Update app.py

app.py

@@ -11,193 +11,196 @@ from langchain_cohere import ChatCohere
 import random
 
 # Streamlit app
-st.set_page_config(page_title="JobFit CV/Resume Matcher 💼", page_icon="💼", layout="wide")
+st.title("Resume Matcher")
 
-# Sidebar design
-def apply_sidebar_colors():
-    st.markdown(
-        """
-        <style>
-        .sidebar .sidebar-content {
-            background: linear-gradient(45deg, #ff6f61, #ffcc33, #6f9dff, #93f5a3);
-            color: white;
-        }
-        </style>
-        """,
-        unsafe_allow_html=True
-    )
-
-apply_sidebar_colors()
-
-# App title with emojis
-st.title("💼 JobFit CV/Resume Matcher")
-
-# Sidebar for API key, job description, and user details
+# Sidebar for API key input and user details
 with st.sidebar:
-    st.header("🔑 Enter Your Details")
-    
     with st.form(key="user_details_form", clear_on_submit=True):
+        
         # Field for API key
-        st.subheader("🌐 Cohere API Key")
+        st.header("Cohere API Key")
         st.markdown("You can get your API key from [Cohere's website](https://dashboard.cohere.com/).")
         api_key = st.text_input("Enter your Cohere API Key", type="password")
 
-        # Job description input with enhanced style
-        st.subheader("📝 Job Description")
-        st.markdown("""
-            <style>
-            .job-description-textarea {
-                background-color: #f7f7f7;
-                border: 2px solid #ff6f61;
-                border-radius: 8px;
-                padding: 10px;
-                font-weight: bold;
-                font-size: 16px;
-                color: #333;
-            }
-            </style>
-        """, unsafe_allow_html=True)
-
-        # Ensure the default value is fetched from session state if it exists
-        job_description = st.text_area("Paste the Job Description here", 
-                                       placeholder="Enter the job description you're applying for...", 
-                                       height=200, 
-                                       key="job_description", 
-                                       help="Provide the job description for matching with your resume.",
-                                       value=st.session_state.get("job_description", ""))
-
-        # Initialize other session state variables if not present
+        # Check if name and contact are already in session state
         if "name" not in st.session_state:
             st.session_state["name"] = ""
         if "contact" not in st.session_state:
             st.session_state["contact"] = ""
 
+        # Generate or retrieve a unique user ID
         if "user_id" not in st.session_state:
             st.session_state["user_id"] = str(random.randint(1000000000, 9999999999))
-
+        
         user_id = st.session_state["user_id"]
-
-        # User details inputs
-        st.subheader("👤 Personal Information")
-        name = st.text_input("Name", st.session_state["name"], placeholder="Enter your full name...")
-        contact = st.text_input("Contact Information", st.session_state["contact"], placeholder="Email, phone number, or LinkedIn...")
-
-        st.subheader("💼 Professional Background")
-        skills = st.text_area("Skills", placeholder="List your skills (one per line)...")
-        experience = st.text_area("Experience", placeholder="Work experience details (one per line)...")
-        education = st.text_area("Education", placeholder="Educational qualifications (one per line)...")
-        projects = st.text_area("Projects", placeholder="Notable projects (one per line)...")
-
-        submit_button = st.form_submit_button(label="Save Details")
-
-    # Save the data if all fields are filled
+        
+        st.header("Enter Your Details")
+        name = st.text_input("Name", st.session_state["name"])
+        contact = st.text_input("Contact - Email, Number, links, etc", st.session_state["contact"])
+        skills = st.text_area("Skills - Technical, Soft, etc (one per line)", "")
+        experience = st.text_area("Experience - Company Name, Duration, Role, Responsibilities etc (one per line)", "")
+        education = st.text_area("Education - Degree Name, University Name, Duration etc (one per line)", "")
+        project = st.text_area("Projects - Name, Features etc (one per line)", "")
+
+        submit_button = st.form_submit_button(label="Save")
+    
     if submit_button:
-        if all([api_key, job_description, name, contact, skills, experience, education, projects]):
+        if all([api_key, name, contact, skills, experience, education, project]):
             st.session_state["api_key"] = api_key
             st.session_state["name"] = name
             st.session_state["contact"] = contact
-            st.session_state["job_description"] = job_description
             st.session_state["skills"] = skills
             st.session_state["experience"] = experience
             st.session_state["education"] = education
-            st.session_state["projects"] = projects
-            st.success("✅ Details Saved Successfully!")
+            st.session_state["project"] = project
+            st.session_state["saved"] = True
+            st.success("Details saved successfully!")
         else:
-            st.warning("⚠️ Please fill out all fields to proceed.")
+            st.warning("Please fill out all fields.")
 
