Update app.py

app.py

@@ -1,23 +1,17 @@
 import os
-os.environ["WANDB_DISABLED"] = "true"
+os.environ["WANDB_DISABLED"] = "true"  # Disable online logging
 
-from fastapi import FastAPI
-from pydantic import BaseModel
+import gradio as gr
 from sentence_transformers import SentenceTransformer, util
 import pandas as pd
 import numpy as np
 
-# ------------------------
-# FastAPI app
-# ------------------------
-app = FastAPI(title="Super-Intelligent Internship Matcher")
-
 # ------------------------
 # Load CSV and pre-fine-tuned model
 # ------------------------
-df = pd.read_csv("converted (1).csv")
 MODEL_PATH = os.path.join(os.path.dirname(__file__), "fine_tuned_internship_model")
-model = SentenceTransformer(MODEL_PATH)  # Load pre-fine-tuned model
+model = SentenceTransformer(MODEL_PATH)
+df = pd.read_csv("converted (1).csv")
 
 # ------------------------
 # Normalization functions
@@ -67,23 +61,13 @@ weights = np.array([0.4,0.3,0.2,0.1])  # Skills, Education, Interest, Location
 intercept = 0
 
 # ------------------------
-# FastAPI request model
+# Matching function
 # ------------------------
-class Candidate(BaseModel):
-    skills: str
-    education: str
-    interest: str
-    location: str
-
-# ------------------------
-# API endpoint
-# ------------------------
-@app.post("/match")
-def match_internship(candidate: Candidate):
-    candidate_skills_input = normalize_skills(candidate.skills)
-    candidate_education_input = normalize_text(candidate.education)
-    candidate_interest_input = normalize_text(candidate.interest)
-    candidate_location_input = candidate.location
+def match_internship(skills, education, interest, location):
+    candidate_skills_input = normalize_skills(skills)
+    candidate_education_input = normalize_text(education)
+    candidate_interest_input = normalize_text(interest)
+    candidate_location_input = location
 
     candidate_skill_embs_input = [model.encode(s, convert_to_tensor=True) for s in candidate_skills_input]
     candidate_edu_emb_input = model.encode(candidate_education_input, convert_to_tensor=True)
@@ -123,4 +107,28 @@ def match_internship(candidate: Candidate):
         })
 
     results.sort(key=lambda x: x['Overall_Match'], reverse=True)
-    return {"top5": results[:5]}
+    # Return top 5 as list of dicts
+    return results[:5]
+
+# ------------------------
+# Gradio interface
+# ------------------------
+inputs = [
+    gr.Textbox(label="Your Skills (comma-separated)"),
+    gr.Textbox(label="Your Education"),
+    gr.Textbox(label="Your Interest / Field"),
+    gr.Textbox(label="Your Location")
+]
+
+outputs = gr.JSON(label="Top 5 Internship Matches")
+
+demo = gr.Interface(
+    fn=match_internship,
+    inputs=inputs,
+    outputs=outputs,
+    title="Super-Intelligent Internship Matcher",
+    description="Enter your skills, education, interest, and location to get top 5 internship matches."
+)
+
+if __name__ == "__main__":
+    demo.launch()