Update llm_part.py

llm_part.py

@@ -1,81 +1,81 @@
-import os
-import requests
-import streamlit as st
-from PyPDF2 import PdfReader
-from langchain.prompts import PromptTemplate
-from langchain_google_genai import ChatGoogleGenerativeAI
-import re
-from langchain_groq import ChatGroq
-from secret_key import gemeni_key,llama_key
-
-api_key = os.getenv("Gemini_api_key")
-llm_1 = ChatGoogleGenerativeAI(model="gemini-pro", api_key=api_key)
-
-api_key2=os.getenv("Llama_api_key")
-MODEL_ID = "llama3-groq-70b-8192-tool-use-preview"
-llm_2=ChatGroq(model=MODEL_ID, temperature=0, groq_api_key=api_key2)
-
-
-
-def download_pdf_from_url(url, local_file_path):
-    response = requests.get(url)
-    with open(local_file_path, 'wb') as f:
-        f.write(response.content)
-
-
-def extract_text_from_pdf(pdf_file_path):
-    reader = PdfReader(pdf_file_path)
-    text = ""
-    for page in reader.pages:
-        extracted_text = page.extract_text()
-        if extracted_text:  
-            text += extracted_text + "\n"  
-    return text.strip()
-
-def clean_html_tags(text):
-    clean_text = re.sub(r"<ul>|</ul>|<li>|</li>", "", text)
-    clean_text = re.sub(r"<.*?>", "", clean_text)
-    return clean_text.strip()
-
-# Define the template for summarization
-template = """
-Based on the following document:
-
-{document_text}
-
-Please provide the summary in a **table format**. Each point should be in its own row, with the following columns:
-
-| **Aspect**               | **Details**                                                         |
-|--------------------------|---------------------------------------------------------------------|
-| What did they do?         | Briefly describe the main task, objective, or experiment.           |
-| Contributions             | Highlight the main contributions of the paper.                     |
-| Hardware                  | Name, model, price (if available), link (if available), function.   |
-| Software                  | Type (commercial/free/custom-developed), version, availability, features. |
-| Dataset                   | Type (public/private), type of data (image, text, video, log), duration, size. |
-| Algorithms                | List the algorithms or models used.                                |
-| Place of Experiment       | Where was the experiment conducted (institution/lab)?               |
-| Claimed Results           | Summarize the key results and findings.                            |
-| Limitations               | Identify limitations or shortcomings.                              |
-| Solutions                 | Suggest possible solutions for overcoming limitations.             |
-| Improvements              | Suggest potential improvements or additions.                       |
-
-Ensure each section is concise but informative.
-"""
-
-# Prompt Template
-prompt = PromptTemplate(template=template, input_variables=["document_text"])
-
-template2 = """
-Paraphrase the following paragraph in academic research format:
-#NO PREAMBLE #
-#DONT INCLUDE ANY BULLET POINTS WRITE IN SINGLE PARAGRAPH#
-
-
-{paragraph}
-"""
-
-# Prompt Template
-prompt2 = PromptTemplate(template=template2, input_variables=["paragraph"])
-
-
-
+import os
+import requests
+import streamlit as st
+from PyPDF2 import PdfReader
+from langchain.prompts import PromptTemplate
+from langchain_google_genai import ChatGoogleGenerativeAI
+import re
+from langchain_groq import ChatGroq
+
+
+api_key = os.getenv("Gemini_api_key")
+llm_1 = ChatGoogleGenerativeAI(model="gemini-pro", api_key=api_key)
+
+api_key2=os.getenv("Llama_api_key")
+MODEL_ID = "llama3-groq-70b-8192-tool-use-preview"
+llm_2=ChatGroq(model=MODEL_ID, temperature=0, groq_api_key=api_key2)
+
+
+
+def download_pdf_from_url(url, local_file_path):
+    response = requests.get(url)
+    with open(local_file_path, 'wb') as f:
+        f.write(response.content)
+
+
+def extract_text_from_pdf(pdf_file_path):
+    reader = PdfReader(pdf_file_path)
+    text = ""
+    for page in reader.pages:
+        extracted_text = page.extract_text()
+        if extracted_text:  
+            text += extracted_text + "\n"  
+    return text.strip()
+
+def clean_html_tags(text):
+    clean_text = re.sub(r"<ul>|</ul>|<li>|</li>", "", text)
+    clean_text = re.sub(r"<.*?>", "", clean_text)
+    return clean_text.strip()
+
+# Define the template for summarization
+template = """
+Based on the following document:
+
+{document_text}
+
+Please provide the summary in a **table format**. Each point should be in its own row, with the following columns:
+
+| **Aspect**               | **Details**                                                         |
+|--------------------------|---------------------------------------------------------------------|
+| What did they do?         | Briefly describe the main task, objective, or experiment.           |
+| Contributions             | Highlight the main contributions of the paper.                     |
+| Hardware                  | Name, model, price (if available), link (if available), function.   |
+| Software                  | Type (commercial/free/custom-developed), version, availability, features. |
+| Dataset                   | Type (public/private), type of data (image, text, video, log), duration, size. |
+| Algorithms                | List the algorithms or models used.                                |
+| Place of Experiment       | Where was the experiment conducted (institution/lab)?               |
+| Claimed Results           | Summarize the key results and findings.                            |
+| Limitations               | Identify limitations or shortcomings.                              |
+| Solutions                 | Suggest possible solutions for overcoming limitations.             |
+| Improvements              | Suggest potential improvements or additions.                       |
+
+Ensure each section is concise but informative.
+"""
+
+# Prompt Template
+prompt = PromptTemplate(template=template, input_variables=["document_text"])
+
+template2 = """
+Paraphrase the following paragraph in academic research format:
+#NO PREAMBLE #
+#DONT INCLUDE ANY BULLET POINTS WRITE IN SINGLE PARAGRAPH#
+
+
+{paragraph}
+"""
+
+# Prompt Template
+prompt2 = PromptTemplate(template=template2, input_variables=["paragraph"])
+
+
+