325 lines
8.7 KiB
Rust
Raw Normal View History

use crate::ai_manager::AIUserService;
use crate::entities::{ChatStatePB, ModelTypePB};
use crate::local_ai::local_llm_chat::LocalAIController;
use crate::notification::{make_notification, ChatNotification, APPFLOWY_AI_NOTIFICATION_KEY};
use crate::persistence::{select_single_message, ChatMessageTable};
use appflowy_plugin::error::PluginError;
use std::collections::HashMap;
use flowy_ai_pub::cloud::{
ChatCloudService, ChatMessage, ChatMessageMetadata, ChatMessageType, CompletionType,
CreateTextChatContext, LocalAIConfig, MessageCursor, RelatedQuestion, RepeatedChatMessage,
RepeatedRelatedQuestion, StreamAnswer, StreamComplete,
};
use flowy_error::{FlowyError, FlowyResult};
use futures::{stream, Sink, StreamExt, TryStreamExt};
use lib_infra::async_trait::async_trait;
use lib_infra::future::FutureResult;
use crate::local_ai::stream_util::QuestionStream;
use crate::stream_message::StreamMessage;
use flowy_storage_pub::storage::StorageService;
use futures_util::SinkExt;
use serde_json::{json, Value};
use std::path::Path;
use std::sync::{Arc, Weak};
use tracing::trace;
pub struct AICloudServiceMiddleware {
cloud_service: Arc<dyn ChatCloudService>,
user_service: Arc<dyn AIUserService>,
local_llm_controller: Arc<LocalAIController>,
storage_service: Weak<dyn StorageService>,
}
impl AICloudServiceMiddleware {
pub fn new(
user_service: Arc<dyn AIUserService>,
cloud_service: Arc<dyn ChatCloudService>,
local_llm_controller: Arc<LocalAIController>,
storage_service: Weak<dyn StorageService>,
) -> Self {
Self {
user_service,
cloud_service,
local_llm_controller,
storage_service,
}
}
pub fn is_local_ai_enabled(&self) -> bool {
self.local_llm_controller.is_enabled()
}
pub async fn index_message_metadata(
&self,
chat_id: &str,
metadata_list: &[ChatMessageMetadata],
index_process_sink: &mut (impl Sink<String> + Unpin),
) -> Result<(), FlowyError> {
if metadata_list.is_empty() {
return Ok(());
}
if self.is_local_ai_enabled() {
let _ = index_process_sink
.send(StreamMessage::IndexStart.to_string())
.await;
self
.local_llm_controller
.index_message_metadata(chat_id, metadata_list, index_process_sink)
.await?;
let _ = index_process_sink
.send(StreamMessage::IndexEnd.to_string())
.await;
} else if let Some(_storage_service) = self.storage_service.upgrade() {
//
}
Ok(())
}
fn get_message_record(&self, message_id: i64) -> FlowyResult<ChatMessageTable> {
let uid = self.user_service.user_id()?;
let conn = self.user_service.sqlite_connection(uid)?;
let row = select_single_message(conn, message_id)?.ok_or_else(|| {
FlowyError::record_not_found().with_context(format!("Message not found: {}", message_id))
})?;
Ok(row)
}
fn handle_plugin_error(&self, err: PluginError) {
if matches!(
err,
PluginError::PluginNotConnected | PluginError::PeerDisconnect
) {
make_notification(
APPFLOWY_AI_NOTIFICATION_KEY,
ChatNotification::UpdateChatPluginState,
)
.payload(ChatStatePB {
model_type: ModelTypePB::LocalAI,
available: false,
})
.send();
}
}
}
#[async_trait]
impl ChatCloudService for AICloudServiceMiddleware {
fn create_chat(
&self,
uid: &i64,
workspace_id: &str,
chat_id: &str,
) -> FutureResult<(), FlowyError> {
self.cloud_service.create_chat(uid, workspace_id, chat_id)
}
async fn create_question(
&self,
workspace_id: &str,
chat_id: &str,
message: &str,
message_type: ChatMessageType,
metadata: &[ChatMessageMetadata],
) -> Result<ChatMessage, FlowyError> {
self
.cloud_service
.create_question(workspace_id, chat_id, message, message_type, metadata)
.await
}
async fn create_answer(
&self,
workspace_id: &str,
chat_id: &str,
message: &str,
question_id: i64,
metadata: Option<serde_json::Value>,
) -> Result<ChatMessage, FlowyError> {
self
.cloud_service