 # Check if the user has saved the details
-if "api_key" in st.session_state:
-    # Main layout for generating the resume
-    st.subheader("🛠️ Generate Your Custom Resume")
-
-    # Convert input fields to lists
-    skills_list = st.session_state["skills"].splitlines()
-    experience_list = st.session_state["experience"].splitlines()
-    education_list = st.session_state["education"].splitlines()
-    project_list = st.session_state["projects"].splitlines()
-
-    # Initialize embeddings and vector store
+if st.session_state.get("saved", False):
+    # Convert inputs to lists (split by new lines)
+    skills_list = [s.strip() for s in st.session_state["skills"].splitlines() if s.strip()]
+    experience_list = [e.strip() for e in st.session_state["experience"].splitlines() if e.strip()]
+    education_list = [e.strip() for e in st.session_state["education"].splitlines() if e.strip()]
+    project_list = [p.strip() for p in st.session_state["project"].splitlines() if p.strip()]
+
+    # Initialize Cohere Embeddings
     embedding_model = CohereEmbeddings(cohere_api_key=st.session_state["api_key"], model="embed-english-light-v3.0")
-    vector_store = Chroma(collection_name="user_data", embedding_function=embedding_model, persist_directory="chroma")
 
-    # Create documents for vector store
-    skill_documents = [Document(page_content=skill, metadata={"user_id": user_id, "type": "skill"}, id=str(uuid4())) for skill in skills_list]
-    experience_documents = [Document(page_content=exp, metadata={"user_id": user_id, "type": "experience"}, id=str(uuid4())) for exp in experience_list]
-    education_documents = [Document(page_content=edu, metadata={"user_id": user_id, "type": "education"}, id=str(uuid4())) for edu in education_list]
-    project_documents = [Document(page_content=proj, metadata={"user_id": user_id, "type": "project"}, id=str(uuid4())) for proj in project_list]
+    # Initialize Chroma vector store
+    vector_store = Chroma(
+        collection_name="user_data",
+        embedding_function=embedding_model,
+        persist_directory="chroma"
+    )
+
+    # Create documents for skills, experience, education, and projects
+    skill_documents = [
+        Document(
+            page_content=skill,
+            metadata={"user_id": user_id, "type": "skill"},
+            id=str(uuid4())
+        )
+        for skill in skills_list
+    ]
+
+    experience_documents = [
+        Document(
+            page_content=exp,
+            metadata={"user_id": user_id, "type": "experience"},
+            id=str(uuid4())
+        )
+        for exp in experience_list
+    ]
+
+    education_documents = [
+        Document(
+            page_content=edu,
+            metadata={"user_id": user_id, "type": "education"},
+            id=str(uuid4())
+        )
+        for edu in education_list
+    ]
+
+    project_documents = [
+        Document(
+            page_content=proj,
+            metadata={"user_id": user_id, "type": "project"},
+            id=str(uuid4())
+        )
+        for proj in project_list
+    ]
 
     # Add documents to the vector store
-    vector_store.add_documents(skill_documents + experience_documents + education_documents + project_documents)
+    vector_store.add_documents(documents=skill_documents)
+    vector_store.add_documents(documents=experience_documents)
+    vector_store.add_documents(documents=education_documents)
+    vector_store.add_documents(documents=project_documents)
 
-    # Button to generate the resume
-    if st.button("📝 Generate Resume"):
+    # Main app layout for job description and resume generation
+    job_description = st.text_area("Job Description", "")
+
+    if st.button("Generate Resume"):
         def remove_duplicates(results):
             seen = set()
             unique_results = []
             for result in results:
-                if result.page_content not in seen:
+                content = result.page_content
+                if content not in seen:
                     unique_results.append(result)
-                    seen.add(result.page_content)
+                    seen.add(content)
             return unique_results
+        
+        # Retrieve relevant information
+        relevant_skills = vector_store.similarity_search_by_vector(
+            embedding=embedding_model.embed_query(job_description), k=10, filter={"type": "skill"}
+        )
+
+        relevant_experience = vector_store.similarity_search_by_vector(
+            embedding=embedding_model.embed_query(job_description), k=4, filter={"type": "experience"}
+        )
+        
+        relevant_education = vector_store.similarity_search_by_vector(
+            embedding=embedding_model.embed_query(job_description), k=4, filter={"type": "education"}
+        )
 
