feat:增加AI生成资料接口

2026-08-02 09:46:32 +08:00
parent 9c9ac3ab1c
commit 5497b881c6
9 changed files with 179 additions and 82 deletions
--- a/agent/prompt.py
+++ b/agent/prompt.py
@@ -1,4 +1,4 @@
-study_prompt = """
+question_prompt = """
 你是一位专业的出题专家，擅长根据学习材料生成高质量的客观题（单选题和多选题）。

 请根据下方【学习材料】生成 5～10 道题目，严格遵守以下要求：
@@ -50,4 +50,35 @@ study_prompt = """
    "select": []
  }
 ]
+"""
+
+knowledge_prompt = """
+你是一位资深教学与教研专家，擅长将各类专业知识系统化梳理，转化为结构清晰、易懂好记的学习资料，适用于不同基础的学习者。
+
+请根据下方【学科】·【模块】·【名称】生成一份高质量学习资料，**以 Markdown 格式输出**，用于系统学习与复习。
+
+要求如下：
+1. 全文控制在 **500~800字**（可根据内容复杂度±10%），语言准确、条理清晰，适合打印或电子阅读。
+2. Markdown 结构必须包含以下一级或二级标题：
+   - ## 模块概述
+     （定义、作用、学习意义，可简要说明该模块在主题中的地位）
+   - ## 核心知识点
+     （分点讲解，重点概念用 **粗体** 标注）
+   - ## 对比与辨析
+     （对比易混淆概念）
+   - ## 记忆口诀 / 核心规律
+     （简洁押韵或逻辑清晰的归纳，便于记忆）
+   - ## 本章小结
+     （总结本模块最核心的要点）
+3. 内容需适配当前主题的属性：
+   - 理工类：突出公式、定理、推导过程、解题思路
+   - 医学类：突出机制、适应症、禁忌症、注意事项
+   - 文科 / 法商 / 管理类：突出概念界定、逻辑框架、典型案例
+4. 写作风格：
+   - 严谨、客观，贴近国内主流教材表述
+   - 避免口语化（如“同学们”“大家注意啦”）
+   - 不假设学习者是在校大学生，兼顾自学者与在职进修人员
+5. 输出要求：
+   - 仅输出 Markdown 正文，不要包含 `<html>`、JSON 或其他格式
+   - 不要在开头重复本提示词内容
 """
--- a/agent/study.py
+++ b/agent/study.py
@@ -1,9 +1,14 @@
 from langchain.agents import create_agent

 from agent.model import model
-from agent.prompt import study_prompt
+from agent.prompt import question_prompt, knowledge_prompt

-study_agent = create_agent(
+question_agent = create_agent(
    model=model,
-    system_prompt=study_prompt
+    system_prompt=question_prompt
+)
+
+knowledge_agent = create_agent(
+    model=model,
+    system_prompt=knowledge_prompt
 )
--- a/main.py
+++ b/main.py
@@ -1,19 +1,7 @@
-from typing import List
-
-from fastapi import FastAPI, UploadFile, File, Depends, Form
-from sqlalchemy.ext.asyncio import AsyncSession
+from fastapi import FastAPI
 from starlette.middleware.cors import CORSMiddleware
-from starlette.responses import StreamingResponse

-from database import get_db
-from schemas.agent import QueryRequest
-from schemas.library import LibraryFileRequest, LibraryFileResponse
-from schemas.mistake import MistakeResponse, MistakeRequest
-from schemas.practice import PracticeRecordResponse, PracticeRecordRequest
-from service import library_service, practice_service, mistake_service
-from service.agent_service import query_agent
-from storage import upload_rustfs
-from ocr import ocr_from_url
+from routers import routers

 app = FastAPI(title="AI Study Service")

@@ -24,62 +12,5 @@ app.add_middleware(
    allow_headers=["*"],
 )

