HackStack

Project Info

WeHeal

Devpost

Inspiration

Our inspiration for WeHeal stemmed from a deep-seated desire to revolutionize the counseling and therapy landscape, aiming to enhance both efficiency and effectiveness. Recognizing the challenge faced by counselors and therapists in managing extensive patient case files while striving to deliver personalized care, we embarked on a journey to create a solution. Consider a scenario where a counselor, with a packed schedule of five patients per day across four days a week, grapples with recalling every detail of a patient's conversation, especially as sessions progress. We sought to bridge this gap by developing a tool that seamlessly integrates with practitioners' workflows, empowering them to provide unparalleled support and care to their clients, regardless of session volume or complexity.

What it does

WeHeal serves as an invaluable AI assistant powered by LangChain to counselors and therapists, streamlining their workflow by efficiently summarizing patient case files and providing tailored recommendations derived from both past and ongoing interactions. Our platform enhances the effectiveness and efficiency of counseling sessions, while keeping the past context to ultimately empower professionals to better support their clients on their journey towards healing and growth.

How we built it

---The project is divided mainly into three parts: Agents powered by Intel's "Prediction Guard" LLM models: to store user data into vector database, contextuatize the user data. The chat history is stored in a Momento DB cache. Agents support the core logic of our application, including summarization of user details based on PDF case data and to provide tailored suggestions to the counselors. Frontend: Built in ReactJS uses the APIs exposed by the backend to showcase how the power of our AI companion. It uses "Canva.dev" for few components. API Backend: Built with flask to bridge the gap between the Agent and the Frontend. ---The deployment is done using "Vercel", as shown in the Demo. ---We built WeHeal using a combination of programming languages and technologies, including Python for backend development, React for the frontend, and various APIs for data analysis and natural language processing. We also utilized cloud services for hosting and deployment.

Challenges we ran into

None of us knew how to do front end development so, we had to learn and deploy at the same time, Canva.dev was a huge help for us in this challenge. Another issue that we faced was LanceDB, which is apparently new to the market with limited community support. Majority issues were faced with LLM chaining together to provide context with chat history and user details. Integrating different components together was also a challenge towards the end.

Accomplishments we're proud of

We ar proud of our idea which could a game-changer for the superheroes who are the counselors helping patients fight mental health issues. We're proud to have successfully developed a functional end to end prototype of WeHeal within the timeframe of the hackathon. This prototype can succesfully be used to demonstrate the power of our LLM agents. Our platform demonstrates the potential to significantly improve the workflow of counselors and therapists, ultimately benefiting both professionals and their clients.

What we learned

Through the process of building WeHeal, we gained valuable experience in full stack web development, RAG, VectorDB, Langchain, and many more technologies that were completely new to us. We also learnt the existence of amazing companies oproviding amazing solutions, some of which we integrated in our application. This includes Intel's Prediction Guard, Canva.dev components, and deployments via VercelW

What's next

Looking ahead, our vision for WeHeal involves a comprehensive evolution aimed at empowering users on their mental wellness journey. We're committed to refining and enhancing the platform to offer a personalized space where individuals can seamlessly upload their daily thoughts. Leveraging advanced algorithms and user data, WeHeal will then intelligently suggest affirmations and curated meditation resources tailored to each user's unique needs and emotional state. Moreover, we're exploring innovative solutions such as blockchain technology to securely store patient case files. This ensures that individuals can seamlessly transition between therapists or counselors without any loss of crucial information. By implementing blockchain, we guarantee the integrity and accessibility of patient records, enabling new practitioners to gain comprehensive insights through smart summaries, thus fostering continuity of care and empowering individuals to receive the support they need, wherever they may be.

Analysis

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Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • FlaskIn code
  • HTMLIn code
  • LangChainIn code
  • LlamaIndexIn code
  • PythonIn code
  • ReactIn code
  • TypeScriptIn code

8 of 8 appear in the indexed code.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

34 KB

Source files

13

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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