Summarization

Supported regions

US & EU

Generate summaries of your audio transcripts using LLM Gateway. This approach gives you full control over the summary format, length, and style by customizing your prompt.

The summarization, summary_model, and summary_type parameters on the transcription API are deprecated. Use LLM Gateway as shown below for more flexible and powerful summaries.

Quickstart

Python

JavaScript

1 import requests
2 import time
3 
4 base_url = "https://api.assemblyai.com"
5 headers = {"authorization": "<YOUR_API_KEY>"}
6 
7 # Step 1: Transcribe your audio file
8 audio_url = "https://assembly.ai/wildfires.mp3"
9 
10 data = {
11     "audio_url": audio_url,
12     "speech_models": ["universal-3-pro", "universal-2"],
13     "language_detection": True
14 }
15 
16 response = requests.post(base_url + "/v2/transcript", json=data, headers=headers)
17 transcript_id = response.json()['id']
18 polling_endpoint = base_url + "/v2/transcript/" + transcript_id
19 
20 while True:
21     transcription_result = requests.get(polling_endpoint, headers=headers).json()
22     if transcription_result['status'] == 'completed':
23         break
24     elif transcription_result['status'] == 'error':
25         raise RuntimeError(f"Transcription failed: {transcription_result['error']}")
26     else:
27         time.sleep(3)
28 
29 # Step 2: Generate a summary using LLM Gateway
30 prompt = "Provide a brief summary of the transcript in bullet point format."
31 
32 llm_gateway_data = {
33     "model": "claude-sonnet-4-6",
34     "messages": [
35         {"role": "user", "content": f"{prompt}\n\nTranscript: {transcription_result['text']}"}
36     ],
37     "max_tokens": 1000
38 }
39 
40 response = requests.post(
41     "https://llm-gateway.assemblyai.com/v1/chat/completions",
42     headers=headers,
43     json=llm_gateway_data
44 )
45 
46 result = response.json()["choices"][0]["message"]["content"]
47 print(result)

Example output

1 - Smoke from hundreds of wildfires in Canada is triggering air quality alerts throughout the US, with skylines from Maine to Maryland to Minnesota appearing gray and smoggy.
2 - Air pollution levels in Baltimore are considered unhealthy, with exposure to high levels leading to various health problems.
3 - With climate change driving more wildfires, experts warn that wide-ranging air quality consequences may become more frequent.

Customize your summary

You can control the summary output by adjusting the prompt. Here are some examples:

Bullet point summary

1 prompt = """Provide a brief summary of the transcript in bullet point format.
2 Focus on the key points and main takeaways."""

Paragraph summary

1 prompt = """Provide a concise paragraph summary of the transcript.
2 Capture the main topics and conclusions."""

Headline summary

1 prompt = """Provide a single sentence headline that captures the main topic
2 of the transcript."""

Conversational summary

1 prompt = """Summarize this conversation between multiple speakers.
2 Include who said what and the key points each speaker made."""

Custom format

You can define any format you need:

1 prompt = """Summarize the transcript using the following format:
2 - Topic: [main topic]
3 - Key Points: [list of 3-5 key points]
4 - Action Items: [any action items mentioned]
5 - Conclusion: [one sentence conclusion]"""

API reference

Step 1: Transcribe audio

$ curl https://api.assemblyai.com/v2/transcript \
> --header "Authorization: <YOUR_API_KEY>" \
> --header "Content-Type: application/json" \
> --data '{
>   "audio_url": "YOUR_AUDIO_URL"
> }'

Poll for the transcript result until the status is completed, then extract the transcript text.

Step 2: Generate summary with LLM Gateway

$ curl https://llm-gateway.assemblyai.com/v1/chat/completions \
> --header "Authorization: <YOUR_API_KEY>" \
> --header "Content-Type: application/json" \
> --data '{
>   "model": "claude-sonnet-4-6",
>   "messages": [
>     {"role": "user", "content": "Provide a brief summary of the transcript.\n\nTranscript: YOUR_TRANSCRIPT_TEXT"}
>   ],
>   "max_tokens": 1000
> }'

Key	Type	Description
`model`	string	The LLM model to use. See available models.
`messages`	array	The messages to send to the model, including your summarization prompt and transcript text.
`max_tokens`	number	Maximum number of tokens in the response. Adjust based on desired summary length.

