///## Identity
You are a [role description]
Your expertise includes [relevant domains from your knowledge base]

///## Style Guardrails
Be concise: Keep responses under 2 sentences unless explaining complex topics.
Be conversational: Use natural language and contractions.

///## Tool Usage Instructions
[Explicit instructions for when to use each skill/function]

///## Response Guidelines
[How to handle information from knowledge base]

///## Tool Usage Instructions
1. Gather initial information about the user's request.
2. Determine the type of request:
 - If user mentions [specific keywords]:
   → Call function `skill_name_1` immediately
 - If user needs [specific capability]:
   → Call function `skill_name_2` with [parameters]
3. After retrieving information:
 - Always summarize what you found
 - Ask if they need additional help

Only answer using the information in ## Related Knowledge Base Contexts.
If ## Related Knowledge Base Contexts is missing or does not contain relevant information, respond:
"There is no related information in knowledge base."

call_analyzed

json
{
  "event": "call_analyzed",
  "call": {
    "call_id": "123",
    "transcript": "...",
    "transcript_object": [...],
    "transcript_with_tool_calls": [...],
    "call_analysis": {
      // Analysis results
    }
  }
}

transcript_updated

transcript_with_tool_calls

json
{
  "call_id": "123",
  "transcript": "...",
  "transcript_object": [...],
  "transcript_with_tool_calls": [...],
  "call_analysis": {
    // Analysis results
  }
}

python
from flask import Flask, request
from retell import Retell
import os

app = Flask(__name__)

@app.route("/webhook", methods=["POST"])
def webhook() :
    raw_body = request.get_data(as_text=True)
    
    if not Retell.verify(
        raw_body,
        os.environ.get("RETELL_API_KEY") ,
        request.headers.get("x-retell-signature")
    ) :
        print("Invalid signature")
        return "", 403
    
    data = request.get_json()
    event = data.get("event")
    call = data.get("call")
    
    if event == "call_analyzed":
        print(f"Call analyzed: {call.get('call_id') }")
        transcript = call.get("transcript")
        transcript_object = call.get("transcript_object")
        transcript_with_tool_calls = call.get("transcript_with_tool_calls")
        
        # Save transcript to file or database
        with open(f"{call.get('call_id') }_transcript.txt", "w") as f:
            f.write(transcript)
    
    return "", 204

if __name__ == "__main__":
    app.run(port=5000)

python
from retell import Retell
import os

client = Retell(api_key=os.environ.get("RETELL_API_KEY") )

call_response = client.call.retrieve("119c3f8e47135a29e65947eeb34cf12d")

transcript = call_response.transcript
transcript_object = call_response.transcript_object
transcript_with_tool_calls = call_response.transcript_with_tool_calls

print(transcript)

pip install flask retell-sdk

transcript

transcript_object

transcript_with_tool_calls

call_analyzed

bash
pip install retell-sdk

python
# Installation: pip install retell-sdk

from retell import Retell
import os

client = Retell(api_key=os.environ.get("RETELL_API_KEY") )

call_response = client.call.retrieve("119c3f8e47135a29e65947eeb34cf12d")

transcript = call_response.transcript
transcript_object = call_response.transcript_object
transcript_with_tool_calls = call_response.transcript_with_tool_calls

print(transcript)

bash
pip install flask retell-sdk

RETELL_API_KEY

python
# Installation: pip install retell-sdk

from retell import Retell
import os

# Option 1: Set environment variable (recommended)
# In your terminal or Replit Secrets: RETELL_API_KEY=your_api_key_here

# Option 2: Pass directly to client (less secure)
client = Retell(api_key="your_api_key_here")

# Or use environment variable
client = Retell(api_key=os.environ.get("RETELL_API_KEY") )

call_response = client.call.retrieve("119c3f8e47135a29e65947eeb34cf12d")

transcript = call_response.transcript
print(transcript)

RETELL_API_KEY

python
# Installation: pip install retell-sdk pandas

from retell import Retell
import os
import csv
import pandas as pd
from datetime import datetime

client = Retell(api_key=os.environ.get("RETELL_API_KEY") )

call_response = client.call.retrieve("119c3f8e47135a29e65947eeb34cf12d")

