Update app.py

app.py

@@ -1,139 +1,276 @@
 import streamlit as st
-from langchain.chat_models import ChatOpenAI
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.memory import ConversationBufferMemory
-
-# Initialize OpenAI LLM
-llm = ChatOpenAI(model="gpt-4", temperature=0.7)
-
-# Define Prompts
-email_prompt = PromptTemplate(
-    input_variables=["professor_name", "university_name", "research_interests", "reason", "resume_text"],
-    template="""
-        Write a professional cold email to {professor_name} at {university_name} expressing interest in their research. 
-        Highlight relevant research interests: {research_interests}. 
-        Explain why you want to work with them: {reason}. Keep it concise and professional.
-    """
-)
-cover_letter_prompt = PromptTemplate(
-    input_variables=["job_title", "company", "key_skills", "resume_text"],
-    template="""
-        Write a professional cover letter for the {job_title} position at {company}. 
-        Highlight key skills: {key_skills}. Keep it formal and tailored to the job.
-    """
-)
-research_statement_prompt = PromptTemplate(
-    input_variables=["research_background", "key_projects", "future_goals"],
-    template="""
-        Write a research statement based on the following:
-        - Background: {research_background}
-        - Key Projects: {key_projects}
-        - Future Research Goals: {future_goals}
-        Keep it structured and professional.
-    """
+from langchain.llms import HuggingFaceHub
+import fitz  # PyMuPDF for PDF extraction
+from PIL import Image
+import os
+import pytesseract
+import re
+
+# Set Hugging Face API Key (Set this in Hugging Face Secrets)
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = st.secrets["HF_TOKEN"]
+
+# Load Free LLM from Hugging Face
+llm = HuggingFaceHub(repo_id="mistralai/Mistral-7B-Instruct-v0.3", model_kwargs={"temperature": 0.5})
+
+# Streamlit App Configuration
+st.set_page_config(page_title="DocuMentorAI", layout="wide", page_icon="📄")
+st.title("📄 DocuMentorAI")
+st.write("Generate professional application documents with ease!")
+
+# Custom CSS for better UI
+st.markdown("""
+<style>
+    .stTextArea textarea { font-size: 16px !important; }
+    .stButton button { width: 100%; background-color: #4CAF50; color: white; }
+    .stDownloadButton button { width: 100%; background-color: #008CBA; color: white; }
+    .stMarkdown { font-size: 18px; }
+    .stSpinner div { margin: auto; }
+</style>
+""", unsafe_allow_html=True)
+
+# Text Input for Job Opening Details
+st.subheader("📢 Enter Opening Details")
+job_opening_text = st.text_area(
+    "Paste the job/research opening details here...",
+    height=150,
+    placeholder="Example: 'We are hiring a Research Assistant at XYZ University. The ideal candidate has experience in machine learning and data analysis...'"
 )
-sop_prompt = PromptTemplate(
-    input_variables=["motivation", "academic_background", "research_experiences", "career_goals", "why_this_program"],
-    template="""
-        Write a Statement of Purpose (SOP) with:
-        - Motivation: {motivation}
-        - Academic Background: {academic_background}
-        - Research Experiences: {research_experiences}
-        - Career Goals: {career_goals}
-        - Why this program: {why_this_program}
-        Ensure it is compelling and well-structured.
-    """
+
+# Upload CV/Resume
+st.subheader("📄 Upload CV/Resume")
+cv_resume_file = st.file_uploader(
+    "Upload your CV/Resume (PDF or Image)",
+    type=["pdf", "png", "jpg", "jpeg"],
+    help="Upload a PDF or image of your CV/Resume for text extraction."
