telnyx-ai-inference-java

📁 team-telnyx/telnyx-ext-agent-skills 📅 2 days ago

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安装命令

npx skills add https://github.com/team-telnyx/telnyx-ext-agent-skills --skill telnyx-ai-inference-java

Agent 安装分布

opencode 2

gemini-cli 2

antigravity 2

claude-code 2

windsurf 2

github-copilot 2

Skill 文档

Telnyx Ai Inference – Java

Installation

// See https://github.com/team-telnyx/telnyx-java for Maven/Gradle setup

Setup

import com.telnyx.sdk.client.TelnyxClient;
import com.telnyx.sdk.client.okhttp.TelnyxOkHttpClient;

TelnyxClient client = TelnyxOkHttpClient.fromEnv();

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

List conversations

Retrieve a list of all AI conversations configured by the user.

GET /ai/conversations

import com.telnyx.sdk.models.ai.conversations.ConversationListParams;
import com.telnyx.sdk.models.ai.conversations.ConversationListResponse;

ConversationListResponse conversations = client.ai().conversations().list();

Create a conversation

Create a new AI Conversation.

POST /ai/conversations

Optional: metadata (object), name (string)

import com.telnyx.sdk.models.ai.conversations.Conversation;
import com.telnyx.sdk.models.ai.conversations.ConversationCreateParams;

Conversation conversation = client.ai().conversations().create();

Get Insight Template Groups

Get all insight groups

GET /ai/conversations/insight-groups

import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupRetrieveInsightGroupsPage;
import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupRetrieveInsightGroupsParams;

InsightGroupRetrieveInsightGroupsPage page = client.ai().conversations().insightGroups().retrieveInsightGroups();

Create Insight Template Group

Create a new insight group

POST /ai/conversations/insight-groups â Required: name

Optional: description (string), webhook (string)

import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupInsightGroupsParams;
import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightTemplateGroupDetail;

InsightGroupInsightGroupsParams params = InsightGroupInsightGroupsParams.builder()
    .name("name")
    .build();
InsightTemplateGroupDetail insightTemplateGroupDetail = client.ai().conversations().insightGroups().insightGroups(params);

Get Insight Template Group

Get insight group by ID

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

import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupRetrieveParams;
import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightTemplateGroupDetail;

InsightTemplateGroupDetail insightTemplateGroupDetail = client.ai().conversations().insightGroups().retrieve("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e");

Update Insight Template Group

Update an insight template group

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

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

import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupUpdateParams;
import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightTemplateGroupDetail;

InsightTemplateGroupDetail insightTemplateGroupDetail = client.ai().conversations().insightGroups().update("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e");

Delete Insight Template Group

Delete insight group by ID

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

import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupDeleteParams;

client.ai().conversations().insightGroups().delete("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e");

Assign Insight Template To Group

Assign an insight to a group

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

import com.telnyx.sdk.models.ai.conversations.insightgroups.insights.InsightAssignParams;

InsightAssignParams params = InsightAssignParams.builder()
    .groupId("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
    .insightId("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
    .build();
client.ai().conversations().insightGroups().insights().assign(params);

Unassign Insight Template From Group

Remove an insight from a group

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

import com.telnyx.sdk.models.ai.conversations.insightgroups.insights.InsightDeleteUnassignParams;

InsightDeleteUnassignParams params = InsightDeleteUnassignParams.builder()
    .groupId("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
    .insightId("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
    .build();
client.ai().conversations().insightGroups().insights().deleteUnassign(params);

Get Insight Templates

Get all insights

GET /ai/conversations/insights

import com.telnyx.sdk.models.ai.conversations.insights.InsightListPage;
import com.telnyx.sdk.models.ai.conversations.insights.InsightListParams;

InsightListPage page = client.ai().conversations().insights().list();

Create Insight Template

Create a new insight

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

Optional: json_schema (object), webhook (string)

import com.telnyx.sdk.models.ai.conversations.insights.InsightCreateParams;
import com.telnyx.sdk.models.ai.conversations.insights.InsightTemplateDetail;

InsightCreateParams params = InsightCreateParams.builder()
    .instructions("instructions")
    .name("name")
    .build();
InsightTemplateDetail insightTemplateDetail = client.ai().conversations().insights().create(params);

