triggered model.	Yes
   Silence hangup configuration	Set the number of silence events that trigger automatic hangup. Range: 1–5 times.	3
   Intelligent Answering Detection	Enabled by default. Automatically detects voice assistants and voicemail. Returns LlmSmartCallReport—call record message and smart status code.	-
   Hang up immediately	When smart answering detects a voice assistant or voicemail, choose whether to end the call immediately. Default is No. Enable this option as needed.	-
   Maximum call duration	Range: 300–3600 seconds. The call ends automatically when the limit is reached.	-
   Morse code playback configuration	When enabled, play an AI-generated Morse code announcement after the conversation ends.	-
   Non-Disruptive Opening	When enabled, the LLM blocks all interruptions during the greeting period. Use this for critical announcements or identity verification to prevent early termination due to customer interjections or background noise. Options: Do not allow any interruption Do not allow interruption during greeting period	-
   Prevent repeated interruptions	If the number of interruptions exceeds the threshold, the Large Language Model (LLM) ignores interruptions for the configured duration, forces completion of its response, and ensures smooth conversation flow. Configurable: Interruptions are not allowed for X seconds after X consecutive interruptions.	-
   Interruption filler words	When enabled, the LLM responds with natural filler words like “Go ahead” or “Hmm” before yielding the floor to the customer. This reduces robotic feel and improves conversational flow.	-

3. Click OK to finish configuration.

Step 3: Associate Xiaoji Agent configuration (optional)

Prerequisites: You have created a Xiaoji Agent. See Xiaoji Agent.

1. Go to the Artificial Intelligence Cloud Call Service console. In the navigation bar, choose LLM Communication > Communication Intelligence Engine > LLM Application Management.

2. Find your application and click Xiaoji Agent Configuration in the Actions column.

3. Set Associate Xiaoji Agent to Yes and select the corresponding Xiaoji Agent.

   Associating a Xiaoji Agent incurs additional fees. See Billing Details for pricing. If you don’t have a suitable Xiaoji Agent, click Create Xiaoji Agent to create one.

Step 4: Configure message receipts (optional)

1. Go to the Artificial Intelligence Cloud Call Service console. In the navigation bar, choose LLM Communication > Communication Intelligence Engine > Message Receipt Configuration.

2. On the Message Receipt Configuration tab, find your desired message type, enable the corresponding toggle, and complete setup.

   Message queue consumption mode

   1. Enable the toggle next to General Queue.

      After enabling, Default Queue shows the queue name (for example, Alicom-Queue-18...-LlmSmartCallReport). Retrieve message receipts from this default queue. Keep Application-Specific Queue disabled.

   2. After configuration, pull messages using the queue name. For a consumption demo, see Lightweight Message Queue (formerly MNS) Consumption Demo.

   HTTP batch push mode

   1. Enable the toggle next to Message Receiving URL.

   2. Enter your message receipt receiving URL in the input field. The system sends messages to this URL via HTTP requests. Ensure your endpoint returns HTTP status code 200.

      For example, enter https://push.example.com/contextpath/receive.do. On successful test, the response is {"code": 0, "msg": "Success"}. To configure different URLs for different applications, enable the Application-Specific URL toggle.