Update app.py

app.py

@@ -9,21 +9,7 @@ load_dotenv()  ## Load all environment variables
 
 genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
 
-def get_gemini_response(input_text):
-    model = genai.GenerativeModel('gemini-1.5-pro')
-    response = model.generate_content(input_text)
-    return response.text
-
-def input_pdf_text(uploaded_file):
-    reader = pdf.PdfReader(uploaded_file)
-    text = ""
-    for page in range(len(reader.pages)):
-        extracted_text = reader.pages[page].extract_text()
-        if extracted_text:
-            text += extracted_text
-    return text
-
-# Prompt Template
+# Define the prompt template
 input_prompt = """
 Hey, act like a skilled and very experienced ATS (Application Tracking System)
 with a deep understanding of tech fields such as software engineering, data science, 
@@ -37,11 +23,43 @@ and identify the missing keywords with high accuracy.
 resume: {text}
 description: {jd}
 
-I want the response in one single JSON string with the following structure:
-{{"JD Match":"%", "MissingKeywords":[], "Profile Summary":""}}
+Return ONLY a JSON response in the following format:
+{{
+  "JD Match": "xx%",
+  "MissingKeywords": ["keyword1", "keyword2", ...],
+  "Profile Summary": "A short summary here"
+}}
+
+DO NOT include any additional text, explanation, or greetings—only return the JSON object.
 """
 
-## Streamlit app
+def get_gemini_response(resume_text, jd_text):
+    """Generates a response from Gemini API based on the resume and job description."""
+    formatted_prompt = input_prompt.format(text=resume_text, jd=jd_text)  # Format the prompt
+    model = genai.GenerativeModel('gemini-1.5-pro')
+    response = model.generate_content(formatted_prompt)
+
+    # Ensure we get only the text response
+    response_text = response.text.strip()
+
+    # Attempt to extract JSON from the response
+    try:
+        parsed_response = json.loads(response_text)
+        return parsed_response  # Return parsed JSON
+    except json.JSONDecodeError:
+        return None  # Return None if response is not valid JSON
+
+def input_pdf_text(uploaded_file):
+    """Extracts text from the uploaded PDF resume."""
+    reader = pdf.PdfReader(uploaded_file)
+    text = ""
+    for page in range(len(reader.pages)):
+        extracted_text = reader.pages[page].extract_text()
+        if extracted_text:
+            text += extracted_text
+    return text
+
+# Streamlit app
 st.title("Smart ATS")
 st.text("Improve Your Resume for ATS Systems")
 
@@ -53,16 +71,13 @@ submit = st.button("Submit")
 if submit:
     if uploaded_file is not None and jd:
         text = input_pdf_text(uploaded_file)
-        formatted_prompt = input_prompt.format(text=text, jd=jd)
-        response = get_gemini_response(formatted_prompt)
-        
-        # Try parsing the response as JSON
-        try:
-            parsed_response = json.loads(response)
-            st.subheader("Job Description Match: " + parsed_response["JD Match"])
-            st.write("Missing Keywords: ", parsed_response["MissingKeywords"])
-            st.write("Profile Summary: ", parsed_response["Profile Summary"])
-        except json.JSONDecodeError:
-            st.error("Error: Could not parse the response. Please check the response format.")
+        response = get_gemini_response(text, jd)  # Pass formatted resume & JD
+
+        if response:
+            st.subheader(f"Job Description Match: {response['JD Match']}")
+            st.write("Missing Keywords: ", response["MissingKeywords"])
+            st.write("Profile Summary: ", response["Profile Summary"])
+        else:
+            st.error("Error: Gemini did not return valid JSON. Please try again.")
     else:
         st.warning("Please upload a resume and enter a job description.")