org.llm4s.llmconnect.provider

Attributes

Companion: object
Supertypes: trait MetricsRecording

trait LLMClient

class Object

trait Matchable

class Any

Attributes

Companion: class
Supertypes: class Object

trait Matchable

class Any
Self type: AnthropicClient.type

DeepSeek LLM client implementation using the OpenAI-compatible API.

Provides access to DeepSeek models including DeepSeek-Chat (V3) with 64K context and DeepSeek-Reasoner (R1) with 128K context for advanced reasoning tasks.

Uses the same request/response format as OpenAI, making it compatible with standard OpenAI tooling and client code patterns.

Value parameters

config: DeepSeek configuration containing API key, model, base URL, and context settings
metrics: MetricsCollector for recording request metrics

Attributes

Companion: object
Supertypes: trait MetricsRecording

trait LLMClient

class Object

trait Matchable

class Any

Attributes

Companion: class
Supertypes: class Object

trait Matchable

class Any
Self type: DeepSeekClient.type

Text embedding provider interface for generating vector representations.

Provides a unified interface for different embedding services (OpenAI, VoyageAI, Ollama). Each implementation handles provider-specific API calls and response formats.

Text content is the primary input; multimedia content (images, audio) should be processed through the UniversalEncoder façade which handles content extraction before embedding.

== Usage Example ==

val provider: EmbeddingProvider = OpenAIEmbeddingProvider.fromConfig(config)
val request = EmbeddingRequest(
 input = Seq("Hello world", "How are you?"),
 model = EmbeddingModelName("text-embedding-3-small")
)
val result: Result[EmbeddingResponse] = provider.embed(request)

Attributes

See also: OpenAIEmbeddingProvider for OpenAI text-embedding models

VoyageAIEmbeddingProvider for VoyageAI embedding models

OllamaEmbeddingProvider for local Ollama embedding models
Supertypes: class Object

trait Matchable

class Any

LLMClient implementation for Google Gemini models.

Provides access to Gemini 2.0, 1.5 Pro, 1.5 Flash and other Gemini models via Google's Generative AI API.

== Supported Features ==

Chat completions
Streaming responses
Tool/function calling
Large context windows (up to 1M+ tokens)

== Configuration ==

export LLM_MODEL=gemini/gemini-2.0-flash
export GOOGLE_API_KEY=your-api-key

== API Format ==

Gemini uses a different message format than OpenAI:

Messages have role (user/model) and parts (array of content)
System instructions are sent separately
Tool calls use functionDeclarations format

Value parameters

config: Gemini configuration with API key, model, and base URL
metrics: metrics collector for observability (default: noop)

Attributes

See also: org.llm4s.llmconnect.config.GeminiConfig for configuration options
Companion: object
Supertypes: trait MetricsRecording

trait LLMClient

class Object

trait Matchable

class Any

Attributes

Companion: class
Supertypes: class Object

trait Matchable

class Any
Self type: GeminiClient.type

Enumeration of supported LLM providers.

Defines the available language model service providers that can be used with llm4s. Each provider has specific configuration requirements and API characteristics.

Attributes

See also: org.llm4s.llmconnect.config.ProviderConfig for provider-specific configuration
Companion: object
Supertypes: class Object

trait Matchable

class Any
Known subtypes: object Anthropic

object Azure

object DeepSeek

object Gemini

object Ollama

object OpenAI

object OpenRouter

object Zai
Show all

Companion object providing LLM provider instances and utilities.

Attributes

Companion: trait
Supertypes: trait Sum

trait Mirror

class Object

trait Matchable

class Any
Self type: LLMProvider.type

Helper trait for recording metrics consistently across all provider clients.

Extracts the common pattern of timing requests, observing outcomes, recording tokens, and calculating costs.

Attributes

Supertypes: class Object

trait Matchable

class Any
Known subtypes: class AnthropicClient

class DeepSeekClient

class GeminiClient

class OllamaClient

class OpenAIClient

class OpenRouterClient

class ZaiClient
Show all

Attributes

Companion: object
Supertypes: trait MetricsRecording

trait LLMClient

class Object

trait Matchable

class Any

Attributes

Companion: class
Supertypes: class Object

trait Matchable

class Any
Self type: OllamaClient.type

Attributes

Supertypes: class Object

trait Matchable

class Any
Self type: OllamaEmbeddingProvider.type

LLMClient implementation supporting both OpenAI and Azure OpenAI services.

Provides a unified interface for interacting with OpenAI's API and Azure's OpenAI service. Handles message conversion between llm4s format and OpenAI format, completion requests, streaming responses, and tool calling (function calling) capabilities.

Uses Azure's OpenAI client library internally, which supports both direct OpenAI and Azure-hosted OpenAI endpoints.

== Extended Thinking / Reasoning Support ==

For OpenAI o1/o3/o4 models with reasoning capabilities, use OpenRouterClient instead, which fully supports the reasoning_effort parameter. The Azure SDK used by this client does not yet expose the reasoning_effort API parameter.

For Anthropic Claude models with extended thinking, use AnthropicClient which has full support for the thinking parameter with budget_tokens.

Value parameters

client: configured Azure OpenAI client instance
config: provider configuration containing context window and reserve completion settings
metrics: metrics collector for observability (default: noop)
model: the model identifier (e.g., "gpt-4", "gpt-3.5-turbo")

Attributes

Companion: object
Supertypes: trait MetricsRecording

trait LLMClient

class Object

trait Matchable

class Any

Factory methods for creating OpenAIClient instances.

Provides safe construction of OpenAI clients with error handling via Result type.

Attributes

Companion: class
Supertypes: class Object

trait Matchable

class Any
Self type: OpenAIClient.type

OpenAI embedding provider implementation.

Provides text embeddings using OpenAI's embedding API (text-embedding-3-small, text-embedding-3-large, text-embedding-ada-002). Supports batch embedding of multiple texts in a single request.

== Supported Models ==

text-embedding-3-small - Efficient, lower cost (recommended)
text-embedding-3-large - Higher quality, higher cost
text-embedding-ada-002 - Legacy model

== Token Usage == The response includes token usage information when available from the API.

Attributes

See also: EmbeddingProvider for the provider interface

org.llm4s.llmconnect.config.EmbeddingProviderConfig for configuration
Supertypes: class Object

trait Matchable

class Any
Self type: OpenAIEmbeddingProvider.type

Attributes

Companion: object
Supertypes: trait MetricsRecording

trait LLMClient

class Object

trait Matchable

class Any

Attributes

Companion: class
Supertypes: class Object

trait Matchable

class Any
Self type: OpenRouterClient.type

Attributes

Supertypes: class Object

trait Matchable

class Any
Self type: VoyageAIEmbeddingProvider.type

Attributes

Companion: object
Supertypes: trait MetricsRecording

trait LLMClient

class Object

trait Matchable

class Any

Attributes

Companion: class
Supertypes: class Object

trait Matchable

class Any
Self type: ZaiClient.type

org.llm4s.llmconnect.provider

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