feat: personalize and stream mentor chat

2026-07-23 19:24:57 +08:00
parent 771882ebf0
commit 95789c837c
11 changed files with 876 additions and 104 deletions
@@ -26,6 +26,7 @@ MEMBER_POST_PATHS = frozenset(
        "/api/screener/run",
        "/api/screener/tracking/refresh",
        "/api/mentors/chat",
+        "/api/mentors/preferences",
        "/api/heaven/hexagram",
        "/api/heaven/personal",
        "/api/heaven/interpret",
@@ -257,6 +257,19 @@ class ReviewDatabase:
                CREATE INDEX IF NOT EXISTS idx_mentor_messages_conversation
                ON mentor_messages(user_id, mentor_id, trade_date, id DESC);

+                CREATE TABLE IF NOT EXISTS mentor_preferences (
+                    user_id INTEGER NOT NULL,
+                    mentor_id TEXT NOT NULL,
+                    pinned INTEGER NOT NULL DEFAULT 0,
+                    sort_order INTEGER NOT NULL DEFAULT 0,
+                    updated_at TEXT NOT NULL,
+                    PRIMARY KEY (user_id, mentor_id),
+                    FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
+                );
+
+                CREATE INDEX IF NOT EXISTS idx_mentor_preferences_user_order
+                ON mentor_preferences(user_id, pinned DESC, sort_order, mentor_id);
+
                CREATE TABLE IF NOT EXISTS strategy_tracks (
                    id INTEGER PRIMARY KEY AUTOINCREMENT,
                    user_id INTEGER NOT NULL,
@@ -1417,6 +1430,48 @@ class ReviewDatabase:
            )
            return int(cursor.rowcount)

+    def list_mentor_preferences(self, user_id: int) -> list[dict[str, Any]]:
+        with self.connect() as connection:
+            rows = connection.execute(
+                """
+                SELECT mentor_id, pinned, sort_order
+                FROM mentor_preferences
+                WHERE user_id = ?
+                ORDER BY sort_order, mentor_id
+                """,
+                (int(user_id),),
+            ).fetchall()
+        return [
+            {
+                "mentor_id": str(row["mentor_id"]),
+                "pinned": bool(row["pinned"]),
+                "sort_order": int(row["sort_order"]),
+            }
+            for row in rows
+        ]
+
+    def save_mentor_preferences(
+        self, user_id: int, ordered_ids: list[str], pinned_ids: set[str]
+    ) -> None:
+        now = datetime.now().astimezone().isoformat(timespec="seconds")
+        values = [
+            (int(user_id), mentor_id, int(mentor_id in pinned_ids), index, now)
+            for index, mentor_id in enumerate(ordered_ids)
+        ]
+        with self.connect() as connection:
+            connection.execute(
+                "DELETE FROM mentor_preferences WHERE user_id = ?",
+                (int(user_id),),
+            )
+            connection.executemany(
+                """
+                INSERT INTO mentor_preferences
+                    (user_id, mentor_id, pinned, sort_order, updated_at)
+                VALUES (?, ?, ?, ?, ?)
+                """,
+                values,
+            )
+
    def save_strategy_tracks(
        self,
        user_id: int,
@@ -5,6 +5,7 @@ import re
 import time
 import urllib.error
 import urllib.request
+from collections.abc import Iterator
 from dataclasses import dataclass
 from pathlib import Path
 from typing import Any
@@ -162,6 +163,29 @@ def chat_with_mentor(
    model: str,
    timeout: int = 90,
 ) -> dict[str, Any]:
+    started = time.perf_counter()
+    answer = "".join(
+        stream_with_mentor(
+            skill, market_context, question, history, api_key, base_url, model, timeout
+        )
+    ).strip()
+    return {
+        "answer": answer,
+        "model": model,
+        "latency_ms": round((time.perf_counter() - started) * 1000),
+    }
+
+
+def stream_with_mentor(
+    skill: MentorSkill,
+    market_context: dict[str, Any],
+    question: str,
+    history: list[dict[str, str]],
+    api_key: str,
+    base_url: str,
+    model: str,
+    timeout: int = 90,
+) -> Iterator[str]:
    if not api_key or not model:
        raise MentorAgentError("LLM API Key 或模型尚未配置。")

@@ -170,7 +194,7 @@ def chat_with_mentor(
    messages.extend(history[-10:])
    messages.append({"role": "user", "content": question})
    payload = json.dumps(
-        {"model": model, "messages": messages, "stream": False},
+        {"model": model, "messages": messages, "stream": True},
        ensure_ascii=False,
    ).encode("utf-8")
    request = urllib.request.Request(
@@ -180,25 +204,41 @@ def chat_with_mentor(
            "Content-Type": "application/json",
            "Authorization": f"Bearer {api_key}",
            "User-Agent": "XiaobaiReviewWeb/0.6",
+            "Accept": "text/event-stream",
        },
        method="POST",
    )
-    started = time.perf_counter()
    try:
        with urllib.request.urlopen(request, timeout=timeout) as response:
-            result = json.loads(response.read().decode("utf-8"))
-        answer = str(result["choices"][0]["message"]["content"]).strip()
-        if not answer:
-            raise KeyError("empty response")
+            yielded = False
+            for raw_line in response:
+                line = raw_line.decode("utf-8", errors="replace").strip()
+                if not line or line.startswith(":"):
+                    continue
+                if line.startswith("data:"):
+                    line = line[5:].strip()
+                if line == "[DONE]":
+                    break
+                try:
+                    result = json.loads(line)
+                except json.JSONDecodeError:
+                    continue
+                choices = result.get("choices") or []
+                if not choices:
+                    continue
+                choice = choices[0] or {}
+                content = (choice.get("delta") or {}).get("content")
+                if content is None:
+                    content = (choice.get("message") or {}).get("content")
+                if content:
+                    yielded = True
+                    yield str(content)
+            if not yielded:
+                raise MentorAgentError("问师模型未返回有效内容。")
    except urllib.error.HTTPError as exc:
        raise MentorAgentError(_http_error_message(exc)) from exc
-    except (urllib.error.URLError, TimeoutError, json.JSONDecodeError, KeyError, IndexError) as exc:
+    except (urllib.error.URLError, TimeoutError, OSError) as exc:
        raise MentorAgentError(f"问师模型调用失败：{exc}") from exc
-    return {
-        "answer": answer,
-        "model": model,
-        "latency_ms": round((time.perf_counter() - started) * 1000),
-    }


