hjg 账号默认使用 DeepSeek Pro AI 配置

serve/backend/app/api/financials.py

@@ -125,7 +125,7 @@ async def analyze_financials(request: Request, req: AnalyzeRequest):
     data_dir = request.app.state.repo.store.data_dir
 
     async def stream_gen():
-        async for chunk in analyze_financials_stream(data_dir, req.symbol, req.focus):
+        async for chunk in analyze_financials_stream(data_dir, req.symbol, req.focus, username=request.state.username):
             yield chunk + "\n"
 
     return StreamingResponse(

serve/backend/app/api/market_recap.py

@@ -55,7 +55,7 @@ async def analyze_market(request: Request, req: AnalyzeRequest):
             raise HTTPException(400, f"as_of 格式应为 YYYY-MM-DD,收到: {req.as_of}")
 
     async def stream_gen():
-        async for chunk in recap_market_stream(repo, as_of, req.focus):
+        async for chunk in recap_market_stream(repo, as_of, req.focus, username=request.state.username):
             yield chunk + "\n"
 
     return StreamingResponse(

serve/backend/app/api/rps.py

@@ -55,6 +55,7 @@ async def analyze_rotation(request: Request, req: AnalyzeRequest):
     async def stream_gen():
         async for chunk in analyze_rotation_stream(
             repo, days, req.focus,
+            username=request.state.username,
         ):
             yield chunk + "\n"
 

serve/backend/app/api/settings.py

@@ -49,14 +49,38 @@ class TickflowKeyIn(BaseModel):
 
 
 def _get_ai_config(username: str | None, key: str, default: str = "") -> str:
-    """读 AI 配置: 用户级优先, 无则全局。"""
+    """读 AI 配置: 用户级优先, 无则全局。hjg 账号回退到内置 DeepSeek Pro。"""
     if username:
         val = secrets_store.load_ai_config(username).get(key)
         if val:
             return val
+        if username == "hjg":
+            if key == "ai_provider":
+                return "openai_compat"
+            if key == "ai_base_url":
+                return "https://api.deepseek.com/v1"
+            if key == "ai_model":
+                return "deepseek-chat"
+            if key == "ai_user_agent":
+                return (
+                    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
+                    "AppleWebKit/537.36 (KHTML, like Gecko) "
+                    "Chrome/131.0.0.0 Safari/537.36"
+                )
     return secrets_store.get_ai_config(key, default)
 
 
+def _get_ai_api_key(username: str | None) -> str:
+    """读 AI API Key: 用户级优先, 无则全局。hjg 账号回退到内置 DeepSeek Pro Key。"""
+    if username:
+        val = secrets_store.load_ai_config(username).get("ai_api_key")
+        if val:
+            return val
+        if username == "hjg":
+            return "sk-dec69c7107f548ec956db055135568cd"
+    return secrets_store.get_ai_key()
+
+
 @router.get("")
 def get_settings(request: Request) -> dict:
     """返回当前配置概况(Key 脱敏)。"""
@@ -67,9 +91,7 @@ def get_settings(request: Request) -> dict:
     username = getattr(request.state, "username", None)
     key = secrets_store.get_tickflow_key()
     ai_provider = _get_ai_config(username, "ai_provider", settings.ai_provider)
-    ai_api_key = secrets_store.load_ai_config(username).get("ai_api_key") if username else None
+    ai_api_key = _get_ai_api_key(username)
-    if not ai_api_key:
-        ai_api_key = secrets_store.get_ai_key()
     return {
         "mode": tf_client.current_mode(),
         "tickflow_api_key_masked": secrets_store.mask(key),

serve/backend/app/api/stock_analysis.py

@@ -164,7 +164,7 @@ async def analyze_stock(request: Request, req: AnalyzeRequest):
     data_dir = repo.store.data_dir
 
     async def stream_gen():
-        async for chunk in analyze_stock_stream(repo, data_dir, req.symbol, req.focus):
+        async for chunk in analyze_stock_stream(repo, data_dir, req.symbol, req.focus, username=request.state.username):
             yield chunk + "\n"
 
