<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->

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"),  # This is the default and can be omitted
    public_key=os.environ.get("TELNYX_PUBLIC_KEY"),  # Required for client.webhooks.unwrap() (webhook verification)
)

All examples below assume client is already initialized as shown above.

Error Handling

All API calls can fail with network errors, rate limits (429), validation errors (422), or authentication errors (401). Always handle errors in production code:

import telnyx

try:
    assistant = client.ai.assistants.create(
        instructions="You are a helpful assistant.",
        name="my-resource",
        model="openai/gpt-4o",
    )
except telnyx.APIConnectionError:
    print("Network error — check connectivity and retry")
    raise
except telnyx.RateLimitError:
    # 429: rate limited — wait, then retry the request (bounded exponential backoff)
    import time
    time.sleep(1)  # Check Retry-After header for actual delay
    # ...retry the call here (give up after a few attempts); otherwise re-raise:
    raise
except telnyx.APIStatusError as e:
    print(f"API error {e.status_code}: {e.message}")
    if e.status_code == 422:
        print("Validation error — check required fields and formats")
    raise  # A failed request must never look like success to the caller

Common error codes: 401 invalid API key, 403 insufficient permissions, 404 resource not found, 422 validation error (check field formats), 429 rate limited (retry with exponential backoff).

Important Notes

• Phone numbers must be in E.164 format (e.g., +13125550001). Include the + prefix and country code. No spaces, dashes, or parentheses.
• Pagination: List methods return an auto-paginating iterator. Use for item in page_result: to iterate through all pages automatically.
• Model availability varies by account. If a model returns 422 "not available for inference", use client.ai.assistants.list() to discover working models. Commonly available: openai/gpt-4o, Qwen/Qwen3-235B-A22B.

Reference Use Rules

Do not invent Telnyx parameters, enums, response fields, or webhook fields.

• If the parameter, enum, or response field you need is not shown inline in this skill, read references/api-details.md before writing code.
• Before using any operation in ## Additional Operations, read the optional-parameters section and the response-schemas section.

Core Tasks

Create an assistant

Assistant creation is the entrypoint for any AI assistant integration. Agents need the exact creation method and the top-level fields returned by the SDK.

client.ai.assistants.create() — POST /ai/assistants

Parameter	Type	Required	Description
name	string	Yes
instructions	string	Yes	System instructions for the assistant.
tags	array[string]	No	Tags associated with the assistant.
model	string	No	ID of the model to use when external_llm is not set.
tools	array[object]	No	Deprecated for new integrations.
...			+28 optional params in references/api-details.md

assistant = client.ai.assistants.create(
    instructions="You are a helpful assistant.",
    name="my-resource",
    model="openai/gpt-4o",
)
print(assistant.id)

Primary response fields:

• assistant.id
• assistant.name
• assistant.model
• assistant.instructions
• assistant.created_at
• assistant.a2a_agents

Chat with an assistant

Chat is the primary runtime path. Agents need the exact assistant method and the response content field.

client.ai.assistants.chat() — POST /ai/assistants/{assistant_id}/chat

Parameter	Type	Required	Description
content	string	Yes	The message content sent by the client to the assistant
conversation_id	string (UUID)	Yes	A unique identifier for the conversation thread, used to mai...
assistant_id	string (UUID)	Yes	Unique identifier of the assistant.
name	string	No	The optional display name of the user sending the message
stream	boolean	No	When true, the response is streamed as Server-Sent Events (`...

response = client.ai.assistants.chat(
    assistant_id="550e8400-e29b-41d4-a716-446655440000",
    content="Tell me a joke about cats",
    conversation_id="42b20469-1215-4a9a-8964-c36f66b406f4",
)
print(response.content)

Primary response fields:

• response.content

Create an assistant test

Test creation is the main validation path for production assistant behavior before deployment.

client.ai.assistants.tests.create() — POST /ai/assistants/tests

Parameter	Type	Required	Description
name	string	Yes	A descriptive name for the assistant test.
destination	string	Yes	The target destination for the test conversation.
instructions	string	Yes	Detailed instructions that define the test scenario and what...
rubric	array[object]	Yes	Evaluation criteria used to assess the assistant's performan...
description	string	No	Optional detailed description of what this test evaluates an...
telnyx_conversation_channel	object	No	The communication channel through which the test will be con...
max_duration_seconds	integer	No	Maximum duration in seconds that the test conversation shoul...
...			+2 optional params in references/api-details.md

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)

Primary response fields:

• assistant_test.test_id
• assistant_test.name
• assistant_test.destination
• assistant_test.created_at
• assistant_test.instructions
• assistant_test.description

---

Important Supporting Operations

Use these when the core tasks above are close to your flow, but you need a common variation or follow-up step.