 def _build_system_prompt(skill: MentorSkill, market_context: dict[str, Any]) -> str:
@@ -50,7 +50,7 @@ from heaven_engine import (
    hexagram_from_lines,
 )
 from llm_strategy import LLMCompilerError, compile_strategy_with_llm, test_llm_connection
-from mentor_agent import MentorAgentError, MentorSkillRegistry, chat_with_mentor
+from mentor_agent import MentorAgentError, MentorSkillRegistry, stream_with_mentor
 from realtime_aggregator import WebRealtimeAggregator
 from screener import (
    FACTOR_FIELDS,
@@ -1353,11 +1353,26 @@ class DashboardService:
        ]
        if not mentors:
            raise ValueError("游资skills 目录中没有可用的 SKILL.md。")
+        stored_preferences = self.database.list_mentor_preferences(self.current_user_id)
+        preferences = {item["mentor_id"]: item for item in stored_preferences}
+        for default_order, mentor in enumerate(mentors):
+            preference = preferences.get(str(mentor.get("id") or ""), {})
+            mentor["pinned"] = bool(preference.get("pinned"))
+            mentor["sort_order"] = int(preference.get("sort_order", 10000 + default_order))
+        mentors.sort(
+            key=lambda item: (
+                not bool(item.get("pinned")),
+                int(item.get("sort_order") or 0),
+            )
+        )
+        for sort_order, mentor in enumerate(mentors):
+            mentor["sort_order"] = sort_order
        snapshot = self.database.get_snapshot(normalized_date)
        actual_date = str((snapshot or {}).get("meta", {}).get("trade_date") or normalized_date)
        return {
            "trade_date": actual_date,
            "mentors": mentors,
+            "preferences_configured": bool(stored_preferences),
            "llm": {
                "configured": self.llm_configured,
                "model": self.llm_primary_model if self.llm_configured else "",
@@ -1366,7 +1381,38 @@ class DashboardService:
            },
        }

-    def mentor_chat(self, payload: dict[str, Any]) -> dict[str, Any]:
+    def save_mentor_preferences(self, payload: dict[str, Any]) -> dict[str, Any]:
+        available_ids = [
+            skill.skill_id
+            for skill in self.mentor_skills.list_skills(
+                include_private=self.membership()["is_admin"]
+            )
+        ]
+        available = set(available_ids)
+        raw_order = payload.get("order")
+        raw_pinned = payload.get("pinned")
+        if not isinstance(raw_order, list) or not isinstance(raw_pinned, list):
+            raise ValueError("问师排序格式不正确。")
+        ordered_ids: list[str] = []
+        for raw_id in raw_order:
+            mentor_id = validate_text(raw_id, "问师角色", 100, required=True)
+            if mentor_id not in available:
+                raise ValueError("问师排序中包含不可用的思维模型。")
+            if mentor_id not in ordered_ids:
+                ordered_ids.append(mentor_id)
+        ordered_ids.extend(mentor_id for mentor_id in available_ids if mentor_id not in ordered_ids)
+        pinned_ids = {
+            validate_text(raw_id, "问师角色", 100, required=True)
+            for raw_id in raw_pinned
+        }
+        if not pinned_ids.issubset(available):
+            raise ValueError("问师置顶中包含不可用的思维模型。")
+        self.database.save_mentor_preferences(
+            self.current_user_id, ordered_ids, pinned_ids
+        )
+        return {"saved": True}
+
+    def mentor_stream(self, payload: dict[str, Any]):
        mentor_id = validate_text(payload.get("mentor_id"), "问师角色", 100, required=True)
        question = validate_text(payload.get("question"), "问题", 2000, required=True)
        trade_date = normalize_date(str(payload.get("trade_date") or date.today().isoformat()))
@@ -1377,66 +1423,73 @@ class DashboardService:
        context = self._build_mentor_context(trade_date, question)

        source = self.ensure_llm_access("mentor")
-        primary_error = ""
-        result = None
-        compiler = "primary"
+        profiles = []
        if self.llm_configured:
-            try:
-                result = chat_with_mentor(
-                    skill,
-                    context,
-                    question,
-                    history,
+            profiles.append(
+                (
+                    "primary",
                    self.llm_primary_api_key,
                    self.llm_primary_base_url,
                    self.llm_primary_model,
                )
-            except MentorAgentError as exc:
-                primary_error = str(exc)
-        if result is None and self.llm_fallback_configured:
-            try:
-                result = chat_with_mentor(
-                    skill,
-                    context,
-                    question,
-                    history,
+            )
+        if self.llm_fallback_configured:
+            profiles.append(
+                (
+                    "fallback",
                    self.llm_fallback_api_key,
                    self.llm_fallback_base_url,
                    self.llm_fallback_model,
                )
-                compiler = "fallback"
-            except MentorAgentError as exc:
-                fallback_error = str(exc)
-                self.record_llm_usage(
-                    "mentor", source, self.llm_fallback_model, "failed"
+            )
+
+        def generate():
+            started = time.perf_counter()
+            last_error: Exception | None = None
+            for compiler, api_key, base_url, model in profiles:
+                try:
+                    upstream = iter(
+                        stream_with_mentor(
+                            skill, context, question, history, api_key, base_url, model
+                        )
+                    )
+                    first = next(upstream)
+                except (MentorAgentError, StopIteration) as exc:
+                    last_error = exc
+                    continue
+                answer_parts = [first]
+                yield {"type": "delta", "content": first}
+                try:
+                    for chunk in upstream:
+                        answer_parts.append(chunk)
+                        yield {"type": "delta", "content": chunk}
+                except MentorAgentError as exc:
+                    self.record_llm_usage("mentor", source, model, "failed")
+                    raise ValueError("智能解读连接中断，请稍后重试。") from exc
+                answer = "".join(answer_parts).strip()
+                latency_ms = round((time.perf_counter() - started) * 1000)
+                self.database.save_mentor_exchange(
+                    self.current_user_id,
+                    mentor_id,
+                    trade_date,
+                    question,
+                    answer,
+                    context["data_trade_date"],
                )
-                raise ValueError("智能解读服务暂不可用，请稍后重试。") from exc
-        if result is None:
-            self.record_llm_usage("mentor", source, self.llm_primary_model, "failed")
-            raise ValueError("智能解读服务暂不可用，请稍后重试。")
-        self.record_llm_usage(
-            "mentor",
-            source,
-            str(result.get("model") or ""),
-            "success",
-            int(result.get("latency_ms") or 0),
-        )
-        self.database.save_mentor_exchange(
-            self.current_user_id,
-            mentor_id,
-            trade_date,
-            question,
-            str(result.get("answer") or ""),
-            context["data_trade_date"],
-        )
-        return {
-            **result,
-            "mentor": skill.public(),
-            "compiler": compiler,
-            "requested_trade_date": trade_date,
-            "data_trade_date": context["data_trade_date"],
-            "notice": "智能解读已自动切换可用服务。" if compiler == "fallback" else "",
-        }
+                self.record_llm_usage("mentor", source, model, "success", latency_ms)
+                yield {
+                    "type": "meta",
+                    "data_trade_date": context["data_trade_date"],
+                    "notice": "智能解读已自动切换可用服务。"
+                    if compiler == "fallback"
+                    else "",
+                }
+                return
+            failed_model = profiles[-1][3] if profiles else self.llm_primary_model
+            self.record_llm_usage("mentor", source, failed_model, "failed")
+            raise ValueError("智能解读服务暂不可用，请稍后重试。") from last_error
+
+        return generate()

