telnyx-ai-inference-python

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

# Telnyx Ai Inference - 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:
    result = client.messages.send(to="+13125550001", from_="+13125550002", text="Hello")
except telnyx.APIConnectionError:
    print("Network error — check connectivity and retry")
except telnyx.RateLimitError:
    # 429: rate limited — wait and retry with exponential backoff
    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

- **Pagination:** List methods return an auto-paginating iterator. Use `for item in page_result:` to iterate through all pages automatically.

## Transcribe speech to text

Transcribe speech to text. This endpoint is consistent with the [OpenAI Transcription API](https://platform.openai.com/docs/api-reference/audio/createTranscription) and may be used with the OpenAI JS or Python SDK.

`POST /ai/audio/transcriptions`

```python
response = client.ai.audio.transcribe(
    model="distil-whisper/distil-large-v2",
)
print(response.text)
```

Returns: `duration` (number), `segments` (array[object]), `text` (string)

## Create a chat completion

Chat with a language model. This endpoint is consistent with the [OpenAI Chat Completions API](https://platform.openai.com/docs/api-reference/chat) and may be used with the OpenAI JS or Python SDK.

`POST /ai/chat/completions` — Required: `messages`

Optional: `api_key_ref` (string), `best_of` (integer), `early_stopping` (boolean), `enable_thinking` (boolean), `frequency_penalty` (number), `guided_choice` (array[string]), `guided_json` (object), `guided_regex` (string), `length_penalty` (number), `logprobs` (boolean), `max_tokens` (integer), `min_p` (number), `model` (string), `n` (number), `presence_penalty` (number), `response_format` (object), `stream` (boolean), `temperature` (number), `tool_choice` (enum: none, auto, required), `tools` (array[object]), `top_logprobs` (integer), `top_p` (number), `use_beam_search` (boolean)

```python
response = client.ai.chat.create_completion(
    messages=[{
        "role": "system",
        "content": "You are a friendly chatbot.",
    }, {
        "role": "user",
        "content": "Hello, world!",
    }],
)
print(response)
```

## List conversations

Retrieve a list of all AI conversations configured by the user. Supports [PostgREST-style query parameters](https://postgrest.org/en/stable/api.html#horizontal-filtering-rows) for filtering. Examples are included for the standard metadata fields, but you can filter on any field in the metadata JSON object.

`GET /ai/conversations`

```python
conversations = client.ai.conversations.list()
print(conversations.data)
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Create a conversation

Create a new AI Conversation.

`POST /ai/conversations`

Optional: `metadata` (object), `name` (string)

```python
conversation = client.ai.conversations.create()
print(conversation.id)
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Get Insight Template Groups

Get all insight groups

`GET /ai/conversations/insight-groups`

```python
page = client.ai.conversations.insight_groups.retrieve_insight_groups()
page = page.data[0]
print(page.id)
```

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

## Create Insight Template Group

Create a new insight group

`POST /ai/conversations/insight-groups` — Required: `name`

Optional: `description` (string), `webhook` (string)

```python
insight_template_group_detail = client.ai.conversations.insight_groups.insight_groups(
    name="my-resource",
)
print(insight_template_group_detail.data)
```

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

## Get Insight Template Group

Get insight group by ID

`GET /ai/conversations/insight-groups/{group_id}`

```python
insight_template_group_detail = client.ai.conversations.insight_groups.retrieve(
    "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
)
print(insight_template_group_detail.data)
```

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

## Update Insight Template Group

Update an insight template group

`PUT /ai/conversations/insight-groups/{group_id}`

Optional: `description` (string), `name` (string), `webhook` (string)

```python
insight_template_group_detail = client.ai.conversations.insight_groups.update(
    group_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
)
print(insight_template_group_detail.data)
```

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

## Delete Insight Template Group

Delete insight group by ID

`DELETE /ai/conversations/insight-groups/{group_id}`

```python
client.ai.conversations.insight_groups.delete(
    "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e