Feature/relatedai

.env

@@ -1,4 +1,4 @@
 SECRET_KEY=bN3hZ6LbHG7nH9YXWULCr-crcS3GAaRELbNBdAyHBuiHH5TRctd0Zbd6OuLRHHa4Fbs
 SENDER_PASSWORD=TXVU2unpCAE2EtEX
-KIMI_API_KEY=sk-icdiHIiv6x8XjJCaN6J6Un7uoVxm6df5WPhflq10ZVFo03D9
+KIMI_API_KEY=sk-WFAukbN3TVJKhkGLF55a5aF702Ec435b8c36A580E8E4D92d
 FERNET_SECRET_KEY=6WssEkvinI_YqwKXdokii2yI6iBiLO_Cjoyq0bBBC5o=

app/api/v1/endpoints/aichat.py

@@ -1,11 +1,15 @@
 from fastapi import Depends, Request
 from fastapi.responses import StreamingResponse
-from app.utils.aichat import kimi_chat_stream
+from app.utils.aichat import kimi_chat_stream, kimi_chat
 from app.utils.redis import get_redis_client
 from app.utils.auth import get_current_user
 import json
 from fastapi import APIRouter
 from app.schemas.aichat import NoteInput
+from sqlalchemy.ext.asyncio import AsyncSession
+from app.utils.get_db import get_db
+from app.utils.readPDF import read_pdf
+from fastapi import HTTPException
 
 
 router = APIRouter()
@@ -47,4 +51,80 @@ async def clear_notes(
     user_id = current_user["id"]
     redis_key = f"aichat:{user_id}"
     redis_client.delete(redis_key)
-    return {"msg": "clear successfully"}
+    return {"msg": "clear successfully"}
+
+@router.get("/review", response_model=dict)
+async def review_notes(
+    article_id: int,
+):
+    path = f"/lhcos-data/{article_id}.pdf"
+    text = await read_pdf(path)
+    text += "\n\n请根据以上内容生成文章综述。"
+    async def ai_stream():
+        full_reply = ""
+        try:
+            async for content in kimi_chat_stream([{"role": "user", "content": text}]):
+                full_reply += content
+                yield f"data: {json.dumps({'content': content}, ensure_ascii=False)}\n\n"
+        except Exception as e:
+            error_str = str(e)
+            if "exceeded model token limit" in error_str:
+                raise HTTPException(
+                    status_code=413,
+                    detail="输入内容过长，超出了模型的token限制"
+                )
+            # 其他类型的错误重新抛出
+            raise
+    return StreamingResponse(ai_stream(), media_type="text/event-stream")
+
+@router.get("/graph", response_model=dict)
+async def generate_graph(
+    note_id: int,
+    db : AsyncSession = Depends(get_db),
+):
+    # 读取数据库获取笔记内容
+    from app.curd.note import get_note_by_id
+    note = await get_note_by_id(db, note_id)
+    if not note:
+        raise HTTPException(status_code=404, detail="Note not found")
+    text = note.content
+    text += """
+    我需要你对于上面的内容生成思维导图，请仅给我返回mermaid代码，不要有其他内容，下面是生成样例，
+        graph TD
+        A[Natural Language Navigation for Service Robots] --> B[Task Definition]
+        A --> C[Challenges]
+        A --> D[Proposed Solution]
+        A --> E[Experimental Results]
+
+        B --> B1["- Predict action sequence from NL instructions"]
+        B --> B2["- Example: 'Walk out of bathroom to right stairs'"]
+
+        C --> C1["- Environment exploration"]
+        C --> C2["- Accurate path following"]
+        C --> C3["- Language-vision relationship modeling"]
+
+        D --> D1[CrossMap Transformer Network]
+        D --> D2[Transformer-based Speaker]
+        D --> D3[Double Back-Translation Model]
+
+        D1 --> D11["- Encodes linguistic/visual features"]
+        D1 --> D12["- Sequentially generates paths"]
+
+        D2 --> D21["- Generates navigation instructions"]
+
+        D3 --> D31["- Paths → Instructions"]
+        D3 --> D32["- Instructions → Paths"]
+        D3 --> D33["- Shared latent features"]
+
+        E --> E1["- Improved instruction understanding"]
+        E --> E2["- Enhanced instruction generation"
+    """
+    try:
+        ans = await kimi_chat([{"role": "user", "content": text}], model="moonshot-v1-32k")
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=f"AI服务异常: {str(e)}"
+        )
+    return {"mermaid_code": ans.strip().replace("```mermaid", "").replace("```", "").strip()}
+

app/curd/note.py

@@ -179,4 +179,12 @@ async def find_self_notes_count_in_db(db: AsyncSession, user_id: int):
     )
     result = await db.execute(stmt)
     count = result.scalar_one_or_none()
-    return count
+    return count
+
+async def get_note_by_id(db: AsyncSession, note_id: int):
+    """
+    根据 ID 获取笔记
+    """
+    stmt = select(Note).where(Note.id == note_id, Note.visible == True)
+    result = await db.execute(stmt)
+    return result.scalar_one_or_none()  # 返回单个笔记或 None

app/utils/aichat.py

@@ -3,10 +3,10 @@
 
 client = AsyncOpenAI(
     api_key=settings.KIMI_API_KEY,
-    base_url="https://api.moonshot.cn/v1",
+    base_url="http://47.93.172.156:3001/v1",
 )
 
-async def kimi_chat_stream(messages, model="moonshot-v1-8k", temperature=0.3):
+async def kimi_chat_stream(messages, model="moonshot-v1-32k", temperature=0.3):
     """
     异步AI流式对话工具方法，传入消息列表，流式返回AI回复内容。
     :param messages: List[dict]
@@ -21,4 +21,16 @@ async def kimi_chat_stream(messages, model="moonshot-v1-8k", temperature=0.3):
     async for chunk in stream:
         content = getattr(chunk.choices[0].delta, "content", None)
         if content:
-            yield content
+            yield content
+
+
+async def kimi_chat(messages, model="moonshot-v1-32k", temperature=0):
+    """
+    异步但不流式AI对话工具方法，传入消息列表，返回AI回复内容。
+    """
+    response = await client.chat.completions.create(
+        model=model,
+        messages=messages,
+        temperature=temperature
+    )
+    return response.choices[0].message.content if response.choices else ""

app/utils/readPDF.py

@@ -0,0 +1,17 @@
+import fitz
+import asyncio
+
+def extract_text_from_pdf(pdf_path):
+    # 打开PDF文件
+    doc = fitz.open(pdf_path)
+    text = ""
+    # 遍历每一页
+    for page_num in range(len(doc) - 2):
+        page = doc.load_page(page_num)  # 加载页面
+        page_text = page.get_text("text") 
+        text += page_text
+    doc.close()  # 关闭PDF文件
+    return text
+
+async def read_pdf(pdf_path: str):
+    return await asyncio.to_thread(extract_text_from_pdf, pdf_path)

requirements.txt

@@ -63,6 +63,7 @@ pycparser==2.22
 pydantic==2.11.2
 pydantic_core==2.33.1
 PyJWT==2.10.1
+PyMuPDF==1.26.0
 PyMySQL==1.1.1
 pytest==8.3.5
 python-dateutil==2.9.0.post0