Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
|
@@ -77,7 +77,7 @@ def analyze_education(text):
|
|
| 77 |
|
| 78 |
def analyze_skills(text):
|
| 79 |
technical_skills = ['python', 'java', 'javascript', 'c++', 'sql', 'machine learning',
|
| 80 |
-
|
| 81 |
found_skills = [skill for skill in technical_skills if skill.lower() in text.lower()]
|
| 82 |
return min(len(found_skills) * 3, 20), ', '.join(found_skills) or 'Nav atrasts'
|
| 83 |
|
|
@@ -128,11 +128,11 @@ def generate_candidate_description(name, experience, education, skills, language
|
|
| 128 |
def analyze_cv(file):
|
| 129 |
if file is None:
|
| 130 |
return "⚠️ Lūdzu, augšupielādējiet CV failu!"
|
| 131 |
-
|
| 132 |
try:
|
| 133 |
file_name = file.name
|
| 134 |
ext = file_name.split('.')[-1].lower()
|
| 135 |
-
|
| 136 |
if ext == 'pdf':
|
| 137 |
text = extract_text_from_pdf(file)
|
| 138 |
elif ext == 'docx':
|
|
@@ -141,19 +141,18 @@ def analyze_cv(file):
|
|
| 141 |
text = extract_text_from_txt(file)
|
| 142 |
else:
|
| 143 |
return "❌ Neatbalstīts faila formāts! Atbalstītie: PDF, DOCX, TXT"
|
| 144 |
-
|
| 145 |
-
# AR NER!
|
| 146 |
name = extract_name_with_ner(text)
|
| 147 |
email = extract_email(text)
|
| 148 |
phone = extract_phone(text)
|
| 149 |
-
|
| 150 |
exp_score, experience = analyze_experience(text)
|
| 151 |
edu_score, education = analyze_education(text)
|
| 152 |
skill_score, skills = analyze_skills(text)
|
| 153 |
lang_score, languages = analyze_languages(text)
|
| 154 |
-
|
| 155 |
total = exp_score + edu_score + skill_score + lang_score
|
| 156 |
-
|
| 157 |
|
| 158 |
# Ģenerē aprakstu par kandidātu
|
| 159 |
candidate_description = generate_candidate_description(name, experience, education, skills, languages)
|
|
@@ -168,7 +167,7 @@ def analyze_cv(file):
|
|
| 168 |
🎓 Izglītība: {edu_score}/30 ({education})
|
| 169 |
💻 Prasmes: {skill_score}/20 ({skills})
|
| 170 |
🌐 Valodas: {lang_score}/20 ({languages})
|
| 171 |
-
|
| 172 |
except Exception as e:
|
| 173 |
return f"❌ Kļūda apstrādājot failu: {str(e)}"
|
| 174 |
|
|
@@ -177,24 +176,16 @@ demo = gr.Interface(
|
|
| 177 |
fn=analyze_cv,
|
| 178 |
inputs=gr.File(label="Ielādējiet CV failu", file_types=['.pdf', '.docx', '.txt']),
|
| 179 |
outputs=gr.Textbox(label="Analīzes rezultāti", lines=25),
|
| 180 |
-
|
| 181 |
-
|
| 182 |
-
-
|
| 183 |
-
- 💼 Darba pieredzi
|
| 184 |
-
- 🎓 Izglītību
|
| 185 |
-
- 🌐 Valodu prasmes
|
| 186 |
-
- 📦 Tehniskās prasmes
|
| 187 |
-
|
| 188 |
-
**Rezultāti tiek vērtēti 100 punktu skalā**
|
| 189 |
-
""",
|
| 190 |
-
- 👤 Personīgo informāc
|
| 191 |
- 💼 Darba pieredzi
|
| 192 |
- 🎓 Izglītību
|
| 193 |
- 🌐 Valodu prasmes
|
| 194 |
- 📚 Tehniskās prasmes
|
| 195 |
|
| 196 |
**Rezultāti tiek vērtēti 100 punktu skalā**
|
| 197 |
-
|
| 198 |
)
|
| 199 |
|
| 200 |
if __name__ == "__main__":
|
|
|
|
| 77 |
|
| 78 |
def analyze_skills(text):
|
| 79 |
technical_skills = ['python', 'java', 'javascript', 'c++', 'sql', 'machine learning',
|
| 80 |
+
'data analysis', 'excel', 'powerpoint', 'word', 'project management']
|
| 81 |
found_skills = [skill for skill in technical_skills if skill.lower() in text.lower()]
|
| 82 |
return min(len(found_skills) * 3, 20), ', '.join(found_skills) or 'Nav atrasts'
|
| 83 |
|
|
|
|
| 128 |
def analyze_cv(file):
|
| 129 |
if file is None:
|
| 130 |
return "⚠️ Lūdzu, augšupielādējiet CV failu!"
|
| 131 |
+
|
| 132 |
try:
|
| 133 |
file_name = file.name
|
| 134 |
ext = file_name.split('.')[-1].lower()
|
| 135 |
+
|
| 136 |
if ext == 'pdf':
|
| 137 |
text = extract_text_from_pdf(file)
|
| 138 |
elif ext == 'docx':
|
|
|
|
| 141 |
text = extract_text_from_txt(file)
|
| 142 |
else:
|
| 143 |
return "❌ Neatbalstīts faila formāts! Atbalstītie: PDF, DOCX, TXT"
|
| 144 |
+
|
|
|
|
| 145 |
name = extract_name_with_ner(text)
|
| 146 |
email = extract_email(text)
|
| 147 |
phone = extract_phone(text)
|
| 148 |
+
|
| 149 |
exp_score, experience = analyze_experience(text)
|
| 150 |
edu_score, education = analyze_education(text)
|
| 151 |
skill_score, skills = analyze_skills(text)
|
| 152 |
lang_score, languages = analyze_languages(text)
|
| 153 |
+
|
| 154 |
total = exp_score + edu_score + skill_score + lang_score
|
| 155 |
+
|
| 156 |
|
| 157 |
# Ģenerē aprakstu par kandidātu
|
| 158 |
candidate_description = generate_candidate_description(name, experience, education, skills, languages)
|
|
|
|
| 167 |
🎓 Izglītība: {edu_score}/30 ({education})
|
| 168 |
💻 Prasmes: {skill_score}/20 ({skills})
|
| 169 |
🌐 Valodas: {lang_score}/20 ({languages})
|
| 170 |
+
"""
|
| 171 |
except Exception as e:
|
| 172 |
return f"❌ Kļūda apstrādājot failu: {str(e)}"
|
| 173 |
|
|
|
|
| 176 |
fn=analyze_cv,
|
| 177 |
inputs=gr.File(label="Ielādējiet CV failu", file_types=['.pdf', '.docx', '.txt']),
|
| 178 |
outputs=gr.Textbox(label="Analīzes rezultāti", lines=25),
|
| 179 |
+
title="📄 CV Automatīskās Analīzes Sistēma",
|
| 180 |
+
description="""Augšupielādējiet CV failu (PDF, DOCX vai TXT), un sistēma automatīski analizēs:
|
| 181 |
+
- 👤 Personīgo informāciju
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 182 |
- 💼 Darba pieredzi
|
| 183 |
- 🎓 Izglītību
|
| 184 |
- 🌐 Valodu prasmes
|
| 185 |
- 📚 Tehniskās prasmes
|
| 186 |
|
| 187 |
**Rezultāti tiek vērtēti 100 punktu skalā**
|
| 188 |
+
"""
|
| 189 |
)
|
| 190 |
|
| 191 |
if __name__ == "__main__":
|