Switched to free model distilgpt2

app.py

@@ -1,23 +1,18 @@
-# !pip install fastapi uvicorn huggingface_hub python-docx --quiet
-
-from fastapi import FastAPI, UploadFile, File
+from fastapi import FastAPI
 from fastapi.responses import FileResponse
 from pydantic import BaseModel
 from typing import List
-from huggingface_hub import InferenceClient
+from transformers import pipeline
 from docx import Document
 from docx.shared import Pt
 from docx.enum.text import WD_ALIGN_PARAGRAPH
 from datetime import datetime
-from collections import defaultdict
 import uuid
-import os
+
 app = FastAPI()
 
-client = InferenceClient(
-    model="meta-llama/Meta-Llama-3-8B-Instruct",
-    token=os.environ["HF_TOKEN"]
-)
+# Load model once at startup
+generator = pipeline("text-generation", model="distilgpt2")
 
 SECTIONS = [
     "Abstract",
@@ -30,7 +25,6 @@ SECTIONS = [
     "Conclusion and Future Work"
 ]
 
-
 class TaskItem(BaseModel):
     task: str
 
@@ -46,28 +40,14 @@ class ReportRequest(BaseModel):
 
 def generate_section(section_name: str, overview: str) -> str:
     prompt = f"""
-You are a professional academic writer. Write a detailed section titled '{section_name}' for a Computer Science graduation project report based on the following project overview:
-
-\"\"\"{overview}\"\"\"
-
-Guidelines:
-- Do NOT include any 'References' at the end of this section.
-- Do NOT include any 'Conclusion' at the end of this section.
-- ONLY write diagrams or tables if they are clearly described in the overview or explicitly required by the user.
-- Use a professional, academic tone with deep elaboration and well-structured content.
-- Do not repeat content across sections.
-- Do not generate a table of contents here.
-- Aim for long and rich content (2 to 10+ pages per section).
+You are an academic writer. Write a section titled '{section_name}' for a graduation project report based on:
+
+{overview}
+
+Avoid conclusions or references. Use formal language.
 """
-    response = client.chat_completion(
-        messages=[
-            {"role": "system", "content": "You are a helpful assistant that writes academic reports."},
-            {"role": "user", "content": prompt}
-        ],
-        max_tokens=4096,
-        temperature=0.7
-    )
-    return response.choices[0].message.content.strip()
+    result = generator(prompt, max_length=512, num_return_sequences=1)
+    return result[0]['generated_text']
 
 def create_word_doc(sections_content, filename="Graduation_Project_Report.docx"):
     doc = Document()
@@ -111,6 +91,7 @@ def generate_report(req: ReportRequest):
 @app.get("/download/{filename}")
 def download_file(filename: str):
     return FileResponse(path=filename, filename=filename, media_type='application/vnd.openxmlformats-officedocument.wordprocessingml.document')
+
 @app.get("/")
 def root():
     return {"status": "Running"}

requirements.txt

@@ -1,4 +1,5 @@
 fastapi
 uvicorn[standard]
-huggingface_hub
 python-docx
+transformers
+torch

test.py

@@ -0,0 +1,15 @@
+import requests
+
+response = requests.post(
+    "https://kaiozwald-BridgeIT.hf.space/generate-report",
+    json={
+        "tasks": [
+            {"task": "Build frontend using React"},
+            {"task": "Connect backend using FastAPI"},
+            {"task": "Use transformers to generate report sections"}
+        ]
+    }
+)
+
+print("Status Code:", response.status_code)
+print("Response Text:", response.text)