 )
 
-# Create LLM Chains
-email_chain = LLMChain(llm=llm, prompt=email_prompt, memory=ConversationBufferMemory(memory_key="history"))
-cover_letter_chain = LLMChain(llm=llm, prompt=cover_letter_prompt, memory=ConversationBufferMemory(memory_key="history"))
-research_statement_chain = LLMChain(llm=llm, prompt=research_statement_prompt, memory=ConversationBufferMemory(memory_key="history"))
-sop_chain = LLMChain(llm=llm, prompt=sop_prompt, memory=ConversationBufferMemory(memory_key="history"))
-
-# Streamlit App
-st.title("AI-Powered Academic & Job Application Generator")
-
-# File Upload for Resume
-st.sidebar.header("Upload Your Resume (Optional)")
-uploaded_file = st.sidebar.file_uploader("Upload a .txt file", type=["txt"])
-
-cv_resume_text = ""
-if uploaded_file is not None:
-    cv_resume_text = uploaded_file.read().decode("utf-8")
-
-# Tabs for Different Documents
-tabs = st.tabs(["Cold Email", "Cover Letter", "Research Statement", "Statement of Purpose"])
-
-# Cold Email Generator
-with tabs[0]:
-    st.header("Generate a Cold Email")
-    professor_name = st.text_input("Professor's Name")
-    university_name = st.text_input("University Name")
-    research_interests = st.text_area("Your Research Interests")
-    reason = st.text_area("Why do you want to work with this professor?")
-
-    if st.button("Generate Email"):
-        email_output = email_chain.run({
-            "professor_name": professor_name,
-            "university_name": university_name,
-            "research_interests": research_interests,
-            "reason": reason,
-            "resume_text": cv_resume_text
-        }).strip()
-        st.markdown(email_output)
-        st.download_button("Download Email", email_output, file_name="cold_email.txt")
-
-# Cover Letter Generator
-with tabs[1]:
-    st.header("Generate a Cover Letter")
-    job_title = st.text_input("Job Title")
-    company_name = st.text_input("Company Name")
-    key_skills = st.text_area("Key Skills for the Job")
+# Function to extract text from PDF
+def extract_text_from_pdf(pdf_file):
+    try:
+        pdf_bytes = pdf_file.read()
+        with fitz.open(stream=pdf_bytes, filetype="pdf") as doc:
+            return " ".join([page.get_text() for page in doc])
+    except Exception as e:
+        st.error(f"Error extracting text from PDF: {e}")
+        return ""
+
+# Function to extract text from Image using OCR
+def extract_text_from_image(image_file):
+    try:
+        image = Image.open(image_file)
+        return pytesseract.image_to_string(image)
+    except Exception as e:
+        st.error(f"Error extracting text from image: {e}")
+        return ""
+
+# Function to extract text from uploaded files
+def extract_text(uploaded_file):
+    if uploaded_file:
+        file_type = uploaded_file.type
+        if file_type == "application/pdf":
+            return extract_text_from_pdf(uploaded_file)
+        else:
+            return extract_text_from_image(uploaded_file)
+    return ""
+
+# Extract text from CV/Resume
+cv_resume_text = extract_text(cv_resume_file)
+
+# Display Extracted Text
+if job_opening_text:
+    with st.expander("🔍 View Entered Opening Details"):
+        st.markdown(f"**Job Opening Details:**\n\n{job_opening_text}")
+
+if cv_resume_text:
+    with st.expander("🔍 View Extracted CV/Resume Details"):
+        st.markdown(f"**CV/Resume Details:**\n\n{cv_resume_text}")
+
+# Function to extract professor name, designation, and university
+def extract_professor_details(text):
+    professor_pattern = r"(Dr\.|Professor|Prof\.?)\s+([A-Z][a-z]+\s[A-Z][a-z]+)"
+    university_pattern = r"(University|Institute|College|School of [A-Za-z]+)"
+    
+    professor_match = re.search(professor_pattern, text)
+    university_match = re.search(university_pattern, text)
+
+    professor_name = professor_match.group(0) if professor_match else "Not Found"
+    university_name = university_match.group(0) if university_match else "Not Found"
+
+    return professor_name, university_name
+
+# Extract professor details if job opening is uploaded
+professor_name, university_name = extract_professor_details(job_opening_text)
+
+# LLM Prompt Templates
+email_template = PromptTemplate.from_template("""
+Write a professional cold email for a research position.
+- Address the professor formally.
+- Introduce yourself and academic background.
+- Express interest in their research.
+- Highlight key skills from your CV.
+- Conclude with a polite request.
