Telnyx Ai Inference - Go

Installation

go get github.com/team-telnyx/telnyx-go

Setup

import (
  "context"
  "fmt"
  "os"

  "github.com/team-telnyx/telnyx-go"
  "github.com/team-telnyx/telnyx-go/option"
)

client := telnyx.NewClient(
  option.WithAPIKey(os.Getenv("TELNYX_API_KEY")),
)

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 "errors"

result, err := client.Messages.Send(ctx, params)
if err != nil {
  var apiErr *telnyx.Error
  if errors.As(err, &apiErr) {
    switch apiErr.StatusCode {
    case 422:
      fmt.Println("Validation error — check required fields and formats")
    case 429:
      // Rate limited — wait and retry with exponential backoff
      fmt.Println("Rate limited, retrying...")
    default:
      fmt.Printf("API error %d: %s\n", apiErr.StatusCode, apiErr.Error())
    }
  } else {
    fmt.Println("Network error — check connectivity and retry")
  }
}

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: Use ListAutoPaging() for automatic iteration: iter := client.Resource.ListAutoPaging(ctx, params); for iter.Next() { item := iter.Current() }.

Transcribe speech to text

Transcribe speech to text. This endpoint is consistent with the OpenAI Transcription API and may be used with the OpenAI JS or Python SDK.

POST /ai/audio/transcriptions

	response, err := client.AI.Audio.Transcribe(context.Background(), telnyx.AIAudioTranscribeParams{
		Model: telnyx.AIAudioTranscribeParamsModelDistilWhisperDistilLargeV2,
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", response.Text)

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

Create a chat completion

Deprecated: Use POST /v2/ai/openai/chat/completions instead. Chat with a language model. This endpoint is consistent with the OpenAI Chat Completions API 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), seed (integer), stop (object), stream (boolean), temperature (number), tool_choice (enum: none, auto, required), tools (array[object]), top_logprobs (integer), top_p (number), use_beam_search (boolean)

	response, err := client.AI.Chat.NewCompletion(context.Background(), telnyx.AIChatNewCompletionParams{
		Messages: []telnyx.AIChatNewCompletionParamsMessage{{
			Role: "system",
			Content: telnyx.AIChatNewCompletionParamsMessageContentUnion{
				OfString: telnyx.String("You are a friendly chatbot."),
			},
		}, {
			Role: "user",
			Content: telnyx.AIChatNewCompletionParamsMessageContentUnion{
				OfString: telnyx.String("Hello, world!"),
			},
		}},
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", response)

List conversations

Retrieve a list of all AI conversations configured by the user. Supports PostgREST-style query parameters 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

	conversations, err := client.AI.Conversations.List(context.Background(), telnyx.AIConversationListParams{})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", 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)

	conversation, err := client.AI.Conversations.New(context.Background(), telnyx.AIConversationNewParams{})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", conversation.ID)

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

Aggregate Conversation Insights

Aggregate conversation insights by specified fields

GET /ai/conversations/conversation-insights/aggregates

	response, err := client.AI.Conversations.ConversationInsights.Aggregate(context.Background(), telnyx.AIConversationConversationInsightAggregateParams{})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", response.Data)

Returns: record_count (integer)

Get Insight Template Groups

Get all insight groups

GET /ai/conversations/insight-groups

	page, err := client.AI.Conversations.InsightGroups.GetInsightGroups(context.Background(), telnyx.AIConversationInsightGroupGetInsightGroupsParams{})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", page)

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)

	insightTemplateGroupDetail, err := client.AI.Conversations.InsightGroups.InsightGroups(context.Background(), telnyx.AIConversationInsightGroupInsightGroupsParams{
		Name: "my-resource",
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", insightTemplateGroupDetail.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}

	insightTemplateGroupDetail, err := client.AI.Conversations.InsightGroups.Get(context.Background(), "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", insightTemplateGroupDetail.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)

	insightTemplateGroupDetail, err := client.AI.Conversations.InsightGroups.Update(
		context.Background(),
		"182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
		telnyx.AIConversationInsightGroupUpdateParams{},
	)
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", insightTemplateGroupDetail.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}

	err := client.AI.Conversations.InsightGroups.Delete(context.Background(), "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
	if err != nil {
		log.Fatal(err)
	}

