translated resume

app.py

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+import gradio as gr
+import logging
+import dwani
+import os
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Configure dwani API settings from environment variables
+dwani.api_key = os.getenv("DWANI_API_KEY")
+dwani.api_base = os.getenv("DWANI_API_BASE_URL")
+
+
+def translate_to_kannada(text):
+    """Translate English text to Kannada using dwani.Translate.run_translate."""
+    if not text or text.strip() == "":
+        return ""
+
+    try:
+        resp = dwani.Translate.run_translate(
+            sentences=text,
+            src_lang="english",
+            tgt_lang="kannada"
+        )
+        if isinstance(resp, dict):
+            translated = resp.get("translated_text")
+            if translated:
+                return translated.strip()
+            if "translations" in resp and isinstance(resp["translations"], list):
+                return " ".join(t.strip() for t in resp["translations"] if isinstance(t, str))
+            return str(resp).strip()
+        elif isinstance(resp, str):
+            return resp.strip()
+        else:
+            return str(resp).strip()
+    except Exception as e:
+        logger.error(f"Translation error: {e}")
+        return f"Translation error: {e}"
+
+
+def process_pdf(pdf_file):
+    logger.debug("Received inputs - PDF: %s", pdf_file)
+
+    if not pdf_file:
+        logger.error("No PDF file provided")
+        return None
+
+    file_path = pdf_file.name if hasattr(pdf_file, 'name') else pdf_file
+    pages = {1, 2}
+    src_lang_code = "eng_Latn"
+    tgt_lang_code = "kan_Knda"
+
+    results = {}
+    for page_number in pages:
+        try:
+            result = dwani.Documents.run_extract(
+                file_path=file_path,
+                page_number=page_number,
+                src_lang=src_lang_code,
+                tgt_lang=tgt_lang_code
+            )
+            page_data = None
+            for p in result.get('pages', []):
+                if p.get('processed_page') == page_number:
+                    page_data = p
+                    break
+
+            if page_data is None:
+                results[f"Page {page_number}"] = {"error": "No data returned for this page"}
+                continue
+
+            results[f"Page {page_number}"] = {
+                "Original Text": page_data.get("page_content", "N/A"),
+                "Response": ""
+            }
+        except dwani.exceptions.DwaniAPIError as e:
+            logger.error(f"Dhwani API error on page {page_number}: {str(e)}")
+            results[f"Page {page_number}"] = {"error": f"API error: {str(e)}"}
+        except Exception as e:
+            logger.error(f"Unexpected error on page {page_number}: {str(e)}")
+            results[f"Page {page_number}"] = {"error": f"Unexpected error: {str(e)}"}
+
+    contact_en = extract_contact_details(results)
+    objective_en = extract_objective(results)
+    education_en = extract_education_details(results)
+    work_experience_en = extract_workexperience_details(results)
+    skills_en = extract_skill(results)
+    certifications_en = extract_certifications(results)
+
+    contact_kan = translate_to_kannada(contact_en)
+    objective_kan = translate_to_kannada(objective_en)
+    education_kan = translate_to_kannada(education_en)
+    work_experience_kan = translate_to_kannada(work_experience_en)
+    skills_kan = translate_to_kannada(skills_en)
+    certifications_kan = translate_to_kannada(certifications_en)
+
+    formatted_resume = format_resume(contact_kan, objective_kan, education_kan, work_experience_kan, skills_kan, certifications_kan)
+
+    text_filename = "resume.txt"
+    with open(text_filename, "w", encoding="utf-8") as f:
+        f.write(formatted_resume)
+
+    return text_filename
+
+
+def extract_text_from_response(chat_response):
+    if isinstance(chat_response, dict):
+        for key in ("text", "response", "content"):
+            if key in chat_response and isinstance(chat_response[key], str):
+                return chat_response[key]
+        return str(chat_response)
+    elif isinstance(chat_response, str):
+        return chat_response
+    else:
+        return str(chat_response)
+
+
+def extract_contact_details(extracted_resume):
+    resume_str = str(extracted_resume)
+    prompt = resume_str + " return only contact details from the resume "
+    response = dwani.Chat.direct(prompt=prompt, model="gemma3")
+    return extract_text_from_response(response)
+
+
+def extract_objective(extracted_resume):
+    resume_str = str(extracted_resume)
+    prompt = resume_str + " return only objective or professional summary from the resume "
+    response = dwani.Chat.direct(prompt=prompt, model="gemma3")
+    return extract_text_from_response(response)
+
+
+def extract_education_details(extracted_resume):
+    resume_str = str(extracted_resume)
+    prompt = resume_str + " return only education details from the resume "
+    response = dwani.Chat.direct(prompt=prompt, model="gemma3")
+    return extract_text_from_response(response)
+
+
+def extract_workexperience_details(extracted_resume):
+    resume_str = str(extracted_resume)
+    prompt = resume_str + " return only work experience from the resume "
+    response = dwani.Chat.direct(prompt=prompt, model="gemma3")
+    return extract_text_from_response(response)
+
+
+def extract_skill(extracted_resume):
+    resume_str = str(extracted_resume)
+    prompt = resume_str + " return only skills from the resume "
+    response = dwani.Chat.direct(prompt=prompt, model="gemma3")
+    return extract_text_from_response(response)
+
+
+def extract_certifications(extracted_resume):
+    resume_str = str(extracted_resume)
+    prompt = resume_str + " return only certifications from the resume "
+    response = dwani.Chat.direct(prompt=prompt, model="gemma3")
+    return extract_text_from_response(response)
+
+
+def safe_strip(value):
+    if isinstance(value, dict):
+        value = extract_text_from_response(value)
+    return str(value).strip()
+
+
+def format_resume(contact, objective, education, work_experience, skills, certifications):
+    return f"""# Resume (Kannada)
+
+## ಸಂಪರ್ಕ ವಿವರಗಳು (Contact Details)
+{safe_strip(contact)}
+
+## ಉದ್ದೇಶ (Objective)
+{safe_strip(objective)}
+
+## ಶಿಕ್ಷಣ (Education)
+{safe_strip(education)}
+
+## ಕೆಲಸದ ಅನುಭವ (Work Experience)
+{safe_strip(work_experience)}
+
+## ಕೌಶಲ್ಯಗಳು (Skills)
+{safe_strip(skills)}
+
+## ಪ್ರಮಾಣಪತ್ರಗಳು (Certifications)
+{safe_strip(certifications)}
+"""
+
+
+with gr.Blocks(title="Resume Translator with Kannada Translation") as resume_translator:
+    gr.Markdown("# Resume Upload")
+    gr.Markdown("Upload a Resume PDF to extract, translate to Kannada, and download.")
+
+    with gr.Row():
+        with gr.Column():
+            pdf_input = gr.File(label="Upload Resume", file_types=[".pdf"])
+            submit_btn = gr.Button("Process")
+
+        with gr.Column():
+            text_output = gr.File(label="Download Formatted Resume (.txt)")
+
+    submit_btn.click(
+        fn=process_pdf,
+        inputs=[pdf_input],
+        outputs=text_output
+    )
+
+
+if __name__ == "__main__":
+    resume_translator.launch()

requirements.txt

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+dwani
+gradio
+requests
+logging