fix: manage_scheduled_task + search_web 注入 + 删除 LM Studio

- manage_scheduled_task: INSERT 加 user_id='', 检查 psql 退出码
- search_web: 用 python json.dumps 构造请求体（防止注入）
- 删除 lmstudio.rs / LmStudioConfig，仅保留 DeepSeek
- config.json 移除 lmstudio 段

config.json

@@ -9,11 +9,6 @@
       "api_key": "${DEEPSEEK_API_KEY}",
       "model": "${DEEPSEEK_MODEL}",
       "base_url": "${DEEPSEEK_BASE_URL}"
-    },
-    "lmstudio": {
-      "base_url": "${LM_STUDIO_BASE_URL}",
-      "model": "${LM_STUDIO_MODEL}",
-      "api_key": "${LM_STUDIO_API_KEY}"
     }
   }
 }

resources/skills/manage_scheduled_task/scripts/manage.sh

@@ -15,23 +15,30 @@ case "$ACTION" in
 add)
   [ -z "$CMD" ] && echo '{"error":"add 需要 command 参数"}' && exit 0
   psql "$DB_URL" -v name="$NAME" -v desc="$DESC" -v cmd="$CMD" -v interval="$INTERVAL" << 'SQL'
-    INSERT INTO scheduled_tasks (id, name, description, command, interval_seconds, enabled, next_run_at)
-    VALUES (gen_random_uuid(), :'name', :'desc', :'cmd', :interval, true, NOW() + interval ':interval seconds')
+    INSERT INTO scheduled_tasks (id, name, description, command, interval_seconds, enabled, user_id, next_run_at)
+    VALUES (gen_random_uuid(), :'name', :'desc', :'cmd', :interval, true, '', NOW() + interval ':interval seconds')
     ON CONFLICT (name) DO UPDATE SET command=EXCLUDED.command, interval_seconds=EXCLUDED.interval_seconds, enabled=true, description=EXCLUDED.description
 SQL
-  echo '{"ok":true,"action":"add","name":"'"$NAME"'"}'
+  if [ $? -eq 0 ]; then
+    echo '{"ok":true,"action":"add","name":"'"$NAME"'"}'
+  else
+    echo '{"error":"添加失败"}'
+  fi
   ;;
 delete)
-  psql "$DB_URL" -v name="$NAME" -c "DELETE FROM scheduled_tasks WHERE name = :'name'" 2>/dev/null
-  echo '{"ok":true,"action":"delete","name":"'"$NAME"'"}'
+  psql "$DB_URL" -v name="$NAME" -c "DELETE FROM scheduled_tasks WHERE name = :'name'" 2>/dev/null && \
+    echo '{"ok":true,"action":"delete","name":"'"$NAME"'"}' || \
+    echo '{"error":"删除失败"}'
   ;;
 enable)
-  psql "$DB_URL" -v name="$NAME" -c "UPDATE scheduled_tasks SET enabled = true WHERE name = :'name'" 2>/dev/null
-  echo '{"ok":true,"action":"enable","name":"'"$NAME"'"}'
+  psql "$DB_URL" -v name="$NAME" -c "UPDATE scheduled_tasks SET enabled = true WHERE name = :'name'" 2>/dev/null && \
+    echo '{"ok":true,"action":"enable","name":"'"$NAME"'"}' || \
+    echo '{"error":"启用失败"}'
   ;;
 disable)
-  psql "$DB_URL" -v name="$NAME" -c "UPDATE scheduled_tasks SET enabled = false WHERE name = :'name'" 2>/dev/null
-  echo '{"ok":true,"action":"disable","name":"'"$NAME"'"}'
+  psql "$DB_URL" -v name="$NAME" -c "UPDATE scheduled_tasks SET enabled = false WHERE name = :'name'" 2>/dev/null && \
+    echo '{"ok":true,"action":"disable","name":"'"$NAME"'"}' || \
+    echo '{"error":"禁用失败"}'
   ;;
 *)
   echo '{"error":"未知操作: '"$ACTION"'（支持: add, delete, enable, disable）"}'

resources/skills/search_web/scripts/search.sh

@@ -9,9 +9,16 @@ COUNT=$(echo "$input" | python3 -c "import sys,json; print(json.load(sys.stdin).
 API_KEY="${TAVILY_API_KEY}"
 [ -z "$API_KEY" ] && echo '{"error":"请设置 TAVILY_API_KEY"}' && exit 0
 
