Merge pull request #4 from ParagGhatage/pr-3

Pr 3

Author: ParagGhatage

backend/app/__

@@ -0,0 +1,51 @@
+import os
+import tempfile
+import json
+import requests
+import pandas as pd
+from fastapi import APIRouter, HTTPException, Query
+from dotenv import load_dotenv
+
+# Load .env file (make sure you have HF_TOKEN inside it)
+load_dotenv()
+
+router = APIRouter()
+
+HF_REPO_ID = os.getenv("HF_DATA_REPO")  # your repo ID
+HF_TOKEN = os.getenv("HF_TOKEN")  # Hugging Face API token
+BASE_URL = f"https://huggingface.co/datasets/{HF_REPO_ID}/resolve/main/uploads"
+
+
+@router.get("/get-file")
+async def get_file(filename: str = Query(..., description="Filename to extract from Hugging Face dataset")):
+    try:
+        file_url = f"{BASE_URL}/{filename}.csv"
+
+        headers = {}
+        if HF_TOKEN:
+            headers["Authorization"] = f"Bearer {HF_TOKEN}"
+
+        response = requests.get(file_url, headers=headers)
+
+        if response.status_code != 200:
+            raise HTTPException(status_code=404, detail=f"File not found at {file_url}")
+
+        # Save temporarily
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as tmp:
+            tmp.write(response.content)
+            tmp_path = tmp.name
+
+        # Load with pandas
+        df = pd.read_csv(tmp_path)
+
+        # Clean data for JSON
+        df = df.replace([float("inf"), float("-inf")], None)
+        df = df.where(pd.notnull(df), None)
+
+        json_str = df.head(50).to_json(orient="records", force_ascii=False, default_handler=str)
+        records = json.loads(json_str)
+
+        return {"filename": filename, "records": records}
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Error processing file: {str(e)}")

backend/app/components/ExtractFile/extract.py

@@ -6,13 +6,13 @@
 from fastapi import HTTPException
 import pandas as pd
 import pyreadstat
-from requests.exceptions import HTTPError
+from huggingface_hub.utils import HfHubHTTPError as HTTPError
 
 load_dotenv()
 
 HF_TOKEN = os.getenv("HF_TOKEN")
 
-HF_DATA_REPO = "Thunder1245/Zero-ML-dataset-2"
+HF_DATA_REPO = "prthm20/ZeoMl"
 
 api = HfApi()
 

backend/app/components/Upload/data_upload.py

@@ -36,4 +36,14 @@ async def upload_file(file: UploadFile = File(...)):
         raise HTTPException(status_code=500, detail=str(e))
 
 
+@router.get("/get-file")
+async def get_file(filename: str):
+    from app.components.ExtractFile.extract import get_file as extract_file
+    try:
+        res = await extract_file(filename)
+
+        return res
 
+    except Exception as e:
+        print(e)
+        raise HTTPException(status_code=500, detail=str(e))

backend/app/routes/routes.py

@@ -17,4 +17,4 @@ dependencies = [
     "lxml>=6.0.1",
     "html5lib>=1.1",
     "beautifulsoup4>=4.13.5",
-]
+]