修复ai

ai_client.py

@@ -55,10 +55,24 @@ def _use_openai() -> bool:
     return _ai_provider() in ("openai", "openai_compatible", "gateway")
 
 
-def _read_image_base64(image_path: str) -> Optional[str]:
+def _image_mime_for_path(path: str) -> str:
+    ext = os.path.splitext(str(path or ""))[1].lower()
+    if ext == ".png":
+        return "image/png"
+    if ext in (".jpg", ".jpeg"):
+        return "image/jpeg"
+    if ext == ".webp":
+        return "image/webp"
+    if ext == ".gif":
+        return "image/gif"
+    return "image/jpeg"
+
+
+def _read_image_base64(image_path: str) -> Optional[tuple]:
     try:
         with open(image_path, "rb") as f:
-            return base64.b64encode(f.read()).decode("utf-8")
+            b64 = base64.b64encode(f.read()).decode("utf-8")
+        return b64, _image_mime_for_path(image_path)
     except Exception:
         return None
 
@@ -66,15 +80,15 @@ def _read_image_base64(image_path: str) -> Optional[str]:
 def _collect_images(
     image_paths: Optional[Sequence[str]] = None,
     images_b64: Optional[Sequence[str]] = None,
-) -> List[str]:
-    out: List[str] = []
+) -> List[tuple]:
+    out: List[tuple] = []
     for p in image_paths or []:
-        b = _read_image_base64(p)
-        if b:
-            out.append(b)
+        item = _read_image_base64(p)
+        if item:
+            out.append(item)
     for b in images_b64 or []:
         if b:
-            out.append(str(b))
+            out.append((str(b), "image/jpeg"))
     return out
 
 
@@ -85,7 +99,7 @@ def _openai_chat_url() -> str:
     return f"{base}/chat/completions"
 
 
-def _generate_openai(prompt: str, images: List[str], temperature: float) -> str:
+def _generate_openai(prompt: str, images: List[tuple], temperature: float) -> str:
     api_key = _openai_api_key()
     if not api_key:
         return "AI 调用失败：未配置 OPENAI_API_KEY（请在当前实例目录 .env 中设置，修改后需重启服务）"
@@ -95,11 +109,11 @@ def _generate_openai(prompt: str, images: List[str], temperature: float) -> str:
     }
     if images:
         content: List[dict] = [{"type": "text", "text": prompt}]
-        for b64 in images:
+        for b64, mime in images:
             content.append(
                 {
                     "type": "image_url",
-                    "image_url": {"url": f"data:image/jpeg;base64,{b64}"},
+                    "image_url": {"url": f"data:{mime};base64,{b64}"},
                 }
             )
         messages = [{"role": "user", "content": content}]
@@ -126,7 +140,7 @@ def _generate_openai(prompt: str, images: List[str], temperature: float) -> str:
     return (msg.get("content") or "").strip() or "AI 生成失败：空内容"
 
 
-def _generate_ollama(prompt: str, images: List[str], temperature: float) -> str:
+def _generate_ollama(prompt: str, images: List[tuple], temperature: float) -> str:
     payload = {
         "model": _ollama_model(),
         "prompt": prompt,
@@ -134,7 +148,7 @@ def _generate_ollama(prompt: str, images: List[str], temperature: float) -> str:
         "options": {"temperature": temperature},
     }
     if images:
-        payload["images"] = images
+        payload["images"] = [b64 for b64, _mime in images]
     r = requests.post(_ollama_api(), json=payload, timeout=_ai_timeout_seconds())
     r.raise_for_status()
     return (r.json().get("response") or "").strip() or "AI 生成失败"
@@ -167,6 +181,12 @@ def ai_generate(
 
 
 def ai_review(trades_text: str, period_title: str, image_paths=None) -> str:
+    n_img = len(image_paths or [])
+    attach_note = (
+        f"【系统说明：已向模型附带 {n_img} 张复盘附图（自动K线或上传截图），请结合附图分析第5节。】\n\n"
+        if n_img
+        else "【系统说明：本次未附带复盘附图，第5节请写明「无附图，无法看图」；保存复盘记录时可勾选「自动生成K线图」。】\n\n"
+    )
     prompt = f"""
 你是一位专业交易教练。下面是用户的{period_title}交易记录，请做简洁、可执行的复盘（中文）。
 
@@ -188,7 +208,7 @@ def ai_review(trades_text: str, period_title: str, image_paths=None) -> str:
 交易记录：
 {trades_text}
 """.strip()
-    return ai_generate(prompt, image_paths=image_paths, temperature=0.2)
+    return attach_note + ai_generate(prompt, image_paths=image_paths, temperature=0.2)
 
 
 def ai_short_advice(prompt_text: str) -> str: