Spaces:
Runtime error
Runtime error
Upload 3 files
Browse files- app.py +100 -0
- llm_part.py +81 -0
- requirements.txt +8 -0
app.py
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import streamlit as st
|
2 |
+
import llm_part
|
3 |
+
import os
|
4 |
+
from langchain_groq import ChatGroq
|
5 |
+
|
6 |
+
# Sidebar to select the LLM model
|
7 |
+
st.sidebar.title("LLM Model Selector")
|
8 |
+
llm_model = st.sidebar.selectbox("Select LLM Model", ("Google Gemini", "Llama"))
|
9 |
+
|
10 |
+
|
11 |
+
# Define Llama-specific configurations
|
12 |
+
if llm_model == "Google Gemini": # Check if "Google Gemini" is selected
|
13 |
+
llm = llm_part.llm_1 # Assign Google Gemini to llm
|
14 |
+
else:
|
15 |
+
llm = llm_part.llm_2 # Use the Llama model
|
16 |
+
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
# Main app
|
21 |
+
st.title("Jony's Custom Research Notes Extracted from PDFs Using " + llm_model)
|
22 |
+
option = st.selectbox("Select PDF Source:", ("Enter URL", "Upload Local File"))
|
23 |
+
|
24 |
+
document_text = ""
|
25 |
+
|
26 |
+
if option == "Enter URL":
|
27 |
+
pdf_url = st.text_input("Enter the PDF URL:")
|
28 |
+
|
29 |
+
if pdf_url:
|
30 |
+
try:
|
31 |
+
with st.spinner("Processing PDF from URL..."):
|
32 |
+
local_pdf_path = "downloaded_paper.pdf"
|
33 |
+
llm_part.download_pdf_from_url(pdf_url, local_pdf_path)
|
34 |
+
document_text = llm_part.extract_text_from_pdf(local_pdf_path)
|
35 |
+
os.remove(local_pdf_path)
|
36 |
+
|
37 |
+
except Exception as e:
|
38 |
+
st.error(f"Error processing PDF from URL: {e}")
|
39 |
+
|
40 |
+
elif option == "Upload Local File":
|
41 |
+
uploaded_file = st.file_uploader("Choose a PDF file", type="pdf")
|
42 |
+
|
43 |
+
if uploaded_file is not None:
|
44 |
+
try:
|
45 |
+
with st.spinner("Processing uploaded PDF..."):
|
46 |
+
local_pdf_path = "uploaded_paper.pdf"
|
47 |
+
with open(local_pdf_path, "wb") as f:
|
48 |
+
f.write(uploaded_file.read())
|
49 |
+
document_text = llm_part.extract_text_from_pdf(local_pdf_path)
|
50 |
+
os.remove(local_pdf_path)
|
51 |
+
|
52 |
+
except Exception as e:
|
53 |
+
st.error(f"Error processing uploaded PDF: {e}")
|
54 |
+
|
55 |
+
if document_text:
|
56 |
+
with st.spinner("Generating the summary..."):
|
57 |
+
query = llm_part.prompt.format(document_text=document_text[:20000])
|
58 |
+
result = llm.invoke(query)
|
59 |
+
st.write("### Summary in Table Format:")
|
60 |
+
st.write(result.content)
|
61 |
+
lines = result.content.split('\n')
|
62 |
+
paragraph_output = []
|
63 |
+
|
64 |
+
for line in lines[2:]:
|
65 |
+
if "|" not in line or not line.strip():
|
66 |
+
continue
|
67 |
+
|
68 |
+
parts = [part.strip() for part in line.split("|") if part.strip()]
|
69 |
+
if len(parts) == 2:
|
70 |
+
_, details = parts
|
71 |
+
if "Not specified" in details or "Not mentioned" in details:
|
72 |
+
continue
|
73 |
+
details_clean = llm_part.clean_html_tags(details)
|
74 |
+
paragraph_output.append(details_clean)
|
75 |
+
|
76 |
+
paragraph_output = ". ".join(paragraph_output) + "."
|
77 |
+
paragraph_output = paragraph_output.replace(" ,", ",").replace(" .", ".")