Get an assistant

Fetch the current state before updating, deleting, or making control-flow decisions.

client.ai.assistants.retrieve() — GET /ai/assistants/{assistant_id}

Parameter	Type	Required	Description
assistant_id	string (UUID)	Yes	Unique identifier of the assistant.
call_control_id	string (UUID)	No	Filter results by call control id.
fetch_dynamic_variables_from_webhook	boolean	No	Whether to fetch dynamic variables from the configured webho...
from_	string (E.164)	No	Start of the filter range.
...			+1 optional params in references/api-details.md

assistant = client.ai.assistants.retrieve(
    assistant_id="550e8400-e29b-41d4-a716-446655440000",
)
print(assistant.id)

Primary response fields:

• assistant.id
• assistant.name
• assistant.created_at
• assistant.a2a_agents
• assistant.avatar_settings
• assistant.conversation_flow

Update an assistant

Create or provision an additional resource when the core tasks do not cover this flow.

client.ai.assistants.update() — POST /ai/assistants/{assistant_id}

Parameter	Type	Required	Description
assistant_id	string (UUID)	Yes	Unique identifier of the assistant.
tags	array[string]	No	Tags associated with the assistant.
name	string	No
model	string	No	ID of the model to use when external_llm is not set.
...			+31 optional params in references/api-details.md

assistant = client.ai.assistants.update(
    assistant_id="550e8400-e29b-41d4-a716-446655440000",
    instructions="You are a friendly support assistant for Acme. Keep answers short.",
)
print(assistant.id)

Primary response fields:

• assistant.id
• assistant.name
• assistant.created_at
• assistant.a2a_agents
• assistant.avatar_settings
• assistant.conversation_flow

List assistants

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.list() — GET /ai/assistants

assistants_list = client.ai.assistants.list()
print(assistants_list.data)

Response wrapper:

• items: assistants_list.data

Primary item fields:

• id
• name
• created_at
• a2a_agents
• avatar_settings
• conversation_flow

List deleted assistants

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.deleted.list() — GET /ai/assistants/deleted

Parameter	Type	Required	Description
page[number]	integer	No	Page number to retrieve (1-based).
page[size]	integer	No	Number of items to return per page.

page = client.ai.assistants.deleted.list()
print(page.data)

Response wrapper:

• items: page.data
• pagination: page.meta

Primary item fields:

• id
• name
• created_at
• a2a_agents
• avatar_settings
• conversation_flow

Import assistants from external provider

Import existing assistants from an external provider instead of creating from scratch.

client.ai.assistants.imports() — POST /ai/assistants/import

Parameter	Type	Required	Description
provider	enum (elevenlabs, vapi, retell)	Yes	The external provider to import assistants from.
api_key_ref	string	Yes	Integration secret pointer that refers to the API key for th...
import_ids	array[string]	No	Optional list of assistant IDs to import from the external p...
Idempotency-Key	string	No	Optional opaque, unquoted key for safely retrying the same l...

assistants_list = client.ai.assistants.imports(
    api_key_ref="my-openai-key",
    provider="elevenlabs",
)
print(assistants_list.data)

Response wrapper:

• items: assistants_list.data

Primary item fields:

• id
• name
• created_at
• a2a_agents
• avatar_settings
• conversation_flow

Get All Tags

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.tags.list() — GET /ai/assistants/tags

tags = client.ai.assistants.tags.list()
print(tags.tags)

Primary response fields:

• tags.tags

List assistant tests with pagination

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.tests.list() — GET /ai/assistants/tests

Parameter	Type	Required	Description
test_suite	string	No	Filter tests by test suite name
telnyx_conversation_channel	string	No	Filter tests by communication channel (e.g., 'web_chat', 'sm...
destination	string	No	Filter tests by destination (phone number, webhook URL, etc....
...			+1 optional params in references/api-details.md

page = client.ai.assistants.tests.list()
page = page.data[0]
print(page.test_id)

Response wrapper:

• items: page.data
• pagination: page.meta

Primary item fields:

• name
• created_at
• description
• destination
• instructions
• max_duration_seconds

Get all test suite names

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.tests.test_suites.list() — GET /ai/assistants/tests/test-suites

test_suites = client.ai.assistants.tests.test_suites.list()
print(test_suites.data)

Response wrapper:

• items: test_suites.data

Primary item fields:

• data

---

Additional Operations

Use the core tasks above first. The operations below are indexed here with exact SDK methods and required params; use references/api-details.md for full optional params, response schemas, and lower-frequency webhook payloads. Before using any operation below, read the optional-parameters section and the response-schemas section so you do not guess missing fields.

