Update pages/model.py

pages/model.py

@@ -1,92 +1,86 @@
-import streamlit as st
 import os
-from langchain_community.chat_models import ChatHuggingFace
-from langchain_huggingface import HuggingFaceEndpoint
+import streamlit as st
 from langchain_community.document_loaders import UnstructuredPDFLoader
-
+from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
+import tempfile
 
 os.environ["HF_TOKEN"]=os.getenv('HF_Token')
 os.environ["HUGGINGFACEHUB_API_KEY"]=os.getenv('HF_Token')
 
-llm_config = HuggingFaceEndpoint(
-    repo_id="meta-llama/Llama-3.1-8B-Instruct",
+llm_skeleton = HuggingFaceEndpoint(
+    repo_id="deepseek-ai/DeepSeek-R1",
     provider="nebius",
-    temperature=0.5,
-    max_new_tokens=300,
+    temperature=0.7,
+    max_new_tokens=150,
     task="conversational"
 )
+
 llm = ChatHuggingFace(
-    llm=llm_config,
-    repo_id="meta-llama/Llama-3.1-8B-Instruct",
-    provider="nebius"
+    llm=llm_skeleton,
+    repo_id="deepseek-ai/DeepSeek-R1",
+    provider="nebius",
+    temperature=0.7,
+    max_new_tokens=150,
+    task="conversational"
 )
 
-
-st.set_page_config(page_title="Smart Resume-JD Extractor", layout="centered")
-st.markdown("""
-    <div style="text-align:center; padding: 30px; background-color: #f3f4f6; border-radius: 12px;">
-        <h1 style="color:#2c3e50;">📄 PrescriptoHire: Resume & JD Extractor</h1>
-        <p style="color:#555; font-size: 16px;">AI-powered tool to extract & compare details from resumes and job descriptions</p>
-    </div>
-""", unsafe_allow_html=True)
-
-
-resume_file = st.file_uploader("Upload Candidate Resume (PDF)", type=["pdf"])
-jd_file = st.file_uploader("Upload Job Description (PDF)", type=["pdf"])
-
-
-st.markdown("<p style='text-align:center; margin:10px 0;'>-- OR --</p>", unsafe_allow_html=True)
-jd_text_input = st.text_area("Paste Job Description Text")
-
-
-if st.button("🔍 Extract & Compare"):
-    if not resume_file:
-        st.error("Please upload a resume PDF to proceed.")
+def extract_text_from_pdf(uploaded_file):
+    try:
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
+            tmp_file.write(uploaded_file.read())
+            tmp_path = tmp_file.name
+        loader = UnstructuredPDFLoader(tmp_path)
+        return loader.load()[0].page_content
+    except Exception as e:
+        st.error(f"Error reading PDF file: {e}")
+        return ""
+
+def extract_text_from_txt(uploaded_file):
+    try:
+        return uploaded_file.read().decode("utf-8")
+    except Exception as e:
+        st.error(f"Error reading text file: {e}")
+        return ""
+
+st.set_page_config(page_title="Resume & JD Extractor", layout="centered")
+st.title("📄 Resume & Job Description Extractor")
+
+resume_file = st.file_uploader("Upload Resume (PDF)", type=["pdf"])
+jd_file = st.file_uploader("Upload Job Description (PDF or TXT)", type=["pdf", "txt"])
+jd_text = st.text_area("Or paste Job Description text here")
+
+if st.button("🔍 Extract Data"):
+    if not resume_file and not (jd_file or jd_text):
+        st.warning("Please upload at least one file (Resume or JD) or paste JD text.")
     else:
-        # Extract Resume Text
-        resume_text = UnstructuredPDFLoader(resume_file).load()[0].page_content
-
-        resume_prompt = f"""
-        Extract the following from the resume:
-        1. Name
-        2. Contact Info
-        3. Education
-        4. Experience
-        5. Skills
-        6. Projects and Achievements
-
-        Resume Text:
-        {resume_text}
-        """
-        with st.spinner("Extracting from Resume..."):
-            resume_output = llm.invoke(resume_prompt)
-        st.success("Resume data extracted!")
-        st.subheader("🧾 Resume Summary")
-        st.write(resume_output)
-
-    # Process JD (file or text)
-    if jd_file or jd_text_input:
+        if resume_file:
+            resume_text = extract_text_from_pdf(resume_file)
+            if resume_text:
+                resume_prompt = (
+                    "Extract the following from the resume:\n"
+                    "1. Name\n2. Education\n3. Experience\n4. Skills\n5. Project Names and Results\n\n"
+                    f"Resume:\n{resume_text}"
+                )
+                resume_data = llm.invoke(resume_prompt)
+                st.subheader("📌 Extracted Resume Data")
+                st.markdown(f"<div style='background-color:#f9f9f9;padding:10px;border-radius:8px;'>{resume_data}</div>", unsafe_allow_html=True)
+
+        jd_text_extracted = ""
         if jd_file:
-            jd_text = UnstructuredPDFLoader(jd_file).load()[0].page_content
-        else:
-            jd_text = jd_text_input
-
-        jd_prompt = f"""
-        Extract the following from the job description:
-        1. Job Title
-        2. Company Name
-        3. Experience Required
-        4. Key Responsibilities
-        5. Skills & Qualifications
-        6. Location
-
-        Job Description:
-        {jd_text}
-        """
-        with st.spinner("Extracting from Job Description..."):
-            jd_output = llm.invoke(jd_prompt)
-        st.success("Job description data extracted!")
-        st.subheader("📌 Job Description Summary")
-        st.write(jd_output)
-    else:
-        st.warning("Please upload or paste a job description.")
+            if jd_file.type == "application/pdf":
+                jd_text_extracted = extract_text_from_pdf(jd_file)
+            elif jd_file.type == "text/plain":
+                jd_text_extracted = extract_text_from_txt(jd_file)
+        elif jd_text:
+            jd_text_extracted = jd_text
+
+        if jd_text_extracted:
+            jd_prompt = (
+                "Extract the following from the job description:\n"
+                "1. Job ID\n2. Company Name\n3. Role\n4. Experience Required\n5. Skills Required\n"
+                "6. Education Required\n7. Location\n\n"
+                f"Job Description:\n{jd_text_extracted}"
+            )
+            jd_data = llm.invoke(jd_prompt)
+            st.subheader("📌 Extracted Job Description Data")
+            st.markdown(f"<div style='background-color:#f9f9f9;padding:10px;border-radius:8px;'>{jd_data}</div>", unsafe_allow_html=True)