https://github.com/vikassrini/physicianai-chatbot
Real Time Physician Chatbot
https://github.com/vikassrini/physicianai-chatbot
blender fastapi llm rag readyplayerme
Last synced: 3 months ago
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Real Time Physician Chatbot
- Host: GitHub
- URL: https://github.com/vikassrini/physicianai-chatbot
- Owner: vikassrini
- Created: 2024-10-26T12:42:30.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-17T03:10:20.000Z (over 1 year ago)
- Last Synced: 2025-02-17T03:30:30.917Z (over 1 year ago)
- Topics: blender, fastapi, llm, rag, readyplayerme
- Language: Python
- Homepage:
- Size: 4.39 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# RealTime Physician Chatbot
The user can ask any health realted question to the chatbot. The user may upload pdf's of his helath report to ask questions based on them as well. Please pass only 1 pdf per session and if the first question is not answered proprly please try again before closing the application.
## Demo of my chatbot working.
https://github.com/user-attachments/assets/9d0f6dc8-ebfe-4135-bd94-2031fa970dc0
## Steps to run the bot
1. **Clone the Repository:**
```
git clone https://github.com/vikassrini/Chatbot.git
cd Chatbot
```
2. **Set Up a Virtual Environment (Optional but Recommended):**
```
# For macOS and Linux:
python3 -m venv venv
# For Windows:
python -m venv venv
```
3. **Activate the Virtual Environment:**
```
# For macOS and Linux:
source venv/bin/activate
# For Windows:
.\venv\Scripts\activate
```
4. **Install Required Dependencies:**
```pip install -r requirements.txt```
5. **Set up the Environment Variables:**
Create .toml file
```
touch keys.toml
```
You can get your OpenAI API key from here - [Link to get OpenAI API key](https://openai.com/blog/openai-api)
```
# add the following API key
[api_keys]
service_1_key =
```
6. **Setup MongoDB:(optional)**
[Download MongoDB from here](https://www.mongodb.com/try/download/community-kubernetes-operator)
Connect to the database using the connection string.
7. **Setup Weaviate:**
Run a local instance of Weavitate:
Install docker on your machine , do this following this [Installation Guide](https://docs.docker.com/get-started/get-docker/).
Run the following command to start weavite
```
docker compose up
```
8. **Run the application using the command:**
```
uvicorn chatapp:app --reload
```