use dioxus::prelude::*; use crate::components::PageHeader; use crate::i18n::{t, Locale}; use crate::models::{EmbeddingEntry, LlmProvider, ModelEntry, ProviderConfig}; /// Providers page for configuring LLM and embedding model backends. /// /// Two-column layout: left side has a configuration form, right side /// shows the currently active provider status. #[component] pub fn ProvidersPage() -> Element { let locale = use_context::>(); let l = *locale.read(); let mut selected_provider = use_signal(|| LlmProvider::Ollama); let mut selected_model = use_signal(|| "llama3.1:8b".to_string()); let mut selected_embedding = use_signal(|| "nomic-embed-text".to_string()); let mut api_key = use_signal(String::new); let mut saved = use_signal(|| false); let models = mock_models(); let embeddings = mock_embeddings(); // Filter models/embeddings by selected provider let provider_val = selected_provider.read().clone(); let available_models: Vec<_> = models .iter() .filter(|m| m.provider == provider_val) .collect(); let available_embeddings: Vec<_> = embeddings .iter() .filter(|e| e.provider == provider_val) .collect(); let active_config = ProviderConfig { provider: provider_val.clone(), selected_model: selected_model.read().clone(), selected_embedding: selected_embedding.read().clone(), api_key_set: !api_key.read().is_empty(), }; rsx! { section { class: "providers-page", PageHeader { title: t(l, "providers.title"), subtitle: t(l, "providers.subtitle"), } div { class: "providers-layout", div { class: "providers-form", div { class: "form-group", label { "{t(l, \"providers.provider\")}" } select { class: "form-select", value: "{provider_val.label()}", onchange: move |evt: Event| { let val = evt.value(); let prov = match val.as_str() { "Hugging Face" => LlmProvider::HuggingFace, "OpenAI" => LlmProvider::OpenAi, "Anthropic" => LlmProvider::Anthropic, _ => LlmProvider::Ollama, }; selected_provider.set(prov); saved.set(false); }, option { value: "Ollama", "Ollama" } option { value: "Hugging Face", "Hugging Face" } option { value: "OpenAI", "OpenAI" } option { value: "Anthropic", "Anthropic" } } } div { class: "form-group", label { "{t(l, \"providers.model\")}" } select { class: "form-select", value: "{selected_model}", onchange: move |evt: Event| { selected_model.set(evt.value()); saved.set(false); }, for m in &available_models { option { value: "{m.id}", "{m.name} ({m.context_window}k ctx)" } } } } div { class: "form-group", label { "{t(l, \"providers.embedding_model\")}" } select { class: "form-select", value: "{selected_embedding}", onchange: move |evt: Event| { selected_embedding.set(evt.value()); saved.set(false); }, for e in &available_embeddings { option { value: "{e.id}", "{e.name} ({e.dimensions}d)" } } } } div { class: "form-group", label { "{t(l, \"providers.api_key\")}" } input { class: "form-input", r#type: "password", placeholder: "{t(l, \"providers.api_key_placeholder\")}", value: "{api_key}", oninput: move |evt: Event| { api_key.set(evt.value()); saved.set(false); }, } } button { class: "btn-primary", onclick: move |_| saved.set(true), "{t(l, \"providers.save_config\")}" } if *saved.read() { p { class: "form-success", "{t(l, \"providers.config_saved\")}" } } } div { class: "providers-status", h3 { "{t(l, \"providers.active_config\")}" } div { class: "status-card", div { class: "status-row", span { class: "status-label", "{t(l, \"providers.provider\")}" } span { class: "status-value", "{active_config.provider.label()}" } } div { class: "status-row", span { class: "status-label", "{t(l, \"providers.model\")}" } span { class: "status-value", "{active_config.selected_model}" } } div { class: "status-row", span { class: "status-label", "{t(l, \"providers.embedding\")}" } span { class: "status-value", "{active_config.selected_embedding}" } } div { class: "status-row", span { class: "status-label", "{t(l, \"providers.api_key\")}" } span { class: "status-value", if active_config.api_key_set { "{t(l, \"common.set\")}" } else { "{t(l, \"common.not_set\")}" } } } } } } } } } /// Returns mock model entries for all providers. fn mock_models() -> Vec { vec![ ModelEntry { id: "llama3.1:8b".into(), name: "Llama 3.1 8B".into(), provider: LlmProvider::Ollama, context_window: 128, }, ModelEntry { id: "llama3.1:70b".into(), name: "Llama 3.1 70B".into(), provider: LlmProvider::Ollama, context_window: 128, }, ModelEntry { id: "mistral:7b".into(), name: "Mistral 7B".into(), provider: LlmProvider::Ollama, context_window: 32, }, ModelEntry { id: "meta-llama/Llama-3.1-8B".into(), name: "Llama 3.1 8B".into(), provider: LlmProvider::HuggingFace, context_window: 128, }, ModelEntry { id: "gpt-4o".into(), name: "GPT-4o".into(), provider: LlmProvider::OpenAi, context_window: 128, }, ModelEntry { id: "claude-sonnet-4-6".into(), name: "Claude Sonnet 4.6".into(), provider: LlmProvider::Anthropic, context_window: 200, }, ] } /// Returns mock embedding entries for all providers. fn mock_embeddings() -> Vec { vec![ EmbeddingEntry { id: "nomic-embed-text".into(), name: "Nomic Embed Text".into(), provider: LlmProvider::Ollama, dimensions: 768, }, EmbeddingEntry { id: "sentence-transformers/all-MiniLM-L6-v2".into(), name: "MiniLM-L6-v2".into(), provider: LlmProvider::HuggingFace, dimensions: 384, }, EmbeddingEntry { id: "text-embedding-3-small".into(), name: "Embedding 3 Small".into(), provider: LlmProvider::OpenAi, dimensions: 1536, }, EmbeddingEntry { id: "voyage-3".into(), name: "Voyage 3".into(), provider: LlmProvider::Anthropic, dimensions: 1024, }, ] }