+### Input:
+- Professor: {professor_name}
+- University: {university_name}
+- Research Interests: {research_interests}
+- Why This Lab: {reason}
+- CV Highlights: {resume_text}
+### Output:
+A well-structured, professional cold email.
+""")
+
+cover_letter_template = PromptTemplate.from_template("""
+Write a compelling job application cover letter.
+- Address the employer formally.
+- Mention job title and where you found it.
+- Highlight key skills and experiences.
+- Relate background to the company.
+- Conclude with enthusiasm.
+### Input:
+- Job Title: {job_title}
+- Company: {company}
+- Key Skills: {key_skills}
+- CV Highlights: {resume_text}
+### Output:
+A strong, well-formatted cover letter.
+""")
+
+research_statement_template = PromptTemplate.from_template("""
+Write a research statement for Ph.D. applications.
+- Discuss research background and motivation.
+- Explain key research experiences and findings.
+- Outline future research interests and goals.
+- Highlight contributions to the field.
+### Input:
+- Research Background: {research_background}
+- Key Research Projects: {key_projects}
+- Future Goals: {future_goals}
+### Output:
+A well-structured, professional research statement.
+""")
+
+sop_template = PromptTemplate.from_template("""
+Write a compelling Statement of Purpose (SOP).
+- Introduce motivation for graduate studies.
+- Discuss academic background.
+- Explain relevant experiences and research.
+- Outline career goals.
+- Justify fit for the program.
+### Input:
+- Motivation: {motivation}
+- Academic Background: {academic_background}
+- Research & Projects: {research_experiences}
+- Career Goals: {career_goals}
+- Why This Program: {why_this_program}
+### Output:
+A well-structured SOP.
+""")
+
+# LangChain Chains
+email_chain = LLMChain(llm=llm, prompt=email_template)
+cover_letter_chain = LLMChain(llm=llm, prompt=cover_letter_template)
+research_statement_chain = LLMChain(llm=llm, prompt=research_statement_template)
+sop_chain = LLMChain(llm=llm, prompt=sop_template)
+
+# User Inputs
+st.subheader("📩 Generate Application Documents")
+tab1, tab2, tab3, tab4 = st.tabs(["Cold Email", "Cover Letter", "Research Statement", "SOP"])
+
+# Cold Email Generation
+with tab1:
+    st.write(f"🧑‍🏫 **Detected Professor:** {professor_name} at {university_name}")
+    research_interests = st.text_area("Research Interests", placeholder="Example: Machine Learning, Data Analysis, etc.")
+    reason = st.text_area("Why this professor/lab?", placeholder="Example: I am particularly interested in your work on...")
+    
+    if st.button("Generate Cold Email"):
+        if not job_opening_text or not cv_resume_text:
+            st.error("Please provide job opening details and upload your CV/Resume.")
+        else:
+            with st.spinner("Generating Cold Email..."):
+                try:
+                    email = email_chain.run({
+                        "professor_name": professor_name,
+                        "university_name": university_name,
+                        "research_interests": research_interests,
+                        "reason": reason,
+                        "resume_text": cv_resume_text
+                    })
+                    st.markdown("**Generated Cold Email:**")
+                    st.markdown(email)
+                    st.download_button("Download Email", email, file_name="cold_email.txt")
+                except Exception as e:
+                    st.error(f"Error generating cold email: {e}")
+
+# Cover Letter Generation
+with tab2:
+    job_title = st.text_input("Job Title", placeholder="Example: Research Assistant")
+    company_name = university_name if university_name != "Not Found" else st.text_input("Company/University", placeholder="Example: XYZ University")
+    key_skills = st.text_area("Key Skills", placeholder="Example: Python, Machine Learning, Data Analysis")
 
     if st.button("Generate Cover Letter"):
-        cover_letter_output = cover_letter_chain.run({
-            "job_title": job_title,
-            "company": company_name,
-            "key_skills": key_skills,
-            "resume_text": cv_resume_text
-        }).strip()
-        st.markdown(cover_letter_output)
-        st.download_button("Download Cover Letter", cover_letter_output, file_name="cover_letter.txt")
-
-# Research Statement Generator
-with tabs[2]:
-    st.header("Generate a Research Statement")
-    research_background = st.text_area("Your Research Background")
-    key_projects = st.text_area("Key Projects You've Worked On")
-    future_goals = st.text_area("Future Research Goals")
+        if not job_opening_text or not cv_resume_text:
+            st.error("Please provide job opening details and upload your CV/Resume.")
