Added project RAG pdf reader

pdf-rag-app/.vs/VSWorkspaceState.json

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+{
+  "ExpandedNodes": [
+    ""
+  ],
+  "PreviewInSolutionExplorer": false
+}

pdf-rag-app/.vs/pdf-rag-app.slnx/v18/DocumentLayout.json

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+{
+  "Version": 1,
+  "WorkspaceRootPath": "C:\\Users\\anand\\endee\\pdf-rag-app\\",
+  "Documents": [],
+  "DocumentGroupContainers": [
+    {
+      "Orientation": 0,
+      "VerticalTabListWidth": 256,
+      "DocumentGroups": []
+    }
+  ]
+}

pdf-rag-app/main.py

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+from fastapi import FastAPI, UploadFile
+import shutil
+import os
+
+# Gemini
+import google.generativeai as genai
+
+# PDF Reader
+from pypdf import PdfReader
+
+# Load API key
+from dotenv import load_dotenv
+load_dotenv()
+
+genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
+model = genai.GenerativeModel("gemini-pro")
+
+app = FastAPI()
+
+# simple memory storage
+PDF_TEXT = ""
+
+@app.post("/upload/")
+async def upload_pdf(file: UploadFile):
+    global PDF_TEXT
+
+    with open(file.filename, "wb") as buffer:
+        shutil.copyfileobj(file.file, buffer)
+
+    reader = PdfReader(file.filename)
+    text = ""
+
+    for page in reader.pages:
+        text += page.extract_text()
+
+    PDF_TEXT = text
+
+    return {"message": "PDF uploaded and processed"}
+
+@app.get("/ask/")
+def ask_question(query: str):
+    global PDF_TEXT
+
+    prompt = f"""
+    Answer the question based on this PDF content:
+
+    {PDF_TEXT[:3000]}
+
+    Question: {query}
+    """
+
+    response = model.generate_content(prompt)
+
+    return {"answer": response.text}