Create app.py

app.py

@@ -0,0 +1,31 @@
+import os, gradio
+from langchain.document_loaders import UnstructuredPDFLoader
+from langchain.indexes import VectorstoreIndexCreator
+from detectron2.config import get_cfg
+import nltk
+
+try:
+  nltk.data.find('tokenizers/punkt')
+except LookupError:
+  nltk.download('punkt')
+
+os.environ['OPENAI_API_KEY'] = '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'
+
+cfg = get_cfg()    
+cfg.MODEL.DEVICE = 'gpu'
+
+text_folder = 'AsomBarta-NewsLetter'
+loaders = [UnstructuredPDFLoader(os.path.join(text_folder, fn)) for fn in os.listdir(text_folder)]
+
+index = VectorstoreIndexCreator().from_loaders(loaders)
+
+description = '''This is an AI conversational agent who you can ask questions to. The ONLY documents it has access to are the Asom Barta newspapers from July 2022 to May 2023. 
+So, the bot can only frame its answers based on its worldview attained from the Asom Barta newspapers. If you ask it about anything not pertaining to the content of the 
+newspapers, it will simply reply with "I don't know". Enjoy!'''
+
+def chat_response(query):
+  return index.query(query)
+
+interface = gradio.Interface(fn=chat_response, inputs="text", outputs="text", title='Asom Barta Q&A Bot', description=description)
+
+interface.launch()