Topic Detection
Topic Detection detects topics throughout the input text.
topics
boolean   Default: false
Try this feature out in our API Playground!
Topic Detection accepts an input text, divides it into a list of segments comprised of sections of the text, and identifies key topics found within each segment.
"results": {
"topics": {
"segments": [
{
"text": "Hi I'm calling to get a refund on my recent purchase. Sure I'd be happy to help you with that. What was the number for you order?",
"start_word": 0,
"end_word": 26,
"topics": [
{ "topic": "Refund", "confidence_score": 0.91318 },
{ "topic": "Order Number", "confidence_score": 0.95342 }
]
},
{
"text": "Ok thanks for that. It looks like you made this purchase online, is that correct? Yes I ordered this online on your website a few days ago.",
"start_word": 45,
"end_word": 72,
"topics": [
{
"topic": "Online Transacation", "confidence_score": 0.741929
}
]
}
]
}
}
The list of topics that can be identified are not a fixed list; this TSLM powered feature is able to generate topics based on the context of the language content in the text. You may also choose to use the optional custom-topic
parameter to provide a custom topic you want detected if present within the provided text.
Enable Feature
To enable Topic Detection, use the following parameter in the query string when you call Deepgram’s /read
endpoint:
topics=true
Basic Text Request
To analyze text from a file on your computer, run the following curl command in a terminal or your favorite API client.
curl -vX POST \
-H "Authorization: Token YOUR_DEEPGRAM_API_KEY" \
-H "Content-Type: application/json" \
-d '{"text": "YOUR_TEXT_INPUT"}' \
"https://api.deepgram.com/v1/read?topics=true&language=en"
Replace
YOUR_DEEPGRAM_API_KEY
with your Deepgram API Key.
Basic URL Request
To analyze text from a hosted file, run the following curl command in a terminal or your favorite API client. (Try testing it out with the hosted file https://static.deepgram.com/examples/aura.txt)
Custom Topics Request
To tell the model to only return topics from your own custom list of topics, add custom_topic_mode=strict
and custom_topic=
followed by the list of topics. (Use the URL encoding%20
to represent a space between each word in the list.)
If you want to return your own custom list of topics in addition to Deegpram's list of topics, set custom_intent_mode=extended
and add your custom list.
curl -vX POST \
-H "Authorization: Token YOUR_DEEPGRAM_API_KEY" \
-H "Content-Type: application/json" \
-d '{"text": "YOUR_TEXT_INPUT"}' \
"https://api.deepgram.com/v1/read?topics=true&language=en&custom_topic_mode=strict&custom_topic=refund&custom_topic=online_transaction&custom_topic=Order%20Number"
Read our Text Intelligence Getting Started guide, which will walk you through making a basic text request and a basic URL request with the Deepgram SDKs.
Query Parameters
Parameter | Value | Type | Description |
---|---|---|---|
topics | true | boolean | Enables Topic Detection |
language | en | string | The language of your input text (Only English is supported at this time.) |
custom_topic | ex: animals | string | Optional. A custom topic you want the model to detect within your input text if present. Submit up to 100. |
custom_topic_mode | extended , strict | string | Optional. Sets how the model will interpret strings submitted to the custom_topic param. When strict , the model will only return topics submitted using the custom_topic param. When extended , the model will return its own detected topics in addition to those submitted using the custom_topic param. |
Analyze Response
When the file is finished processing, you’ll receive a JSON response that has the following basic structure:
{
"metadata": {
"request_id": "c313ae16-2c3b-4c51-87a6-920a8aa1d899",
"created": "2023-11-28T01:44:27.083Z",
"language": "en",
"topics_info": {
"model_uuid": "ba5b22e4-b39a-4550-a4bc-d8655f5092bc",
"input_tokens": 22,
"output_tokens": 4
}
},
"results": {
"topics": {
"segments": [
{
"text": "Hi I'm calling to get a refund on my recent purchase. Sure I'd be happy to help you with that. What was the number for you order?",
"start_word": 0,
"end_word": 26,
"topics": [
{ "topic": "Refund", "confidence_score": 0.91318 },
{ "topic": "Order Number", "confidence_score": 0.95342 }
]
},
{
"text": "Ok thanks for that. It looks like you made this purchase online, is that correct? Yes I ordered this online on your website a few days ago.",
"start_word": 45,
"end_word": 72,
"topics": [{ "topic": "Online Transacation", "confidence_score": 0.741929 }]
}
]
}
}
}
Use the API reference or the API Playground to view the detailed response.
The response object values for topics
are:
segments
: The list of segments of text identified by the model as containing notable topics.topic
: The name of the topic detected by the model.confidence_score
: a floating point from 0 to 1 representing the models confidence in this prediction.
API Error Responses
Unsupported Language
Status 400
If you request Topic Detection with an unsupported language by specifying a language code such as topics=true&language=es
or topics=true&detect_language=true
where the detected language is unsupported, you will get the error message below.
{
"err_code":"INVALID_QUERY_PARAMETER",
"err_msg":"Request specified unsupported language: <language_name>. Only English is supported.",
"request_id":"XXXX"
}
Token Limit Exceeded
Status 400
If the request's input length exceeded the 150k token rate limit per request, you will get the error message below.
{
"err_code": "TOKEN_LIMIT_EXCEEDED",
"err_msg": "Text input for <api_name> currently supports up to 150K tokens. Please revise your text input to fit within the defined token limit. For more information, please visit our API documentation.",
"request_id": "XXXX"
}
Missing Query Parameter
Status 400
If the request sent contained only the feature parameter (topics
) but not the language
parameter, you will receive this error.
{
"err_code":"INVALID_QUERY_PARAMETER",
"err_msg":"Failed to deserialize query parameters: missing field `language`",
"request_id":"XXX"
}
Updated 7 months ago