Task completed

Rohit C/Internship request letter.txt

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+I am writing to express my interest in the LLM internship opportunity at Hardpoint Consulting, as mentioned in regards to the International Hackathon 2024. With a strong academic background and a passion for AI, LLM and Web Development, I am eager to contribute to your esteemed organization and further develop my skills in any area required.
+
+I have been honing my knowledge in using LLM integrated with Python frameworks. Through my projects and hackathons, I have developed a keen understanding of LLM training, which I am eager to apply in a professional setting.
+
+During my internship, I am keen to immerse myself in any task assigned, with the goal of gaining practical experience and contributing to the success of your team. I am particularly drawn to the vision of this organization and am excited about this opportunity.
+
+In the short term, my one-year goal is to gain as much novel experiences as possible. Over the next three years, I aim to venture into integrating AI and LLMs into day-to-day uses of people. Looking further ahead, my five-year goal is to lead a team of passionate developers to conquer every corner of AI and to develop versions competing even today's tech giants.
+
+Thank you for considering my application. I am excited about the opportunity to contribute to Hardpoint Consulting and look forward to the possibility of discussing how my skills and experience align with your internship program.
+
+Sincerely,
+
+Rohit C.

Rohit C/XTRKT/.env

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+SECRET_KEY = #Your Django secret key
+ENGINE = #Your database engine
+NAME = #Your database name
+USER = #Your database username
+PASSWORD = #Your database password
+HOST = #Your database host name
+PORT = #Your database port number
+API_SECRET = #Your convertapi secret key
+API_KEY = #Your gemini api secret key

Rohit C/XTRKT/README.md

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+# XTRKT
+
+## Work Flow
+
+The landing page of the website is given below. It contains a brief description of the project and also gives the user the option to upload a folder containing the dataset to be processed.
+
+<img src="images/home.png" alt="Home Page" width="500" height="250">
+
+The upload button gives the user the option to choose the specified pdf containing the data as depicted below.
+
+<img src="images/upload.png" alt="Home Page" width="500" height="250">
+
+The processing of the dataset takes place inside the upload() function in the views.py file within the task folder of the project.
+The images are parsed one by one and passed to the OCR module of the project and the text extracted by it to the Gemini API via prompts.
+LLM returns the data that need to be generated related to the content provided.
+These values are then stored in the Output table of the database.
+
+<img src="images/database.png" alt="Database" width="500" height="250">
+
+Further on this data is integrated into the frontend to display the output in the specified format to the users where they can edit it accordingly.
+
+<img src="images/extract.png" alt="Extract" width="500" height="250">
+
+Now the users can either trash the extracts or continue to enter their research.
+
+<img src="images/research.png" alt="Research" width="500" height="250">
+
+The users now obtain an additional view of the extracted data along with its relation to their research.
+
+<img src="images/additional.png" alt="Research" width="500" height="250">
+
+The users can now choose to save the data permanently or trash it entirely.
+
+<img src="images/store.png" alt="Research" width="500" height="250">
+
+The user is also provided with an option to create an Excel sheet format of the output being displayed by the click of a button.
+
+<img src="images/create.png" alt="Create" width="500" height="250">
+
+The excel sheet is created in the excel folder within the media directory of the project.
+The user now gets the option to download the excel file onto his/her local system.
+
+<img src="images/download.png" alt="Download" width="500" height="250">
+
+The downloaded .xlsx file can be viewed on any excel sheet view supported platforms.
+
+<img src="images/excel.png" alt="Excel" width="500" height="250">
+
+The users can also view all the data saved so far by clicking the 'View saved data' button on the home page.
+
+<img src="images/saved.png" alt="Research" width="500" height="250">
+
+Thus XTRKT brings forth a seamless integration of AI, Prompt engineering, Web development and Database management to provide the user with the best results for a variety of datasets.
+
+## Technology Stack
+- The project the built using the Django Model-View-Template(MVT) Architecture for full stack web development.
+- Tesseract module is being used for text detection from images.
+- Google Gemini 1.0 Pro API is used for prompting.
+- A local MySQL database is used to store the data extracted through prompts.
+
+## Where to Look
+
+- Refer the 'views.py' file in the task folder to get a well documented code of the backend.
+- Refer the 'templates' folder to see the HTML pages developed for this project.
+- Refer the 'media' folder to view sample dataset and the excel sheet generated for it.
+- Refer the '.env' file to know the list of environment variables and API keys required to run this code.
+- Install the requirements.txt using the command 'pip install -r requirements.txt'.
+- Run the project using the command 'py manage.py runserver'
+
+Regards,
+
+Rohit C.