-RESP=$(curl -s -X POST "https://api.tavily.com/search" \
-  -H "Content-Type: application/json" \
-  -d "{\"api_key\":\"$API_KEY\",\"query\":\"$QUERY\",\"max_results\":$COUNT,\"include_answer\":true}")
+export SEARCH_QUERY="$QUERY" SEARCH_COUNT="$COUNT"
+RESP=$(python3 -c "
+import urllib.request, json, os
+key = os.environ['TAVILY_API_KEY']
+query = os.environ['SEARCH_QUERY']
+count = int(os.environ.get('SEARCH_COUNT', 5))
+body = json.dumps({'api_key': key, 'query': query, 'max_results': count, 'include_answer': True}).encode()
+req = urllib.request.Request('https://api.tavily.com/search', data=body, headers={'Content-Type': 'application/json'})
+print(urllib.request.urlopen(req).read().decode())
+" 2>/dev/null)
 
 export RESP QUERY COUNT
 python3 -c "

src/config.rs

@@ -15,17 +15,11 @@ pub struct AppConfig {
 
 #[derive(Debug, Clone, Deserialize)]
 pub struct LlmConfig {
-    /// LLM 提供商：deepseek | lmstudio
     #[serde(default = "default_llm_provider")]
     pub provider: String,
 
-    /// DeepSeek 配置
     #[serde(default)]
     pub deepseek: DeepSeekConfig,
-
-    /// LM Studio 配置
-    #[serde(default)]
-    pub lmstudio: LmStudioConfig,
 }
 
 #[derive(Debug, Clone, Deserialize)]
@@ -38,16 +32,6 @@ pub struct DeepSeekConfig {
     pub base_url: String,
 }
 
-#[derive(Debug, Clone, Deserialize)]
-pub struct LmStudioConfig {
-    #[serde(default = "default_lmstudio_base_url")]
-    pub base_url: String,
-    #[serde(default = "default_lmstudio_model")]
-    pub model: String,
-    #[serde(default)]
-    pub api_key: String,
-}
-
 #[derive(Debug, Clone, Deserialize)]
 pub struct StorageConfig {
     /// 状态文件目录
@@ -76,14 +60,6 @@ fn default_deepseek_base_url() -> String {
     env_or_default("DEEPSEEK_BASE_URL", "https://api.deepseek.com/v1")
 }
 
-fn default_lmstudio_base_url() -> String {
-    env_or_default("LM_STUDIO_BASE_URL", "http://localhost:1234/v1")
-}
-
-fn default_lmstudio_model() -> String {
-    env_or_default("LM_STUDIO_MODEL", "local-model")
-}
-
 fn default_state_dir() -> String {
     ".data/weixin-ilink".to_string()
 }
@@ -97,7 +73,6 @@ impl Default for LlmConfig {
         Self {
             provider: default_llm_provider(),
             deepseek: DeepSeekConfig::default(),
-            lmstudio: LmStudioConfig::default(),
         }
     }
 }
@@ -112,16 +87,6 @@ impl Default for DeepSeekConfig {
     }
 }
 
-impl Default for LmStudioConfig {
-    fn default() -> Self {
-        Self {
-            base_url: default_lmstudio_base_url(),
-            model: default_lmstudio_model(),
-            api_key: String::new(),
-        }
-    }
-}
-
 impl Default for StorageConfig {
     fn default() -> Self {
         Self {