Get Insight Template

Get insight by ID

GET /ai/conversations/insights/{insight_id}

import com.telnyx.sdk.models.ai.conversations.insights.InsightRetrieveParams;
import com.telnyx.sdk.models.ai.conversations.insights.InsightTemplateDetail;

InsightTemplateDetail insightTemplateDetail = client.ai().conversations().insights().retrieve("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e");

Update Insight Template

Update an insight template

PUT /ai/conversations/insights/{insight_id}

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

import com.telnyx.sdk.models.ai.conversations.insights.InsightTemplateDetail;
import com.telnyx.sdk.models.ai.conversations.insights.InsightUpdateParams;

InsightTemplateDetail insightTemplateDetail = client.ai().conversations().insights().update("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e");

Delete Insight Template

Delete insight by ID

DELETE /ai/conversations/insights/{insight_id}

import com.telnyx.sdk.models.ai.conversations.insights.InsightDeleteParams;

client.ai().conversations().insights().delete("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e");

Get a conversation

Retrieve a specific AI conversation by its ID.

GET /ai/conversations/{conversation_id}

import com.telnyx.sdk.models.ai.conversations.ConversationRetrieveParams;
import com.telnyx.sdk.models.ai.conversations.ConversationRetrieveResponse;

ConversationRetrieveResponse conversation = client.ai().conversations().retrieve("conversation_id");

Update conversation metadata

Update metadata for a specific conversation.

PUT /ai/conversations/{conversation_id}

Optional: metadata (object)

import com.telnyx.sdk.models.ai.conversations.ConversationUpdateParams;
import com.telnyx.sdk.models.ai.conversations.ConversationUpdateResponse;

ConversationUpdateResponse conversation = client.ai().conversations().update("conversation_id");

Delete a conversation

Delete a specific conversation by its ID.

DELETE /ai/conversations/{conversation_id}

import com.telnyx.sdk.models.ai.conversations.ConversationDeleteParams;

client.ai().conversations().delete("conversation_id");

Get insights for a conversation

Retrieve insights for a specific conversation

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

import com.telnyx.sdk.models.ai.conversations.ConversationRetrieveConversationsInsightsParams;
import com.telnyx.sdk.models.ai.conversations.ConversationRetrieveConversationsInsightsResponse;

ConversationRetrieveConversationsInsightsResponse response = client.ai().conversations().retrieveConversationsInsights("conversation_id");

Create Message

Add a new message to the conversation.

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

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

import com.telnyx.sdk.models.ai.conversations.ConversationAddMessageParams;

ConversationAddMessageParams params = ConversationAddMessageParams.builder()
    .conversationId("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")
    .role("role")
    .build();
client.ai().conversations().addMessage(params);

Get conversation messages

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

GET /ai/conversations/{conversation_id}/messages

import com.telnyx.sdk.models.ai.conversations.messages.MessageListParams;
import com.telnyx.sdk.models.ai.conversations.messages.MessageListResponse;

MessageListResponse messages = client.ai().conversations().messages().list("conversation_id");

Get Tasks by Status

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

GET /ai/embeddings

import com.telnyx.sdk.models.ai.embeddings.EmbeddingListParams;
import com.telnyx.sdk.models.ai.embeddings.EmbeddingListResponse;

EmbeddingListResponse embeddings = client.ai().embeddings().list();

Embed documents

Perform embedding on a Telnyx Storage Bucket using an embedding model.

POST /ai/embeddings â Required: bucket_name

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

import com.telnyx.sdk.models.ai.embeddings.EmbeddingCreateParams;
import com.telnyx.sdk.models.ai.embeddings.EmbeddingResponse;

EmbeddingCreateParams params = EmbeddingCreateParams.builder()
    .bucketName("bucket_name")
    .build();
EmbeddingResponse embeddingResponse = client.ai().embeddings().create(params);

List embedded buckets

Get all embedding buckets for a user.

