Configuration

Client Configuration

config := omnillm.ClientConfig{
    Providers: []omnillm.ProviderConfig{
        {
            Provider: omnillm.ProviderNameOpenAI,
            APIKey:   "your-api-key",
            BaseURL:  "https://custom-endpoint.com/v1", // Optional
            Extra: map[string]any{
                "timeout": 60, // Custom provider-specific settings
            },
        },
    },
}

Request Parameters

ChatCompletionRequest supports the following parameters:

Parameter	Type	Providers	Description
Model	string	All	Model identifier (required)
Messages	[]Message	All	Conversation messages (required)
MaxTokens	*int	All	Maximum tokens to generate
Temperature	*float64	All	Randomness (0.0-2.0)
TopP	*float64	All	Nucleus sampling threshold
TopK	*int	Anthropic, Gemini, Ollama	Top K token selection
Stop	[]string	All	Stop sequences
PresencePenalty	*float64	OpenAI, X.AI	Penalize tokens by presence
FrequencyPenalty	*float64	OpenAI, X.AI	Penalize tokens by frequency
Seed	*int	OpenAI, X.AI, Ollama	Reproducible outputs
N	*int	OpenAI	Number of completions
ResponseFormat	*ResponseFormat	OpenAI, Gemini	JSON mode
Logprobs	*bool	OpenAI	Return log probabilities
TopLogprobs	*int	OpenAI	Top logprobs count (0-20)
User	*string	OpenAI	End-user identifier
LogitBias	map[string]int	OpenAI	Token bias adjustments

Example: Advanced Request

// Helper for pointer values
func ptr[T any](v T) *T { return &v }

// Reproducible outputs with seed
response, err := client.CreateChatCompletion(ctx, &omnillm.ChatCompletionRequest{
    Model:    omnillm.ModelGPT4o,
    Messages: messages,
    Seed:     ptr(42), // Same seed = same output
})

// JSON mode response
response, err := client.CreateChatCompletion(ctx, &omnillm.ChatCompletionRequest{
    Model:    omnillm.ModelGPT4o,
    Messages: messages,
    ResponseFormat: &omnillm.ResponseFormat{Type: "json_object"},
})

// TopK sampling (Anthropic/Gemini/Ollama)
response, err := client.CreateChatCompletion(ctx, &omnillm.ChatCompletionRequest{
    Model:    omnillm.ModelClaude3Sonnet,
    Messages: messages,
    TopK:     ptr(40), // Consider only top 40 tokens
})

Logging Configuration

OmniLLM supports injectable logging via Go's standard log/slog package:

import (
    "log/slog"
    "os"

    "github.com/agentplexus/omnillm"
)

logger := slog.New(slog.NewJSONHandler(os.Stderr, &slog.HandlerOptions{
    Level: slog.LevelDebug,
}))

client, err := omnillm.NewClient(omnillm.ClientConfig{
    Providers: []omnillm.ProviderConfig{
        {Provider: omnillm.ProviderNameOpenAI, APIKey: "your-api-key"},
    },
    Logger: logger,
})

Context-Aware Logging

Attach request-scoped attributes to all log output:

import "github.com/grokify/mogo/log/slogutil"

reqLogger := slog.Default().With(
    slog.String("trace_id", traceID),
    slog.String("user_id", userID),
)

ctx = slogutil.ContextWithLogger(ctx, reqLogger)

// All internal logging will now include trace_id and user_id
response, err := client.CreateChatCompletionWithMemory(ctx, sessionID, req)