|
78 |
+
paragraph_output = paragraph_output.replace(". CNN", ". In this approach, CNN").replace("Federated learning (FL)", "The use of Federated Learning (FL)")
|
79 |
+
|
80 |
+
paragraph_output = paragraph_output.replace("The use of Federated Learning", "The study explores the use of Federated Learning")
|
81 |
+
paragraph_output = paragraph_output.replace("In this approach, CNN", "In this approach, a combination of CNN models was used to enhance performance")
|
82 |
+
paragraph_output = paragraph_output.replace("achieved", "yielded results indicating")
|
83 |
+
paragraph_output = paragraph_output.replace("slightly lower", "only marginally lower")
|
84 |
+
|
85 |
+
query2 = llm_part.prompt2.format(paragraph=paragraph_output)
|
86 |
+
result2 = llm.invoke(query2)
|
87 |
+
st.write("### Answer in Paragraph Style:")
|
88 |
+
st.markdown("""
|
89 |
+
<style>
|
90 |
+
.justified-text {
|
91 |
+
text-align: justify;
|
92 |
+
}
|
93 |
+
</style>
|
94 |
+
""", unsafe_allow_html=True)
|
95 |
+
|
96 |
+
st.markdown(f"<div class='justified-text'>{result2.content}</div>", unsafe_allow_html=True)
|
97 |
+
|
98 |
+
|
99 |
+
#pip install -r requirements.txt
|
100 |
+
|
llm_part.py
ADDED
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import os
|
2 |
+
import requests
|
3 |
+
import streamlit as st
|
4 |
+
from PyPDF2 import PdfReader
|
5 |
+
from langchain.prompts import PromptTemplate
|
6 |
+
from langchain_google_genai import ChatGoogleGenerativeAI
|
7 |
+
import re
|
8 |
+
from langchain_groq import ChatGroq
|
9 |
+
from secret_key import gemeni_key,llama_key
|
10 |
+
|
11 |
+
api_key = os.getenv("Gemini_api_key")
|
12 |
+
llm_1 = ChatGoogleGenerativeAI(model="gemini-pro", api_key=api_key)
|
13 |
+
|
14 |
+
api_key2=os.getenv("Llama_api_key")
|
15 |
+
MODEL_ID = "llama3-groq-70b-8192-tool-use-preview"
|
16 |
+
llm_2=ChatGroq(model=MODEL_ID, temperature=0, groq_api_key=api_key2)
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
def download_pdf_from_url(url, local_file_path):
|
21 |
+
response = requests.get(url)
|
22 |
+
with open(local_file_path, 'wb') as f:
|
23 |
+
f.write(response.content)
|
24 |
+
|
25 |
+
|
26 |
+
def extract_text_from_pdf(pdf_file_path):
|
27 |
+
reader = PdfReader(pdf_file_path)
|
28 |
+
text = ""
|
29 |
+
for page in reader.pages:
|
30 |
+
extracted_text = page.extract_text()
|
31 |
+
if extracted_text:
|
32 |
+
text += extracted_text + "\n"
|
33 |
+
return text.strip()
|
34 |
+
|
35 |
+
def clean_html_tags(text):
|
36 |
+
clean_text = re.sub(r"<ul>|</ul>|<li>|</li>", "", text)
|
37 |
+
clean_text = re.sub(r"<.*?>", "", clean_text)
|
38 |
+
return clean_text.strip()
|
39 |
+
|
40 |
+
# Define the template for summarization
|
41 |
+
template = """
|
42 |
+
Based on the following document:
|
43 |
+
|
44 |
+
{document_text}
|
45 |
+
|
46 |
+
Please provide the summary in a **table format**. Each point should be in its own row, with the following columns:
|
47 |
+
|
48 |
+
| **Aspect** | **Details** |
|
49 |
+
|--------------------------|---------------------------------------------------------------------|
|
50 |
+
| What did they do? | Briefly describe the main task, objective, or experiment. |
|
51 |
+
| Contributions | Highlight the main contributions of the paper. |
|
52 |
+
| Hardware | Name, model, price (if available), link (if available), function. |
|
53 |
+
| Software | Type (commercial/free/custom-developed), version, availability, features. |
|
54 |
+
| Dataset | Type (public/private), type of data (image, text, video, log), duration, size. |
|
55 |
+
| Algorithms | List the algorithms or models used. |
|
56 |
+
| Place of Experiment | Where was the experiment conducted (institution/lab)? |
|
57 |
+
| Claimed Results | Summarize the key results and findings. |
|
58 |
+
| Limitations | Identify limitations or shortcomings. |
|
59 |
+
| Solutions | Suggest possible solutions for overcoming limitations. |
|
60 |
+
| Improvements | Suggest potential improvements or additions. |
|
61 |
+
|
62 |
+
Ensure each section is concise but informative.
|
63 |
+
"""
|
64 |
+
|
65 |
+
# Prompt Template
|
66 |
+
prompt = PromptTemplate(template=template, input_variables=["document_text"])
|
67 |
+
|
68 |
+
template2 = """
|
69 |
+
Paraphrase the following paragraph in academic research format:
|
70 |
+
#NO PREAMBLE #
|
71 |
+
#DONT INCLUDE ANY BULLET POINTS WRITE IN SINGLE PARAGRAPH#
|
72 |
+
|
73 |
+
|
74 |
+
{paragraph}
|
75 |
+
"""
|
76 |
+
|
77 |
+
# Prompt Template
|
78 |
+
prompt2 = PromptTemplate(template=template2, input_variables=["paragraph"])
|
79 |
+
|
80 |
+
|
81 |
+
|
requirements.txt
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
|
2 |
+
requests
|
3 |
+
streamlit
|
4 |
+
PyPDF2
|
5 |
+
langchain
|
6 |
+
langchain-google-genai
|
7 |
+
langchain-groq
|
8 |
+
langchain_community
|