rig-core 0.40.0

An opinionated library for building LLM powered applications.
Documentation
// ================================================================
//! Together AI Completion Integration
//! From [Together AI Reference](https://docs.together.ai/docs/chat-overview)
// ================================================================

use crate::providers::openai;

use super::client::TogetherExt;

// ================================================================
// Together Completion Models
// ================================================================

pub const YI_34B_CHAT: &str = "zero-one-ai/Yi-34B-Chat";
pub const OLMO_7B_INSTRUCT: &str = "allenai/OLMo-7B-Instruct";
pub const CHRONOS_HERMES_13B: &str = "Austism/chronos-hermes-13b";
pub const ML318BR: &str = "carson/ml318br";
pub const DOLPHIN_2_5_MIXTRAL_8X7B: &str = "cognitivecomputations/dolphin-2.5-mixtral-8x7b";
pub const DBRX_INSTRUCT: &str = "databricks/dbrx-instruct";
pub const DEEPSEEK_LLM_67B_CHAT: &str = "deepseek-ai/deepseek-llm-67b-chat";
pub const DEEPSEEK_CODER_33B_INSTRUCT: &str = "deepseek-ai/deepseek-coder-33b-instruct";
pub const PLATYPUS2_70B_INSTRUCT: &str = "garage-bAInd/Platypus2-70B-instruct";
pub const GEMMA_2_9B_IT: &str = "google/gemma-2-9b-it";
pub const GEMMA_2B_IT: &str = "google/gemma-2b-it";
pub const GEMMA_2_27B_IT: &str = "google/gemma-2-27b-it";
pub const GEMMA_7B_IT: &str = "google/gemma-7b-it";
pub const LLAMA_3_70B_INSTRUCT_GRADIENT_1048K: &str =
    "gradientai/Llama-3-70B-Instruct-Gradient-1048k";
pub const MYTHOMAX_L2_13B: &str = "Gryphe/MythoMax-L2-13b";
pub const MYTHOMAX_L2_13B_LITE: &str = "Gryphe/MythoMax-L2-13b-Lite";
pub const LLAVA_NEXT_MISTRAL_7B: &str = "llava-hf/llava-v1.6-mistral-7b-hf";
pub const ZEPHYR_7B_BETA: &str = "HuggingFaceH4/zephyr-7b-beta";
pub const KOALA_7B: &str = "togethercomputer/Koala-7B";
pub const VICUNA_7B_V1_3: &str = "lmsys/vicuna-7b-v1.3";
pub const VICUNA_13B_V1_5_16K: &str = "lmsys/vicuna-13b-v1.5-16k";
pub const VICUNA_13B_V1_5: &str = "lmsys/vicuna-13b-v1.5";
pub const VICUNA_13B_V1_3: &str = "lmsys/vicuna-13b-v1.3";
pub const KOALA_13B: &str = "togethercomputer/Koala-13B";
pub const VICUNA_7B_V1_5: &str = "lmsys/vicuna-7b-v1.5";
pub const CODE_LLAMA_34B_INSTRUCT: &str = "codellama/CodeLlama-34b-Instruct-hf";
pub const LLAMA_3_8B_CHAT_HF_INT4: &str = "togethercomputer/Llama-3-8b-chat-hf-int4";
pub const LLAMA_3_2_90B_VISION_INSTRUCT_TURBO: &str =
    "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo";
pub const LLAMA_3_2_11B_VISION_INSTRUCT_TURBO: &str =
    "meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo";
pub const LLAMA_3_2_3B_INSTRUCT_TURBO: &str = "meta-llama/Llama-3.2-3B-Instruct-Turbo";
pub const LLAMA_3_8B_CHAT_HF_INT8: &str = "togethercomputer/Llama-3-8b-chat-hf-int8";
pub const LLAMA_3_1_70B_INSTRUCT_TURBO: &str = "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo";
pub const LLAMA_2_13B_CHAT: &str = "meta-llama/Llama-2-13b-chat-hf";
pub const LLAMA_3_70B_INSTRUCT_LITE: &str = "meta-llama/Meta-Llama-3-70B-Instruct-Lite";
pub const LLAMA_3_8B_CHAT_HF: &str = "meta-llama/Llama-3-8b-chat-hf";
pub const LLAMA_3_70B_CHAT_HF: &str = "meta-llama/Llama-3-70b-chat-hf";
pub const LLAMA_3_8B_INSTRUCT_TURBO: &str = "meta-llama/Meta-Llama-3-8B-Instruct-Turbo";
pub const LLAMA_3_8B_INSTRUCT_LITE: &str = "meta-llama/Meta-Llama-3-8B-Instruct-Lite";
pub const LLAMA_3_1_405B_INSTRUCT_LITE_PRO: &str =
    "meta-llama/Meta-Llama-3.1-405B-Instruct-Lite-Pro";
pub const LLAMA_2_7B_CHAT: &str = "meta-llama/Llama-2-7b-chat-hf";
pub const LLAMA_3_1_405B_INSTRUCT_TURBO: &str = "meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo";
pub const LLAMA_VISION_FREE: &str = "meta-llama/Llama-Vision-Free";
pub const LLAMA_3_70B_INSTRUCT_TURBO: &str = "meta-llama/Meta-Llama-3-70B-Instruct-Turbo";
pub const LLAMA_3_1_8B_INSTRUCT_TURBO: &str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo";
pub const CODE_LLAMA_7B_INSTRUCT_TOGETHER: &str = "togethercomputer/CodeLlama-7b-Instruct";
pub const CODE_LLAMA_34B_INSTRUCT_TOGETHER: &str = "togethercomputer/CodeLlama-34b-Instruct";
