mirror of
https://gitlab.com/ArkHost/HelixNotes.git
synced 2026-07-24 07:45:57 +02:00
v1.0.0 - Initial release
This commit is contained in:
Yuri Karamian
@@ -0,0 +1,405 @@
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use reqwest::Client;
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use serde_json::json;
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use tauri::{AppHandle, Emitter};
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use crate::types::AiStreamEvent;
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const ANTHROPIC_API_URL: &str = "https://api.anthropic.com/v1/messages";
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const OPENAI_API_URL: &str = "https://api.openai.com/v1/chat/completions";
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pub fn ai_request(
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app: AppHandle,
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provider: String,
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api_key: String,
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model: String,
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system_prompt: String,
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user_message: String,
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request_id: String,
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) {
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std::thread::spawn(move || {
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let rt = tokio::runtime::Runtime::new().unwrap();
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rt.block_on(async {
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let result = match provider.as_str() {
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"openai" => {
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stream_openai(
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&app,
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&api_key,
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&model,
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&system_prompt,
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&user_message,
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&request_id,
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)
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.await
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}
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_ => {
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stream_anthropic(
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&app,
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&api_key,
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&model,
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&system_prompt,
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&user_message,
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&request_id,
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)
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.await
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}
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};
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if let Err(e) = result {
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "error".to_string(),
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text: None,
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error: Some(e),
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},
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);
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}
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});
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});
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}
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async fn stream_anthropic(
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app: &AppHandle,
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api_key: &str,
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model: &str,
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system_prompt: &str,
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user_message: &str,
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_request_id: &str,
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) -> Result<(), String> {
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let client = Client::new();
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let body = json!({
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"model": model,
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"max_tokens": 4096,
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"stream": true,
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"system": system_prompt,
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"messages": [
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{
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"role": "user",
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"content": user_message
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}
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]
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});
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let response = client
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.post(ANTHROPIC_API_URL)
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.header("x-api-key", api_key)
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.header("anthropic-version", "2023-06-01")
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.header("content-type", "application/json")
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.json(&body)
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.send()
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.await
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.map_err(|e| format!("Request failed: {}", e))?;
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if !response.status().is_success() {
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let status = response.status();
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let body_text = response.text().await.unwrap_or_default();
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return Err(format!("API error {}: {}", status, body_text));
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}
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// Parse SSE stream
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use futures::StreamExt;
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let mut stream = response.bytes_stream();
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let mut buffer = String::new();
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while let Some(chunk) = stream.next().await {
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let chunk = chunk.map_err(|e| format!("Stream error: {}", e))?;
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buffer.push_str(&String::from_utf8_lossy(&chunk));
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// Process complete SSE events from buffer
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while let Some(event_end) = buffer.find("\n\n") {
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let event_str = buffer[..event_end].to_string();
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buffer = buffer[event_end + 2..].to_string();
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for line in event_str.lines() {
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if let Some(data) = line.strip_prefix("data: ") {
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if data == "[DONE]" {
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "done".to_string(),
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text: None,
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error: None,
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},
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);
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return Ok(());
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}
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if let Ok(parsed) = serde_json::from_str::<serde_json::Value>(data) {
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let event_type = parsed["type"].as_str().unwrap_or("");
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match event_type {
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"content_block_delta" => {
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if let Some(text) = parsed["delta"]["text"].as_str() {
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "text".to_string(),
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text: Some(text.to_string()),
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error: None,
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},
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);
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}
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}
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"message_stop" => {
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "done".to_string(),
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text: None,
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error: None,
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},
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);
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return Ok(());
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}
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"error" => {
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let msg = parsed["error"]["message"]
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.as_str()
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.unwrap_or("Unknown API error");
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "error".to_string(),
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text: None,
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error: Some(msg.to_string()),
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},
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);
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return Err(msg.to_string());
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}
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_ => {}
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}
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}
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}
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}
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}
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}
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// Stream ended — send done
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "done".to_string(),
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text: None,
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error: None,
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},
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);
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Ok(())
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}
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async fn stream_openai(
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app: &AppHandle,
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api_key: &str,
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model: &str,
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system_prompt: &str,
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user_message: &str,
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_request_id: &str,
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) -> Result<(), String> {
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let client = Client::new();
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let is_gpt5 = model.starts_with("gpt-5");
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let token_key = if is_gpt5 {
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"max_completion_tokens"
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} else {
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"max_tokens"
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};
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let mut body = json!({
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"model": model,