Operation	SDK method	Endpoint	Use when	Required params
Get test suite run history	client.ai.assistants.tests.test_suites.runs.list()	GET /ai/assistants/tests/test-suites/{suite_name}/runs	Fetch the current state before updating, deleting, or making control-flow decisions.	suite_name
Trigger test suite execution	client.ai.assistants.tests.test_suites.runs.trigger()	POST /ai/assistants/tests/test-suites/{suite_name}/runs	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	suite_name
Get assistant test by ID	client.ai.assistants.tests.retrieve()	GET /ai/assistants/tests/{test_id}	Fetch the current state before updating, deleting, or making control-flow decisions.	test_id
Update an assistant test	client.ai.assistants.tests.update()	PUT /ai/assistants/tests/{test_id}	Modify an existing resource without recreating it.	test_id
Delete an assistant test	client.ai.assistants.tests.delete()	DELETE /ai/assistants/tests/{test_id}	Remove, detach, or clean up an existing resource.	test_id
Get test run history for a specific test	client.ai.assistants.tests.runs.list()	GET /ai/assistants/tests/{test_id}/runs	Fetch the current state before updating, deleting, or making control-flow decisions.	test_id
Trigger a manual test run	client.ai.assistants.tests.runs.trigger()	POST /ai/assistants/tests/{test_id}/runs	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	test_id
Get specific test run details	client.ai.assistants.tests.runs.retrieve()	GET /ai/assistants/tests/{test_id}/runs/{run_id}	Fetch the current state before updating, deleting, or making control-flow decisions.	test_id, run_id
Delete an assistant	client.ai.assistants.delete()	DELETE /ai/assistants/{assistant_id}	Remove, detach, or clean up an existing resource.	assistant_id
Get Canary Deploy	client.ai.assistants.canary_deploys.retrieve()	GET /ai/assistants/{assistant_id}/canary-deploys	Fetch the current state before updating, deleting, or making control-flow decisions.	assistant_id
Create Canary Deploy	client.ai.assistants.canary_deploys.create()	POST /ai/assistants/{assistant_id}/canary-deploys	Create or provision an additional resource when the core tasks do not cover this flow.	assistant_id
Update Canary Deploy	client.ai.assistants.canary_deploys.update()	PUT /ai/assistants/{assistant_id}/canary-deploys	Modify an existing resource without recreating it.	assistant_id
Delete Canary Deploy	client.ai.assistants.canary_deploys.delete()	DELETE /ai/assistants/{assistant_id}/canary-deploys	Remove, detach, or clean up an existing resource.	assistant_id
Assistant Sms Chat	client.ai.assistants.send_sms()	POST /ai/assistants/{assistant_id}/chat/sms	Run assistant chat over SMS instead of direct API chat.	from_, to, assistant_id
Assistant WhatsApp Chat	client.ai.assistants.whatsapp()	POST /ai/assistants/{assistant_id}/chat/whatsapp	Create or provision an additional resource when the core tasks do not cover this flow.	from_, to, content, assistant_id
Clone Assistant	client.ai.assistants.clone()	POST /ai/assistants/{assistant_id}/clone	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	assistant_id
Get a deleted assistant	client.ai.assistants.deleted.get()	GET /ai/assistants/{assistant_id}/deleted	Fetch the current state before updating, deleting, or making control-flow decisions.	assistant_id
Enhance Assistant Instructions	client.ai.assistants.instructions.enhance()	POST /ai/assistants/{assistant_id}/instructions/enhance	Create or provision an additional resource when the core tasks do not cover this flow.	assistant_id
Restore an assistant	client.ai.assistants.restore()	POST /ai/assistants/{assistant_id}/restore	Create or provision an additional resource when the core tasks do not cover this flow.	assistant_id
List scheduled events	client.ai.assistants.scheduled_events.list()	GET /ai/assistants/{assistant_id}/scheduled_events	Fetch the current state before updating, deleting, or making control-flow decisions.	assistant_id
Create a scheduled event	client.ai.assistants.scheduled_events.create()	POST /ai/assistants/{assistant_id}/scheduled_events	Create or provision an additional resource when the core tasks do not cover this flow.	telnyx_conversation_channel, telnyx_end_user_target, telnyx_agent_target, scheduled_at_fixed_datetime, +1 more