pub const CODE_LLAMA_13B_INSTRUCT: &str = "codellama/CodeLlama-13b-Instruct-hf";
pub const CODE_LLAMA_13B_INSTRUCT_TOGETHER: &str = "togethercomputer/CodeLlama-13b-Instruct";
pub const LLAMA_2_13B_CHAT_TOGETHER: &str = "togethercomputer/llama-2-13b-chat";
pub const LLAMA_2_7B_CHAT_TOGETHER: &str = "togethercomputer/llama-2-7b-chat";
pub const LLAMA_3_8B_INSTRUCT: &str = "meta-llama/Meta-Llama-3-8B-Instruct";
pub const LLAMA_3_70B_INSTRUCT: &str = "meta-llama/Meta-Llama-3-70B-Instruct";
pub const CODE_LLAMA_70B_INSTRUCT: &str = "codellama/CodeLlama-70b-Instruct-hf";
pub const LLAMA_2_70B_CHAT_TOGETHER: &str = "togethercomputer/llama-2-70b-chat";
pub const LLAMA_3_1_8B_INSTRUCT_REFERENCE: &str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Reference";
pub const LLAMA_3_1_70B_INSTRUCT_REFERENCE: &str =
    "meta-llama/Meta-Llama-3.1-70B-Instruct-Reference";
pub const WIZARDLM_2_8X22B: &str = "microsoft/WizardLM-2-8x22B";
pub const MISTRAL_7B_INSTRUCT_V0_1: &str = "mistralai/Mistral-7B-Instruct-v0.1";
pub const MISTRAL_7B_INSTRUCT_V0_2: &str = "mistralai/Mistral-7B-Instruct-v0.2";
pub const MISTRAL_7B_INSTRUCT_V0_3: &str = "mistralai/Mistral-7B-Instruct-v0.3";
pub const MIXTRAL_8X7B_INSTRUCT_V0_1: &str = "mistralai/Mixtral-8x7B-Instruct-v0.1";
pub const MIXTRAL_8X22B_INSTRUCT_V0_1: &str = "mistralai/Mixtral-8x22B-Instruct-v0.1";
pub const NOUS_HERMES_2_MIXTRAL_8X7B_DPO: &str = "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO";
pub const NOUS_HERMES_LLAMA2_70B: &str = "NousResearch/Nous-Hermes-Llama2-70b";
pub const NOUS_HERMES_2_MIXTRAL_8X7B_SFT: &str = "NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT";
pub const NOUS_HERMES_LLAMA2_13B: &str = "NousResearch/Nous-Hermes-Llama2-13b";
pub const NOUS_HERMES_2_MISTRAL_DPO: &str = "NousResearch/Nous-Hermes-2-Mistral-7B-DPO";
pub const NOUS_HERMES_LLAMA2_7B: &str = "NousResearch/Nous-Hermes-llama-2-7b";
pub const NOUS_CAPYBARA_V1_9: &str = "NousResearch/Nous-Capybara-7B-V1p9";
pub const HERMES_2_THETA_LLAMA_3_70B: &str = "NousResearch/Hermes-2-Theta-Llama-3-70B";
pub const OPENCHAT_3_5: &str = "openchat/openchat-3.5-1210";
pub const OPENORCA_MISTRAL_7B_8K: &str = "Open-Orca/Mistral-7B-OpenOrca";
pub const QWEN_2_72B_INSTRUCT: &str = "Qwen/Qwen2-72B-Instruct";
pub const QWEN2_5_72B_INSTRUCT_TURBO: &str = "Qwen/Qwen2.5-72B-Instruct-Turbo";
pub const QWEN2_5_7B_INSTRUCT_TURBO: &str = "Qwen/Qwen2.5-7B-Instruct-Turbo";
pub const QWEN1_5_110B_CHAT: &str = "Qwen/Qwen1.5-110B-Chat";
pub const QWEN1_5_72B_CHAT: &str = "Qwen/Qwen1.5-72B-Chat";
pub const QWEN_2_1_5B_INSTRUCT: &str = "Qwen/Qwen2-1.5B-Instruct";
pub const QWEN_2_7B_INSTRUCT: &str = "Qwen/Qwen2-7B-Instruct";
pub const QWEN1_5_14B_CHAT: &str = "Qwen/Qwen1.5-14B-Chat";
pub const QWEN1_5_1_8B_CHAT: &str = "Qwen/Qwen1.5-1.8B-Chat";
pub const QWEN1_5_32B_CHAT: &str = "Qwen/Qwen1.5-32B-Chat";
pub const QWEN1_5_7B_CHAT: &str = "Qwen/Qwen1.5-7B-Chat";
pub const QWEN1_5_0_5B_CHAT: &str = "Qwen/Qwen1.5-0.5B-Chat";
pub const QWEN1_5_4B_CHAT: &str = "Qwen/Qwen1.5-4B-Chat";
pub const SNORKEL_MISTRAL_PAIRRM_DPO: &str = "snorkelai/Snorkel-Mistral-PairRM-DPO";
pub const SNOWFLAKE_ARCTIC_INSTRUCT: &str = "Snowflake/snowflake-arctic-instruct";
pub const ALPACA_7B: &str = "togethercomputer/alpaca-7b";
pub const OPENHERMES_2_MISTRAL_7B: &str = "teknium/OpenHermes-2-Mistral-7B";
pub const OPENHERMES_2_5_MISTRAL_7B: &str = "teknium/OpenHermes-2p5-Mistral-7B";
pub const GUANACO_65B: &str = "togethercomputer/guanaco-65b";
pub const GUANACO_13B: &str = "togethercomputer/guanaco-13b";
pub const GUANACO_33B: &str = "togethercomputer/guanaco-33b";
pub const GUANACO_7B: &str = "togethercomputer/guanaco-7b";
pub const REMM_SLERP_L2_13B: &str = "Undi95/ReMM-SLERP-L2-13B";
pub const TOPPY_M_7B: &str = "Undi95/Toppy-M-7B";
pub const SOLAR_10_7B_INSTRUCT_V1: &str = "upstage/SOLAR-10.7B-Instruct-v1.0";
pub const SOLAR_10_7B_INSTRUCT_V1_INT4: &str = "togethercomputer/SOLAR-10.7B-Instruct-v1.0-int4";
pub const WIZARDLM_13B_V1_2: &str = "WizardLM/WizardLM-13B-V1.2";

