app.py

from fastapi import FastAPI, Request, Query
from fastapi.templating import Jinja2Templates
from fastapi import File, UploadFile
from fastapi.responses import FileResponse
from fastapi.responses import Response

from pydantic import BaseModel
from sentence_transformers import SentenceTransformer
import faiss
import numpy as np
import json
import io

app = FastAPI()
model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
embedding_dimension = 384 # 384 is the dimensionality of the MiniLM model
index = faiss.IndexFlatL2(embedding_dimension)  
documents = []

templates = Jinja2Templates(directory=".")

class EmbedRequest(BaseModel):
    texts: list[str]

class SearchRequest(BaseModel):
    text: str
    n: int = 5
    
@app.get("/")
def read_root(request: Request):
    return templates.TemplateResponse("index.html", {"request": request})


@app.post("/embed")
def embed_strings(request: EmbedRequest):
    new_documents = request.texts
    new_embeddings = model.encode(new_documents)
    index.add(np.array(new_embeddings))
    new_size = index.ntotal
    documents.extend(new_documents)
    return {
        "message": f"{len(new_documents)} new strings embedded and added to FAISS database. New size of the database: {new_size}"
    }


@app.post("/search")
def search_string(request: SearchRequest):
    embedding = model.encode([request.text])
    distances, indices = index.search(np.array(embedding), request.n)

    # Get the documents associated with the returned indices
    found_documents = [documents[i] for i in indices[0]]

    return {
        "distances": distances[0].tolist(),
        "indices": indices[0].tolist(),
        "documents": found_documents
    }

#########################
## database management ##
#########################
@app.get("/admin/database/length")
def get_database_length():
    return {"length": index.ntotal}

@app.post("/admin/database/reset")
def reset_database():
    global index
    global documents
    index = faiss.IndexFlatL2(embedding_dimension)
    documents = []
    return {"message": "Database reset"}

@app.get("/admin/documents/download")
def download_documents():
    # Convert the documents list to a JSON string
    documents_json = json.dumps({"texts": documents})

    # Create a response with the JSON string as the content
    response = Response(content=documents_json, media_type="application/json")

    # Set the content disposition header to trigger a download
    response.headers["Content-Disposition"] = "attachment; filename=documents.json"

    return response

##### TESTING ######
@app.post("/admin/documents/upload")
def upload_documents(request: EmbedRequest):
    documents.extend(request.texts)
    return {
        "message": f"{len(documents)} new documents uploaded"
    }

@app.get("/admin/database/download")
def download_database():
    # Save the FAISS index and documents list to a single file
    data = {
        "index": faiss.write_index_binary(index),
        "documents": documents
    }
    with open("database.json", "w") as f:
        json.dump(data, f)

    # Create a response with the database file as the content
    response = FileResponse("database.json")

    # Set the content disposition header to trigger a download
    response.headers["Content-Disposition"] = "attachment; filename=database.json"

    return response

@app.post("/admin/database/upload")
def upload_database(file: UploadFile = File(...)):
    # Read the contents of the uploaded file
    contents = json.load(file.file)

    # Load the FAISS index from the file contents
    index = faiss.read_index_binary(contents["index"])

    # Load the documents list from the file contents
    documents.clear()
    documents.extend(contents["documents"])

    return {"message": "Database uploaded", "documents": documents}