    def mentor_messages(self, mentor_id: str, trade_date: str) -> list[dict[str, Any]]:
        mentor_id = validate_text(mentor_id, "问师角色", 100, required=True)
@@ -3929,8 +3982,15 @@ class RequestHandler(BaseHTTPRequestHandler):
        if parsed.path == "/api/screener/tracking/refresh":
            self.refresh_screener_tracking()
            return
+        if parsed.path == "/api/mentors/preferences":
+            try:
+                result = SERVICE.save_mentor_preferences(self.read_json_body())
+                self.send_json({"ok": True, **result})
+            except (ValueError, json.JSONDecodeError) as exc:
+                self.send_json({"error": str(exc)}, HTTPStatus.BAD_REQUEST)
+            return
        if parsed.path == "/api/mentors/chat":
-            self.mentor_chat()
+            self.stream_mentor_chat()
            return
        if parsed.path == "/api/heaven/hexagram":
            self.heaven_hexagram()
@@ -4439,13 +4499,29 @@ class RequestHandler(BaseHTTPRequestHandler):
        except Exception as exc:
            self.send_json({"error": f"跟踪刷新失败：{exc}"}, HTTPStatus.INTERNAL_SERVER_ERROR)

-    def mentor_chat(self) -> None:
+    def stream_mentor_chat(self) -> None:
        try:
            body = self.read_json_body()
-            result = SERVICE.mentor_chat(body)
-            self.send_json({"ok": True, **result})
+            stream = SERVICE.mentor_stream(body)
        except (ValueError, json.JSONDecodeError) as exc:
            self.send_json({"error": str(exc)}, HTTPStatus.BAD_REQUEST)
+            return
+        self.send_response(HTTPStatus.OK)
+        self.send_header("Content-Type", "application/x-ndjson; charset=utf-8")
+        self.send_header("Cache-Control", "no-cache, no-transform")
+        self.send_header("X-Accel-Buffering", "no")
+        self.send_header("Connection", "close")
+        self.end_headers()
+        try:
+            for event in stream:
+                self._write_stream_event(event)
+            self._write_stream_event({"type": "done"})
+        except (ValueError, MentorAgentError) as exc:
+            self._write_stream_event({"type": "error", "error": str(exc)})
+        except (BrokenPipeError, ConnectionResetError):
+            pass
+        finally:
+            self.close_connection = True