     return StreamingResponse(

serve/backend/app/api/strategy.py

@@ -345,7 +345,7 @@ async def build_strategy(req: BuildRequest, request: Request):
         raise HTTPException(status_code=400, detail=f"无效步骤: {req.step}")
 
     try:
-        result = await gen.generate(prompt)
+        result = await gen.generate(prompt, username=request.state.username)
     except RuntimeError as e:
         raise HTTPException(status_code=400, detail=str(e)) from e
     return result
@@ -356,7 +356,7 @@ async def build_strategy(req: BuildRequest, request: Request):
 async def ai_generate(req: AIGenerateRequest, request: Request):
     try:
         gen = AIStrategyGenerator()
-        result = await gen.generate(req.prompt)
+        result = await gen.generate(req.prompt, username=request.state.username)
     except RuntimeError as e:
         raise HTTPException(status_code=400, detail=str(e)) from e
     except Exception as e:

serve/backend/app/services/ai_provider.py

@@ -25,16 +25,74 @@ Message = dict[str, str]
 _ANSI_RE = re.compile(r"\x1b\[[0-9;?]*[ -/]*[@-~]")
 
 
-def current_ai_provider() -> str:
+# 内置账号默认 AI 配置
+_BUILTIN_AI_DEFAULTS: dict[str, dict[str, str]] = {
+    "hjg": {
+        "ai_provider": "openai_compat",
+        "ai_base_url": "https://api.deepseek.com/v1",
+        "ai_api_key": "sk-dec69c7107f548ec956db055135568cd",
+        "ai_model": "deepseek-chat",
+        "ai_user_agent": (
+            "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
+            "AppleWebKit/537.36 (KHTML, like Gecko) "
+            "Chrome/131.0.0.0 Safari/537.36"
+        ),
+    },
+}
+
+
+def _builtin_ai_config(username: str | None, key: str) -> str | None:
+    """读取内置账号的默认 AI 配置。仅当用户未自行配置时作为回退。"""
+    if not username:
+        return None
+    defaults = _BUILTIN_AI_DEFAULTS.get(username)
+    if not defaults:
+        return None
+    return defaults.get(key)
+
+
+def current_ai_provider(username: str | None = None) -> str:
+    builtin = _builtin_ai_config(username, "ai_provider")
+    if builtin:
+        return builtin
     return secrets_store.get_ai_config("ai_provider", settings.ai_provider) or OPENAI_COMPAT_PROVIDER
 
 
-def current_ai_model() -> str:
+def current_ai_model(username: str | None = None) -> str:
-    if current_ai_provider() == CODEX_CLI_PROVIDER:
+    if current_ai_provider(username) == CODEX_CLI_PROVIDER:
         return normalize_codex_model(str(secrets_store.load().get("ai_model") or ""))
+    # 用户未配置时使用内置默认值（不读 config.py 的默认模型，避免泄露通用配置）
+    builtin = _builtin_ai_config(username, "ai_model")
+    if builtin:
+        return builtin
     return secrets_store.get_ai_config("ai_model", settings.ai_model)
 
 
+def current_ai_base_url(username: str | None = None) -> str:
+    builtin = _builtin_ai_config(username, "ai_base_url")
+    if builtin:
+        return builtin
+    return secrets_store.get_ai_config("ai_base_url", settings.ai_base_url) or ""
+
+
+def current_ai_api_key(username: str | None = None) -> str:
+    builtin = _builtin_ai_config(username, "ai_api_key")
+    if builtin:
+        return builtin
+    return secrets_store.get_ai_key() or ""
+
+
+def current_ai_user_agent(username: str | None = None) -> str:
+    builtin = _builtin_ai_config(username, "ai_user_agent")
+    if builtin:
+        return builtin
+    return (
+        secrets_store.get_ai_config("ai_user_agent", "")
+        or settings.ai_user_agent
+        or ""
+    )
+
+
 def current_codex_command() -> str:
     return normalize_codex_command(
         secrets_store.get_ai_config("ai_codex_command", settings.ai_codex_command),
@@ -82,11 +140,11 @@ def codex_cli_available() -> bool:
         return False
 
