EduConnect / requirements.txt
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Implemented LLM model and wired it to APIs
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fastapi==0.95.2 # Core framework for building APIs.
uvicorn[standard]==0.18.3 # ASGI server for FastAPI, supports live reloading.
requests==2.28.* # For making HTTP requests, if needed by our app.
torch==1.11.* # PyTorch, for handling deep learning models.
sentencepiece==0.1.* # For chat text processing
mtcnn==0.1.1 # For face detection in images.
python-jose[cryptography]==3.3.* # For creating, parsing, and verifying JWT tokens.
python-multipart==0.0.5 # Necessary for form data handling, including file uploads.
numpy==1.23.0 # Updated to resolve conflict
chromadb==0.4.22 # Vector database interaction libraries.
keras-facenet==0.3.2 # For face recognition and embedding, used alongside MTCNN.
jinja2==3.0.* # For Admin site redndering
bcrypt==4.1.* # For hashing secrets
opencv-python-headless==4.5.5.* # For image handling images
tensorflow # Tensorflow is needed by MTCNN for facial recognition
scipy # The scipy is required for keras-facenet
tinydb # The in memory database for storing JWT tokens
langchain # Langgchain for RAG
llama-cpp-python # To load the model
sentence-transformers # For text embeddings
pypdf # Handling PDF files