Assign Insight Template To Group

Assign an insight to a group

POST /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/assign

	err := client.AI.Conversations.InsightGroups.Insights.Assign(
		context.Background(),
		"182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
		telnyx.AIConversationInsightGroupInsightAssignParams{
			GroupID: "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
		},
	)
	if err != nil {
		log.Fatal(err)
	}

Unassign Insight Template From Group

Remove an insight from a group

DELETE /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/unassign

	err := client.AI.Conversations.InsightGroups.Insights.DeleteUnassign(
		context.Background(),
		"182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
		telnyx.AIConversationInsightGroupInsightDeleteUnassignParams{
			GroupID: "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
		},
	)
	if err != nil {
		log.Fatal(err)
	}

Get Insight Templates

Get all insights

GET /ai/conversations/insights

	page, err := client.AI.Conversations.Insights.List(context.Background(), telnyx.AIConversationInsightListParams{})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", page)

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Create Insight Template

Create a new insight

POST /ai/conversations/insights — Required: instructions, name

Optional: json_schema (object), webhook (string)

	insightTemplateDetail, err := client.AI.Conversations.Insights.New(context.Background(), telnyx.AIConversationInsightNewParams{
		Instructions: "You are a helpful assistant.",
		Name: "my-resource",
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", insightTemplateDetail.Data)

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Get Insight Template

Get insight by ID

GET /ai/conversations/insights/{insight_id}

	insightTemplateDetail, err := client.AI.Conversations.Insights.Get(context.Background(), "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", insightTemplateDetail.Data)

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Update Insight Template

Update an insight template

PUT /ai/conversations/insights/{insight_id}

Optional: instructions (string), json_schema (object), name (string), webhook (string)

	insightTemplateDetail, err := client.AI.Conversations.Insights.Update(
		context.Background(),
		"182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
		telnyx.AIConversationInsightUpdateParams{},
	)
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", insightTemplateDetail.Data)

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Delete Insight Template

Delete insight by ID

DELETE /ai/conversations/insights/{insight_id}

	err := client.AI.Conversations.Insights.Delete(context.Background(), "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
	if err != nil {
		log.Fatal(err)
	}

Get a conversation

Retrieve a specific AI conversation by its ID.

GET /ai/conversations/{conversation_id}

	conversation, err := client.AI.Conversations.Get(context.Background(), "conversation_id")
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", conversation.Data)

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

Update conversation metadata

Update metadata for a specific conversation.

PUT /ai/conversations/{conversation_id}

Optional: metadata (object)

	conversation, err := client.AI.Conversations.Update(
		context.Background(),
		"conversation_id",
		telnyx.AIConversationUpdateParams{},
	)
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", conversation.Data)

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

Delete a conversation

Delete a specific conversation by its ID.

DELETE /ai/conversations/{conversation_id}

	err := client.AI.Conversations.Delete(context.Background(), "conversation_id")
	if err != nil {
		log.Fatal(err)
	}

Get insights for a conversation

Retrieve insights for a specific conversation

GET /ai/conversations/{conversation_id}/conversations-insights

	response, err := client.AI.Conversations.GetConversationsInsights(context.Background(), "conversation_id")
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", response.Data)

Returns: conversation_insights (array[object]), created_at (date-time), id (string), status (enum: pending, in_progress, completed, failed)

Create Message

Add a new message to the conversation. Used to insert a new messages to a conversation manually ( without using chat endpoint )

POST /ai/conversations/{conversation_id}/message — Required: role

Optional: content (string), metadata (object), name (string), sent_at (date-time), tool_call_id (string), tool_calls (array[object]), tool_choice (object)

	err := client.AI.Conversations.AddMessage(
		context.Background(),
		"182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
		telnyx.AIConversationAddMessageParams{
			Role: "user",
		},
	)
	if err != nil {
		log.Fatal(err)
	}

Get conversation messages

Retrieve messages for a specific conversation, including tool calls made by the assistant.

GET /ai/conversations/{conversation_id}/messages

	page, err := client.AI.Conversations.Messages.List(
		context.Background(),
		"conversation_id",
		telnyx.AIConversationMessageListParams{},
	)
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", page)

Returns: created_at (date-time), role (enum: user, assistant, tool), sent_at (date-time), text (string), tool_calls (array[object])

Get Tasks by Status

Retrieve tasks for the user that are either queued, processing, failed, success or partial_success based on the query string. Defaults to queued and processing.

GET /ai/embeddings

	embeddings, err := client.AI.Embeddings.List(context.Background(), telnyx.AIEmbeddingListParams{})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", embeddings.Data)

Returns: bucket (string), created_at (date-time), finished_at (date-time), status (enum: queued, processing, success, failure, partial_success), task_id (string), task_name (string), user_id (string)

Embed documents

Perform embedding on a Telnyx Storage Bucket using an embedding model. The current supported file types are:

• PDF
• HTML
• txt/unstructured text files
• json
• csv
• audio / video (mp3, mp4, mpeg, mpga, m4a, wav, or webm ) - Max of 100mb file size. Any files not matching the above types will be attempted to be embedded as unstructured text.

POST /ai/embeddings — Required: bucket_name

Optional: document_chunk_overlap_size (integer), document_chunk_size (integer), embedding_model (object), loader (object)

	embeddingResponse, err := client.AI.Embeddings.New(context.Background(), telnyx.AIEmbeddingNewParams{
		BucketName: "my-bucket",
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", embeddingResponse.Data)

Returns: created_at (string), finished_at (string | null), status (string), task_id (uuid), task_name (string), user_id (uuid)

List embedded buckets

Get all embedding buckets for a user.

GET /ai/embeddings/buckets

	buckets, err := client.AI.Embeddings.Buckets.List(context.Background())
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", buckets.Data)

Returns: buckets (array[string])

Get file-level embedding statuses for a bucket

Get all embedded files for a given user bucket, including their processing status.

GET /ai/embeddings/buckets/{bucket_name}

	bucket, err := client.AI.Embeddings.Buckets.Get(context.Background(), "bucket_name")
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", bucket.Data)

Returns: created_at (date-time), error_reason (string), filename (string), last_embedded_at (date-time), status (string), updated_at (date-time)

Disable AI for an Embedded Bucket

Deletes an entire bucket's embeddings and disables the bucket for AI-use, returning it to normal storage pricing.

DELETE /ai/embeddings/buckets/{bucket_name}

	err := client.AI.Embeddings.Buckets.Delete(context.Background(), "bucket_name")
	if err != nil {
		log.Fatal(err)
	}

Search for documents

Perform a similarity search on a Telnyx Storage Bucket, returning the most similar num_docs document chunks to the query. Currently the only available distance metric is cosine similarity which will return a distance between 0 and 1. The lower the distance, the more similar the returned document chunks are to the query.

POST /ai/embeddings/similarity-search — Required: bucket_name, query

Optional: num_of_docs (integer)

	response, err := client.AI.Embeddings.SimilaritySearch(context.Background(), telnyx.AIEmbeddingSimilaritySearchParams{
		BucketName: "my-bucket",
		Query: "What is Telnyx?",
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", response.Data)

Returns: distance (number), document_chunk (string), metadata (object)

Embed URL content

Embed website content from a specified URL, including child pages up to 5 levels deep within the same domain. The process crawls and loads content from the main URL and its linked pages into a Telnyx Cloud Storage bucket.

POST /ai/embeddings/url — Required: url, bucket_name

	embeddingResponse, err := client.AI.Embeddings.URL(context.Background(), telnyx.AIEmbeddingURLParams{
		BucketName: "my-bucket",
		URL: "https://example.com/resource",
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", embeddingResponse.Data)

Returns: created_at (string), finished_at (string | null), status (string), task_id (uuid), task_name (string), user_id (uuid)

Get an embedding task's status

Check the status of a current embedding task. Will be one of the following:

• queued - Task is waiting to be picked up by a worker
• processing - The embedding task is running
• success - Task completed successfully and the bucket is embedded
• failure - Task failed and no files were embedded successfully
• partial_success - Some files were embedded successfully, but at least one failed

GET /ai/embeddings/{task_id}

	embedding, err := client.AI.Embeddings.Get(context.Background(), "task_id")
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", embedding.Data)

Returns: created_at (string), finished_at (string), status (enum: queued, processing, success, failure, partial_success), task_id (uuid), task_name (string)

List fine tuning jobs

Retrieve a list of all fine tuning jobs created by the user.

