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Last Updated: March 18, 2025
By using our integrated custom LLM prompts, you can generate an action items list from your transcribed meetings. To use
this, you just need to add the custom_prompt input parameter to your transcription request.
In this example, we’ll use a Python script to transcribe an audio file and tell it to use the custom_prompt input
parameter to generate the action items. We’ll use the following input parameters:
payload = {"input": {
"custom_prompt": "The following is a meeting transcription. Summarize internally, and then generate a list of action items from the meeting. Only use real actions that make sense to do, ignore anything unimportant. Rewrite each task to be more clear and concise. Format it in a markdown compatible list to make it easy to read.",
"url": audio_file_url,
"diarization": True,
"language_code": "en",
"return_as_file": False
}}
Python script
We’re going to create a file and name it action-items.py. We’re then going to use the above parameters in the
following Python script:
import requests
import time
audio_file_url = "url/to/audio/file.mp3" # replace with your audio file URL
salad_api_key = "YOUR_SALAD_API_KEY" # replace with your Salad API key
organization_name = "YOUR_ORGANIZATION_NAME" # replace with your organization name
payload = {"input": {
"custom_prompt": "The following is a meeting transcription. Summarize internally, and then generate a list of action items from the meeting. Only use real actions that make sense to do, ignore anything unimportant. Rewrite each task to be more clear and concise. Format it in a markdown compatible list to make it easy to read.",
"url": audio_file_url,
"diarization": True,
"language_code": "en",
"return_as_file": False
}}
headers = {
"Salad-Api-Key": salad_api_key,
"Content-Type": "application/json"
}
url = f"https://api.salad.com/api/public/organizations/{organization_name}/inference-endpoints/transcribe/jobs"
response = requests.post(url, json=payload, headers=headers)
response = response.json()
job_id=response["id"]
print (f'Job ID: {job_id}')
while True:
time.sleep(5)
try:
result = requests.get(f"{url}/{job_id}", headers=headers)
result = result.json()
if result["status"] == "created" or result["status"] == "pending" or result["status"] == "started" or result["status"] == "running":
print(f'Current job status is {result["status"]}')
elif result["status"] == "failed":
print(f'Job failed')
break
elif result["output"]:
print(result["output"]["llm_result"])
break
else:
print(f'Current job status is {result["status"]}')
except Exception as e:
print(f'Error retrieving transcription result: {e}')
break
- Make sure to replace
url/to/audio/file.mp3 with the URL of your audio file.
- Replace
YOUR_SALAD_API_KEY with
your Salad API key.
- Replace
YOUR_ORGANIZATION_NAME with your organization name.
- Run the script using with
python action-items.py.
In this script, we’re telling the LLM to read through the transcription, and generate a list of important action items.
We’re also asking it to format it to be easily readable in markdown format. It will be returned in the llm_result
field of the response. We’re then printing the result of this field to the console. Your console will look something
like this once it finishes:
Output
Job ID: abcdef6c-1234-41e8-b81b-ecc1109033ed
Current job status is running
Current job status is running
Current job status is running
Current job status is running
Current job status is running
Current job status is running
Current job status is running
Current job status is running
Current job status is running
The meeting discusses migrating to Salad Transcription API from our existing provider.
**Action Items:**
* Schedule a follow-up meeting to discuss transcription migration with the team
* Assign tasks to team members for the new project
* Test out the Salad Transcription API for the next meeting
* Set up billing for Salad
* Onboard Aardvark to the project
* Configure the new server