src/llm/lmstudio.rs

@@ -1,157 +0,0 @@
-use crate::llm::provider::{parse_chat_chunk, LlmProvider, ParsedChunk, StreamReceiver, StreamSender};
-use crate::llm::types::{ConversationConfig, Message, StreamChunk};
-use async_trait::async_trait;
-use reqwest::Client as HttpClient;
-use tokio::sync::mpsc;
-
-/// LM Studio 提供商（OpenAI 兼容接口）
-pub struct LmStudioProvider {
-    http: HttpClient,
-    base_url: String,
-    api_key: String,
-}
-
-impl LmStudioProvider {
-    pub fn new() -> Result<Self, String> {
-        let base_url = std::env::var("LM_STUDIO_BASE_URL")
-            .unwrap_or_else(|_| "http://localhost:1234/v1".to_string());
-        // 标准化 base_url: 确保有协议和 /v1 路径
-        let base_url = normalize_base_url(&base_url);
-        let api_key = std::env::var("LM_STUDIO_API_KEY").unwrap_or_default();
-
-        Ok(Self {
-            http: HttpClient::builder()
-                .timeout(std::time::Duration::from_secs(120))
-                .build()
-                .map_err(|e| format!("创建 HTTP client 失败: {}", e))?,
-            base_url,
-            api_key,
-        })
-    }
-}
-
-#[async_trait]
-impl LlmProvider for LmStudioProvider {
-    fn name(&self) -> &str {
-        "lmstudio"
-    }
-
-    async fn chat_stream(
-        &self,
-        config: &ConversationConfig,
-        messages: &[Message],
-    ) -> Result<StreamReceiver, String> {
-        let url = format!("{}/chat/completions", self.base_url);
-
-        let body = serde_json::json!({
-            "model": config.model,
-            "messages": messages,
-            "temperature": config.temperature,
-            "max_tokens": config.max_tokens,
-            "stream": true,
-        });
-
-        let (tx, rx) = mpsc::channel::<StreamChunk>(64);
-        let http = self.http.clone();
-        let api_key = self.api_key.clone();
-
-        tokio::spawn(async move {
-            if let Err(e) = stream_openai(http, &url, &api_key, body, tx.clone()).await {
-                let _ = tx.send(StreamChunk::Error(e)).await;
-            }
-        });
-
-        Ok(rx)
-    }
-}
-
-/// 与 DeepSeek 公用相同的 SSE 流式处理，但去除 thinking 相关字段
-async fn stream_openai(
-    http: HttpClient,
-    url: &str,
-    api_key: &str,
-    body: serde_json::Value,
-    tx: StreamSender,
-) -> Result<(), String> {
-    let mut req = http.post(url).header("Content-Type", "application/json");
-
-    if !api_key.is_empty() {
-        req = req.header("Authorization", format!("Bearer {}", api_key));
-    }
-
-    let response = req
-        .json(&body)
-        .send()
-        .await
-        .map_err(|e| format!("请求失败: {}", e))?;
-
-    if !response.status().is_success() {
-        let status = response.status();
-        let text = response.text().await.unwrap_or_default();
-        let _ = tx.send(StreamChunk::Error(format!("HTTP {}: {}", status, text))).await;
-        return Err(format!("HTTP {}: {}", status, text));
-    }
-
-    let mut full_text = String::new();
-    let mut buf = String::new();
-    let mut stream = response.bytes_stream();
-
-    use futures_util::StreamExt;
-    while let Some(chunk_result) = stream.next().await {
-        let chunk = chunk_result.map_err(|e| format!("读取流失败: {}", e))?;
-        let text = String::from_utf8_lossy(&chunk);
-        buf.push_str(&text);
-
-        while let Some(line_end) = buf.find('\n') {
-            let line = buf[..line_end].to_string();
-            buf = buf[line_end + 1..].to_string();
-            let trimmed = line.trim();
-            if trimmed.is_empty() {
-                continue;
-            }
-
-            // LM Studio 使用标准 OpenAI SSE 格式
-            if let Some(parsed) = parse_chat_chunk(trimmed) {
-                match parsed {
-                    ParsedChunk::Text(t) => {
-                        full_text.push_str(&t);
-                        let _ = tx.send(StreamChunk::Text(t)).await;
-                    }
-                    ParsedChunk::Reasoning(r) => {
-                        let _ = tx.send(StreamChunk::Reasoning(r)).await;
-                    }
-                    _ => {}
-                }
-            }
-        }
-    }
-
-    let _ = tx
-        .send(StreamChunk::Done {
-            text: full_text,
-            reasoning: None,
-            tool_calls: None,
-            usage: None,
-        })
-        .await;
-    Ok(())
-}
-
-/// 确保 base_url 有协议前缀和 /v1 路径
-fn normalize_base_url(raw: &str) -> String {
-    let raw = raw.trim();
-    let with_protocol = if raw.starts_with("http://") || raw.starts_with("https://") {
-        raw.to_string()
-    } else {
-        format!("http://{}", raw)
-    };
-
-    // 去掉末尾 /
-    let trimmed = with_protocol.trim_end_matches('/');
-    // 确保路径以 /v1 结尾
-    if trimmed.ends_with("/v1") {
-        trimmed.to_string()
-    } else {
-        format!("{}/v1", trimmed)
-    }
-}

src/llm/mod.rs

@@ -1,6 +1,5 @@
 pub mod conversation;
 pub mod deepseek;
-pub mod lmstudio;
 pub mod provider;
 pub mod types;
 

src/llm/provider.rs

@@ -27,16 +27,8 @@ pub trait LlmProvider: Send + Sync {
 pub type BoxedProvider = Arc<dyn LlmProvider>;
 
 /// 从配置创建恰当的提供商
-pub fn create_provider(config: &ConversationConfig) -> Result<BoxedProvider, String> {
-    let provider = std::env::var("LLM_PROVIDER")
-        .unwrap_or_else(|_| "deepseek".to_string())
-        .to_lowercase();
-
-    match provider.as_str() {
-        "deepseek" => Ok(Arc::new(super::deepseek::DeepSeekProvider::new()?)),
-        "lmstudio" => Ok(Arc::new(super::lmstudio::LmStudioProvider::new()?)),
-        _ => Err(format!("不支持的 LLM 提供商: {}", provider)),
-    }
+pub fn create_provider(_config: &ConversationConfig) -> Result<BoxedProvider, String> {
+    Ok(Arc::new(super::deepseek::DeepSeekProvider::new()?))
 }
 
 // ─── 内部：SSE 解析工具 ───

src/main.rs

@@ -230,12 +230,7 @@ async fn cmd_listen(
     let conversation = if enable_llm {
         let sys_prompt = std::env::var("WEIXIN_LLM_SYSTEM_PROMPT")
             .unwrap_or_else(|_| DEFAULT_SYSTEM_PROMPT.to_string());
-        let provider = std::env::var("LLM_PROVIDER").unwrap_or_else(|_| "deepseek".to_string());
-        let model = if provider == "lmstudio" {
-            config.llm.lmstudio.model.clone()
-        } else {
-            config.llm.deepseek.model.clone()
-        };
+        let model = config.llm.deepseek.model.clone();
 
         let mut cfg = ConversationConfig {
             system_prompt: sys_prompt,