    def heaven_hexagram(self) -> None:
        try:
@@ -65,6 +65,9 @@ const state = {
  mentorQuery: "",
  mentorGrade: "all",
  mentorDirectoryOpen: false,
+  mentorSortMode: false,
+  mentorSavingPreferences: false,
+  mentorController: null,
  heavenSetup: null,
  heavenManualData: null,
  personalField: null,
@@ -554,6 +557,7 @@ function bindEvents() {
  });
  document.querySelector("#closeMentorDirectory").addEventListener("click", () => toggleMentorDirectory(false));
  document.querySelector("#mentorDirectoryBackdrop").addEventListener("click", () => toggleMentorDirectory(false));
+  document.querySelector("#mentorSortToggle").addEventListener("click", toggleMentorSortMode);
  document.querySelector("#mentorSearchInput").addEventListener("input", (event) => {
    state.mentorQuery = event.target.value.trim().toLocaleLowerCase("zh-CN");
    renderMentorDirectory();
@@ -2045,6 +2049,13 @@ async function loadMentorSetup(force = false) {
    const query = new URLSearchParams({ trade_date: elements.tradeDate.value });
    const payload = await apiRequest(`/api/mentors/setup?${query}`);
    payload.requestedDate = requestedDate;
+    if (!payload.preferences_configured) {
+      payload.mentors.sort((first, second) => {
+        if (Boolean(first.private) !== Boolean(second.private)) return first.private ? -1 : 1;
+        return String(first.name || "").localeCompare(String(second.name || ""), "zh-CN");
+      });
+      payload.mentors.forEach((mentor, index) => { mentor.sort_order = index; });
+    }
    state.mentorSetup = payload;
    const selectedExists = payload.mentors.some((item) => item.id === state.selectedMentorId);
    state.selectedMentorId = selectedExists ? state.selectedMentorId : payload.mentors[0]?.id || "";
@@ -2075,6 +2086,7 @@ function renderMentorDirectory() {
  const mentors = state.mentorSetup?.mentors || [];
  const query = state.mentorQuery;
  const filtered = mentors.filter((mentor) => {
+    if (state.mentorSortMode) return true;
    if (state.mentorGrade !== "all" && mentor.evidence?.grade !== state.mentorGrade) return false;
    if (!query) return true;
    const haystack = [
@@ -2086,28 +2098,180 @@ function renderMentorDirectory() {
      ...(mentor.focus || []),
    ].filter(Boolean).join(" ").toLocaleLowerCase("zh-CN");
    return haystack.includes(query);
-  }).sort((first, second) => {
-    if (Boolean(first.private) !== Boolean(second.private)) return first.private ? -1 : 1;
-    return String(first.name || "").localeCompare(String(second.name || ""), "zh-CN");
  });
  setText("mentorCount", filtered.length === mentors.length ? `${mentors.length} 位` : `${filtered.length} / ${mentors.length} 位`);
+  const sortToggle = document.querySelector("#mentorSortToggle");
+  sortToggle.classList.toggle("active", state.mentorSortMode);
+  sortToggle.setAttribute("aria-pressed", String(state.mentorSortMode));
+  sortToggle.querySelector("span").textContent = state.mentorSortMode ? "完成" : "整理";
+  document.querySelector("#mentorSortHint").hidden = !state.mentorSortMode;
+  document.querySelector("#mentorSearchInput").disabled = state.mentorSortMode;
+  document.querySelectorAll("[data-mentor-grade]").forEach((button) => {
+    button.disabled = state.mentorSortMode;
+  });
  const container = document.querySelector("#mentorList");
-  container.innerHTML = filtered.map((mentor) => `
-    <button type="button" class="mentor-option ${mentor.id === state.selectedMentorId ? "active" : ""}" data-mentor-id="${escapeHtml(mentor.id)}" aria-pressed="${mentor.id === state.selectedMentorId}">
-      <span class="mentor-option-copy">
-        <strong>${escapeHtml(mentor.name)}</strong>
-        <em title="${escapeHtml(mentor.description || "")}">${escapeHtml(mentor.description || mentor.tagline || "思维模型")}</em>
-      </span>
-      <span class="mentor-option-badges">${renderMentorBadges(mentor)}</span>
-    </button>
-  `).join("");
+  container.classList.toggle("is-sorting", state.mentorSortMode);
+  container.innerHTML = filtered.map((mentor) => {
+    const group = mentors.filter((item) => Boolean(item.pinned) === Boolean(mentor.pinned));
+    const groupIndex = group.findIndex((item) => item.id === mentor.id);
+    return `
+      <article class="mentor-option ${mentor.id === state.selectedMentorId ? "active" : ""} ${mentor.pinned ? "is-pinned" : ""}"
+        data-mentor-card="${escapeHtml(mentor.id)}" draggable="${state.mentorSortMode && !state.mentorSavingPreferences}">
+        <button type="button" class="mentor-option-main" data-mentor-id="${escapeHtml(mentor.id)}" aria-pressed="${mentor.id === state.selectedMentorId}" ${state.mentorLoading ? "disabled" : ""}>
+          <span class="mentor-option-copy">
+            <strong>${escapeHtml(mentor.name)}</strong>
+            <em title="${escapeHtml(mentor.description || "")}">${escapeHtml(mentor.description || mentor.tagline || "思维模型")}</em>
+          </span>
+          <span class="mentor-option-badges">${renderMentorBadges(mentor)}</span>
+        </button>
+        <span class="mentor-option-tools">
+          <button type="button" class="mentor-pin-button ${mentor.pinned ? "active" : ""}" data-mentor-pin="${escapeHtml(mentor.id)}"
+            aria-label="${mentor.pinned ? "取消置顶" : "置顶"}${escapeHtml(mentor.name)}" title="${mentor.pinned ? "取消置顶" : "置顶"}" ${state.mentorSavingPreferences ? "disabled" : ""}>
+            <i data-lucide="pin"></i>
+          </button>
+          ${state.mentorSortMode ? `
+            <button type="button" class="mentor-order-button" data-mentor-move="up" data-mentor-target="${escapeHtml(mentor.id)}" aria-label="上移${escapeHtml(mentor.name)}" title="上移" ${groupIndex <= 0 || state.mentorSavingPreferences ? "disabled" : ""}><i data-lucide="chevron-up"></i></button>
+            <button type="button" class="mentor-order-button" data-mentor-move="down" data-mentor-target="${escapeHtml(mentor.id)}" aria-label="下移${escapeHtml(mentor.name)}" title="下移" ${groupIndex >= group.length - 1 || state.mentorSavingPreferences ? "disabled" : ""}><i data-lucide="chevron-down"></i></button>
+          ` : ""}
+        </span>
+      </article>
+    `;
+  }).join("");
  document.querySelector("#mentorListEmpty").hidden = filtered.length > 0;
  document.querySelectorAll("[data-mentor-id]").forEach((button) => {
    button.addEventListener("click", () => selectMentor(button.dataset.mentorId));
  });
+  document.querySelectorAll("[data-mentor-pin]").forEach((button) => {
+    button.addEventListener("click", () => toggleMentorPin(button.dataset.mentorPin));
+  });
+  document.querySelectorAll("[data-mentor-move]").forEach((button) => {
+    button.addEventListener("click", () => moveMentor(button.dataset.mentorTarget, button.dataset.mentorMove));
+  });
+  document.querySelectorAll("[data-mentor-card]").forEach((card) => {
+    card.addEventListener("dragstart", handleMentorDragStart);
+    card.addEventListener("dragover", handleMentorDragOver);
+    card.addEventListener("drop", handleMentorDrop);
+    card.addEventListener("dragend", clearMentorDragState);
+  });
  refreshIcons();
 }

+function toggleMentorSortMode() {
+  state.mentorSortMode = !state.mentorSortMode;
+  if (state.mentorSortMode) {
+    state.mentorQuery = "";
+    state.mentorGrade = "all";
+    document.querySelector("#mentorSearchInput").value = "";
+    document.querySelectorAll("[data-mentor-grade]").forEach((button) => {
+      button.classList.toggle("active", button.dataset.mentorGrade === "all");
+    });
+  }
+  renderMentorDirectory();
+}
+
+async function toggleMentorPin(mentorId) {
+  if (state.mentorSavingPreferences) return;
+  const mentors = state.mentorSetup?.mentors || [];
+  const index = mentors.findIndex((item) => item.id === mentorId);
+  if (index < 0) return;
+  const [mentor] = mentors.splice(index, 1);
+  mentor.pinned = !mentor.pinned;
+  if (mentor.pinned) {
+    mentors.unshift(mentor);
+  } else {
+    const firstUnpinned = mentors.findIndex((item) => !item.pinned);
+    mentors.splice(firstUnpinned < 0 ? mentors.length : firstUnpinned, 0, mentor);
+  }
+  normalizeMentorOrder();
+  renderMentorWorkspace();
+  await persistMentorPreferences();
+}
+
+async function moveMentor(mentorId, direction) {
+  if (state.mentorSavingPreferences) return;
+  const mentors = state.mentorSetup?.mentors || [];
+  const index = mentors.findIndex((item) => item.id === mentorId);
+  if (index < 0) return;
+  const step = direction === "up" ? -1 : 1;
+  const targetIndex = index + step;
+  if (targetIndex < 0 || targetIndex >= mentors.length) return;
+  if (Boolean(mentors[index].pinned) !== Boolean(mentors[targetIndex].pinned)) return;
+  [mentors[index], mentors[targetIndex]] = [mentors[targetIndex], mentors[index]];
+  normalizeMentorOrder();
+  renderMentorDirectory();
+  await persistMentorPreferences();
+}
+
+function handleMentorDragStart(event) {
+  if (!state.mentorSortMode || state.mentorSavingPreferences) {
+    event.preventDefault();
+    return;
+  }
+  state.mentorDragId = event.currentTarget.dataset.mentorCard || "";
+  event.dataTransfer.effectAllowed = "move";
+  event.dataTransfer.setData("text/plain", state.mentorDragId);
+  event.currentTarget.classList.add("is-dragging");
+}
+
+function handleMentorDragOver(event) {
+  const source = state.mentorSetup?.mentors.find((item) => item.id === state.mentorDragId);
+  const target = state.mentorSetup?.mentors.find((item) => item.id === event.currentTarget.dataset.mentorCard);
+  if (!source || !target || Boolean(source.pinned) !== Boolean(target.pinned)) return;
+  event.preventDefault();
+  event.dataTransfer.dropEffect = "move";
+  event.currentTarget.classList.add("is-drag-over");
+}
+
+async function handleMentorDrop(event) {
+  event.preventDefault();
+  const sourceId = state.mentorDragId || event.dataTransfer.getData("text/plain");
+  const targetId = event.currentTarget.dataset.mentorCard || "";
+  clearMentorDragState();
+  if (!sourceId || !targetId || sourceId === targetId) return;
+  const mentors = state.mentorSetup?.mentors || [];
+  const sourceIndex = mentors.findIndex((item) => item.id === sourceId);
+  const targetIndex = mentors.findIndex((item) => item.id === targetId);
+  if (sourceIndex < 0 || targetIndex < 0) return;
+  if (Boolean(mentors[sourceIndex].pinned) !== Boolean(mentors[targetIndex].pinned)) return;
+  const [mentor] = mentors.splice(sourceIndex, 1);
+  const insertionIndex = mentors.findIndex((item) => item.id === targetId);
+  mentors.splice(insertionIndex, 0, mentor);
+  normalizeMentorOrder();
+  renderMentorDirectory();
+  await persistMentorPreferences();
+}
+
+function clearMentorDragState() {
+  state.mentorDragId = "";
+  document.querySelectorAll(".mentor-option.is-dragging, .mentor-option.is-drag-over").forEach((item) => {
+    item.classList.remove("is-dragging", "is-drag-over");
+  });
+}
+
+function normalizeMentorOrder() {
+  (state.mentorSetup?.mentors || []).forEach((mentor, index) => {
+    mentor.sort_order = index;
+  });
+}
+
+async function persistMentorPreferences() {
+  const mentors = state.mentorSetup?.mentors || [];
+  state.mentorSavingPreferences = true;
+  renderMentorDirectory();
+  try {
+    await apiRequest("/api/mentors/preferences", "POST", {
+      order: mentors.map((item) => item.id),
+      pinned: mentors.filter((item) => item.pinned).map((item) => item.id),
+    });
+  } catch (error) {
+    showToast(error.message || "问师顺序保存失败");
+    await loadMentorSetup(true);
+  } finally {
+    state.mentorSavingPreferences = false;
+    renderMentorDirectory();
+  }
+}
+
 function renderMentorBadges(mentor, expanded = false) {
  const badges = [];
  if (mentor.private) {
@@ -2166,13 +2330,14 @@ function renderMentorMessages() {
    `;
  } else {
    container.innerHTML = state.mentorMessages.map((message) => `
-      <article class="mentor-message ${message.role}">
+      <article class="mentor-message ${message.role} ${message.error ? "is-error" : ""}">
        <div class="mentor-message-label">${message.role === "user" ? "我" : escapeHtml(selected?.name || "问师")}</div>
        <div class="mentor-message-content">${message.role === "assistant" ? formatMentorAnswer(message.content) : escapeHtml(message.content)}</div>
-        ${message.meta ? `<small>${escapeHtml(message.meta)}</small>` : ""}
+        ${message.streaming ? '<span class="assistant-stream-caret" aria-hidden="true"></span>' : ""}
+        ${message.meta && !message.streaming ? `<small>${escapeHtml(message.meta)}</small>` : ""}
      </article>
    `).join("");
-    if (state.mentorLoading) {
+    if (state.mentorLoading && !state.mentorMessages.some((message) => message.streaming)) {
      container.insertAdjacentHTML("beforeend", `
        <article class="mentor-message assistant loading-message">
          <div class="mentor-message-label">${escapeHtml(selected?.name || "问师")}</div>
@@ -2184,6 +2349,7 @@ function renderMentorMessages() {
  document.querySelector("#clearMentorChatButton").disabled = !state.mentorMessages.length || state.mentorLoading;
  document.querySelector("#mentorQuestion").disabled = state.mentorLoading || !state.selectedMentorId;
  document.querySelector("#sendMentorQuestion").disabled = state.mentorLoading || !state.selectedMentorId;
+  document.querySelector("#mentorSortToggle").disabled = state.mentorLoading;
  requestAnimationFrame(() => { container.scrollTop = container.scrollHeight; });
 }

@@ -2198,36 +2364,99 @@ async function sendMentorQuestion(event) {
    content: item.content.slice(0, 3500),
  }));
  state.mentorMessages.push({ role: "user", content: question });
+  const responseMessage = { role: "assistant", content: "", streaming: true, meta: "" };
+  state.mentorMessages.push(responseMessage);
  input.value = "";
  state.mentorLoading = true;
+  state.mentorController = new AbortController();
  hideMentorNotice();
  renderMentorMessages();
+  renderMentorDirectory();
  setStatus("问师正在读取复盘数据");
  try {
-    const payload = await apiRequest("/api/mentors/chat", "POST", {
-      mentor_id: state.selectedMentorId,
-      trade_date: elements.tradeDate.value,
-      question,
-      history,
-    });
-    state.mentorMessages.push({
-      role: "assistant",
-      content: payload.answer,
-      meta: `${displayCompactDate(payload.data_trade_date)} · 回答完成`,
-    });
-    if (payload.notice) showMentorNotice(payload.notice);
+    await streamMentorRequest(
+      {
+        mentor_id: state.selectedMentorId,
+        trade_date: elements.tradeDate.value,
+        question,
+        history,
+      },
+      state.mentorController.signal,
+      (chunk) => {
+        responseMessage.content += chunk;
+        scheduleMentorRender();
+      },
+      (meta) => {
+        responseMessage.meta = `${displayCompactDate(meta.data_trade_date || elements.tradeDate.value)} · 回答完成`;
+        if (meta.notice) showMentorNotice(meta.notice);
+      },
+    );
+    responseMessage.streaming = false;
    setStatus("问师回答完成");
  } catch (error) {
+    responseMessage.streaming = false;
+    responseMessage.error = true;
+    if (!responseMessage.content) {
+      state.mentorMessages = state.mentorMessages.filter((item) => item !== responseMessage);
+    }
    showMentorNotice(error.message || "问师回答失败");
    showToast(error.message || "问师回答失败");
    setStatus("问师回答失败");
  } finally {
    state.mentorLoading = false;
+    state.mentorController = null;
    renderMentorMessages();
+    renderMentorDirectory();
    input.focus();
  }
 }