GET /ai/fine_tuning/jobs

	jobs, err := client.AI.FineTuning.Jobs.List(context.Background())
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", jobs.Data)

Returns: created_at (integer), finished_at (integer | null), hyperparameters (object), id (string), model (string), organization_id (string), status (enum: queued, running, succeeded, failed, cancelled), trained_tokens (integer | null), training_file (string)

Create a fine tuning job

Create a new fine tuning job.

POST /ai/fine_tuning/jobs — Required: model, training_file

Optional: hyperparameters (object), suffix (string)

	fineTuningJob, err := client.AI.FineTuning.Jobs.New(context.Background(), telnyx.AIFineTuningJobNewParams{
		Model: "openai/gpt-4o",
		TrainingFile: "training-data.jsonl",
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", fineTuningJob.ID)

Returns: created_at (integer), finished_at (integer | null), hyperparameters (object), id (string), model (string), organization_id (string), status (enum: queued, running, succeeded, failed, cancelled), trained_tokens (integer | null), training_file (string)

Get a fine tuning job

Retrieve a fine tuning job by job_id.

GET /ai/fine_tuning/jobs/{job_id}

	fineTuningJob, err := client.AI.FineTuning.Jobs.Get(context.Background(), "job_id")
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", fineTuningJob.ID)

Returns: created_at (integer), finished_at (integer | null), hyperparameters (object), id (string), model (string), organization_id (string), status (enum: queued, running, succeeded, failed, cancelled), trained_tokens (integer | null), training_file (string)

Cancel a fine tuning job

Cancel a fine tuning job.

POST /ai/fine_tuning/jobs/{job_id}/cancel

	fineTuningJob, err := client.AI.FineTuning.Jobs.Cancel(context.Background(), "job_id")
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", fineTuningJob.ID)

Returns: created_at (integer), finished_at (integer | null), hyperparameters (object), id (string), model (string), organization_id (string), status (enum: queued, running, succeeded, failed, cancelled), trained_tokens (integer | null), training_file (string)

Get available models

Deprecated: Use GET /v2/ai/openai/models instead. Returns the same ModelsResponse payload as the OpenAI-compatible endpoint — open-source LLMs hosted on Telnyx (e.g. moonshotai/Kimi-K2.6, zai-org/GLM-5.1-FP8, MiniMaxAI/MiniMax-M2.7), embedding models, and fine-tuned models — kept around for backwards compatibility.

GET /ai/models

	response, err := client.AI.GetModels(context.Background())
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", response.Data)

Returns: base_model (string | null), context_length (integer), created (date-time), description (string | null), id (string), is_fine_tunable (boolean), is_vision_supported (boolean), languages (array[string]), license (string), max_completion_tokens (integer | null), object (string), organization (string), owned_by (string), parameters (integer), parameters_str (string | null), pricing (object), recommended_for_assistants (boolean), regions (array[string]), task (string), tier (enum: small, medium, large, unlisted)

Create embeddings

Creates an embedding vector representing the input text. This endpoint is compatible with the OpenAI Embeddings API and may be used with the OpenAI JS or Python SDK by setting the base URL to https://api.telnyx.com/v2/ai/openai.

POST /ai/openai/embeddings — Required: input, model

Optional: dimensions (integer), encoding_format (enum: float, base64), user (string)

	response, err := client.AI.OpenAI.Embeddings.NewEmbeddings(context.Background(), telnyx.AIOpenAIEmbeddingNewEmbeddingsParams{
		Input: telnyx.AIOpenAIEmbeddingNewEmbeddingsParamsInputUnion{
			OfString: telnyx.String("The quick brown fox jumps over the lazy dog"),
		},
		Model: "thenlper/gte-large",
	})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", response.Data)

Returns: data (array[object]), model (string), object (string), usage (object)

List embedding models

Returns a list of available embedding models. This endpoint is compatible with the OpenAI Models API format.

GET /ai/openai/embeddings/models

	response, err := client.AI.OpenAI.Embeddings.ListEmbeddingModels(context.Background())
	if err != nil {
		log.Fatal(err)
	}
	fmt.Printf("%+v\n", response.Data)

Returns: created (integer), id (string), object (string), owned_by (string)

Create a response