GET /ai/embeddings/buckets

import com.telnyx.sdk.models.ai.embeddings.buckets.BucketListParams;
import com.telnyx.sdk.models.ai.embeddings.buckets.BucketListResponse;

BucketListResponse buckets = client.ai().embeddings().buckets().list();

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}

import com.telnyx.sdk.models.ai.embeddings.buckets.BucketRetrieveParams;
import com.telnyx.sdk.models.ai.embeddings.buckets.BucketRetrieveResponse;

BucketRetrieveResponse bucket = client.ai().embeddings().buckets().retrieve("bucket_name");

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}

import com.telnyx.sdk.models.ai.embeddings.buckets.BucketDeleteParams;

client.ai().embeddings().buckets().delete("bucket_name");

Search for documents

Perform a similarity search on a Telnyx Storage Bucket, returning the most similar num_docs document chunks to the query.

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

Optional: num_of_docs (integer)

import com.telnyx.sdk.models.ai.embeddings.EmbeddingSimilaritySearchParams;
import com.telnyx.sdk.models.ai.embeddings.EmbeddingSimilaritySearchResponse;

EmbeddingSimilaritySearchParams params = EmbeddingSimilaritySearchParams.builder()
    .bucketName("bucket_name")
    .query("query")
    .build();
EmbeddingSimilaritySearchResponse response = client.ai().embeddings().similaritySearch(params);

Embed URL content

Embed website content from a specified URL, including child pages up to 5 levels deep within the same domain.

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

import com.telnyx.sdk.models.ai.embeddings.EmbeddingResponse;
import com.telnyx.sdk.models.ai.embeddings.EmbeddingUrlParams;

EmbeddingUrlParams params = EmbeddingUrlParams.builder()
    .bucketName("bucket_name")
    .url("url")
    .build();
EmbeddingResponse embeddingResponse = client.ai().embeddings().url(params);

Get an embedding task’s status

Check the status of a current embedding task.

GET /ai/embeddings/{task_id}

import com.telnyx.sdk.models.ai.embeddings.EmbeddingRetrieveParams;
import com.telnyx.sdk.models.ai.embeddings.EmbeddingRetrieveResponse;

EmbeddingRetrieveResponse embedding = client.ai().embeddings().retrieve("task_id");

List all clusters

GET /ai/clusters

import com.telnyx.sdk.models.ai.clusters.ClusterListPage;
import com.telnyx.sdk.models.ai.clusters.ClusterListParams;

ClusterListPage page = client.ai().clusters().list();

Compute new clusters

Starts a background task to compute how the data in an embedded storage bucket is clustered.

POST /ai/clusters â Required: bucket

Optional: files (array[string]), min_cluster_size (integer), min_subcluster_size (integer), prefix (string)

import com.telnyx.sdk.models.ai.clusters.ClusterComputeParams;
import com.telnyx.sdk.models.ai.clusters.ClusterComputeResponse;

ClusterComputeParams params = ClusterComputeParams.builder()
    .bucket("bucket")
    .build();
ClusterComputeResponse response = client.ai().clusters().compute(params);

Fetch a cluster

GET /ai/clusters/{task_id}

import com.telnyx.sdk.models.ai.clusters.ClusterRetrieveParams;
import com.telnyx.sdk.models.ai.clusters.ClusterRetrieveResponse;

ClusterRetrieveResponse cluster = client.ai().clusters().retrieve("task_id");

Delete a cluster

DELETE /ai/clusters/{task_id}

import com.telnyx.sdk.models.ai.clusters.ClusterDeleteParams;

client.ai().clusters().delete("task_id");

Fetch a cluster visualization

GET /ai/clusters/{task_id}/graph

import com.telnyx.sdk.core.http.HttpResponse;
import com.telnyx.sdk.models.ai.clusters.ClusterFetchGraphParams;

HttpResponse response = client.ai().clusters().fetchGraph("task_id");

Transcribe speech to text

Transcribe speech to text.

POST /ai/audio/transcriptions

import com.telnyx.sdk.models.ai.audio.AudioTranscribeParams;
import com.telnyx.sdk.models.ai.audio.AudioTranscribeResponse;

AudioTranscribeParams params = AudioTranscribeParams.builder()
    .model(AudioTranscribeParams.Model.DISTIL_WHISPER_DISTIL_LARGE_V2)
    .build();
AudioTranscribeResponse response = client.ai().audio().transcribe(params);

Create a chat completion

Chat with a language model.