-
-@app.post("/library/upload")
-def upload(file: UploadFile = File(...), filename: str = Form(...)):
-    url = upload_rustfs(file.file, filename)
-    return ocr_from_url(url)
-
-
-@app.post("/library/question")
-def generate(query: QueryRequest):
-    """流式对话"""
-    return StreamingResponse(
-        query_agent(query),
-        media_type="text/event-stream"
-    )
-
-
-@app.get("/library/files", response_model=List[LibraryFileResponse])
-async def list_files(db: AsyncSession = Depends(get_db)):
-    return await library_service.list_files(db)
-
-
-@app.get("/library/files/{id}", response_model=LibraryFileResponse)
-async def get_file(id: int, db: AsyncSession = Depends(get_db)):
-    return await library_service.get_file(db, id)
-
-
-@app.post("/library/files", response_model=bool)
-async def add_file(data: LibraryFileRequest, db: AsyncSession = Depends(get_db)):
-    return await library_service.add_file(db, data)
-
-
-@app.put("/library/files/{id}", response_model=bool)
-async def edit_file(id: int, data: LibraryFileRequest, db: AsyncSession = Depends(get_db)):
-    return await library_service.edit_file(db, id, data)
-
-
-@app.get("/practice/record/{id}", response_model=List[PracticeRecordResponse])
-async def get_record(id: int, db: AsyncSession = Depends(get_db)):
-    return await practice_service.get_record(db, id)
-
-
-@app.post("/practice/record", response_model=bool)
-async def add_record(data: PracticeRecordRequest, db: AsyncSession = Depends(get_db)):
-    return await practice_service.add_record(db, data)
-
-
-@app.get("/mistake", response_model=List[MistakeResponse])
-async def list_mistakes(db: AsyncSession = Depends(get_db)):
-    return await mistake_service.list_mistakes(db)
-
-
-@app.post("/mistake", response_model=bool)
-async def list_mistakes(data: list[MistakeRequest], db: AsyncSession = Depends(get_db)):
-    return await mistake_service.add_mistakes(db, data)
-
-
-@app.delete("/mistake/{id}", response_model=bool)
-async def remove_mistake(id: int, db: AsyncSession = Depends(get_db)):
-    return await mistake_service.remove_mistake(db, id)
+for router in routers:
+    app.include_router(router)
--- a/routers/init.py
+++ b/routers/init.py
@@ -0,0 +1,9 @@
+from .library import router as library_router
+from .practice import router as practice_router
+from .mistake import router as mistake_router
+
+routers = [
+    library_router,
+    practice_router,
+    mistake_router,
+]
--- a/routers/library.py
+++ b/routers/library.py
@@ -0,0 +1,55 @@
+from typing import List
+from fastapi import APIRouter, Depends, File, Form, UploadFile
+from sqlalchemy.ext.asyncio import AsyncSession
+from starlette.responses import StreamingResponse
+
+from database import get_db
+from schemas.library import LibraryFileRequest, LibraryFileResponse
+from schemas.agent import QueryQuestionRequest, QueryKnowledgeRequest
+from service import library_service, agent_service
+from storage import upload_rustfs
+from ocr import ocr_from_url
+
+router = APIRouter(prefix="/library", tags=["Library"])
+
+
+@router.post("/upload")
+def upload(file: UploadFile = File(...), filename: str = Form(...)):
+    url = upload_rustfs(file.file, filename)
+    return ocr_from_url(url)
+
+
+@router.post("/question")
+def generate_question(query: QueryQuestionRequest):
+    return StreamingResponse(
+        agent_service.query_question_agent(query),
+        media_type="text/event-stream",
+    )
+
+
+@router.post("/knowledge")
+def generate_knowledge(query: QueryKnowledgeRequest):
+    return StreamingResponse(
+        agent_service.query_knowledge_agent(query),
+        media_type="text/event-stream",
+    )
+
+
+@router.get("/files", response_model=List[LibraryFileResponse])
+async def list_files(db: AsyncSession = Depends(get_db)):
+    return await library_service.list_files(db)
+
+
+@router.get("/files/{file_id}", response_model=LibraryFileResponse)
+async def get_file(file_id: int, db: AsyncSession = Depends(get_db)):
+    return await library_service.get_file(db, file_id)
+
+
+@router.post("/files", response_model=bool)
+async def add_file(data: LibraryFileRequest, db: AsyncSession = Depends(get_db)):
+    return await library_service.add_file(db, data)
+
+
+@router.put("/files/{file_id}", response_model=bool)
+async def edit_file(file_id: int, data: LibraryFileRequest, db: AsyncSession = Depends(get_db)):
+    return await library_service.edit_file(db, file_id, data)
--- a/routers/mistake.py
+++ b/routers/mistake.py
@@ -0,0 +1,24 @@
+from typing import List
+from fastapi import APIRouter, Depends
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from database import get_db
+from schemas.mistake import MistakeResponse, MistakeRequest
+from service import mistake_service
+
+router = APIRouter(prefix="/mistake", tags=["Mistake"])
+
+
+@router.get("", response_model=List[MistakeResponse])
+async def list_mistakes(db: AsyncSession = Depends(get_db)):
+    return await mistake_service.list_mistakes(db)
+
+
+@router.post("", response_model=bool)
+async def add_mistakes(data: list[MistakeRequest], db: AsyncSession = Depends(get_db)):
+    return await mistake_service.add_mistakes(db, data)
+
+
+@router.delete("/{mistake_id}", response_model=bool)
+async def remove_mistake(mistake_id: int, db: AsyncSession = Depends(get_db)):
+    return await mistake_service.remove_mistake(db, mistake_id)
--- a/routers/practice.py
+++ b/routers/practice.py
@@ -0,0 +1,19 @@
+from typing import List
+from fastapi import APIRouter, Depends
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from database import get_db
+from schemas.practice import PracticeRecordResponse, PracticeRecordRequest
+from service import practice_service
+
+router = APIRouter(prefix="/practice", tags=["Practice"])
+
+
+@router.get("/record/{user_id}", response_model=List[PracticeRecordResponse])
+async def get_record(user_id: int, db: AsyncSession = Depends(get_db)):
+    return await practice_service.get_record(db, user_id)
+
+
+@router.post("/record", response_model=bool)
+async def add_record(data: PracticeRecordRequest, db: AsyncSession = Depends(get_db), ):
+    return await practice_service.add_record(db, data)
--- a/schemas/agent.py
+++ b/schemas/agent.py
@@ -1,5 +1,11 @@
 from pydantic import BaseModel