Response

1 {
2   "choices": [
3     {
4       "message": {
5         "content": "Your generated summary text..."
6       }
7     }
8   ]
9 }

Next steps

LLM Gateway Overview - Learn more about available models and features
Apply LLM Gateway to pre-recorded audio - General guide for using LLM Gateway with transcripts
Basic Chat Completions - Learn more about the chat completions API
Structured Outputs - Constrain responses to a specific JSON schema

Supported regions

US & EU

Generate summaries of your audio transcripts using LLM Gateway. This approach gives you full control over the summary format, length, and style by customizing your prompt.

The summarization, summary_model, and summary_type parameters on the transcription API are deprecated. Use LLM Gateway as shown below for more flexible and powerful summaries.

Quickstart

Python

JavaScript

1 import requests
2 import time
3 
4 base_url = "https://api.assemblyai.com"
5 headers = {"authorization": "<YOUR_API_KEY>"}
6 
7 # Step 1: Transcribe your audio file
8 audio_url = "https://assembly.ai/wildfires.mp3"
9 
10 data = {
11     "audio_url": audio_url,
12     "speech_models": ["universal-3-pro", "universal-2"],
13     "language_detection": True
14 }
15 
16 response = requests.post(base_url + "/v2/transcript", json=data, headers=headers)
17 transcript_id = response.json()['id']
18 polling_endpoint = base_url + "/v2/transcript/" + transcript_id
19 
20 while True:
21     transcription_result = requests.get(polling_endpoint, headers=headers).json()
22     if transcription_result['status'] == 'completed':
23         break
24     elif transcription_result['status'] == 'error':
25         raise RuntimeError(f"Transcription failed: {transcription_result['error']}")
26     else:
27         time.sleep(3)
28 
29 # Step 2: Generate a summary using LLM Gateway
30 prompt = "Provide a brief summary of the transcript in bullet point format."
31 
32 llm_gateway_data = {
33     "model": "claude-sonnet-4-6",
34     "messages": [
35         {"role": "user", "content": f"{prompt}\n\nTranscript: {transcription_result['text']}"}
36     ],
37     "max_tokens": 1000
38 }
39 
40 response = requests.post(
41     "https://llm-gateway.assemblyai.com/v1/chat/completions",
42     headers=headers,
43     json=llm_gateway_data
44 )
45 
46 result = response.json()["choices"][0]["message"]["content"]
47 print(result)

Example output

1 - Smoke from hundreds of wildfires in Canada is triggering air quality alerts throughout the US, with skylines from Maine to Maryland to Minnesota appearing gray and smoggy.
2 - Air pollution levels in Baltimore are considered unhealthy, with exposure to high levels leading to various health problems.
3 - With climate change driving more wildfires, experts warn that wide-ranging air quality consequences may become more frequent.

Customize your summary

You can control the summary output by adjusting the prompt. Here are some examples:

Bullet point summary

1 prompt = """Provide a brief summary of the transcript in bullet point format.
2 Focus on the key points and main takeaways."""

Paragraph summary

1 prompt = """Provide a concise paragraph summary of the transcript.
2 Capture the main topics and conclusions."""

Headline summary

1 prompt = """Provide a single sentence headline that captures the main topic
2 of the transcript."""

Conversational summary

1 prompt = """Summarize this conversation between multiple speakers.
2 Include who said what and the key points each speaker made."""

Custom format

You can define any format you need:

1 prompt = """Summarize the transcript using the following format:
2 - Topic: [main topic]
3 - Key Points: [list of 3-5 key points]
4 - Action Items: [any action items mentioned]
5 - Conclusion: [one sentence conclusion]"""

API reference

Step 1: Transcribe audio

$ curl https://api.assemblyai.com/v2/transcript \
> --header "Authorization: <YOUR_API_KEY>" \
> --header "Content-Type: application/json" \
> --data '{
>   "audio_url": "YOUR_AUDIO_URL"
> }'

Poll for the transcript result until the status is completed, then extract the transcript text.

Step 2: Generate summary with LLM Gateway

$ curl https://llm-gateway.assemblyai.com/v1/chat/completions \
> --header "Authorization: <YOUR_API_KEY>" \
> --header "Content-Type: application/json" \
> --data '{
>   "model": "claude-sonnet-4-6",
>   "messages": [
>     {"role": "user", "content": "Provide a brief summary of the transcript.\n\nTranscript: YOUR_TRANSCRIPT_TEXT"}
>   ],
>   "max_tokens": 1000
> }'

Key	Type	Description
`model`	string	The LLM model to use. See available models.
`messages`	array	The messages to send to the model, including your summarization prompt and transcript text.
`max_tokens`	number	Maximum number of tokens in the response. Adjust based on desired summary length.

Response

1 {
2   "choices": [
3     {
4       "message": {
5         "content": "Your generated summary text..."
6       }
7     }
8   ]
9 }

Next steps

LLM Gateway Overview - Learn more about available models and features
Apply LLM Gateway to pre-recorded audio - General guide for using LLM Gateway with transcripts
Basic Chat Completions - Learn more about the chat completions API
Structured Outputs - Constrain responses to a specific JSON schema

1	import requests
2	import time
3
4	base_url = "https://api.assemblyai.com"
5	headers = {"authorization": "<YOUR_API_KEY>"}
6
7	# Step 1: Transcribe your audio file
8	audio_url = "https://assembly.ai/wildfires.mp3"
9
10	data = {
11	"audio_url": audio_url,
12	"speech_models": ["universal-3-pro", "universal-2"],
13	"language_detection": True
14	}
15
16	response = requests.post(base_url + "/v2/transcript", json=data, headers=headers)
17	transcript_id = response.json()['id']
18	polling_endpoint = base_url + "/v2/transcript/" + transcript_id
19
20	while True:
21	transcription_result = requests.get(polling_endpoint, headers=headers).json()
22	if transcription_result['status'] == 'completed':
23	break
24	elif transcription_result['status'] == 'error':
25	raise RuntimeError(f"Transcription failed: {transcription_result['error']}")
26	else:
27	time.sleep(3)
28
29	# Step 2: Generate a summary using LLM Gateway
30	prompt = "Provide a brief summary of the transcript in bullet point format."
31
32	llm_gateway_data = {
33	"model": "claude-sonnet-4-6",
34	"messages": [
35	{"role": "user", "content": f"{prompt}\n\nTranscript: {transcription_result['text']}"}
36	],
37	"max_tokens": 1000
38	}
39
40	response = requests.post(
41	"https://llm-gateway.assemblyai.com/v1/chat/completions",
42	headers=headers,
43	json=llm_gateway_data
44	)
45
46	result = response.json()["choices"][0]["message"]["content"]
47	print(result)

1	- Smoke from hundreds of wildfires in Canada is triggering air quality alerts throughout the US, with skylines from Maine to Maryland to Minnesota appearing gray and smoggy.
2	- Air pollution levels in Baltimore are considered unhealthy, with exposure to high levels leading to various health problems.
3	- With climate change driving more wildfires, experts warn that wide-ranging air quality consequences may become more frequent.

1	prompt = """Provide a brief summary of the transcript in bullet point format.
2	Focus on the key points and main takeaways."""

1	prompt = """Provide a concise paragraph summary of the transcript.
2	Capture the main topics and conclusions."""

1	prompt = """Provide a single sentence headline that captures the main topic
2	of the transcript."""

1	prompt = """Summarize this conversation between multiple speakers.
2	Include who said what and the key points each speaker made."""

1	prompt = """Summarize the transcript using the following format:
2	- Topic: [main topic]
3	- Key Points: [list of 3-5 key points]
4	- Action Items: [any action items mentioned]
5	- Conclusion: [one sentence conclusion]"""

$	curl https://api.assemblyai.com/v2/transcript \
>	--header "Authorization: <YOUR_API_KEY>" \
>	--header "Content-Type: application/json" \
>	--data '{
>	"audio_url": "YOUR_AUDIO_URL"
>	}'

$	curl https://llm-gateway.assemblyai.com/v1/chat/completions \
>	--header "Authorization: <YOUR_API_KEY>" \
>	--header "Content-Type: application/json" \
>	--data '{
>	"model": "claude-sonnet-4-6",
>	"messages": [
>	{"role": "user", "content": "Provide a brief summary of the transcript.\n\nTranscript: YOUR_TRANSCRIPT_TEXT"}
>	],
>	"max_tokens": 1000
>	}'

1	{
2	"choices": [
3	{
4	"message": {
5	"content": "Your generated summary text..."
6	}
7	}
8	]
9	}