+        else:
+            with st.spinner("Generating Cover Letter..."):
+                try:
+                    cover_letter = cover_letter_chain.run({
+                        "job_title": job_title,
+                        "company": company_name,
+                        "key_skills": key_skills,
+                        "resume_text": cv_resume_text
+                    })
+                    st.markdown("**Generated Cover Letter:**")
+                    st.markdown(cover_letter)
+                    st.download_button("Download Cover Letter", cover_letter, file_name="cover_letter.txt")
+                except Exception as e:
+                    st.error(f"Error generating cover letter: {e}")
+
+# Research Statement Generation
+with tab3:
+    research_background = st.text_area("Research Background", placeholder="Example: My research focuses on...")
+    key_projects = st.text_area("Key Research Projects", placeholder="Example: Developed a machine learning model for...")
+    future_goals = st.text_area("Future Research Goals", placeholder="Example: I aim to explore...")
 
     if st.button("Generate Research Statement"):
-        research_statement_output = research_statement_chain.run({
-            "research_background": research_background,
-            "key_projects": key_projects,
-            "future_goals": future_goals
-        }).strip()
-        st.markdown(research_statement_output)
-        st.download_button("Download Research Statement", research_statement_output, file_name="research_statement.txt")
-
-# Statement of Purpose Generator
-with tabs[3]:
-    st.header("Generate a Statement of Purpose (SOP)")
-    motivation = st.text_area("Your Motivation for Graduate Studies")
-    academic_background = st.text_area("Your Academic Background")
-    research_experiences = st.text_area("Your Research Experiences")
-    career_goals = st.text_area("Your Career Goals")
-    why_this_program = st.text_area("Why This Program?")
+        with st.spinner("Generating Research Statement..."):
+            try:
+                research_statement = research_statement_chain.run({
+                    "research_background": research_background,
+                    "key_projects": key_projects,
+                    "future_goals": future_goals
+                })
+                st.markdown("**Generated Research Statement:**")
+                st.markdown(research_statement)
+                st.download_button("Download Research Statement", research_statement, file_name="research_statement.txt")
+            except Exception as e:
+                st.error(f"Error generating research statement: {e}")
+
+# SOP Generation
+with tab4:
+    motivation = st.text_area("Motivation for Graduate Studies", placeholder="Example: I have always been passionate about...")
+    academic_background = st.text_area("Academic Background", placeholder="Example: I completed my undergraduate degree in...")
+    research_experiences = st.text_area("Research & Projects", placeholder="Example: During my undergraduate studies, I worked on...")
+    career_goals = st.text_area("Career Goals", placeholder="Example: My long-term goal is to...")
+    why_this_program = st.text_area("Why This Program", placeholder="Example: This program aligns with my research interests because...")
 
     if st.button("Generate SOP"):
-        sop_output = sop_chain.run({
-            "motivation": motivation,
-            "academic_background": academic_background,
-            "research_experiences": research_experiences,
-            "career_goals": career_goals,
-            "why_this_program": why_this_program
-        }).strip()
-        st.markdown(sop_output)
-        st.download_button("Download SOP", sop_output, file_name="sop.txt")
+        with st.spinner("Generating SOP..."):
+            try:
+                sop = sop_chain.run({
+                    "motivation": motivation,
+                    "academic_background": academic_background,
+                    "research_experiences": research_experiences,
+                    "career_goals": career_goals,
+                    "why_this_program": why_this_program
+                })
+                st.markdown("**Generated SOP:**")
+                st.markdown(sop)
+                st.download_button("Download SOP", sop, file_name="sop.txt")
+            except Exception as e:
+                st.error(f"Error generating SOP: {e}")
+
+# Reset Button
+if st.button("🔄 Reset All Inputs and Outputs"):
+    st.experimental_rerun()