Update app.py

app.py

@@ -2,7 +2,111 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 
 data = '''
-SARATH CHANDRA BANDREDDI **Professional Summary** Intern-level Python Developer skilled in AI, Django, and web development. Proficient in Python and AI, dedicated to continuous learning. Keen to contribute to software solutions and collaborate in a team environment. **Education** B.Tech in Computer Science (AI & ML), Vasireddy Venkatadri Institute of Technology, India (2021–2025), GPA: 8.60 **Tech Stack** - **Languages**: Python, Java, JavaScript, C, R, Shell - **Frontend**: HTML, CSS, Jinja - **Libraries**: TensorFlow, Keras, LlamaIndex, OpenCV, Sklearn, Numpy, Pandas, Django - **Platforms**: Kaggle, Google-Colabs, Git, GitHub, AWS, Figma - **Databases**: SQL, Oracle, MySQL **Projects** - **Face Recognition** (VGGFace | TensorFlow, Keras, OpenCV, Django) Developed a face recognition app achieving 97.86% accuracy on a 31-class dataset. Launched through Django on an online server. - **SCRAM** (Gemini-pro LLM, Google API, TensorFlow, Django) Built a Django-based college resource management system with LLM chatbot, face recognition, and 2-FS authentication. - **Document & Data Query AI Agent** (Llama3, Ollama, LlamaIndex) Created an AI agent for document-based Q&A and CSV visualization, integrating NLP and data retrieval. **Certifications** Python: Kaggle, SoloLearn, HackerRank, GUVI ML: Coursera, Kaggle, Microsoft, IBM Deep Learning: NPTEL, Kaggle, IBM Django: Microsoft AWS: AWS Academy Cloud Foundations, Cloud Architecting NPTEL: Java (ELITE), Data Science (ELITE + SILVER) **Achievements** 2nd Place in Python Hackathon (15 colleges, RVR&JC) **Find Me Online** LinkedIn, GitHub, Kaggle, HackerRank, CodeChef, LeetCode, Portfolio
+SARATH CHANDRA BANDREDDI
+# PROFESSIONAL SUMMARY:
+```
+    Intern-level Python Developer focused on AI and Django. Skilled in Python, AI development, and building robust web 
+    applications. Dedicated to continuous learning and staying updated with the latest industry trends and technologies. Eager to
+    contribute to innovative software solutions and work collaboratively in a team environment.
+```
+
+# TECH STACK:
+```
+    ➢ Languages : Python, Java, JavaScript, C, R
+    ➢ Scripting : Shell Scripting
+    ➢ Markup Languages : HTML, CSS, Jinja Coding, UML
+    ➢ Operating Systems : Linux, Windows
+    ➢ IDE Tools : VS Code, RStudio, Pycharm
+    ➢ Libraries/Frameworks : TensorFlow, Keras, LlamaIndex, Ollama, OpenCV, Sklearn, Numpy, Pandas, Django
+    ➢ Tools / Platforms : Kaggle, Google-Colabs, Git, GitHub, AWS, Figma
+    ➢ Databases : SQL, Oracle, My SQL
+```
+# EDUCATION PROFILE:
+```
+    ------------------------------------------------------------------------------------|
+    | Course                     | Institution                      | CGPA | Duration   |
+    |----------------------------|----------------------------------|------|------------|
+    | B.Tech-CSE (AI & ML)       | VVIT - Vasireddy Venkatadri      | 8.59 | 2021-2025  |
+    | 12th Class                 | Narayana Junior College          | 9.22 | 2020-2021  |
+    | 10th Class                 | Narayana High School             | 9.7  | 2018-2019  |
+    ------------------------------------------------------------------------------------|
+```
+
+# PROJECTS:
+```
+    ## FACE RECOGNITION VGGFace (LINK-"kaggle-notebook-link:https://www.kaggle.com/code/sarath02003/face-recognition-using-vggface2") -Individual project [Tensorflow | Keras | OpenCV |Django]:
+    ```
+        Developed a face recognition application utilizing the VGGFace architecture with TensorFlow, attaining exceptional accuracy on 
+        a bespoke 29-class dataset. Launched the system through Hugging face space on an online server, showcasing advanced 
+        capabilities in artificial neural networks and computer vision. Check the live application ("live-exegution-link:https://huggingface.co/spaces/Sarath0x8f/Celebrity_Recognition").
