Create app.py

app.py

@@ -0,0 +1,48 @@
+import gradio as gr
+import fitz
+from PyPDF2 import PdfReader
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.vectorstores import FAISS
+from langchain.chains.question_answering import load_qa_chain
+from langchain.llms import OpenAI
+
+def read_pdf(pdf_file, prompt):
+    try:
+        text = ""
+        with open(pdf_file.name, "rb") as file:
+            doc = fitz.open(file)
+            for page in doc:
+                text += page.get_text()
+        
+        # split the text into several chunks
+        text_splitter = CharacterTextSplitter(
+            separator = "\n",
+            chunk_size = 1000,
+            chunk_overlap = 200,
+            length_function = len,
+        )
+        texts = text_splitter.split_text(text)
+        
+        # download embedding from OpenAI
+        embeddings = OpenAIEmbeddings()
+        docsearch = FAISS.from_texts(texts, embeddings)
+        
+        chain = load_qa_chain(OpenAI(), chain_type="stuff")
+
+        docs = docsearch.similarity_search(prompt)
+        answer = chain.run(input_documents = docs, question = prompt)
+        
+        return answer
+
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+iface = gr.Interface(
+    read_pdf,
+    inputs=["file","text"],
+    outputs="text",
+    title="PDF Reader",
+    description="Upload a PDF file!",
+)
+iface.launch()