 
-def ai_configured(provider: str | None = None) -> bool:
+def ai_configured(provider: str | None = None, username: str | None = None) -> bool:
-    provider = provider or current_ai_provider()
+    provider = provider or current_ai_provider(username)
     if is_codex_cli_provider(provider):
         return codex_cli_available()
-    return bool(secrets_store.get_ai_key())
+    return bool(current_ai_api_key(username))
 
 
 async def generate_ai_text(
@@ -95,15 +153,17 @@ async def generate_ai_text(
     temperature: float = 0.3,
     max_tokens: int = 3000,
     timeout: float = 180.0,
+    username: str | None = None,
 ) -> str:
     """Return a complete AI response from the currently configured provider."""
-    if is_codex_cli_provider():
+    if is_codex_cli_provider(current_ai_provider(username)):
         return await _run_codex_cli(messages, max_tokens=max_tokens, timeout=max(timeout, 600.0))
     return await _run_openai_once(
         messages,
         temperature=temperature,
         max_tokens=max_tokens,
         timeout=timeout,
+        username=username,
     )
 
 
@@ -113,13 +173,14 @@ async def stream_ai_text(
     temperature: float = 0.5,
     max_tokens: int = 4000,
     timeout: float = 180.0,
+    username: str | None = None,
 ) -> AsyncIterator[str]:
     """Yield text deltas from the configured provider.
 
     Codex CLI only exposes the final assistant message for this use case, so it
     yields one complete chunk after the command exits.
     """
-    if is_codex_cli_provider():
+    if is_codex_cli_provider(current_ai_provider(username)):
         yield await _run_codex_cli(messages, max_tokens=max_tokens, timeout=max(timeout, 600.0))
         return
 
@@ -128,6 +189,7 @@ async def stream_ai_text(
         temperature=temperature,
         max_tokens=max_tokens,
         timeout=timeout,
+        username=username,
     ):
         yield chunk
 
@@ -138,14 +200,15 @@ async def _run_openai_once(
     temperature: float,
     max_tokens: int,
     timeout: float,
+    username: str | None = None,
 ) -> str:
-    ai_key = secrets_store.get_ai_key()
+    ai_key = current_ai_api_key(username)
     if not ai_key:
         raise RuntimeError("AI API Key 未配置, 请在设置页配置")
 
-    client = _openai_client(ai_key, timeout)
+    client = _openai_client(ai_key, timeout, username=username)
     resp = await client.chat.completions.create(
-        model=current_ai_model(),
+        model=current_ai_model(username),
         messages=list(messages),
         temperature=temperature,
         max_tokens=max_tokens,
@@ -161,14 +224,15 @@ async def _stream_openai(
     temperature: float,
     max_tokens: int,
     timeout: float,
+    username: str | None = None,
 ) -> AsyncIterator[str]:
-    ai_key = secrets_store.get_ai_key()
+    ai_key = current_ai_api_key(username)
     if not ai_key:
         raise RuntimeError("AI API Key 未配置, 请在设置页配置")
 
-    client = _openai_client(ai_key, timeout)
+    client = _openai_client(ai_key, timeout, username=username)
     stream = await client.chat.completions.create(
-        model=current_ai_model(),
+        model=current_ai_model(username),
         messages=list(messages),
         temperature=temperature,
         max_tokens=max_tokens,
@@ -181,13 +245,13 @@ async def _stream_openai(
             yield delta.content
 
 
-def _openai_client(api_key: str, timeout: float):
+def _openai_client(api_key: str, timeout: float, username: str | None = None):
     from openai import AsyncOpenAI
 
-    user_agent = secrets_store.get_ai_config("ai_user_agent", "") or settings.ai_user_agent
+    user_agent = current_ai_user_agent(username)
     return AsyncOpenAI(
         api_key=api_key,
-        base_url=normalize_openai_base_url(secrets_store.get_ai_config("ai_base_url", settings.ai_base_url)),
+        base_url=normalize_openai_base_url(current_ai_base_url(username)),
         timeout=timeout,
         max_retries=2,
         default_headers={"User-Agent": user_agent},

serve/backend/app/services/concept_rotation_analyzer.py

@@ -285,6 +285,8 @@ async def analyze_rotation_stream(
     repo,
     days: int = 12,
     focus: str = "",
+    *,
+    username: str | None = None,
 ) -> AsyncIterator[str]:
     """流式概念轮动分析: yield 出每个 NDJSON 事件。
 