# Extract data with timestamps
call_id = call_response.call_id
start_timestamp = call_response.start_timestamp
end_timestamp = call_response.end_timestamp
duration_ms = call_response.duration_ms
transcript = call_response.transcript
transcript_object = call_response.transcript_object

# Print transcript with timestamps
print(f"Call ID: {call_id}")
print(f"Start: {datetime.fromtimestamp(start_timestamp/1000) }")
print(f"End: {datetime.fromtimestamp(end_timestamp/1000) }")
print(f"Duration: {duration_ms}ms")
print(f"\nTranscript:\n{transcript}")

# Option 1: Save as CSV using pandas
def save_to_csv_pandas(call_data, filename="call_transcript.csv") :
    df = pd.DataFrame([{
        "call_id": call_data.call_id,
        "start_timestamp": call_data.start_timestamp,
        "end_timestamp": call_data.end_timestamp,
        "duration_ms": call_data.duration_ms,
        "transcript": call_data.transcript
    }])
    df.to_csv(filename, index=False)
    print(f"Saved to {filename}")

# Option 2: Save as CSV using csv module
def save_to_csv_basic(call_data, filename="call_transcript.csv") :
    with open(filename, 'w', newline='', encoding='utf-8') as f:
        writer = csv.writer(f)
        writer.writerow(["call_id", "start_timestamp", "end_timestamp", "duration_ms", "transcript"])
        writer.writerow([
            call_data.call_id,
            call_data.start_timestamp,
            call_data.end_timestamp,
            call_data.duration_ms,
            call_data.transcript
        ])
    print(f"Saved to {filename}")

# Choose your preferred method
save_to_csv_pandas(call_response

)
# OR
# save_to_csv_basic(call_response)

start_timestamp

end_timestamp

duration_ms

transcript_object

python
# Save detailed transcript with word timestamps
def save_detailed_transcript_csv(call_data, filename="detailed_transcript.csv") :
    rows = []
    for utterance in call_data.transcript_object:
        for word_data in utterance.get("words", []) :
            rows.append({
                "call_id": call_data.call_id,
                "role": utterance.get("role") ,
                "word": word_data.get("word") ,
                "start": word_data.get("start") ,
                "end": word_data.get("end")
            })
    
    df = pd.DataFrame(rows)
    df.to_csv(filename, index=False)
    print(f"Saved detailed transcript to {filename}")

save_detailed_transcript_csv(call_response)

bash
pip install retell-sdk pandas

os.environ.get("xxxx")

None

RETELL_API_KEY

python
# Installation: pip install retell-sdk pandas

from retell import Retell
import os
import csv
import pandas as pd
from datetime import datetime

# Option 1: Use environment variable (recommended)
# Set RETELL_API_KEY in your environment first
client = Retell(api_key=os.environ.get("RETELL_API_KEY") )

# Option 2: Pass API key directly (replace with your actual key)
# client = Retell(api_key="your_actual_retell_api_key_here")

# Replace with your actual call ID
call_response = client.call.retrieve("your_actual_call_id_here")

# Extract data with timestamps
call_id = call_response.call_id
start_timestamp = call_response.start_timestamp
end_timestamp = call_response.end_timestamp
duration_ms = call_response.duration_ms
transcript = call_response.transcript
transcript_object = call_response.transcript_object

# Print transcript with timestamps
print(f"Call ID: {call_id}")
print(f"Start: {datetime.fromtimestamp(start_timestamp/1000) }")
print(f"End: {datetime.fromtimestamp(end_timestamp/1000) }")
print(f"Duration: {duration_ms}ms")
print(f"\nTranscript:\n{transcript}")

# Option 1: Save as CSV using pandas
def save_to_csv_pandas(call_data, filename="call_transcript.csv") :
    df = pd.DataFrame([{
        "call_id": call_data.call_id,
        "start_timestamp": call_data.start_timestamp,
        "end_timestamp": call_data.end_timestamp,
        "duration_ms": call_data.duration_ms,
        "transcript": call_data.transcript
    }])
    df.to_csv(filename, index=False)
    print(f"Saved to {filename}")

# Option 2: Save as CSV using csv module
def save_to_csv_basic(call_data, filename="call_transcript.csv") :
    with open(filename, 'w', newline='', encoding='utf-8') as f:
        writer = csv.writer(f)
        writer.writerow(["call_id", "start_timestamp", "end_timestamp", "duration_ms", "transcript"])
        writer.writerow([
            call_data.call_id,

call_data.start_timestamp,
            call_data.end_timestamp,
            call_data.duration_ms,
            call_data.transcript
        ])
    print(f"Saved to {filename}")

# Save detailed transcript with word timestamps
def save_detailed_transcript_csv(call_data, filename="detailed_transcript.csv") :
    rows = []
    for utterance in call_data.transcript_object:
        for word_data in utterance.get("words", []) :
            rows.append({
                "call_id": call_data.call_id,
                "role": utterance.get("role") ,
                "word": word_data.get("word") ,
                "start": word_data.get("start") ,
                "end": word_data.get("end")
            })
    
    df = pd.DataFrame(rows)
    df.to_csv(filename, index=False)
    print(f"Saved detailed transcript to {filename}")

# Choose your preferred method
save_to_csv_pandas(call_response)
# OR
# save_to_csv_basic(call_response)
# OR
# save_detailed_transcript_csv(call_response)

export RETELL_API_KEY=your_actual_api_key

RETELL_API_KEY

client = Retell(api_key=os.environ.get("RETELL_API_KEY") )

client = Retell(api_key="your_actual_retell_api_key_here")

"your_actual_call_id_here"

ve_dialogue_transcript_csv(call_response, call_start_time)

python
# Installation: pip install retell-sdk pandas

from retell import Retell
import os
import pandas as pd
from datetime import datetime, timedelta

client = Retell(api_key=os.environ.get("RETELL_API_KEY") )

call_response = client.call.retrieve("your_actual_call_id_here")

# Extract call metadata
call_id = call_response.call_id
start_timestamp = call_response.start_timestamp  # milliseconds since epoch
transcript_object = call_response.transcript_object

# Convert start timestamp to datetime
call_start_time = datetime.fromtimestamp(start_timestamp / 1000)

# Save dialogue-level transcript with accurate timestamps
def save_dialogue_transcript_csv(call_data, call_start, filename="dialogue_transcript.csv") :
    rows = []
    
    for utterance in call_data.transcript_object:
        role = utterance.get("role")
        content = utterance.get("content")
        words = utterance.get("words", [])
        
        # Get first word's start time (seconds from call start)
        if words:
            utterance_start_sec = words[0].get("start")
            utterance_end_sec = words[-1].get("end")
            
            # Calculate absolute timestamp
            absolute_start = call_start + timedelta(seconds=utterance_start_sec)
            absolute_end = call_start + timedelta(seconds=utterance_end_sec)
            
            rows.append({
                "call_id": call_data.call_id,
                "role": role,
                "content": content,
                "start_seconds_from_call_start": utterance_start_sec,
                "end_seconds_from_call_start": utterance_end_sec,
                "absolute_start_timestamp": absolute_start.isoformat() ,
                "absolute_end_timestamp": absolute_end.isoformat()
            })
    
    df = pd.DataFrame(rows)
    df.to_csv(filename, index=False)
    print(f"Saved dialogue transcript to {filename}")

sa

transcript_object

start

end

start_timestamp

transcript_object

.get()

python
# Installation: pip install retell-sdk pandas

from retell import Retell
import os
import pandas as pd
from datetime import datetime, timedelta

client = Retell(api_key=os.environ.get("RETELL_API_KEY") )

call_response = client.call.retrieve("your_actual_call_id_here")

# Extract call metadata
call_id = call_response.call_id
start_timestamp = call_response.start_timestamp  # milliseconds since epoch
transcript_object = call_response.transcript_object

# Convert start timestamp to datetime
call_start_time = datetime.fromtimestamp(start_timestamp / 1000)

# Save dialogue-level transcript with accurate timestamps
def save_dialogue_transcript_csv(call_data, call_start, filename="dialogue_transcript.csv") :
    rows = []
    
    for utterance in call_data.transcript_object:
        role = utterance.role
        content = utterance.content
        words = utterance.words if hasattr(utterance, 'words') else []
        
        # Get first word's start time (seconds from call start)
        if words:
            utterance_start_sec = words[0].start
            utterance_end_sec = words[-1].end
            
            # Calculate absolute timestamp
            absolute_start = call_start + timedelta(seconds=utterance_start_sec)
            absolute_end = call_start + timedelta(seconds=utterance_end_sec)
            
            rows.append({
                "call_id": call_data.call_id,
                "role": role,
                "content": content,
                "start_seconds_from_call_start": utterance_start_sec,
                "end_seconds_from_call_start": utterance_end_sec,
                "absolute_start_timestamp": absolute_start.isoformat() ,
                "absolute_end_timestamp": absolute_end.isoformat()
            })
    
    df = pd.DataFrame(rows)
    df.to_csv(filename, index=False)
    print(f"Saved dialogue transcript to {filename}")

sa

ve_dialogue_transcript_csv(call_response, call_start_time)

utterance.get("role")

utterance.role

utterance.get("content")

utterance.content

utterance.get("words", [])

utterance.words if hasattr(utterance, 'words') else []

words[0].get("start")

words[0].start

words[-1].get("end")

words[-1].end

transcript_object

role

content

words

kb_config

json
"kb_config": {
  "top_k": 3,
  "filter_score": 0.6
}

knowledge_base_ids

json
"knowledge_base_ids": [
  "<string>"
]

sip:sip.retellai.com

max_call_duration_ms

{{session_duration}}

Equation: {{user_name}} exists
Result: True if variable is defined

{{current_time}}

end_call_after_silence_ms

max_call_duration_ms

{{current_time_[timezone]}}

{{current_time_Asia/Hong_Kong}}

{{current_time_[timezone]}}

{{current_hour_[timezone]}}

{{current_calendar_[timezone]}}

{{current_time_Australia/Sydney}}

{{current_time_America/New_York}}

{{current_hour_Australia/Sydney}}

{{current_calendar_Australia/Sydney}}

{{current_time_{{my_timezone}}}}

my_timezone

Asia/Hong_Kong

{{current_time_Asia/Hong_Kong}}

retell_llm_dynamic_variables

json
{
  "retell_llm_dynamic_variables": {
    "user_name": "John Smith",
    "product_name": "Premium Plan"
  }
}

guardrail_config

language

yue-CN

pronunciation_dictionary

json
"pronunciation_dictionary": [
  {
    "word": "actually",
    "alphabet": "ipa",
    "phoneme": "ˈæktʃuəli"
  }
]

pronunciation_dictionary

eleven turbo v2

json
"pronunciation_dictionary": [
  {
    "word": "笹",
    "alphabet": "ipa",
    "phoneme": "sai3"
  }
]

eleven turbo v2

boosted_keywords

json
"boosted_keywords": [
  "笹"
]

{{session_duration}}

{{current_agent_state}}

{{previous_agent_state}}

{{current_time}}

{{current_time_[timezone]}}

{{current_hour}}

{{current_hour_[timezone]}}

{{current_calendar}}

{{current_calendar_[timezone]}}

{{session_type}}

json
{
  "id": "start",
  "type": "conversation",
  "instruction": {
    "type": "prompt",
    "text": "Greet the customer and ask how you can help them."
  },
  "edges": [
    {
      "id": "edge_1",
      "transition_condition": {
        "type": "prompt",
        "prompt": "Customer wants to book appointment"
      },
      "destination_node_id": "book_appointment"
    }
  ]
}

## Tool Usage Instructions
1. Determine the type of request:
 - If customer mentions "refund" or "money back":
 → Call function `transfer_to_support` immediately