Telnyx AI Assistants Python

<!-- 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
)

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")
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: 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. |

| ... | | | +23 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.conversation_flow

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 |

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 |

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.conversation_flow
• assistant.description
• assistant.dynamic_variables

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. |

| ... | | | +27 optional params in references/api-details.md |

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.conversation_flow
• assistant.description
• assistant.dynamic_variables

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
• conversation_flow
• description
• dynamic_variables

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... |

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
• conversation_flow
• description
• dynamic_variables

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

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 | Name of the suite. |

| 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). |

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. | 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 |

| 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 |

| 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 |

| 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.