+let mentorRenderFrame = 0;
+
+function scheduleMentorRender() {
+  if (mentorRenderFrame) return;
+  mentorRenderFrame = requestAnimationFrame(() => {
+    mentorRenderFrame = 0;
+    renderMentorMessages();
+  });
+}
+
+async function streamMentorRequest(body, signal, onDelta, onMeta) {
+  const response = await fetch("/api/mentors/chat", {
+    method: "POST",
+    headers: {
+      "Content-Type": "application/json",
+      ...(state.csrfToken ? { "X-CSRF-Token": state.csrfToken } : {}),
+    },
+    body: JSON.stringify(body),
+    signal,
+  });
+  if (!response.ok) {
+    const payload = await response.json().catch(() => ({}));
+    throw new Error(payload.error || "问师暂不可用");
+  }
+  if (!response.body) throw new Error("当前浏览器不支持流式回答");
+  const reader = response.body.getReader();
+  const decoder = new TextDecoder();
+  let buffer = "";
+  const consume = (line) => {
+    if (!line.trim()) return;
+    const event = JSON.parse(line);
+    if (event.type === "delta") onDelta(String(event.content || ""));
+    if (event.type === "meta") onMeta(event);
+    if (event.type === "error") throw new Error(event.error || "问师回答失败");
+  };
+  while (true) {
+    const { value, done } = await reader.read();
+    buffer += decoder.decode(value || new Uint8Array(), { stream: !done });
+    const lines = buffer.split("\n");
+    buffer = lines.pop() || "";
+    lines.forEach(consume);
+    if (done) break;
+  }
+  if (buffer.trim()) consume(buffer);
+}
+
 function useMentorQuickPrompt(prompt) {
  const input = document.querySelector("#mentorQuestion");
  input.value = prompt || "";
@@ -2278,13 +2507,45 @@ function hideMentorNotice() {
 }

 function formatMentorAnswer(content) {
-  return escapeHtml(content).split("\n").map((line) => {
+  const blocks = [];
+  let listType = "";
+  let listItems = [];
+  const flushList = () => {
+    if (!listItems.length) return;
+    blocks.push(`<${listType} class="mentor-answer-list">${listItems.map((item) => `<li>${item}</li>`).join("")}</${listType}>`);
+    listItems = [];
+    listType = "";
+  };
+  String(content || "").replace(/\r\n?/g, "\n").replace(/\n{3,}/g, "\n\n").split("\n").forEach((rawLine) => {
+    const line = rawLine.trim();
+    if (!line) {
+      flushList();
+      return;
+    }
    const heading = line.match(/^#{1,3}\s+(.+)$/);
-    if (heading) return `<strong class="mentor-answer-heading">${formatMentorInline(heading[1])}</strong>`;
-    if (/^-{3,}$/.test(line.trim())) return '<span class="mentor-answer-rule"></span>';
-    if (line.startsWith("&gt; ")) return `<span class="mentor-answer-quote">${formatMentorInline(line.slice(5))}</span>`;
-    return formatMentorInline(line);
-  }).join("<br>");
+    const bullet = line.match(/^[-*]\s+(.+)$/);
+    const ordered = line.match(/^\d+[.、]\s*(.+)$/);
+    if (heading) {
+      flushList();
+      blocks.push(`<strong class="mentor-answer-heading">${formatMentorInline(escapeHtml(heading[1]))}</strong>`);
+    } else if (/^-{3,}$/.test(line)) {
+      flushList();
+      blocks.push('<span class="mentor-answer-rule"></span>');
+    } else if (line.startsWith("> ")) {
+      flushList();
+      blocks.push(`<span class="mentor-answer-quote">${formatMentorInline(escapeHtml(line.slice(2)))}</span>`);
+    } else if (bullet || ordered) {
+      const nextType = bullet ? "ul" : "ol";
+      if (listType && listType !== nextType) flushList();
+      listType = nextType;
+      listItems.push(formatMentorInline(escapeHtml((bullet || ordered)[1])));
+    } else {
+      flushList();
+      blocks.push(`<p class="mentor-answer-paragraph">${formatMentorInline(escapeHtml(line))}</p>`);
+    }
+  });
+  flushList();
+  return blocks.join("");
 }

 function formatMentorInline(content) {
@@ -813,7 +813,10 @@
          <div id="mentorDirectoryContent" class="mentor-directory-content">
            <div class="workspace-heading mentor-directory-heading">
              <div><h3>思维模型</h3><span id="mentorCount">0 位</span></div>
-              <button id="closeMentorDirectory" class="icon-button mentor-directory-close" type="button" aria-label="关闭思维模型目录" title="关闭"><i data-lucide="x"></i></button>
+              <div class="mentor-directory-actions">
+                <button id="mentorSortToggle" class="mentor-sort-toggle" type="button" aria-pressed="false" title="整理顺序"><i data-lucide="list-ordered"></i><span>整理</span></button>
+                <button id="closeMentorDirectory" class="icon-button mentor-directory-close" type="button" aria-label="关闭思维模型目录" title="关闭"><i data-lucide="x"></i></button>
+              </div>
            </div>
            <label class="mentor-search-field">
              <span class="visually-hidden">搜索思维模型</span>
@@ -826,6 +829,7 @@
              <button type="button" data-mentor-grade="B">B 多源</button>
              <button type="button" data-mentor-grade="C">C 推演</button>
            </div>
+            <p id="mentorSortHint" class="mentor-sort-hint" hidden>拖动卡片，或使用箭头调整顺序</p>
            <div id="mentorList" class="mentor-list"></div>
            <div id="mentorListEmpty" class="mentor-list-empty" hidden>没有符合条件的思维模型</div>
            <p class="mentor-evidence-legend">素材等级反映蒸馏依据，不代表人物能力或收益水平。</p>
@@ -11779,7 +11779,7 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  height: 100%;
  min-height: 0;
  display: grid;
-  grid-template-rows: auto auto auto minmax(0, 1fr) auto;
+  grid-template-rows: auto auto auto auto minmax(0, 1fr) auto;
  gap: 10px;
  padding: 14px 12px 10px;
 }
@@ -11805,6 +11805,39 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  font-size: 11px;
 }

