mirror of
https://github.com/AppFlowy-IO/AppFlowy.git
synced 2025-11-02 11:04:02 +00:00
Revert "chore: try to fix the mobile build" (#7844)
This reverts commit 3f06f6415aee635e1e39cc772ece081484f0ab14.
This commit is contained in:
Lucas
GitHub
parent
2463107c6c
commit
168b29abe3
@ -23,6 +23,8 @@ use flowy_ai_pub::persistence::{
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use flowy_ai_pub::user_service::AIUserService;
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use futures_util::SinkExt;
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use lib_infra::util::get_operating_system;
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use ollama_rs::generation::embeddings::request::{EmbeddingsInput, GenerateEmbeddingsRequest};
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use ollama_rs::Ollama;
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use serde::{Deserialize, Serialize};
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use std::ops::Deref;
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use std::path::PathBuf;
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@ -32,11 +34,6 @@ use tokio_stream::StreamExt;
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use tracing::{debug, error, info, instrument, warn};
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use uuid::Uuid;
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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use ollama_rs::generation::embeddings::request::{EmbeddingsInput, GenerateEmbeddingsRequest};
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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use ollama_rs::Ollama;
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#[derive(Clone, Debug, Serialize, Deserialize)]
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pub struct LocalAISetting {
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pub ollama_server_url: String,
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@ -62,7 +59,6 @@ pub struct LocalAIController {
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current_chat_id: ArcSwapOption<Uuid>,
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store_preferences: Weak<KVStorePreferences>,
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user_service: Arc<dyn AIUserService>,
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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ollama: ArcSwapOption<Ollama>,
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}
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@ -95,105 +91,87 @@ impl LocalAIController {
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res_impl,
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));
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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let ollama = {
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let mut ollama = ArcSwapOption::default();
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let sys = get_operating_system();
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if sys.is_desktop() {
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let setting = local_ai_resource.get_llm_setting();
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ollama.store(
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Ollama::try_new(&setting.ollama_server_url)
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.map(Arc::new)
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.ok(),
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);
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}
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ollama
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};
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let ollama = ArcSwapOption::default();
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let sys = get_operating_system();
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if sys.is_desktop() {
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let setting = local_ai_resource.get_llm_setting();
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ollama.store(
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Ollama::try_new(&setting.ollama_server_url)
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.map(Arc::new)
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.ok(),
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);
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// Subscribe to state changes
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let mut running_state_rx = local_ai.subscribe_running_state();
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let cloned_llm_res = Arc::clone(&local_ai_resource);
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let cloned_store_preferences = store_preferences.clone();
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let cloned_local_ai = Arc::clone(&local_ai);
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let cloned_user_service = Arc::clone(&user_service);
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// Subscribe to state changes
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let mut running_state_rx = local_ai.subscribe_running_state();
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let cloned_llm_res = Arc::clone(&local_ai_resource);
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let cloned_store_preferences = store_preferences.clone();
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let cloned_local_ai = Arc::clone(&local_ai);
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let cloned_user_service = Arc::clone(&user_service);
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// Spawn a background task to listen for plugin state changes
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tokio::spawn(async move {
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while let Some(state) = running_state_rx.next().await {
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// Skip if we can't get workspace_id
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let Ok(workspace_id) = cloned_user_service.workspace_id() else {
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continue;
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};
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let key = crate::local_ai::controller::local_ai_enabled_key(&workspace_id.to_string());
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info!("[AI Plugin] state: {:?}", state);
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// Read whether plugin is enabled from store; default to true
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if let Some(store_preferences) = cloned_store_preferences.upgrade() {
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let enabled = store_preferences.get_bool(&key).unwrap_or(true);
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// Only check resource status if the plugin isn't in "UnexpectedStop" and is enabled
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let (plugin_downloaded, lack_of_resource) =
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if !matches!(state, RunningState::UnexpectedStop { .. }) && enabled {
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// Possibly check plugin readiness and resource concurrency in parallel,
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// but here we do it sequentially for clarity.
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let downloaded = is_plugin_ready();
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let resource_lack = cloned_llm_res.get_lack_of_resource().await;
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(downloaded, resource_lack)
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} else {
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(false, None)
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};
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// If plugin is running, retrieve version
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let plugin_version = if matches!(state, RunningState::Running { .. }) {
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match cloned_local_ai.plugin_info().await {
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Ok(info) => Some(info.version),
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Err(_) => None,
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}
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} else {
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None
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// Spawn a background task to listen for plugin state changes
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tokio::spawn(async move {
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while let Some(state) = running_state_rx.next().await {
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// Skip if we can't get workspace_id
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let Ok(workspace_id) = cloned_user_service.workspace_id() else {
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continue;
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};
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// Broadcast the new local AI state
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let new_state = RunningStatePB::from(state);
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chat_notification_builder(
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APPFLOWY_AI_NOTIFICATION_KEY,
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ChatNotification::UpdateLocalAIState,
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)
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.payload(LocalAIPB {
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enabled,
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plugin_downloaded,
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lack_of_resource,
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state: new_state,
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plugin_version,
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})
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.send();
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} else {
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warn!("[AI Plugin] store preferences is dropped");
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}
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}
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});
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let key = crate::local_ai::controller::local_ai_enabled_key(&workspace_id.to_string());
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info!("[AI Plugin] state: {:?}", state);
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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{
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Self {
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ai_plugin: local_ai,
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resource: local_ai_resource,
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current_chat_id: ArcSwapOption::default(),
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store_preferences,
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user_service,
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ollama,
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}
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// Read whether plugin is enabled from store; default to true
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if let Some(store_preferences) = cloned_store_preferences.upgrade() {
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let enabled = store_preferences.get_bool(&key).unwrap_or(true);
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// Only check resource status if the plugin isn't in "UnexpectedStop" and is enabled
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let (plugin_downloaded, lack_of_resource) =
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if !matches!(state, RunningState::UnexpectedStop { .. }) && enabled {
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// Possibly check plugin readiness and resource concurrency in parallel,
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// but here we do it sequentially for clarity.
