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tessl/maven-dev-langchain4j--langchain4j-github-models

This package provides a deprecated integration module that enables Java applications to interact with GitHub Models through the LangChain4j framework. It offers chat models (both synchronous and streaming), embedding models, and support for AI services with tool integration, JSON schema responses, and responsible AI features. The module wraps Azure AI Inference SDK to provide a unified API for accessing various language models hosted on GitHub Models, including chat completion capabilities, embeddings generation, and content filtering management. As of version 1.10.0, this module has been marked for deprecation and future removal, with users recommended to migrate to the langchain4j-openai-official module for enhanced functionality and better integration. The library is designed for reusability as a foundational component in LLM-powered Java applications that need to leverage GitHub-hosted AI models, offering builder patterns for configuration, support for proxy options, custom timeouts, and comprehensive model service versioning capabilities.

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Files

embedding-model-api.mddocs/api/

Embedding Model API Reference

API reference for GitHubModelsEmbeddingModel - text embedding generation.

Class

package dev.langchain4j.model.github;

public class GitHubModelsEmbeddingModel extends DimensionAwareEmbeddingModel {
    public static final int BATCH_SIZE = 16;

    public Response<List<Embedding>> embedAll(List<TextSegment> textSegments);
    public String modelName();
    public static Builder builder();
    protected Integer knownDimension();
}

Constants

BATCH_SIZE

public static final int BATCH_SIZE = 16;

Maximum segments per API request. Lists larger than 16 are automatically split into multiple batches.

Value: 16

Methods

embedAll

public Response<List<Embedding>> embedAll(List<TextSegment> textSegments);

Generate embeddings for text segments. Automatically batches large lists.

Parameters:

  • textSegments: List<TextSegment> - Segments to embed

Returns:

  • Response<List<Embedding>> - Embeddings and token usage

Throws:

  • HttpResponseException - On API errors

Note: Lists > 16 segments split into multiple batches transparently

modelName

public String modelName();

Get model name.

Returns:

  • String - Model identifier

builder

public static Builder builder();

Create builder instance. Uses SPI factory if registered.

Returns:

  • Builder - Builder instance

knownDimension

protected Integer knownDimension();

Get known embedding dimension (protected, internal use).

Returns:

  • Integer - Dimension, or null if unknown

Builder API

public static class Builder {
    // Required
    public Builder gitHubToken(String gitHubToken);
    public Builder modelName(String modelName);
    public Builder modelName(GitHubModelsEmbeddingModelName modelName);

    // Endpoint
    public Builder endpoint(String endpoint);
    public Builder serviceVersion(ModelServiceVersion serviceVersion);

    // Embedding
    public Builder dimensions(Integer dimensions);

    // Network
    public Builder timeout(Duration timeout);
    public Builder maxRetries(Integer maxRetries);
    public Builder proxyOptions(ProxyOptions proxyOptions);
    public Builder customHeaders(Map<String, String> customHeaders);

    // Advanced
    public Builder embeddingsClient(EmbeddingsClient embeddingsClient);
    public Builder logRequestsAndResponses(boolean logRequestsAndResponses);
    public Builder userAgentSuffix(String userAgentSuffix);

    public GitHubModelsEmbeddingModel build();
}

gitHubToken

public Builder gitHubToken(String gitHubToken);

Set GitHub personal access token (required).

Parameters:

  • gitHubToken: String - GitHub token

Returns:

  • Builder

modelName

public Builder modelName(String modelName);
public Builder modelName(GitHubModelsEmbeddingModelName modelName);

Set embedding model name (required).

Parameters:

  • modelName: String or GitHubModelsEmbeddingModelName - Model identifier

Returns:

  • Builder

endpoint

public Builder endpoint(String endpoint);

Set API endpoint (default: https://models.inference.ai.azure.com).

Parameters:

  • endpoint: String - Endpoint URL

Returns:

  • Builder

serviceVersion

public Builder serviceVersion(ModelServiceVersion serviceVersion);

Set Azure API service version.

Parameters:

  • serviceVersion: ModelServiceVersion - API version

Returns:

  • Builder

dimensions

public Builder dimensions(Integer dimensions);

Set custom embedding dimensions (if model supports).

Parameters:

  • dimensions: Integer - Desired dimension

Returns:

  • Builder

Note: Not all models support custom dimensions

timeout

public Builder timeout(Duration timeout);

Set request timeout.

Parameters:

  • timeout: Duration - Timeout duration

Returns:

  • Builder

maxRetries

public Builder maxRetries(Integer maxRetries);

Set maximum retry attempts.

Parameters:

  • maxRetries: Integer - Max retries

Returns:

  • Builder

proxyOptions

public Builder proxyOptions(ProxyOptions proxyOptions);

Set HTTP proxy configuration.

Parameters:

  • proxyOptions: ProxyOptions - Proxy configuration

Returns:

  • Builder

customHeaders

public Builder customHeaders(Map<String, String> customHeaders);

Set custom HTTP headers.

Parameters:

  • customHeaders: Map<String, String> - Custom headers

Returns:

  • Builder

embeddingsClient

public Builder embeddingsClient(EmbeddingsClient embeddingsClient);

Set custom Azure AI embeddings client (overrides other config).

Parameters:

  • embeddingsClient: EmbeddingsClient - Custom client

Returns:

  • Builder

logRequestsAndResponses

public Builder logRequestsAndResponses(boolean logRequestsAndResponses);

Enable request/response logging.

Parameters:

  • logRequestsAndResponses: boolean - Enable logging

Returns:

  • Builder

userAgentSuffix

public Builder userAgentSuffix(String userAgentSuffix);

Set User-Agent suffix.

Parameters:

  • userAgentSuffix: String - Suffix

Returns:

  • Builder

build

public GitHubModelsEmbeddingModel build();

Build model instance.

Returns:

  • GitHubModelsEmbeddingModel

Throws:

  • IllegalStateException - If required fields missing

Types

import dev.langchain4j.model.embedding.DimensionAwareEmbeddingModel;
import dev.langchain4j.data.embedding.Embedding;
import dev.langchain4j.data.segment.TextSegment;
import dev.langchain4j.model.output.Response;
import dev.langchain4j.model.output.TokenUsage;
import com.azure.ai.inference.EmbeddingsClient;
import com.azure.ai.inference.ModelServiceVersion;
import com.azure.core.http.ProxyOptions;
import com.azure.core.exception.HttpResponseException;
import java.time.Duration;
import java.util.List;
import java.util.Map;

Install with Tessl CLI

npx tessl i tessl/maven-dev-langchain4j--langchain4j-github-models

docs

api

chat-model-api.md

embedding-model-api.md

model-names-api.md

streaming-chat-model-api.md

index.md

quick-reference.md

tile.json