+.mentor-directory-actions {
+  display: flex;
+  align-items: center;
+  gap: 4px;
+}
+
+.mentor-sort-toggle {
+  min-height: 30px;
+  display: inline-flex;
+  align-items: center;
+  gap: 5px;
+  padding: 0 8px;
+  border: 1px solid var(--border);
+  border-radius: 4px;
+  background: var(--surface);
+  color: var(--text-muted);
+  cursor: pointer;
+  font: inherit;
+  font-size: 10px;
+}
+
+.mentor-sort-toggle:hover,
+.mentor-sort-toggle.active {
+  border-color: color-mix(in srgb, var(--action) 38%, var(--border));
+  background: var(--action-soft);
+  color: var(--action);
+}
+
+.mentor-sort-toggle .lucide {
+  width: 13px;
+  height: 13px;
+}
+
 .mentor-search-field {
  height: 40px;
  display: grid;
@@ -11876,6 +11909,14 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  outline-offset: 1px;
 }

+.mentor-sort-hint {
+  margin: 0;
+  padding: 0 3px;
+  color: var(--text-muted);
+  font-size: 9px;
+  line-height: 1.4;
+}
+
 .mentor-list {
  min-height: 0;
  display: grid;
@@ -11893,7 +11934,7 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  grid-template-columns: minmax(0, 1fr) auto;
  align-items: center;
  gap: 8px;
-  padding: 8px 9px;
+  padding: 0 5px 0 0;
  border: 1px solid transparent;
  border-bottom-color: var(--border);
  border-radius: 4px;
@@ -11901,6 +11942,96 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  transition: border-color var(--motion-fast) ease, background-color var(--motion-fast) ease;
 }

+.mentor-option-main {
+  min-width: 0;
+  min-height: 64px;
+  display: grid;
+  grid-template-columns: minmax(0, 1fr) auto;
+  align-items: center;
+  gap: 8px;
+  padding: 8px 5px 8px 9px;
+  border: 0;
+  background: transparent;
+  color: inherit;
+  cursor: pointer;
+  font: inherit;
+  text-align: left;
+}
+
+.mentor-option-main:disabled {
+  cursor: default;
+}
+
+.mentor-option .mentor-option-tools {
+  display: flex;
+  align-items: center;
+  gap: 2px;
+  margin: 0;
+  overflow: visible;
+  color: inherit;
+  font-size: inherit;
+  line-height: normal;
+  white-space: normal;
+}
+
+.mentor-pin-button,
+.mentor-order-button {
+  width: 28px;
+  min-width: 28px;
+  height: 30px;
+  display: grid;
+  place-items: center;
+  padding: 0;
+  border: 0;
+  border-radius: 4px;
+  background: transparent;
+  color: var(--text-muted);
+  cursor: pointer;
+}
+
+.mentor-pin-button:hover,
+.mentor-order-button:hover:not(:disabled) {
+  background: var(--surface-muted);
+  color: var(--text);
+}
+
+.mentor-pin-button.active {
+  background: #fff7df;
+  color: #9a6815;
+}
+
+.mentor-pin-button.active .lucide {
+  fill: currentColor;
+}
+
+.mentor-pin-button .lucide,
+.mentor-order-button .lucide {
+  width: 14px;
+  height: 14px;
+}
+
+.mentor-order-button:disabled {
+  color: color-mix(in srgb, var(--text-muted) 35%, transparent);
+  cursor: default;
+}
+
+.mentor-list.is-sorting .mentor-option {
+  cursor: grab;
+}
+
+.mentor-list.is-sorting .mentor-option-badges {
+  display: none;
+}
+
+.mentor-option.is-dragging {
+  opacity: 0.45;
+}
+
+.mentor-option.is-drag-over {
+  border-color: var(--action);
+  background: var(--action-soft);
+}
+
 .mentor-option:hover {
  border-color: var(--border-strong);
  background: var(--surface);
@@ -11923,6 +12054,16 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  gap: 4px;
 }

+.mentor-option .mentor-option-copy {
+  display: grid;
+  margin: 0;
+  overflow: visible;
+  color: inherit;
+  font-size: inherit;
+  line-height: normal;
+  white-space: normal;
+}
+
 .mentor-option-copy strong {
  overflow: hidden;
  font-size: 13px;
@@ -11949,6 +12090,16 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  gap: 4px;
 }

+.mentor-option .mentor-option-badges {
+  display: flex;
+  margin: 0;
+  overflow: visible;
+  color: inherit;
+  font-size: inherit;
+  line-height: normal;
+  white-space: normal;
+}
+
 .mentor-option-badges {
  max-width: 76px;
 }
@@ -11971,6 +12122,13 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  white-space: nowrap;
 }

+.mentor-option .mentor-badge {
+  display: inline-flex;
+  margin: 0;
+  overflow: visible;
+  line-height: 1;
+}
+
 .mentor-badge .lucide {
  width: 11px;
  height: 11px;
@@ -12057,6 +12215,47 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
  max-height: none;
 }

+.mentor-message {
+  margin-bottom: 12px;
+}
+
+.mentor-message-content {
+  line-height: 1.62;
+  white-space: normal;
+}
+
+.mentor-message .mentor-answer-paragraph {
+  margin: 0 0 6px;
+  line-height: inherit;
+}
+
+.mentor-message .mentor-answer-paragraph:last-child {
+  margin-bottom: 0;
+}
+
+.mentor-answer-heading {
+  display: block;
+  margin: 9px 0 4px;
+  line-height: 1.45;
+}
+
+.mentor-message-content > .mentor-answer-heading:first-child {
+  margin-top: 0;
+}
+
+.mentor-answer-list {
+  margin: 3px 0 7px;
+  padding-left: 20px;
+}
+
+.mentor-answer-list li + li {
+  margin-top: 3px;
+}
+
+.mentor-message.is-error {
+  border-color: var(--danger);
+}
+
@media (min-width: 721px) and (max-width: 1023px) {
  .mentor-layout {
    grid-template-columns: 280px minmax(0, 1fr);
@@ -12181,6 +12380,12 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
    display: grid;
  }

+  .mentor-sort-toggle {
+    min-height: 44px;
+    padding: 0 10px;
+    font-size: 11px;
+  }
+
  .mentor-search-field {
    height: 44px;
  }
@@ -12199,6 +12404,13 @@ button.account-role-badge:focus-visible { outline: 2px solid var(--blue); outlin
    min-height: 68px;
  }