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"stream": true,
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token_key: 4096,
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"messages": [
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{
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"role": "system",
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"content": system_prompt
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},
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{
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"role": "user",
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"content": user_message
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}
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]
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});
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// GPT-5 models don't support temperature
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if !is_gpt5 {
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body["temperature"] = json!(0.7);
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}
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let response = client
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.post(OPENAI_API_URL)
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.header("Authorization", format!("Bearer {}", api_key))
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.header("content-type", "application/json")
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.json(&body)
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.send()
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.await
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.map_err(|e| format!("Request failed: {}", e))?;
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if !response.status().is_success() {
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let status = response.status();
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let body_text = response.text().await.unwrap_or_default();
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return Err(format!("API error {}: {}", status, body_text));
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}
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use futures::StreamExt;
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let mut stream = response.bytes_stream();
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let mut buffer = String::new();
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while let Some(chunk) = stream.next().await {
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let chunk = chunk.map_err(|e| format!("Stream error: {}", e))?;
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buffer.push_str(&String::from_utf8_lossy(&chunk));
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while let Some(event_end) = buffer.find("\n\n") {
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let event_str = buffer[..event_end].to_string();
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buffer = buffer[event_end + 2..].to_string();
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for line in event_str.lines() {
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if let Some(data) = line.strip_prefix("data: ") {
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if data == "[DONE]" {
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "done".to_string(),
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text: None,
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error: None,
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},
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);
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return Ok(());
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}
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if let Ok(parsed) = serde_json::from_str::<serde_json::Value>(data) {
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// OpenAI streaming: choices[0].delta.content
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if let Some(content) = parsed["choices"][0]["delta"]["content"].as_str() {
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if !content.is_empty() {
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "text".to_string(),
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text: Some(content.to_string()),
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error: None,
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},
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);
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}
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}
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// Check finish_reason
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if let Some(reason) = parsed["choices"][0]["finish_reason"].as_str() {
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if reason == "stop" || reason == "length" {
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "done".to_string(),
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text: None,
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error: None,
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},
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);
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return Ok(());
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}
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}
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// Check for error in stream
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if let Some(err) = parsed["error"]["message"].as_str() {
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "error".to_string(),
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text: None,
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error: Some(err.to_string()),
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},
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);
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return Err(err.to_string());
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}
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}
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}
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}
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}
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}
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let _ = app.emit(
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"ai-stream",
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AiStreamEvent {
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event_type: "done".to_string(),
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text: None,
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error: None,
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},
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);
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Ok(())
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}
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pub async fn test_connection(provider: &str, api_key: &str, model: &str) -> Result<String, String> {
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match provider {
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"openai" => test_openai(api_key, model).await,
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_ => test_anthropic(api_key, model).await,
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}
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}
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async fn test_anthropic(api_key: &str, model: &str) -> Result<String, String> {
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let client = Client::new();
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let body = json!({
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"model": model,
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"max_tokens": 10,
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"messages": [
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{
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"role": "user",
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"content": "Hi"
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}
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]
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});
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let response = client
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.post(ANTHROPIC_API_URL)
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.header("x-api-key", api_key)
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.header("anthropic-version", "2023-06-01")
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.header("content-type", "application/json")
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.json(&body)
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.send()
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.await
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.map_err(|e| format!("Connection failed: {}", e))?;
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if response.status().is_success() {
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Ok("Connection successful".to_string())
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} else {
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let status = response.status();
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let body_text = response.text().await.unwrap_or_default();
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Err(format!("API error {}: {}", status, body_text))
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}
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}
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async fn test_openai(api_key: &str, model: &str) -> Result<String, String> {
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let client = Client::new();
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let is_gpt5 = model.starts_with("gpt-5");
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let token_key = if is_gpt5 {
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"max_completion_tokens"
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} else {
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"max_tokens"
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};
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let body = json!({
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"model": model,
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token_key: 10,
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"messages": [
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{
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"role": "user",
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"content": "Hi"
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}
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]
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});
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let response = client
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.post(OPENAI_API_URL)
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.header("Authorization", format!("Bearer {}", api_key))
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.header("content-type", "application/json")
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.json(&body)
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.send()
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.await
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.map_err(|e| format!("Connection failed: {}", e))?;
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if response.status().is_success() {
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Ok("Connection successful".to_string())
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} else {
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let status = response.status();
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let body_text = response.text().await.unwrap_or_default();
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Err(format!("API error {}: {}", status, body_text))
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}
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}
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