+        Leveraged advanced facial recognition techniques using a custom dataset created to simulate real-world conditions and developed Celebrity Recognition Application. 
+        Utilized data augmentation strategies, including shear, zoom, rotation, and brightness adjustments, to enhance model robustness. 
+        Implemented transfer learning with the VGGFace model to accelerate training and improve accuracy to 98, incorporating custom fully connected layers and freezing certain layers for optimal performance. 
+        Explored various optimizers (Adam, Adagrad, RMSprop) to optimize the model, demonstrating the critical role of optimizer selection in deep learning tasks. Integrated advanced training callbacks, such as EarlyStopping and ReduceLROnPlateau, 
+        to prevent overfitting and ensure efficient training processes. Conducted thorough evaluations of the model on training and validation datasets, achieving significant improvements in loss and accuracy metrics. 
+        Developed a deep understanding of data handling, model architecture customization, and training strategies, contributing to a more effective facial recognition model. 
+        Looking forward to further advancements in the field of deep learning and facial recognition.
+        - Mastered creating custom datasets using OpenCV, organizing training and test sets, and achieving 97.86% accuracy.
+        - Trained deep learning models for image classification, leading to the publication of two papers in peer-reviewed journals 
+        focusing on advancements in facial recognition technology.
+    ```
+    ## SCRAM (LINK-"Secure-Campus-Resource-and-Access-Management-link:https://github.com/21bq1a4210/E2E_Project/graphs/contributors") - Minor project [Gemini-pro (LLM) & Google API | Tensorflow | Keras | OpenCV | Django]:
+    ```
+        Engineered a robust, secure Django-based system for comprehensive college resource and access management, incorporating 
+        advanced features such as user management, complaint registration, and a chatbot assistant. Seamlessly integrated Gemini-Pro 
+        LLM with Google API and introduced face recognition technology for enhanced attendance tracking.
+        Led the development of a robust and secure Django-based system designed to streamline college resource and access management as part of my End-to-End Project. The platform integrates several key functionalities such as user management, complaint registration, attendance management system, and a chatbot assistant.
+
+        Here are my contribution to the project:
+        
+        User Authentication & Security: Developed a comprehensive user authentication system using Django's default authentication and implemented 2-Step Verification (2SV) for password recovery, improving overall system security and reliability. Engineered a single-page application for password recovery with two-step verification, enhancing user convenience.
+        Face Recognition Attendance System: Created a one short face recognition model using FaceNet and MTCNN to manage attendance, with a unique feature allowing students to mark their attendance only once per day and within the campus premises. This innovation ensures strict attendance integrity and security.
+        Chatbot Integration: Built and integrated the AskVVIT chatbot to assist with college-related inquiries. Initially deployed with the Gemini Pro LLM and Google API, the chatbot provided an interactive platform for students and staff. Due to response time limitations (one response per minute), the model was later replaced with LLaMA 3.2:1B and also tried with LLaMA 3:latest, significantly enhancing response efficiency.
+        Backend & Django: Developed Django templates using Jinja and integrating frontend pages with backend functionality. Created models for user registration and attendence management system.
+        
+        This project not only enhanced resource management at the college but also introduced modern technologies such as face recognition and AI-driven chatbots, setting a foundation for future advancements in academic institution management systems. 
+        • Devised robust user authentication and 2-FS password authentication, enhancing system security and reliability.
+        • Led the project team, developing comprehensive Django templates, seamlessly integrating custom chatbot functionalities 
+        using LLM and created a one short face recognition for attendance management system .
+    ```
+    ## Document and Data Query AI Agent - Individual project [Llama3 | Ollama | LlamaIndex]
+    ```
+        Created a sophisticated AI agent for document-based Q&A and CSV data visualization, utilizing Llama3 and Ollama for cuttingedge natural language processing. Integrated Llama Indexing for efficient data retrieval and robust document parsing within an 
+        intuitive user interface.
+        • Combined HuggingFace embedding generation and a resilient query retry mechanism, boosting data accuracy and system 
+        reliability.
+        • Demonstrated deep expertise in deep learning and real-time data processing, significantly improving system performance 
+        and user experience.
+    ```
+    ## Personal Portfolio - Individual project [HTML | CSS | JS]:
+    ```
+        Designed and developed a responsive personal portfolio("LINK:https://21bq1a4210.github.io/MyPortfolio-/") website using HTML, CSS, and JavaScript, showcasing strong UI/UX principles. Deployed the website online using GitHub Pages, making it accessible for users worldwide. The website features multiple sections, including Home, About, Services, Portfolio, and Contact, providing a comprehensive overview of my skills and projects. Implemented interactive elements like a contact form integrated with EmailJS for seamless communication and added an AI chatbot, Tidio's Lyro, to enhance user engagement and provide additional information about me. Crafted unique visuals using AI-generated images to personalize the portfolio and demonstrate creativity. This project ignited my interest in web development, transforming initial reluctance into enthusiasm for building dynamic and interactive web experiences.
+    ```
+    ## OBJECT SEGMENTATION - Individual project [yoloV8, RoboFlow]:
+    ```
+        Built a versatile Python script using OpenCV and scikit image for image processing tasks.like object segmentation, using YoloV8, OpenCV, sklearn. Implemented functionalities like grayscale contrast nhancement, image similarity measurement (SSIM), and object segmentation YOLOv8 Demonstrated the script s capabilities through image processing, evaluation, and visualization. Planned to explore integration of advanced deep learning models for further functionalities.
+        Here is the ("notebook link: Object_Segmentation_&_ComparisonObject_Segmentation_&_Comparison.ipynb:https://colab.research.google.com/drive/1cpNEx_u70I26Ex0alZZxoFa47p6fpoDz?usp=sharing")
+    ```
+```
+
+#CERTIFICATION:
+```
+    ➢ Python Programming : Kaggle, SoloLearn, HackerRank, GUVI.
+    ➢ Machine Learning : Coursera, Kaggle, Microsoft, IBM
+    ➢ Deep Learning : Kaggle, NPTEL, OpenCVUniversity, IBM.
+    ➢ Google Skill Boost(profile) : Introduction to Gen AI LP, Gemini for Google Cloud LP, Gen AI for Developers Learning Paths.
+    ➢ Django : Microsoft
+    ➢ AWS : AWS Academy Cloud Foundations, AWS Academy Cloud Architecting
+    ➢ NPTEL (exam) : Java (ELITE), Data Science (ELITE + SILVER)
+```
+#ACHIEVEMENTS:
+```
+    Secure runner up in a Python Intramural technical fest at RVR&JC college (LINK)
+```
+# Contact me or Hire me:
+```
+    To dowlode my resume open Files in the resume. There you can find my email and other info.
+```
 '''
 
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
@@ -19,7 +123,7 @@ def respond(
     # System message defining assistant behavior
     system_message = {
         "role": "system",
-        "content": f"Act and chat as a professional fresher seeking a job and your name is SARATH. Here is about you: {data}. You should answer questions based on this information only."
+        "content": f"Act and chat as SARATH who is a professional fresher seeking a job and your name is SARATH. Here is about you(SARATH): {data}. You should answer questions based on this information only."
     }
 
     messages = [system_message]