Upload 4 files

Dockerfile

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+FROM python:3.10-slim 
+WORKDIR /app 
+COPY requirements.txt . 
+RUN pip install --no-cache-dir -r requirements.txt 
+COPY . . 
+CMD ["python", "app.py"] 

README.md

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----
-title: Aitutor
-emoji: 🐠
-colorFrom: green
-colorTo: gray
-sdk: docker
-pinned: false
-license: apache-2.0
-short_description: ai tutor
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AI Tutor Application 
+ 
+This is an AI tutor application for exam preparation. 
+ 
+## Features 
+- RAG-based question answering 
+- PDF and image upload 
+- Text-to-speech responses 

app.py

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+import gradio as gr 
+from documents.loader import DocumentLoader 
+from utils.rag_pipeline import RAGPipeline 
+ 
+loader = DocumentLoader() 
+rag = RAGPipeline() 
+ 
+def process_query(question, history): 
+    return f"AI Tutor: I received your question: {question}" 
+ 
+def upload_file(file): 
+    return f"Uploaded: {file.name}" 
+ 
+with gr.Blocks() as demo: 
+    gr.Markdown("# AI Tutor for Exam Preparation") 
+    with gr.Row(): 
+        with gr.Column(): 
+            file_input = gr.File(label="Upload PDF/Image") 
+            upload_btn = gr.Button("Upload") 
+            upload_output = gr.Textbox(label="Upload Status") 
+        with gr.Column(): 
+            chatbot = gr.Chatbot() 
+            msg = gr.Textbox(label="Your question") 
+            send_btn = gr.Button("Send") 
+ 
+    upload_btn.click(upload_file, inputs=file_input, outputs=upload_output) 
+    send_btn.click(process_query, inputs=msg, outputs=chatbot) 
+ 
+demo.launch() 

requirements.txt

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+gradio
+transformers
+sentence-transformers
+chromadb
+langchain
+langchain-huggingface
+pillow
+pypdf
+python-multipart
+accelerate
+torch
+datasets
+huggingface-hub