.create_answer(workspace_id, chat_id, message, question_id, metadata)
.await
}
async fn stream_answer(
&self,
workspace_id: &str,
chat_id: &str,
question_id: i64,
) -> Result<StreamAnswer, FlowyError> {
if self.local_llm_controller.is_running() {
let row = self.get_message_record(question_id)?;
match self
.local_llm_controller
.stream_question(chat_id, &row.content, json!([]))
.await
{
Ok(stream) => Ok(QuestionStream::new(stream).boxed()),
Err(err) => {
self.handle_plugin_error(err);
Ok(stream::once(async { Err(FlowyError::local_ai_unavailable()) }).boxed())
},
}
} else {
self
.cloud_service
.stream_answer(workspace_id, chat_id, question_id)
.await
}
}
async fn get_answer(
&self,
workspace_id: &str,
chat_id: &str,
question_message_id: i64,
) -> Result<ChatMessage, FlowyError> {
if self.local_llm_controller.is_running() {
let content = self.get_message_record(question_message_id)?.content;
match self
.local_llm_controller
.ask_question(chat_id, &content)
.await
{
Ok(answer) => {
// TODO(nathan): metadata
let message = self
.cloud_service
.create_answer(workspace_id, chat_id, &answer, question_message_id, None)
.await?;
Ok(message)
},
Err(err) => {
self.handle_plugin_error(err);
Err(FlowyError::local_ai_unavailable())
},
}
} else {
self
.cloud_service
.get_answer(workspace_id, chat_id, question_message_id)
.await
}
}
async fn get_chat_messages(
&self,
workspace_id: &str,
chat_id: &str,
offset: MessageCursor,
limit: u64,
) -> Result<RepeatedChatMessage, FlowyError> {
self
.cloud_service
.get_chat_messages(workspace_id, chat_id, offset, limit)
.await
}
async fn get_related_message(
&self,
workspace_id: &str,
chat_id: &str,
message_id: i64,
) -> Result<RepeatedRelatedQuestion, FlowyError> {
if self.local_llm_controller.is_running() {
let questions = self
.local_llm_controller
.get_related_question(chat_id)
.await
.map_err(|err| FlowyError::local_ai().with_context(err))?;
trace!("LocalAI related questions: {:?}", questions);
let items = questions
.into_iter()
.map(|content| RelatedQuestion {
content,
metadata: None,
})
.collect::<Vec<_>>();
Ok(RepeatedRelatedQuestion { message_id, items })
} else {
self
.cloud_service
.get_related_message(workspace_id, chat_id, message_id)
.await
}
}
async fn stream_complete(
&self,
workspace_id: &str,
text: &str,
complete_type: CompletionType,
) -> Result<StreamComplete, FlowyError> {
if self.local_llm_controller.is_running() {
match self
.local_llm_controller
.complete_text(text, complete_type as u8)
.await
{
Ok(stream) => Ok(
stream
.map_err(|err| FlowyError::local_ai().with_context(err))
.boxed(),
),
Err(err) => {
self.handle_plugin_error(err);
Ok(stream::once(async { Err(FlowyError::local_ai_unavailable()) }).boxed())
},
}
} else {
self
.cloud_service
.stream_complete(workspace_id, text, complete_type)
.await
}
}
async fn index_file(
&self,
workspace_id: &str,
file_path: &Path,
chat_id: &str,
metadata: Option<HashMap<String, Value>>,
) -> Result<(), FlowyError> {
if self.local_llm_controller.is_running() {
self
.local_llm_controller
.index_file(chat_id, Some(file_path.to_path_buf()), None, metadata)
.await
.map_err(|err| FlowyError::local_ai().with_context(err))?;
Ok(())
} else {
self
.cloud_service
.index_file(workspace_id, file_path, chat_id, metadata)
.await
}
}
async fn get_local_ai_config(&self, workspace_id: &str) -> Result<LocalAIConfig, FlowyError> {
self.cloud_service.get_local_ai_config(workspace_id).await
}
async fn create_chat_context(
&self,
workspace_id: &str,
chat_context: CreateTextChatContext,
) -> Result<(), FlowyError> {
if self.local_llm_controller.is_running() {
// TODO(nathan): support offline ai context
Ok(())
} else {
self
.cloud_service
.create_chat_context(workspace_id, chat_context)
.await
}
}
}