Create Custom LLM Prompts

1
import requests
2
import time
3
4
base_url = "https://api.assemblyai.com"
5
6
headers = {
7
  "authorization": "<YOUR_API_KEY>"
8
}
9
10
# Step 1: Transcribe an audio file.
11
# You can use a local filepath:
12
# with open("./my-audio.mp3", "rb") as f:
13
# response = requests.post(base_url + "/v2/upload",
14
#                         headers=headers,
15
#                         data=f)
16
# upload_url = response.json()["upload_url"]
17
18
# Or use a publicly-accessible URL:
19
upload_url = "https://assembly.ai/call.mp4"
20
21
data = {
22
  "audio_url": upload_url
23
}
24
25
response = requests.post(base_url + "/v2/transcript", headers=headers, json=data)
26
27
transcript_id = response.json()["id"]
28
polling_endpoint = base_url + f"/v2/transcript/{transcript_id}"
29
30
while True:
31
  transcript = requests.get(polling_endpoint, headers=headers).json()
32
33
  if transcript["status"] == "completed":
34
    break
35
36
  elif transcript["status"] == "error":
37
    raise RuntimeError(f"Transcription failed: {transcript['error']}")
38
39
  else:
40
    time.sleep(3)
41
42
# Step 2: Define your prompt.
43
prompt = "What was the emotional sentiment of the phone call?"
44
45
# Step 3: Apply LeMUR.
46
lemur_data = {
47
  "prompt": prompt,
48
  "transcript_ids": [transcript_id],
49
  "final_model": "anthropic/claude-sonnet-4-20250514",
50
}
51
52
result = requests.post(base_url + "/lemur/v3/generate/task", headers=headers, json=lemur_data)
53
print(result.json()["response"])