-        # Search for relevant information based on the job description
-        relevant_skills = vector_store.similarity_search_by_vector(embedding_model.embed_query(st.session_state["job_description"]), k=10, filter={"type": "skill"})
-        relevant_experience = vector_store.similarity_search_by_vector(embedding_model.embed_query(st.session_state["job_description"]), k=4, filter={"type": "experience"})
-        relevant_education = vector_store.similarity_search_by_vector(embedding_model.embed_query(st.session_state["job_description"]), k=4, filter={"type": "education"})
-        relevant_projects = vector_store.similarity_search_by_vector(embedding_model.embed_query(st.session_state["job_description"]), k=4, filter={"type": "project"})
+        relevant_project = vector_store.similarity_search_by_vector(
+            embedding=embedding_model.embed_query(job_description), k=4, filter={"type": "project"}
+        )
 
-        # Format the results
+        # Format the relevant information
         skills_content = "\n".join([doc.page_content for doc in remove_duplicates(relevant_skills)])
         experience_content = "\n".join([doc.page_content for doc in remove_duplicates(relevant_experience)])
         education_content = "\n".join([doc.page_content for doc in remove_duplicates(relevant_education)])
-        projects_content = "\n".join([doc.page_content for doc in remove_duplicates(relevant_projects)])
+        project_content = "\n".join([doc.page_content for doc in remove_duplicates(relevant_project)])
 
-        # Create a prompt to generate the resume
+        # Create a system prompt to generate a resume
         system_prompt = f"""
-        Generate a well-structured resume for {st.session_state['name']} with the following details:
-        
-        Job Description: {st.session_state['job_description']}
+        Generate a resume with the following details:
+
+        Guidelines:
+        Be specific and use active voice.
+        Avoid errors, passive language, and personal pronouns.
+        Ensure consistency and readability.
+
+        Avoid:
+        Spelling/grammar errors, missing contact info, poor organization.
+
+        Action Verbs Examples:
+        Leadership: Led, Managed
+        Communication: Presented, Promoted
+        Technical: Engineered, Programmed
+        Organizational: Organized, Implemented
+
+        Details:
+        Job Description: {job_description}
         Name: {st.session_state['name']}
         Contact: {st.session_state['contact']}
+        Projects: {project_content}
         Skills: {skills_content}
         Experience: {experience_content}
         Education: {education_content}
-        Projects: {projects_content}
 
-        Follow this structure:
-        - Name and contact at the top.
-        - Skills, experience, education, and projects listed clearly.
-        - Use bullet points and headings where needed.
+        Formatting:
+        Start with name and contact.
+        List experience, education, projects and skills in order.
+        Use headings and bullet points.
+
+        Instruction:
+        Do not add any extra text or headings from yourself; use only the provided details.
         """
 
         # Initialize ChatCohere
         chat_model = ChatCohere(cohere_api_key=st.session_state["api_key"])
 
-        # Generate resume
+        # Generate the resume
         resume_output = chat_model.invoke(input=system_prompt)
 
-        # Display the generated resume and a copy button
-        st.subheader("📄 Generated Resume")
-        st.text_area("Your Resume", resume_output.content, height=400)
-        st.button("📋 Copy Resume to Clipboard")
-
-    # Cover Letter Section
-    st.subheader("📩 Generate Cover Letter")
-    cover_letter_prompt = f"""
-    Create a cover letter for {st.session_state['name']} for the following job description:
-    
-    Job Description: {st.session_state['job_description']}
-    
-    Ensure the cover letter is professional and tailored to the job.
-    """
-
-    # Generate cover letter using ChatCohere
-    cover_letter_output = chat_model.invoke(input=cover_letter_prompt)
-
-    # Display the generated cover letter
-    st.subheader("📄 Generated Cover Letter")
-    st.text_area("Your Cover Letter", cover_letter_output.content, height=400)
-    st.button("📋 Copy Cover Letter to Clipboard")
+        # Display the generated resume
+        st.subheader("Generated Resume")
+        st.write(resume_output.content)
 
 else:
-    st.warning("⚠️ Please enter your details in the sidebar.")
+    st.info("Please fill out your details in the sidebar and click Save to proceed.")