// =================================================================
// Rig Implementation Types
// =================================================================

/// Together AI completion model, driven by the shared OpenAI Chat Completions path.
pub type CompletionModel<H = reqwest::Client> =
    openai::completion::GenericCompletionModel<TogetherExt, H>;

#[cfg(test)]
mod tests {
    use crate::client::CompletionClient;
    use crate::completion::{CompletionError, CompletionModel};
    use crate::providers::openai::completion::{
        CompletionRequest as OpenAICompletionRequest, OpenAIRequestParams,
    };
    use crate::test_utils::RecordingHttpClient;
    use crate::{OneOrMany, message};

    use super::super::client::Client;

    #[tokio::test]
    async fn completion_preserves_raw_provider_error_json_on_api_error_envelope() {
        let body = r#"{"error":"model unavailable","code":"model_overloaded"}"#;
        let http_client =
            RecordingHttpClient::with_error_response(http::StatusCode::ACCEPTED, body);
        let client = Client::builder()
            .api_key("test-key")
            .http_client(http_client)
            .build()
            .expect("build client");
        let model = client.completion_model("meta-llama/Meta-Llama-3-70B-Instruct-Turbo");
        let request = model.completion_request("hello").build();

        let error = model
            .completion(request)
            .await
            .expect_err("completion should fail with provider error envelope");

        match &error {
            CompletionError::ProviderResponse(stored) => {
                assert_eq!(stored.body, body);
                assert_eq!(stored.status, Some(http::StatusCode::ACCEPTED));
                assert_eq!(error.provider_response_body(), Some(body));
                assert_eq!(
                    error.provider_response_status(),
                    Some(http::StatusCode::ACCEPTED)
                );
                let json = error
                    .provider_response_json()
                    .expect("raw body should be valid JSON")
                    .expect("parsed JSON should be present");
                assert_eq!(json["code"], "model_overloaded");
                assert_eq!(json["error"], "model unavailable");
            }
            other => panic!("expected ProviderResponse, got {other:?}"),
        }
    }

    #[test]
    fn together_request_conversion_errors_when_all_messages_are_filtered() {
        let request = crate::completion::CompletionRequest {
            preamble: None,
            chat_history: OneOrMany::one(message::Message::Assistant {
                id: None,
                content: OneOrMany::one(message::AssistantContent::reasoning("hidden")),
            }),
            documents: vec![],
            tools: vec![],
            temperature: None,
            max_tokens: None,
            tool_choice: None,
            additional_params: None,
            model: None,
            output_schema: None,
        };

        let result = OpenAICompletionRequest::try_from(OpenAIRequestParams {
            model: "meta-llama/test-model".to_string(),
            request,
            strict_tools: false,
            tool_result_array_content: false,
            supports_response_format: false,
            supports_tools: true,
        });
        assert!(matches!(result, Err(CompletionError::RequestError(_))));
    }
}