Notes

Write a note in this area. It's really easy to share with others. Click here ...from fastapi import FastAPI
from pydantic import BaseModel
from vector_store import get_relevant_text, create_vector_store
from llm_processing import query_llm
from generation.generate_slides import generate_pptx
from generation.generate_quiz import generate_quiz
from generation.generate_study_guide import generate_study_guide

app = FastAPI()

# Initialize the Vector DB
vector_db = create_vector_store()

# Request Model
class GenerateRequest(BaseModel):
material_type: str
textbook: str
chapter: str
custom_notes: str = ""

# Different prompts for each material type
def get_prompt(material_type, textbook, chapter, custom_notes):
if material_type.lower() == "powerpoint slides":
return f"""
Generate an educational PowerPoint slide deck for the textbook '{textbook}', Chapter: '{chapter}'.
- Each slide should contain concise bullet points summarizing key concepts.
- Ensure an easy-to-understand format, using simple language.
- {custom_notes if custom_notes else ''}
"""

elif material_type.lower() == "quiz/test":
return f"""
Create a quiz for the textbook '{textbook}', Chapter: '{chapter}'.
- Generate 5-10 multiple-choice and short-answer questions.
- Include answer keys at the end.
- Questions should cover all major concepts.
- {custom_notes if custom_notes else ''}
"""

elif material_type.lower() == "study guide":
return f"""
Generate a detailed study guide for the textbook '{textbook}', Chapter: '{chapter}'.
- Summarize key topics with explanations.
- Include important definitions and examples.
- Format the content in an easy-to-read way.
- {custom_notes if custom_notes else ''}
"""

else:
return None

@app.post("/generate/")
async def generate_material(request: GenerateRequest):
prompt = get_prompt(request.material_type, request.textbook, request.chapter, request.custom_notes)
if not prompt:
return {"error": "Invalid material type"}

relevant_texts = get_relevant_text(prompt)
combined_text = " ".join(relevant_texts)

# Generate content using LLM
generated_content = query_llm(combined_text)

# Select appropriate generation method
if request.material_type.lower() == "powerpoint slides":
filename = generate_pptx(generated_content)
elif request.material_type.lower() == "quiz/test":
filename = generate_quiz(generated_content)
elif request.material_type.lower() == "study guide":
filename = generate_study_guide(generated_content)
else:
return {"error": "Invalid material type"}

return {"message": "Material generated successfully", "file": filename}

@app.get("/")
async def root():
return {"message": "WisTech AI Teaching Assistant is running!"}