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telnyx-ai-assistants-python Create and manage AI voice assistants with custom personalities, knowledge bases, and tool integrations. This skill provides Python SDK examples.
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Mehr aus diesem Repository Complete Telnyx toolkit — ready-to-use tools (STT, TTS, RAG, Networking, 10DLC) plus SDK documentation for JavaScript, Python, Go, Java, and Ruby.
Automated Telnyx bot account signup via challenge-response
Track agent activities using the Telnyx AI Missions API. Use this skill when executing multi-step tasks that should be logged and tracked. Supports creating voice/SMS agents, scheduling calls, and retrieving conversation insights. Use when tasks involve calling people, sending SMS, or any substantial tracked work.
name telnyx-ai-assistants-python description Create and manage AI voice assistants with custom personalities, knowledge bases, and tool integrations. This skill provides Python SDK examples. metadata {"author":"telnyx","product":"ai-assistants","language":"python","generated_by":"telnyx-ext-skills-generator"}
Telnyx Ai Assistants - Python
Installation
pip install telnyx
Setup
import os
from telnyx import Telnyx
client = Telnyx(
api_key=os.environ.get("TELNYX_API_KEY" ),
)
All examples below assume client is already initialized as shown above.
List assistants
Retrieve a list of all AI Assistants configured by the user.
GET /ai/assistants
assistants_list = client.ai.assistants.list ()
print (assistants_list.data)
Create an assistant
Create a new AI Assistant.
POST /ai/assistants — Required: name, model, instructions
assistant = client.ai.assistants.create(
instructions="instructions" ,
model="model" ,
name="name"
print
id
Get an assistant Retrieve an AI Assistant configuration by assistant_id.
GET /ai/assistants/{assistant_id}
assistant = client.ai.assistants.retrieve(
assistant_id="assistant_id" ,
)
print (assistant.id )
Update an assistant Update an AI Assistant's attributes.
POST /ai/assistants/{assistant_id}
assistant = client.ai.assistants.update(
assistant_id="assistant_id" ,
)
print (assistant.id )
Delete an assistant Delete an AI Assistant by assistant_id.
DELETE /ai/assistants/{assistant_id}
assistant = client.ai.assistants.delete(
"assistant_id" ,
)
print (assistant.id )
Assistant Chat (BETA) This endpoint allows a client to send a chat message to a specific AI Assistant.
POST /ai/assistants/{assistant_id}/chat — Required: content, conversation_id
response = client.ai.assistants.chat(
assistant_id="assistant_id" ,
content="Tell me a joke about cats" ,
conversation_id="42b20469-1215-4a9a-8964-c36f66b406f4" ,
)
print (response.content)
Assistant Sms Chat Send an SMS message for an assistant.
POST /ai/assistants/{assistant_id}/chat/sms — Required: from, to
response = client.ai.assistants.send_sms(
assistant_id="assistant_id" ,
from_="from" ,
to="to" ,
)
print (response.conversation_id)
Clone Assistant Clone an existing assistant, excluding telephony and messaging settings.
POST /ai/assistants/{assistant_id}/clone
assistant = client.ai.assistants.clone(
"assistant_id" ,
)
print (assistant.id )
Import assistants from external provider Import assistants from external providers.
POST /ai/assistants/import — Required: provider, api_key_ref
assistants_list = client.ai.assistants.imports(
api_key_ref="api_key_ref" ,
provider="elevenlabs" ,
)
print (assistants_list.data)
List scheduled events Get scheduled events for an assistant with pagination and filtering
GET /ai/assistants/{assistant_id}/scheduled_events
page = client.ai.assistants.scheduled_events.list (
assistant_id="assistant_id" ,
)
page = page.data[0 ]
print (page)
Create a scheduled event Create a scheduled event for an assistant
POST /ai/assistants/{assistant_id}/scheduled_events — Required: telnyx_conversation_channel, telnyx_end_user_target, telnyx_agent_target, scheduled_at_fixed_datetime
from datetime import datetime
scheduled_event_response = client.ai.assistants.scheduled_events.create(
assistant_id="assistant_id" ,
scheduled_at_fixed_datetime=datetime.fromisoformat("2025-04-15T13:07:28.764" ),
telnyx_agent_target="telnyx_agent_target" ,
telnyx_conversation_channel="phone_call" ,
telnyx_end_user_target="telnyx_end_user_target" ,
)
print (scheduled_event_response)
Get a scheduled event Retrieve a scheduled event by event ID
GET /ai/assistants/{assistant_id}/scheduled_events/{event_id}
scheduled_event_response = client.ai.assistants.scheduled_events.retrieve(
event_id="event_id" ,
assistant_id="assistant_id" ,
)
print (scheduled_event_response)
Delete a scheduled event If the event is pending, this will cancel the event.
DELETE /ai/assistants/{assistant_id}/scheduled_events/{event_id}
client.ai.assistants.scheduled_events.delete(
event_id="event_id" ,
assistant_id="assistant_id" ,
)
List assistant tests with pagination Retrieves a paginated list of assistant tests with optional filtering capabilities
page = client.ai.assistants.tests.list ()
page = page.data[0 ]
print (page.test_id)
Create a new assistant test Creates a comprehensive test configuration for evaluating AI assistant performance
POST /ai/assistants/tests — Required: name, destination, instructions, rubric
assistant_test = client.ai.assistants.tests.create(
destination="+15551234567" ,
instructions="Act as a frustrated customer who received a damaged product. Ask for a refund and escalate if not satisfied with the initial response." ,
name="Customer Support Bot Test" ,
rubric=[{
"criteria" : "Assistant responds within 30 seconds" ,
"name" : "Response Time" ,
}, {
"criteria" : "Provides correct product information" ,
"name" : "Accuracy" ,
}],
)
print (assistant_test.test_id)
Get all test suite names Retrieves a list of all distinct test suite names available to the current user
GET /ai/assistants/tests/test-suites
test_suites = client.ai.assistants.tests.test_suites.list ()
print (test_suites.data)
Get test suite run history Retrieves paginated history of test runs for a specific test suite with filtering options
GET /ai/assistants/tests/test-suites/{suite_name}/runs
page = client.ai.assistants.tests.test_suites.runs.list (
suite_name="suite_name" ,
)
page = page.data[0 ]
print (page.run_id)
Trigger test suite execution Executes all tests within a specific test suite as a batch operation
POST /ai/assistants/tests/test-suites/{suite_name}/runs
test_run_responses = client.ai.assistants.tests.test_suites.runs.trigger(
suite_name="suite_name" ,
)
print (test_run_responses)
Get assistant test by ID Retrieves detailed information about a specific assistant test
GET /ai/assistants/tests/{test_id}
assistant_test = client.ai.assistants.tests.retrieve(
"test_id" ,
)
print (assistant_test.test_id)
Update an assistant test Updates an existing assistant test configuration with new settings
PUT /ai/assistants/tests/{test_id}
assistant_test = client.ai.assistants.tests.update(
test_id="test_id" ,
)
print (assistant_test.test_id)
Delete an assistant test Permanently removes an assistant test and all associated data
DELETE /ai/assistants/tests/{test_id}
client.ai.assistants.tests.delete(
"test_id" ,
)
Get test run history for a specific test Retrieves paginated execution history for a specific assistant test with filtering options
GET /ai/assistants/tests/{test_id}/runs
page = client.ai.assistants.tests.runs.list (
test_id="test_id" ,
)
page = page.data[0 ]
print (page.run_id)
Trigger a manual test run Initiates immediate execution of a specific assistant test
POST /ai/assistants/tests/{test_id}/runs
test_run_response = client.ai.assistants.tests.runs.trigger(
test_id="test_id" ,
)
print (test_run_response.run_id)
Get specific test run details Retrieves detailed information about a specific test run execution
GET /ai/assistants/tests/{test_id}/runs/{run_id}
test_run_response = client.ai.assistants.tests.runs.retrieve(
run_id="run_id" ,
test_id="test_id" ,
)
print (test_run_response.run_id)
Get all versions of an assistant Retrieves all versions of a specific assistant with complete configuration and metadata
GET /ai/assistants/{assistant_id}/versions
assistants_list = client.ai.assistants.versions.list (
"assistant_id" ,
)
print (assistants_list.data)
Get a specific assistant version Retrieves a specific version of an assistant by assistant_id and version_id
GET /ai/assistants/{assistant_id}/versions/{version_id}
assistant = client.ai.assistants.versions.retrieve(
version_id="version_id" ,
assistant_id="assistant_id" ,
)
print (assistant.id )
Update a specific assistant version Updates the configuration of a specific assistant version.
POST /ai/assistants/{assistant_id}/versions/{version_id}
assistant = client.ai.assistants.versions.update(
version_id="version_id" ,
assistant_id="assistant_id" ,
)
print (assistant.id )
Delete a specific assistant version Permanently removes a specific version of an assistant.
DELETE /ai/assistants/{assistant_id}/versions/{version_id}
client.ai.assistants.versions.delete(
version_id="version_id" ,
assistant_id="assistant_id" ,
)
Promote an assistant version to main Promotes a specific version to be the main/current version of the assistant.
POST /ai/assistants/{assistant_id}/versions/{version_id}/promote
assistant = client.ai.assistants.versions.promote(
version_id="version_id" ,
assistant_id="assistant_id" ,
)
print (assistant.id )
Get Canary Deploy Endpoint to get a canary deploy configuration for an assistant.
GET /ai/assistants/{assistant_id}/canary-deploys
canary_deploy_response = client.ai.assistants.canary_deploys.retrieve(
"assistant_id" ,
)
print (canary_deploy_response.assistant_id)
Create Canary Deploy Endpoint to create a canary deploy configuration for an assistant.
POST /ai/assistants/{assistant_id}/canary-deploys — Required: versions
canary_deploy_response = client.ai.assistants.canary_deploys.create(
assistant_id="assistant_id" ,
versions=[{
"percentage" : 1 ,
"version_id" : "version_id" ,
}],
)
print (canary_deploy_response.assistant_id)
Update Canary Deploy Endpoint to update a canary deploy configuration for an assistant.
PUT /ai/assistants/{assistant_id}/canary-deploys — Required: versions
canary_deploy_response = client.ai.assistants.canary_deploys.update(
assistant_id="assistant_id" ,
versions=[{
"percentage" : 1 ,
"version_id" : "version_id" ,
}],
)
print (canary_deploy_response.assistant_id)
Delete Canary Deploy Endpoint to delete a canary deploy configuration for an assistant.
DELETE /ai/assistants/{assistant_id}/canary-deploys
client.ai.assistants.canary_deploys.delete(
"assistant_id" ,
)
Get assistant texml Get an assistant texml by assistant_id.
GET /ai/assistants/{assistant_id}/texml
response = client.ai.assistants.get_texml(
"assistant_id" ,
)
print (response)
Test Assistant Tool Test a webhook tool for an assistant
POST /ai/assistants/{assistant_id}/tools/{tool_id}/test
response = client.ai.assistants.tools.test(
tool_id="tool_id" ,
assistant_id="assistant_id" ,
)
print (response.data)
List Integrations List all available integrations.
integrations = client.ai.integrations.list ()
print (integrations.data)
List User Integrations List user setup integrations
GET /ai/integrations/connections
connections = client.ai.integrations.connections.list ()
print (connections.data)
Get User Integration connection By Id Get user setup integrations
GET /ai/integrations/connections/{user_connection_id}
connection = client.ai.integrations.connections.retrieve(
"user_connection_id" ,
)
print (connection.data)
Delete Integration Connection Delete a specific integration connection.
DELETE /ai/integrations/connections/{user_connection_id}
client.ai.integrations.connections.delete(
"user_connection_id" ,
)
List Integration By Id Retrieve integration details
GET /ai/integrations/{integration_id}
integration = client.ai.integrations.retrieve(
"integration_id" ,
)
print (integration.id )
List MCP Servers Retrieve a list of MCP servers.
page = client.ai.mcp_servers.list ()
page = page.items[0 ]
print (page.id )
Create MCP Server POST /ai/mcp_servers — Required: name, type, url
mcp_server = client.ai.mcp_servers.create(
name="name" ,
type ="type" ,
url="url" ,
)
print (mcp_server.id )
Get MCP Server Retrieve details for a specific MCP server.
GET /ai/mcp_servers/{mcp_server_id}
mcp_server = client.ai.mcp_servers.retrieve(
"mcp_server_id" ,
)
print (mcp_server.id )
Update MCP Server Update an existing MCP server.
PUT /ai/mcp_servers/{mcp_server_id}
mcp_server = client.ai.mcp_servers.update(
mcp_server_id="mcp_server_id" ,
)
print (mcp_server.id )
Delete MCP Server Delete a specific MCP server.
DELETE /ai/mcp_servers/{mcp_server_id}
client.ai.mcp_servers.delete(
"mcp_server_id" ,
)
