add difficultie

server/app.py

@@ -2,10 +2,13 @@ from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from inference import rag_chain
 from pydantic import BaseModel
-from fastapi.staticfiles import StaticFiles 
+from fastapi.staticfiles import StaticFiles
+from data.load_data import retriever_pre
+
 
 class Body(BaseModel):
     subject: str
+    difficultie: str
 
 
 app = FastAPI()
@@ -17,15 +20,21 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
+
 @app.post("/generate_questions")
 async def generate_questions(body: Body):
     subject = body.subject
-    query = f"Quero que você gere questões de biologia, sendo do assunto: {subject}."
+    difficultie = body.difficultie
+    query = f"Quero que você gere questões de biologia, sendo do assunto: {subject} e sendo da dificuldade: {difficultie}."
     res = rag_chain.invoke(f"""{query}""")
-    return res
+    return {
+        "res": res,
+    }
 
-# app.mount("/", StaticFiles(directory="static", html=True), name="static")
+
+app.mount("/", StaticFiles(directory="static", html=True), name="static")
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run("app:app", host="0.0.0.0", port=8000)
+
+    uvicorn.run("app:app", host="0.0.0.0", port=8000)

server/data/load_data.py

@@ -6,8 +6,8 @@ from langchain.retrievers.self_query.base import SelfQueryRetriever
 from llm.gemini import gemini_embeddings, llm
 from utils.questions_parser import parse_question
 
+
 try:
-    
     vectorstore = Chroma(
         persist_directory="./chroma_db", embedding_function=gemini_embeddings
     )
@@ -44,6 +44,7 @@ except Exception as e:
         persist_directory="./chroma_db", embedding_function=gemini_embeddings
     )
 
+
 metadata_field_info = [
     AttributeInfo(
         name="topico",
@@ -67,7 +68,7 @@ metadata_field_info = [
     ),
 ]
 
-document_content_description = "Questões de biologia"
+document_content_description = "Questões de matérias do ensino médio."
 
 retriever = SelfQueryRetriever.from_llm(
     llm, vectorstore, document_content_description, metadata_field_info, verbose=True

server/inference.py

@@ -2,9 +2,14 @@ from langchain.schema.runnable import RunnablePassthrough
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_core.runnables import RunnableLambda
 
-from llm.gemini import questions_template, format_questions_instructions, questions_parser
+from llm.gemini import (
+    questions_template,
+    format_questions_instructions,
+    questions_parser,
+)
 from data.load_data import retriever
 
+
 def get_questions(_dict):
     question = _dict["question"]
     context = _dict["context"]
@@ -13,9 +18,9 @@ def get_questions(_dict):
         question=question,
         format_questions_instructions=format_questions_instructions,
     )
-    
+
     tries = 0
-    
+
     while tries < 3:
         try:
             chat = ChatGoogleGenerativeAI(model="gemini-pro")
@@ -36,5 +41,3 @@ rag_chain = {
     "context": retriever | RunnableLambda(format_docs),
     "question": RunnablePassthrough(),
 } | RunnableLambda(get_questions)
-
-

web/src/App.jsx

@@ -13,6 +13,7 @@ import 'react-toastify/dist/ReactToastify.css';
 function App() {
 
   const [subject, setSubject] = useState("");
+  const [difficultie, setDifficultie] = useState("");
 
   const [menuState, setMenuState] = useState(true);
   const [isLoading, setIsLoading] = useState(false);
@@ -30,6 +31,11 @@ function App() {
     { label: "Biofísica", value: "biofisica" },
   ]
 
+  const difficulties = [
+    { label: "Fácil", value: "facil" },
+    { label: "Intermediária", value: "intermediaria" },
+    { label: "Difícil", value: "dificil" },
+  ]
   const handleSubmit = async (e) => {
     e.preventDefault();
     setIsLoading(true);
@@ -40,7 +46,7 @@ function App() {
           "Content-Type": "application/json"
         },
         body: JSON.stringify({
-          subject
+          subject, difficultie
         })
       });
       console.log(res)
@@ -127,8 +133,19 @@ function App() {
                 ))}
               </SelectContent>
             </Select>
+            <h2>Selecione uma dificuldade:</h2>
+            <Select onValueChange={value => setDifficultie(value)}>
+              <SelectTrigger className="w-[180px]">
+                <SelectValue placeholder="Dificuldade" />
+              </SelectTrigger>
+              <SelectContent onChange={e => console.log(e)}>
+                {difficulties && difficulties.map(({ label, value }) => (
+                  <SelectItem key={value} value={value}>{label}</SelectItem>
+                ))}
+              </SelectContent>
+            </Select>
             <button className="h-10 bg-purple-500 rounded px-2.5 py-1 mt-5 hover:brightness-110 transition-all flex items-center justify-center disabled:hover:brightness-75 disabled:brightness-75"
-              disabled={isLoading || !subject}>
+              disabled={isLoading || !subject || !difficultie}>
               {
                 isLoading ?
                   <div className="animate-spin h-5 w-5 border-2 border-white border-r-purple-500 rounded-full"></div>

web/tsconfig.json

@@ -1,10 +1,10 @@
 {
-    "compilerOptions": {
-      "baseUrl": ".",
-      "paths": {
-        "@/*": [
-          "./src/*"
-        ]
-      }
+  "compilerOptions": {
+    "baseUrl": ".",
+    "paths": {
+      "@/*": [
+        "./src/*"
+      ]
     }
   }
+}