+  .mentor-pin-button,
+  .mentor-order-button {
+    width: 40px;
+    min-width: 40px;
+    height: 44px;
+  }
+
  .mentor-chat-panel {
    min-height: 580px;
  }
@@ -218,6 +218,18 @@ async function mockApplication(page, authSession = session()) {
      };
    } else if (url.pathname === "/api/mentors/setup") {
      payload = { trade_date: "20260722", mentors: mentorDirectory(authSession.user.role) };
+    } else if (url.pathname === "/api/mentors/chat") {
+      await route.fulfill({
+        status: 200,
+        contentType: "application/x-ndjson; charset=utf-8",
+        body: [
+          JSON.stringify({ type: "delta", content: "## 判断\n先看市场结构。\n\n" }),
+          JSON.stringify({ type: "delta", content: "- 等待确认\n- 控制仓位" }),
+          JSON.stringify({ type: "meta", data_trade_date: "20260722", notice: "" }),
+          JSON.stringify({ type: "done" }),
+        ].join("\n"),
+      });
+      return;
    }
    else if (url.pathname === "/api/heaven/setup") {
      await route.fulfill({ status: 503, contentType: "application/json", body: JSON.stringify({ error: "测试环境不加载问天数据" }) });
@@ -515,6 +527,30 @@ test("mentor directory exposes evidence filters and private owner metadata", asy
  await expect(page.locator("#activeMentorEvidence")).toHaveText("公开访谈与多源材料");
 });

+test("mentor pins, custom order and streamed replies work together", async ({ page }) => {
+  await mockApplication(page, session("admin", true));
+  await page.goto("/index.html");
+  await page.locator('[data-view="mentorView"]').first().click();
+
+  await page.locator('[data-mentor-pin="source-c"]').click();
+  await expect(page.locator("#mentorList [data-mentor-card]").first()).toHaveAttribute("data-mentor-card", "source-c");
+  await page.locator('[data-mentor-pin="source-b"]').click();
+  await expect(page.locator("#mentorList [data-mentor-card]").first()).toHaveAttribute("data-mentor-card", "source-b");
+
+  await page.locator("#mentorSortToggle").click();
+  await page.locator('[data-mentor-target="source-b"][data-mentor-move="down"]').click();
+  await expect(page.locator("#mentorList [data-mentor-card]").first()).toHaveAttribute("data-mentor-card", "source-c");
+
+  await page.locator('[data-mentor-id="source-c"]').click();
+  await page.locator("#mentorQuestion").fill("现在怎么看？");
+  await page.locator("#sendMentorQuestion").click();
+  const answer = page.locator("#mentorMessages .mentor-message.assistant").last();
+  await expect(answer).toContainText("先看市场结构。");
+  await expect(answer.locator(".mentor-answer-list li")).toHaveCount(2);
+  await expect(answer.locator("br")).toHaveCount(0);
+  await expect(page.locator("#mentorMessages .assistant-stream-caret")).toHaveCount(0);
+});
+
 test("mobile mentor directory opens as a searchable selector and hides private mentors", async ({ page }) => {
  await page.setViewportSize({ width: 375, height: 812 });
  await mockApplication(page, session("user", true));
@@ -78,6 +78,21 @@ class AccountDataBoundaryTests(unittest.TestCase):
            self.database.delete_mentor_messages(self.first["id"], "mentor-a", "20260721"), 2
        )

+    def test_mentor_preferences_are_scoped_by_user(self):
+        self.database.save_mentor_preferences(
+            self.first["id"], ["mentor-b", "mentor-a"], {"mentor-b"}
+        )
+        self.database.save_mentor_preferences(
+            self.second["id"], ["mentor-a", "mentor-b"], set()
+        )
+
+        first = self.database.list_mentor_preferences(self.first["id"])
+        second = self.database.list_mentor_preferences(self.second["id"])
+        self.assertEqual([item["mentor_id"] for item in first], ["mentor-b", "mentor-a"])
+        self.assertTrue(first[0]["pinned"])
+        self.assertEqual([item["mentor_id"] for item in second], ["mentor-a", "mentor-b"])
+        self.assertFalse(any(item["pinned"] for item in second))
+
    def test_latest_data_snapshot_skips_demo_and_future_records(self):
        self.database.save_data_snapshot(
            "stock_detail", "002141:20260718", "tushare", {"marker": "real"}
@@ -17,6 +17,7 @@ class ApiAccessPolicyTests(unittest.TestCase):
            ("POST", "/api/screener/run"): "member",
            ("POST", "/api/screener/tracking/refresh"): "member",
            ("POST", "/api/mentors/chat"): "member",
+            ("POST", "/api/mentors/preferences"): "member",
            ("POST", "/api/heaven/interpret"): "member",
            ("POST", "/api/assistant/chat"): "member",
            ("DELETE", "/api/screener/strategies/42"): "member",
@@ -0,0 +1,71 @@
+from __future__ import annotations
+
+import json
+import unittest
+from pathlib import Path
+from unittest.mock import patch
+
+from mentor_agent import MentorSkill, chat_with_mentor, stream_with_mentor
+
+
+class FakeStreamResponse:
+    def __init__(self, lines: list[bytes]) -> None:
+        self.lines = lines
+
+    def __enter__(self):
+        return iter(self.lines)
+
+    def __exit__(self, exc_type, exc_value, traceback):
+        return False
+
+
+class MentorStreamTests(unittest.TestCase):
+    def setUp(self) -> None:
+        self.skill = MentorSkill(
+            skill_id="test-mentor",
+            name="测试老师",
+            description="测试",
+            tagline="先看事实",
+            focus=("纪律",),
+            content="只做条件化判断。",
+            path=Path("SKILL.md"),
+        )
+        self.lines = [
+            b'data: {"choices":[{"delta":{"content":"first"}}]}\n',
+            b'data: {"choices":[{"delta":{"content":" second"}}]}\n',
+            b"data: [DONE]\n",
+        ]
+
+    def test_stream_requests_upstream_streaming_and_yields_deltas(self):
+        captured = {}
+
+        def open_request(request, timeout):
+            captured["payload"] = json.loads(request.data.decode("utf-8"))
+            captured["accept"] = request.headers.get("Accept")
+            return FakeStreamResponse(self.lines)
+
+        with patch("mentor_agent.urllib.request.urlopen", side_effect=open_request):
+            chunks = list(
+                stream_with_mentor(
+                    self.skill, {"data_trade_date": "20260723"}, "怎么看？", [],
+                    "key", "https://example.test/v1", "model",
+                )
+            )
+
+        self.assertEqual(chunks, ["first", " second"])
+        self.assertTrue(captured["payload"]["stream"])
+        self.assertEqual(captured["accept"], "text/event-stream")
+
+    def test_non_streaming_compatibility_wrapper_collects_chunks(self):
+        with patch(
+            "mentor_agent.urllib.request.urlopen",
+            return_value=FakeStreamResponse(self.lines),
+        ):
+            result = chat_with_mentor(
+                self.skill, {}, "怎么看？", [], "key", "https://example.test/v1", "model"
+            )
+        self.assertEqual(result["answer"], "first second")
+
+
+if __name__ == "__main__":
+    unittest.main()