POST /ai/chat/completions â Required: messages

Optional: api_key_ref (string), best_of (integer), early_stopping (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), tools (array[object]), top_logprobs (integer), top_p (number), use_beam_search (boolean)

import com.telnyx.sdk.models.ai.chat.ChatCreateCompletionParams;
import com.telnyx.sdk.models.ai.chat.ChatCreateCompletionResponse;

ChatCreateCompletionParams params = ChatCreateCompletionParams.builder()
    .addMessage(ChatCreateCompletionParams.Message.builder()
        .content("You are a friendly chatbot.")
        .role(ChatCreateCompletionParams.Message.Role.SYSTEM)
        .build())
    .addMessage(ChatCreateCompletionParams.Message.builder()
        .content("Hello, world!")
        .role(ChatCreateCompletionParams.Message.Role.USER)
        .build())
    .build();
ChatCreateCompletionResponse response = client.ai().chat().createCompletion(params);

List fine tuning jobs

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

GET /ai/fine_tuning/jobs

import com.telnyx.sdk.models.ai.finetuning.jobs.JobListParams;
import com.telnyx.sdk.models.ai.finetuning.jobs.JobListResponse;

JobListResponse jobs = client.ai().fineTuning().jobs().list();

Create a fine tuning job

Create a new fine tuning job.

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

Optional: hyperparameters (object), suffix (string)

import com.telnyx.sdk.models.ai.finetuning.jobs.FineTuningJob;
import com.telnyx.sdk.models.ai.finetuning.jobs.JobCreateParams;

JobCreateParams params = JobCreateParams.builder()
    .model("model")
    .trainingFile("training_file")
    .build();
FineTuningJob fineTuningJob = client.ai().fineTuning().jobs().create(params);

Get a fine tuning job

Retrieve a fine tuning job by job_id.

GET /ai/fine_tuning/jobs/{job_id}

import com.telnyx.sdk.models.ai.finetuning.jobs.FineTuningJob;
import com.telnyx.sdk.models.ai.finetuning.jobs.JobRetrieveParams;

FineTuningJob fineTuningJob = client.ai().fineTuning().jobs().retrieve("job_id");

Cancel a fine tuning job

Cancel a fine tuning job.

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

import com.telnyx.sdk.models.ai.finetuning.jobs.FineTuningJob;
import com.telnyx.sdk.models.ai.finetuning.jobs.JobCancelParams;

FineTuningJob fineTuningJob = client.ai().fineTuning().jobs().cancel("job_id");

Create embeddings

Creates an embedding vector representing the input text.

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

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

import com.telnyx.sdk.models.ai.openai.embeddings.EmbeddingCreateEmbeddingsParams;
import com.telnyx.sdk.models.ai.openai.embeddings.EmbeddingCreateEmbeddingsResponse;

EmbeddingCreateEmbeddingsParams params = EmbeddingCreateEmbeddingsParams.builder()
    .input("The quick brown fox jumps over the lazy dog")
    .model("thenlper/gte-large")
    .build();
EmbeddingCreateEmbeddingsResponse response = client.ai().openai().embeddings().createEmbeddings(params);

List embedding models

Returns a list of available embedding models.

GET /ai/openai/embeddings/models

import com.telnyx.sdk.models.ai.openai.embeddings.EmbeddingListEmbeddingModelsParams;
import com.telnyx.sdk.models.ai.openai.embeddings.EmbeddingListEmbeddingModelsResponse;

EmbeddingListEmbeddingModelsResponse response = client.ai().openai().embeddings().listEmbeddingModels();

Get available models

This endpoint returns a list of Open Source and OpenAI models that are available for use.

GET /ai/models

import com.telnyx.sdk.models.ai.AiRetrieveModelsParams;
import com.telnyx.sdk.models.ai.AiRetrieveModelsResponse;

AiRetrieveModelsResponse response = client.ai().retrieveModels();

Summarize file content

Generate a summary of a file’s contents.

POST /ai/summarize â Required: bucket, filename

Optional: system_prompt (string)

import com.telnyx.sdk.models.ai.AiSummarizeParams;
import com.telnyx.sdk.models.ai.AiSummarizeResponse;

AiSummarizeParams params = AiSummarizeParams.builder()
    .bucket("bucket")
    .filename("filename")
    .build();
AiSummarizeResponse response = client.ai().summarize(params);

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