Update app.py

app.py

@@ -23,22 +23,22 @@ def get_gemini_response(prompt):
     return response.text
 
 def analyze_resume(text):
-    prompt = (
-    "You are an expert resume analyst. Analyze the following resume text and provide the following:\n\n"
-    "1. A concise summary of the resume, focusing on the candidate’s foundational skills, key technical competencies, and significant experiences. Mention their primary areas of interest and the most relevant projects or certifications. Avoid unnecessary details and focus on the core strengths of 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 [Key Fields/Domains]. The candidate has demonstrated proficiency in [Primary Technical Skills] and has experience in [Type of Experience (e.g., internships, projects)]. Their significant projects include [Relevant Projects], and they have pursued certifications in [Relevant Certifications/Fields]. The candidate is passionate about [Primary Interests], and their work highlights their ability to apply their skills in real-world scenarios.\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"
-)
+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"
+    )
 
     analysis = get_gemini_response(prompt + text)
     return analysis