How to Automatically Follow Sales Playbooks with Salad Transcription API - SaladCloud

Last Updated: March 28, 2025 By using our integrated custom LLM prompts, you can automatically follow a Sales Playbook from your transcribed meetings and sales calls to help meet your KPIs. To use this, you just need to add the custom_prompt input parameter to your transcription request.

Custom input parameters

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 answer questions in our mock playbook. We’ll use the following input parameters:

payload = {"input": {
        "custom_prompt": "The following is a sales call transcription. Follow the playbook and answer the questions. If there are no answers, say 'No answer'. Question 1: Did the sales person get the customers name? Question 2: Did the sales person correctly understand the customers requirements? Question 3: Did the sales person ask for the customer's pain point with their existing providor? Question 4: How well and precisely did the sales person answer questions posed by the customer? Question 5: Did the sales person ask the customer how the call went?",
        "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 playbook.py. We’re then going to use the above parameters in the following Python script:

import requests
import time

audio_file_url = "https://your-storage.com/path/to/audio.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 sales call transcription. Follow the playbook and answer the questions. If there are no answers, say 'No answer'. Question 1: Did the sales person get the customers name? Question 2: Did the sales person correctly understand the customers requirements? Question 3: Did the sales person ask for the customer's pain point with their existing provider? Question 4: How well and precisely did the sales person answer questions posed by the customer? Question 5: Did the sales person ask the customer how the call went?",
        "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 https://your-storage.com/path/to/audio.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.
Modify the questions in the custom_prompt parameter to match your playbook.
Run the script using python playbook.py.

In this script, we’re telling the LLM to answer our questions and fill in the sales playbook. 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
Transcription Result: Question 1: Did the sales person get the customer's name?
Yes.

Question 2: Did the sales person correctly understand the customer's requirements?
Yes.

Question 3: Did the sales person ask for the customer's pain point with their existing provider?
No.

Question 4: How well and precisely did the sales person answer questions posed by the customer?
Good, provided relevant information about NVIDIA 50 series controversy.

Question 5: Did the sales person ask the customer how the call went?
No.

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