Telnyx AI Assistants - Python

Installation

bash

pip install telnyx

Setup

python

import os
from telnyx import Telnyx

client = Telnyx(
    api_key=os.environ.get("TELNYX_API_KEY"),  # This is the default and can be omitted
)

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:

python

import telnyx

try:
    assistant = client.ai.assistants.create(
        instructions="You are a helpful assistant.",
        model="openai/gpt-4o",
        name="my-resource",
    )
except telnyx.APIConnectionError:
    print("Network error — check connectivity and retry")
except telnyx.RateLimitError:
    import time
    time.sleep(1)  # Check Retry-After header for actual delay
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")

Common error codes:

invalid API key,

insufficient permissions,

resource not found,

validation error (check field formats),

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
`model`	string	Yes	ID of the model to use.
`instructions`	string	Yes	System instructions for the assistant.
`tools`	array[object]	No	The tools that the assistant can use.
`tool_ids`	array[string]	No
`description`	string	No
...			+12 optional params in references/api-details.md

python

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

Primary response fields:

```
assistant.id
```
```
assistant.name
```
```
assistant.model
```
```
assistant.instructions
```
```
assistant.created_at
```
```
assistant.description
```

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
`name`	string	No	The optional display name of the user sending the message

python

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...
...			+1 optional params in references/api-details.md

python

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
`call_control_id`	string (UUID)	No
`fetch_dynamic_variables_from_webhook`	boolean	No
`from_`	string (E.164)	No
...			+1 optional params in references/api-details.md

python

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.description
```
```
assistant.dynamic_variables
```
```
assistant.dynamic_variables_webhook_url
```

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
`name`	string	No
`model`	string	No	ID of the model to use.
`instructions`	string	No	System instructions for the assistant.
...			+16 optional params in references/api-details.md

python

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

Primary response fields:

```
assistant.id
```
```
assistant.name
```
```
assistant.created_at
```
```
assistant.description
```
```
assistant.dynamic_variables
```
```
assistant.dynamic_variables_webhook_url
```

List assistants

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

client.ai.assistants.list()

—

GET /ai/assistants

python

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

Response wrapper:

items:
```
assistants_list.data
```

Primary item fields:

```
id
```
```
name
```
```
created_at
```
```
description
```
```
dynamic_variables
```
```
dynamic_variables_webhook_url
```

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...

python

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
```
```
description
```
```
dynamic_variables
```
```
dynamic_variables_webhook_url
```

Get All Tags

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

client.ai.assistants.tags.list()

—

GET /ai/assistants/tags

python

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

python

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

python

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

Response wrapper:

items:
```
test_suites.data
```

Primary item fields:

```
data
```

Get test suite run history

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

client.ai.assistants.tests.test_suites.runs.list()

—

GET /ai/assistants/tests/test-suites/{suite_name}/runs

Parameter	Type	Required	Description
`suite_name`	string	Yes
`test_suite_run_id`	string (UUID)	No	Filter runs by specific suite execution batch ID
`status`	string	No	Filter runs by execution status (pending, running, completed...
`page`	object	No	Consolidated page parameter (deepObject style).

python

page = client.ai.assistants.tests.test_suites.runs.list(
    suite_name="my-test-suite",
)
page = page.data[0]
print(page.run_id)

Response wrapper:

items:
```
page.data
```
pagination:
```
page.meta
```

Primary item fields:

```
status
```
```
created_at
```
```
updated_at
```
```
completed_at
```
```
conversation_id
```
```
conversation_insights_id
```

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
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.	`versions` , `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.	`versions` , `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`
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`
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.

telnyx-ai-assistants-python

NPX Install

Tags

SKILL.md Content

Telnyx AI Assistants - Python

Installation

Setup

Error Handling

Important Notes

Reference Use Rules

Core Tasks

Create an assistant

Chat with an assistant

Create an assistant test

Important Supporting Operations

Get an assistant

Update an assistant

List assistants

Import assistants from external provider

Get All Tags

List assistant tests with pagination

Get all test suite names

Get test suite run history

Additional Operations