SaranyaR commited on
Commit
489da94
1 Parent(s): 385c82a

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +101 -0
app.py CHANGED
@@ -0,0 +1,101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import streamlit as st
2
+ from llama_index.core import StorageContext, load_index_from_storage, VectorStoreIndex, SimpleDirectoryReader, ChatPromptTemplate
3
+ from llama_index.llms.huggingface import HuggingFaceInferenceAPI
4
+ from dotenv import load_dotenv
5
+ from llama_index.embeddings.huggingface import HuggingFaceEmbedding
6
+ from llama_index.core import Settings
7
+ import os
8
+ import base64
9
+
10
+ # Load environment variables
11
+ load_dotenv()
12
+
13
+ # Configure the Llama index settings
14
+ Settings.llm = HuggingFaceInferenceAPI(
15
+ model_name="google/gemma-1.1-7b-it",
16
+ tokenizer_name="google/gemma-1.1-7b-it",
17
+ context_window=3000,
18
+ token=os.getenv("HF_TOKEN"),
19
+ max_new_tokens=512,
20
+ generate_kwargs={"temperature": 0.1},
21
+ )
22
+ Settings.embed_model = HuggingFaceEmbedding(
23
+ model_name="BAAI/bge-small-en-v1.5"
24
+ )
25
+
26
+ # Define the directory for persistent storage and data
27
+ PERSIST_DIR = "./db"
28
+ DATA_DIR = "data"
29
+
30
+ # Ensure data directory exists
31
+ os.makedirs(DATA_DIR, exist_ok=True)
32
+ os.makedirs(PERSIST_DIR, exist_ok=True)
33
+
34
+ def displayPDF(file):
35
+ with open(file, "rb") as f:
36
+ base64_pdf = base64.b64encode(f.read()).decode('utf-8')
37
+ pdf_display = f'<iframe src="data:application/pdf;base64,{base64_pdf}" width="100%" height="600" type="application/pdf"></iframe>'
38
+ st.markdown(pdf_display, unsafe_allow_html=True)
39
+
40
+ def data_ingestion():
41
+ documents = SimpleDirectoryReader(DATA_DIR).load_data()
42
+ storage_context = StorageContext.from_defaults()
43
+ index = VectorStoreIndex.from_documents(documents)
44
+ index.storage_context.persist(persist_dir=PERSIST_DIR)
45
+
46
+ def handle_query(query):
47
+ storage_context = StorageContext.from_defaults(persist_dir=PERSIST_DIR)
48
+ index = load_index_from_storage(storage_context)
49
+ chat_text_qa_msgs = [
50
+ (
51
+ "user",
52
+ """You are a Q&A assistant named CHATTO, created by Suriya. You have a specific response programmed for when users specifically ask about your creator, Suriya. The response is: "I was created by Suriya, an enthusiast in Artificial Intelligence. He is dedicated to solving complex problems and delivering innovative solutions. With a strong focus on machine learning, deep learning, Python, generative AI, NLP, and computer vision, Suriya is passionate about pushing the boundaries of AI to explore new possibilities." For all other inquiries, your main goal is to provide answers as accurately as possible, based on the instructions and context you have been given. If a question does not match the provided context or is outside the scope of the document, kindly advise the user to ask questions within the context of the document.
53
+ Context:
54
+ {context_str}
55
+ Question:
56
+ {query_str}
57
+ """
58
+ )
59
+ ]
60
+ text_qa_template = ChatPromptTemplate.from_messages(chat_text_qa_msgs)
61
+
62
+ query_engine = index.as_query_engine(text_qa_template=text_qa_template)
63
+ answer = query_engine.query(query)
64
+
65
+ if hasattr(answer, 'response'):
66
+ return answer.response
67
+ elif isinstance(answer, dict) and 'response' in answer:
68
+ return answer['response']
69
+ else:
70
+ return "Sorry, I couldn't find an answer."
71
+
72
+
73
+ # Streamlit app initialization
74
+ st.title("Chat with your PDF📄")
75
+ st.markdown("Built by [Suriya❤️](https://github.com/theSuriya)")
76
+ st.markdown("chat here👇")
77
+
78
+ if 'messages' not in st.session_state:
79
+ st.session_state.messages = [{'role': 'assistant', "content": 'Hello! Upload a PDF and ask me anything about its content.'}]
80
+
81
+ with st.sidebar:
82
+ st.title("Menu:")
83
+ uploaded_file = st.file_uploader("Upload your PDF Files and Click on the Submit & Process Button")
84
+ if st.button("Submit & Process"):
85
+ with st.spinner("Processing..."):
86
+ filepath = "data/saved_pdf.pdf"
87
+ with open(filepath, "wb") as f:
88
+ f.write(uploaded_file.getbuffer())
89
+ # displayPDF(filepath) # Display the uploaded PDF
90
+ data_ingestion() # Process PDF every time new file is uploaded
91
+ st.success("Done")
92
+
93
+ user_prompt = st.chat_input("Ask me anything about the content of the PDF:")
94
+ if user_prompt:
95
+ st.session_state.messages.append({'role': 'user', "content": user_prompt})
96
+ response = handle_query(user_prompt)
97
+ st.session_state.messages.append({'role': 'assistant', "content": response})
98
+
99
+ for message in st.session_state.messages:
100
+ with st.chat_message(message['role']):
101
+ st.write(message['content'])