Update app.py

app.py

@@ -24,21 +24,22 @@ def get_gemini_response(prompt):
 
 def analyze_resume(text):
     prompt = (
-        "You are an expert resume analyst. Analyze the following resume text and provide the following:\n\n"
-        "1. A brief summary of the resume, including the candidate's main interests and the fields they are most passionate about.\n"
-        "2. A detailed percentage distribution of fields/domains present in the resume, with keywords extracted from the resume. Ensure the total sums up to 100%.\n"
-        "Here is an example of how the output should look like:\n\n"
-        "### Summary\n"
-        "The resume indicates a strong background and interest in machine learning, data science, and software development. The candidate has worked on several projects involving machine learning algorithms, data preprocessing, and building software applications. They have demonstrated proficiency in Python, Java, and various machine learning frameworks. The candidate is passionate about solving complex problems using AI and has a keen interest in continuing to develop their skills in this area.\n\n"
-        "### Percentage Distribution of Fields/Domains\n"
-        "Note: only include standard technologies as keywords.\n"
-        "- *Machine Learning (ML)*: 40%\n"
-        "  - Keywords: Algorithms, Keras, PyTorch, Scikit-Learn, Predictive Models\n"
-        "- *Data Science (DS)*: 30%\n"
-        "  - Keywords: Data Analysis, Pandas, NumPy, Visualization, Statistical Methods\n"
-        "- *Software Development (SD)*: 30%\n"
-        "  - Keywords: Python, Java, Software Engineering, APIs, Git\n"
-    )
+    "You are an expert resume analyst. Analyze the following resume text and provide the following:\n\n"
+    "1. A comprehensive summary of the candidate’s skills, interests, and experience. Highlight their main technical competencies, areas of interest, and any certifications or academic qualifications they have pursued. Emphasize specific projects, internships, or work experiences, and mention any relevant tools, programming languages, or technologies used by the candidate.\n"
+    "2. A detailed percentage distribution of fields/domains present in the resume, with keywords extracted from the resume. Ensure the total sums up to 100%.\n"
+    "Here is an example of how the output should look like:\n\n"
+    "### Summary\n"
+    "This resume showcases a candidate with a strong foundation in [Field/Domain 1], [Field/Domain 2], and [Field/Domain 3]. The candidate has demonstrated proficiency in [Specific Tools/Technologies] and has experience in both [Internships/Projects/Work Experience]. They are passionate about [Specific Interests], and their projects include [Project Examples]. The candidate has also pursued certifications in [Certifications] and has a solid academic background in [Relevant Degrees/Fields].\n\n"
+    "### Percentage Distribution of Fields/Domains\n"
+    "Note: only include standard technologies as keywords.\n"
+    "- [Field/Domain 1]: X%\n"
+    "  - Keywords: [Relevant Keywords]\n"
+    "- [Field/Domain 2]: Y%\n"
+    "  - Keywords: [Relevant Keywords]\n"
+    "- [Field/Domain 3]: Z%\n"
+    "  - Keywords: [Relevant Keywords]\n"
+)
+
     analysis = get_gemini_response(prompt + text)
     return analysis