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let downloaded = is_plugin_ready();
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let resource_lack = cloned_llm_res.get_lack_of_resource().await;
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(downloaded, resource_lack)
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} else {
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(false, None)
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};
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// If plugin is running, retrieve version
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let plugin_version = if matches!(state, RunningState::Running { .. }) {
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match cloned_local_ai.plugin_info().await {
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Ok(info) => Some(info.version),
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Err(_) => None,
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}
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} else {
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None
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};
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// Broadcast the new local AI state
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let new_state = RunningStatePB::from(state);
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chat_notification_builder(
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APPFLOWY_AI_NOTIFICATION_KEY,
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ChatNotification::UpdateLocalAIState,
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)
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.payload(LocalAIPB {
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enabled,
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plugin_downloaded,
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lack_of_resource,
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state: new_state,
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plugin_version,
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})
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.send();
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} else {
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warn!("[AI Plugin] store preferences is dropped");
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}
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}
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});
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}
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#[cfg(not(any(target_os = "macos", target_os = "linux", target_os = "windows")))]
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{
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Self {
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ai_plugin: local_ai,
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resource: local_ai_resource,
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current_chat_id: ArcSwapOption::default(),
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store_preferences,
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user_service,
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}
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Self {
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ai_plugin: local_ai,
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resource: local_ai_resource,
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current_chat_id: ArcSwapOption::default(),
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store_preferences,
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user_service,
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ollama,
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}
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}
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#[instrument(level = "debug", skip_all)]
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@ -329,35 +307,18 @@ impl LocalAIController {
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}
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pub async fn get_all_chat_local_models(&self) -> Vec<AIModel> {
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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{
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self
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.get_filtered_local_models(|name| !name.contains("embed"))
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.await
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}
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#[cfg(not(any(target_os = "macos", target_os = "linux", target_os = "windows")))]
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{
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vec![]
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}
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self
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.get_filtered_local_models(|name| !name.contains("embed"))
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.await
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}
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pub async fn get_all_embedded_local_models(&self) -> Vec<AIModel> {
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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{
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self
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.get_filtered_local_models(|name| name.contains("embed"))
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.await
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}
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#[cfg(not(any(target_os = "macos", target_os = "linux", target_os = "windows")))]
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{
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vec![]
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}
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self
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.get_filtered_local_models(|name| name.contains("embed"))
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.await
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}
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// Helper function to avoid code duplication in model retrieval
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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async fn get_filtered_local_models<F>(&self, filter_fn: F) -> Vec<AIModel>
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where
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F: Fn(&str) -> bool,
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@ -383,43 +344,35 @@ impl LocalAIController {
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let mut conn = self.user_service.sqlite_connection(uid)?;
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match select_local_ai_model(&mut conn, model_name) {
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None => {
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#[cfg(any(target_os = "macos", target_os = "linux", target_os = "windows"))]
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{
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let ollama = self
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.ollama
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.load_full()
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.ok_or_else(|| FlowyError::local_ai().with_context("ollama is not initialized"))?;
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let ollama = self
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.ollama
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.load_full()
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.ok_or_else(|| FlowyError::local_ai().with_context("ollama is not initialized"))?;
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let request = GenerateEmbeddingsRequest::new(
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model_name.to_string(),
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EmbeddingsInput::Single("Hello".to_string()),
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);
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let request = GenerateEmbeddingsRequest::new(
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model_name.to_string(),
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EmbeddingsInput::Single("Hello".to_string()),
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);
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let model_type = match ollama.generate_embeddings(request).await {
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Ok(value) => {
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if value.embeddings.is_empty() {
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ModelType::Chat
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} else {
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ModelType::Embedding
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}
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},
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Err(_) => ModelType::Chat,
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};
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let model_type = match ollama.generate_embeddings(request).await {
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Ok(value) => {
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if value.embeddings.is_empty() {
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ModelType::Chat
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} else {
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ModelType::Embedding
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}
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},
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Err(_) => ModelType::Chat,
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};
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upsert_local_ai_model(
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&mut conn,
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&LocalAIModelTable {
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name: model_name.to_string(),
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model_type: model_type as i16,
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},
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)?;
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Ok(model_type)
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}
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#[cfg(not(any(target_os = "macos", target_os = "linux", target_os = "windows")))]
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{
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Ok(ModelType::Chat)
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}
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upsert_local_ai_model(
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&mut conn,
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&LocalAIModelTable {
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name: model_name.to_string(),
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model_type: model_type as i16,
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},
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)?;
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Ok(model_type)
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},
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Some(r) => Ok(ModelType::from(r.model_type)),
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}
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