-class QueryRequest(BaseModel):
+class QueryQuestionRequest(BaseModel):
    message: str
+
+
+class QueryKnowledgeRequest(BaseModel):
+    subject: str
+    module: str
+    name: str
--- a/service/agent_service.py
+++ b/service/agent_service.py
@@ -1,15 +1,32 @@
 from langchain_core.messages import AIMessageChunk, HumanMessage

-from agent.study import study_agent
-from schemas.agent import QueryRequest
+from agent.study import question_agent, knowledge_agent
+from schemas.agent import QueryQuestionRequest, QueryKnowledgeRequest


-def query_agent(query: QueryRequest):
+def query_question_agent(query: QueryQuestionRequest):
    try:
        user_msg = f"学习内容：\n{query.message}"

        # 流式调用Agent
-        for chunk, metadata in study_agent.stream(
+        for chunk, metadata in question_agent.stream(
+                {"messages": [HumanMessage(content=user_msg)]},
+                stream_mode="messages"
+        ):
+            if isinstance(chunk, AIMessageChunk):
+                if isinstance(chunk, AIMessageChunk) and chunk.content:
+                    yield chunk.content
+    except Exception as e:
+        print(f"\n[错误]: {str(e)}")
+        yield "信息检索失败，请重新输入问题提问"
+
+
+def query_knowledge_agent(query: QueryKnowledgeRequest):
+    try:
+        user_msg = f"学科：{query.subject}，模块：{query.module}， 名称：{query.name}"
+
+        # 流式调用Agent
+        for chunk, metadata in knowledge_agent.stream(
                {"messages": [HumanMessage(content=user_msg)]},
                stream_mode="messages"
        ):