Get a scheduled event	client.ai.assistants.scheduled_events.retrieve()	GET /ai/assistants/{assistant_id}/scheduled_events/{event_id}	Fetch the current state before updating, deleting, or making control-flow decisions.	assistant_id, event_id
Delete a scheduled event	client.ai.assistants.scheduled_events.delete()	DELETE /ai/assistants/{assistant_id}/scheduled_events/{event_id}	Remove, detach, or clean up an existing resource.	assistant_id, event_id
Add Assistant Tag	client.ai.assistants.tags.add()	POST /ai/assistants/{assistant_id}/tags	Create or provision an additional resource when the core tasks do not cover this flow.	tag, assistant_id
Remove Assistant Tag	client.ai.assistants.tags.remove()	DELETE /ai/assistants/{assistant_id}/tags/{tag}	Remove, detach, or clean up an existing resource.	assistant_id, tag
Get assistant texml	client.ai.assistants.get_texml()	GET /ai/assistants/{assistant_id}/texml	Fetch the current state before updating, deleting, or making control-flow decisions.	assistant_id
Add Assistant Tool	client.ai.assistants.tools.add()	PUT /ai/assistants/{assistant_id}/tools/{tool_id}	Modify an existing resource without recreating it.	assistant_id, tool_id
Remove Assistant Tool	client.ai.assistants.tools.remove()	DELETE /ai/assistants/{assistant_id}/tools/{tool_id}	Remove, detach, or clean up an existing resource.	assistant_id, tool_id
Test Assistant Tool	client.ai.assistants.tools.test()	POST /ai/assistants/{assistant_id}/tools/{tool_id}/test	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	assistant_id, tool_id
Get all versions of an assistant	client.ai.assistants.versions.list()	GET /ai/assistants/{assistant_id}/versions	Fetch the current state before updating, deleting, or making control-flow decisions.	assistant_id
Get a specific assistant version	client.ai.assistants.versions.retrieve()	GET /ai/assistants/{assistant_id}/versions/{version_id}	Fetch the current state before updating, deleting, or making control-flow decisions.	assistant_id, version_id
Update a specific assistant version	client.ai.assistants.versions.update()	POST /ai/assistants/{assistant_id}/versions/{version_id}	Create or provision an additional resource when the core tasks do not cover this flow.	assistant_id, version_id
Delete a specific assistant version	client.ai.assistants.versions.delete()	DELETE /ai/assistants/{assistant_id}/versions/{version_id}	Remove, detach, or clean up an existing resource.	assistant_id, version_id
Promote an assistant version to main	client.ai.assistants.versions.promote()	POST /ai/assistants/{assistant_id}/versions/{version_id}/promote	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	assistant_id, version_id
List MCP Servers	client.ai.mcp_servers.list()	GET /ai/mcp_servers	Inspect available resources or choose an existing resource before mutating it.	None
Create MCP Server	client.ai.mcp_servers.create()	POST /ai/mcp_servers	Create or provision an additional resource when the core tasks do not cover this flow.	name, type_, url
Get MCP Server	client.ai.mcp_servers.retrieve()	GET /ai/mcp_servers/{mcp_server_id}	Fetch the current state before updating, deleting, or making control-flow decisions.	mcp_server_id
Update MCP Server	client.ai.mcp_servers.update()	PUT /ai/mcp_servers/{mcp_server_id}	Modify an existing resource without recreating it.	mcp_server_id
Delete MCP Server	client.ai.mcp_servers.delete()	DELETE /ai/mcp_servers/{mcp_server_id}	Remove, detach, or clean up an existing resource.	mcp_server_id
List Tools	client.ai.tools.list()	GET /ai/tools	Inspect available resources or choose an existing resource before mutating it.	None
Create Tool	client.ai.tools.create()	POST /ai/tools	Create or provision an additional resource when the core tasks do not cover this flow.	type_, display_name
Get Tool	client.ai.tools.retrieve()	GET /ai/tools/{tool_id}	Fetch the current state before updating, deleting, or making control-flow decisions.	tool_id
Update Tool	client.ai.tools.update()	PATCH /ai/tools/{tool_id}	Modify an existing resource without recreating it.	tool_id
Delete Tool	client.ai.tools.delete()	DELETE /ai/tools/{tool_id}	Remove, detach, or clean up an existing resource.	tool_id

---

For exhaustive optional parameters, full response schemas, and complete webhook payloads, see references/api-details.md.