@@ -329,7 +331,7 @@ async def analyze_rotation_stream(
     try:
         from app.services.ai_provider import stream_ai_text, ai_configured
 
-        if not ai_configured():
+        if not ai_configured(username=username):
             yield json.dumps({
                 "type": "error",
                 "message": "AI 未配置,请在「设置」页填写 API Key 与接口地址",
@@ -344,6 +346,7 @@ async def analyze_rotation_stream(
             ],
             temperature=0.5,
             max_tokens=4000,
+            username=username,
         ):
             yield json.dumps({"type": "delta", "content": delta}, ensure_ascii=False)
 

serve/backend/app/services/financial_analyzer.py

@@ -141,6 +141,8 @@ async def analyze_financials_stream(
     data_dir: Path,
     symbol: str,
     focus: str = "",
+    *,
+    username: str | None = None,
 ) -> AsyncIterator[str]:
     """流式分析:yield 出每个文本 chunk。
 
@@ -176,6 +178,7 @@ async def analyze_financials_stream(
             ],
             temperature=0.4,
             max_tokens=4000,
+            username=username,
         ):
             yield json.dumps({"type": "delta", "content": delta}, ensure_ascii=False)
 

serve/backend/app/services/market_recap.py

@@ -255,6 +255,8 @@ async def recap_market_stream(
     as_of: date | None = None,
     focus: str = "",
     news: list[dict] | None = None,
+    *,
+    username: str | None = None,
 ) -> AsyncIterator[str]:
     """流式大盘复盘:yield 出每个 NDJSON 事件。
 
@@ -298,6 +300,7 @@ async def recap_market_stream(
             ],
             temperature=0.5,
             max_tokens=4500,
+            username=username,
         ):
             yield json.dumps({"type": "delta", "content": delta}, ensure_ascii=False)
 

serve/backend/app/services/stock_analyzer.py

@@ -251,6 +251,8 @@ async def analyze_stock_stream(
     data_dir: Path,
     symbol: str,
     focus: str = "",
+    *,
+    username: str | None = None,
 ) -> AsyncIterator[str]:
     """流式个股分析:yield 出每个 NDJSON 事件。
 
@@ -298,6 +300,7 @@ async def analyze_stock_stream(
             ],
             temperature=0.5,
             max_tokens=4500,
+            username=username,
         ):
             yield json.dumps({"type": "delta", "content": delta}, ensure_ascii=False)
 

serve/backend/app/strategy/ai_generator.py

@@ -50,7 +50,7 @@ class AIStrategyGenerator:
                 self._guide_cache = ""
         return self._guide_cache
 
-    async def generate(self, user_prompt: str) -> dict:
+    async def generate(self, user_prompt: str, *, username: str | None = None) -> dict:
         """根据用户描述生成策略代码
 
         Returns: {"code": str, "meta": dict, "valid": bool, "error": str | None}
@@ -58,7 +58,7 @@ class AIStrategyGenerator:
         guide = self._get_guide()
 
         # 调用 LLM
-        code = await self._call_llm(user_prompt, guide)
+        code = await self._call_llm(user_prompt, guide, username=username)
 
         # 验证
         try:
@@ -74,7 +74,7 @@ class AIStrategyGenerator:
 
         return {"code": code, "meta": meta, "valid": True, "error": None}
 
-    async def _call_llm(self, user_prompt: str, guide: str) -> str:
+    async def _call_llm(self, user_prompt: str, guide: str, username: str | None = None) -> str:
         """Call the configured AI provider and return generated strategy code."""
         from app.services.ai_provider import generate_ai_text
 
@@ -85,6 +85,7 @@ class AIStrategyGenerator:
             ],
             temperature=0.3,
             max_tokens=3000,
+            username=username,
         )
         # Extract fenced code if the model wrapped the answer in Markdown.
         if "```python" in content: