diff --git a/.gitignore b/.gitignore index 68abc31f88898956e502eb545a6bf6a3582b8cdc..6afe32eeeddf230431874e59f2e8ed5f62b85d48 100644 --- a/.gitignore +++ b/.gitignore @@ -2,4 +2,7 @@ Api/venv # Other versions -Api/out1 \ No newline at end of file +Api/out1 + +# env +.env diff --git a/Api/app/__pycache__/main.cpython-310.pyc b/Api/app/__pycache__/main.cpython-310.pyc index ba25eb501de232fe0a43d20ef786c69573539f21..e2d7c1d15d8f611b4f21cb5fe566684ec2446785 100644 Binary files a/Api/app/__pycache__/main.cpython-310.pyc and b/Api/app/__pycache__/main.cpython-310.pyc differ diff --git a/Api/app/__pycache__/qdrant.cpython-310.pyc b/Api/app/__pycache__/qdrant.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..900a1406c4346024e4f0857df9090ac9be3edc11 Binary files /dev/null and b/Api/app/__pycache__/qdrant.cpython-310.pyc differ diff --git a/Api/app/db_local_storage/__pycache__/documents_db.cpython-310.pyc b/Api/app/db_local_storage/__pycache__/documents_db.cpython-310.pyc index 3dc35a18dcc934f655607bd493c8ba415cdbaca7..7408c06697208468a2cd498aee96189156f38d0a 100644 Binary files a/Api/app/db_local_storage/__pycache__/documents_db.cpython-310.pyc and b/Api/app/db_local_storage/__pycache__/documents_db.cpython-310.pyc differ diff --git a/Api/app/db_local_storage/__pycache__/vector_files_db.cpython-310.pyc b/Api/app/db_local_storage/__pycache__/vector_files_db.cpython-310.pyc index b2d1179bee0cb4deb151eab2d2e1dae7be4c2ee5..45509459d58337bd57af025deea133031bcc94da 100644 Binary files a/Api/app/db_local_storage/__pycache__/vector_files_db.cpython-310.pyc and b/Api/app/db_local_storage/__pycache__/vector_files_db.cpython-310.pyc differ diff --git a/Api/app/db_local_storage/documents_db.py b/Api/app/db_local_storage/documents_db.py deleted file mode 100644 index f6408267be24b79fbcc99a6ba9c77f291f8a2096..0000000000000000000000000000000000000000 --- a/Api/app/db_local_storage/documents_db.py +++ /dev/null @@ -1,2 +0,0 @@ -documents_db = [] -documents_text = [] \ No newline at end of file diff --git a/Api/app/db_local_storage/files_db.py b/Api/app/db_local_storage/files_db.py deleted file mode 100644 index 0e048f8b321efdc783ae365e6720ad1a6bd934ee..0000000000000000000000000000000000000000 --- a/Api/app/db_local_storage/files_db.py +++ /dev/null @@ -1,4 +0,0 @@ -FILES_NAMES_DATABASE = {} -FILES_DIRECTORY = "src/db_local_storage/files" -TEXT_FILES_DIRECTORY = "src/db_local_storage/text_files" -VECTOR_FILES_DIRECTORY = "src/db_local_storage/vector_files/vec_db.json" diff --git a/Api/app/db_local_storage/vector_files_db.py b/Api/app/db_local_storage/vector_files_db.py deleted file mode 100644 index e8b5ab3301961fb4514e272975c55699d58a1f8a..0000000000000000000000000000000000000000 --- a/Api/app/db_local_storage/vector_files_db.py +++ /dev/null @@ -1 +0,0 @@ -vector_files_db = {} \ No newline at end of file diff --git a/Api/app/infrastructure/models/__pycache__/my_models.cpython-310.pyc b/Api/app/infrastructure/models/__pycache__/my_models.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..23d049c10388b62f0c53872154b0f2f963d79ab5 Binary files /dev/null and b/Api/app/infrastructure/models/__pycache__/my_models.cpython-310.pyc differ diff --git a/Api/app/infrastructure/models/my_models.py b/Api/app/infrastructure/models/my_models.py new file mode 100644 index 0000000000000000000000000000000000000000..3128a7d0d7152856602037a81c21dab6eaffa267 --- /dev/null +++ b/Api/app/infrastructure/models/my_models.py @@ -0,0 +1,28 @@ +from pydantic import BaseModel +from typing import Dict, List, Optional + + +class ModelResponse(BaseModel, extra="forbid"): + text: str + isSender: bool + message: Optional[str] = None + + +class EmbeddingCreation(BaseModel, extra="forbid"): + success: bool + message: Optional[str] = None + + +class HybridSearchResponse(BaseModel): + success: bool + data: Optional[List[Dict]] = None + message: Optional[str] = None + + +class Chunk(BaseModel): + index: int + text: str + + +class ChunksResponse(BaseModel): + data: Dict[str, List[Chunk]] diff --git a/Api/app/infrastructure/repository/__pycache__/document_handeler_repository.cpython-310.pyc b/Api/app/infrastructure/repository/__pycache__/document_handeler_repository.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..2cb67bc99b4495f03e2bdede37e8c11922525e90 Binary files /dev/null and b/Api/app/infrastructure/repository/__pycache__/document_handeler_repository.cpython-310.pyc differ diff --git a/Api/app/infrastructure/repository/__pycache__/query_search_repository.cpython-310.pyc b/Api/app/infrastructure/repository/__pycache__/query_search_repository.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..915d7aa4016a95229e7411871c1bbc84cd346205 Binary files /dev/null and b/Api/app/infrastructure/repository/__pycache__/query_search_repository.cpython-310.pyc differ diff --git a/Api/app/infrastructure/repository/__pycache__/updateDocument_repository.cpython-310.pyc b/Api/app/infrastructure/repository/__pycache__/updateDocument_repository.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..6e1885ce454d137bdb4f39a256726bf15dd3a3fe Binary files /dev/null and b/Api/app/infrastructure/repository/__pycache__/updateDocument_repository.cpython-310.pyc differ diff --git a/Api/app/infrastructure/repository/document_handeler_repository.py b/Api/app/infrastructure/repository/document_handeler_repository.py new file mode 100644 index 0000000000000000000000000000000000000000..577c5b8052e8ed1c687d048c682703daceec3f80 --- /dev/null +++ b/Api/app/infrastructure/repository/document_handeler_repository.py @@ -0,0 +1,48 @@ +from typing import Any, List, Tuple +from app.qdrant import QdrantConnectionDb +from qdrant_client import models + + +class DocumentHandelerRepository: + def __init__(self, qdrant_connection_db: QdrantConnectionDb): + self.client = qdrant_connection_db.get_client() + self.collection_name = qdrant_connection_db.get_collection_name() + + def find_points_by_document_name(self, document_name) -> List[int]: + result = self.client.scroll( + collection_name=self.collection_name, + scroll_filter=models.Filter( + must=[ + models.FieldCondition( + key="document_id", match=models.MatchValue(value=document_name) + ) + ] + ), + ) + + if result[0]: + return [point.id for point in result[0]] + + return + + def delete_document_by_id(self, documents_id: List[int]) -> None: + return self.client.delete( + collection_name=self.collection_name, + points_selector=models.PointIdsList(points=documents_id), + ) + + def insert_points(self, points: List[models.PointStruct]) -> models.UpdateResult: + return self.client.upsert( + collection_name=self.collection_name, + wait=True, + points=points, + ) + + def get_all_documents( + self, + ) -> Tuple[List[models.Record], Any]: # models.ScrollResult + return self.client.scroll( + collection_name=self.collection_name, + with_payload=True, + with_vectors=False, + ) diff --git a/Api/app/infrastructure/repository/query_search_repository.py b/Api/app/infrastructure/repository/query_search_repository.py new file mode 100644 index 0000000000000000000000000000000000000000..69630dcecd379129b4d977b5ef15cf2d0bad8b95 --- /dev/null +++ b/Api/app/infrastructure/repository/query_search_repository.py @@ -0,0 +1,20 @@ +from app.qdrant import QdrantConnectionDb +from qdrant_client.models import QueryResponse, Prefetch, NamedVector + + +class QuerySearchRepository: + def __init__(self, qdrant_connection_db: QdrantConnectionDb): + self.client = qdrant_connection_db.get_client() + self.collection_name = qdrant_connection_db.get_collection_name() + + def find_text_by_hybrid_search( + self, prefetch_context: Prefetch, dense_vector: NamedVector + ) -> QueryResponse: + return self.client.query_points( + collection_name=self.collection_name, + prefetch=prefetch_context, + query=dense_vector.vector, + using="text-dense", + with_payload=True, + limit=10, + ) diff --git a/Api/app/main.py b/Api/app/main.py index 555e825a6474220707b920b6b7dec169c8bedcc8..c664aa294b495156c12dd3ea7c90bb184b2639a5 100644 --- a/Api/app/main.py +++ b/Api/app/main.py @@ -1,22 +1,45 @@ import logging +from contextlib import asynccontextmanager import uvicorn from fastapi import APIRouter, FastAPI from fastapi.middleware.cors import CORSMiddleware from fastapi.responses import FileResponse from fastapi.staticfiles import StaticFiles +from transformers import AutoModel, AutoModelForMaskedLM, AutoTokenizer, pipeline + +from app.modules.clearVariables.routes.clearVariables_route import \ + router as clear_variables_routes +from app.modules.documentHandeler.routes.document_handeler_route import \ + router as upload_file_routes +from app.modules.querySearch.routes.querySearch_route import \ + router as query_search_routes + + +@asynccontextmanager +async def lifespan(app: FastAPI): + dense_model_name = "sentence-transformers/all-MiniLM-L6-v2" + sparse_model_name = "prithivida/Splade_PP_en_v1" + qa_model_name = "deepset/roberta-base-squad2" + + dense_tokenizer = AutoTokenizer.from_pretrained(dense_model_name) + dense_model = AutoModel.from_pretrained(dense_model_name) + + sparse_tokenizer = AutoTokenizer.from_pretrained(sparse_model_name) + sparse_model = AutoModelForMaskedLM.from_pretrained(sparse_model_name) + + qa_pipeline = pipeline("question-answering", model=qa_model_name) + + yield { + "dense_tokenizer": dense_tokenizer, + "dense_model": dense_model, + "sparse_tokenizer": sparse_tokenizer, + "sparse_model": sparse_model, + "qa_pipeline": qa_pipeline, + } -from app.modules.querySearch.routes.querySearch_route import ( - router as query_search_routes, -) -from app.modules.uploadDocument.routes.uploadDocument_route import ( - router as upload_file_routes, -) -from app.modules.clearVariables.routes.clearVariables_route import ( - router as clear_variables_routes, -) -app = FastAPI() +app = FastAPI(lifespan=lifespan) origins = [ "http://localhost:8000", @@ -36,7 +59,7 @@ app.add_middleware( ) app_router = APIRouter(prefix="/api") -app_router.include_router(upload_file_routes, prefix="/upload", tags=["upload"]) +app_router.include_router(upload_file_routes, prefix="/document", tags=["document"]) app_router.include_router(query_search_routes, prefix="/query", tags=["query"]) app_router.include_router(clear_variables_routes, prefix="/clear", tags=["clear"]) diff --git a/Api/app/modules/__pycache__/model.cpython-310.pyc b/Api/app/modules/__pycache__/model.cpython-310.pyc index 351e1d57a7bcb4fedcb993917976a3c978d8aa10..d7c07cf7b57f672852f4f115424d27647f93f19e 100644 Binary files a/Api/app/modules/__pycache__/model.cpython-310.pyc and b/Api/app/modules/__pycache__/model.cpython-310.pyc differ diff --git a/Api/app/modules/clearVariables/routes/__pycache__/clearVariables_route.cpython-310.pyc b/Api/app/modules/clearVariables/routes/__pycache__/clearVariables_route.cpython-310.pyc index 0dd061dcd12b6f748fd2261f62371828637c6297..43f6b2ba83e9e6aef05817e61f1c5edded853437 100644 Binary files a/Api/app/modules/clearVariables/routes/__pycache__/clearVariables_route.cpython-310.pyc and b/Api/app/modules/clearVariables/routes/__pycache__/clearVariables_route.cpython-310.pyc differ diff --git a/Api/app/modules/clearVariables/routes/clearVariables_route.py b/Api/app/modules/clearVariables/routes/clearVariables_route.py index 2b205d5290577844f33ab205a8e0cb214df06996..653055779362951eeb6bfe2aa5cb789b2bea6de9 100644 --- a/Api/app/modules/clearVariables/routes/clearVariables_route.py +++ b/Api/app/modules/clearVariables/routes/clearVariables_route.py @@ -1,20 +1,12 @@ -from app.db_local_storage.documents_db import documents_db, documents_text from app.db_local_storage.in_memory_db import query_response_storage -from app.db_local_storage.vector_files_db import vector_files_db -from app.modules.uploadDocument.controllers.file_upload_controller import \ - FileUploadController -from fastapi import APIRouter, File, HTTPException, UploadFile +from fastapi import APIRouter from fastapi.responses import JSONResponse router = APIRouter() -fileUploadController = FileUploadController() + @router.delete("/clear_variables/") async def clear_variables(): - vector_files_db.clear() - documents_db.clear() query_response_storage.clear() - documents_db.clear() - documents_text.clear() - - return JSONResponse(status_code=200, content={"message": "All variables cleared"}) \ No newline at end of file + + return JSONResponse(status_code=200, content={"message": "All variables cleared"}) diff --git a/Api/app/modules/denseEmbeddings/__pycache__/denseEmbeddings.cpython-310.pyc b/Api/app/modules/denseEmbeddings/__pycache__/denseEmbeddings.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..6dc84b55e12678b9dfa4ba9dad0eb9bf68bc9e8a Binary files /dev/null and b/Api/app/modules/denseEmbeddings/__pycache__/denseEmbeddings.cpython-310.pyc differ diff --git a/Api/app/modules/denseEmbeddings/denseEmbeddings.py b/Api/app/modules/denseEmbeddings/denseEmbeddings.py new file mode 100644 index 0000000000000000000000000000000000000000..06612acf33c7bed98882f8bd0910686a144df0a5 --- /dev/null +++ b/Api/app/modules/denseEmbeddings/denseEmbeddings.py @@ -0,0 +1,69 @@ +import torch +from qdrant_client import models +from qdrant_client.models import NamedVector +from transformers import AutoModel, AutoModelForMaskedLM, AutoTokenizer + + +class DenseEmbeddings: + + def __init__( + self, + dense_model: AutoModel, + dense_tokenizer: AutoTokenizer, + sparse_model: AutoModelForMaskedLM, + sparse_tokenizer: AutoTokenizer, + ): + + self.dense_model = dense_model + self.dense_tokenizer = dense_tokenizer + self.sparse_model = sparse_model + self.sparse_tokenizer = sparse_tokenizer + + def get_dense_vector(self, text: str) -> NamedVector: + """ + Get dense vector from the dense model + + :param text: str + :return: NamedVector + """ + inputs = self.dense_tokenizer( + text, return_tensors="pt", padding=True, truncation=True + ) + with torch.no_grad(): + outputs = self.dense_model(**inputs) + + dense_vector = NamedVector( + name="text-dense", + vector=torch.mean(outputs.last_hidden_state, dim=1).squeeze().numpy(), + ) + return dense_vector + + def get_sparse_vector(self, text: str) -> models.SparseVector: + """ + Get sparse vector from the sparse model + + :param text: str + :return: SparseVector + """ + + inputs = self.sparse_tokenizer( + text, return_tensors="pt", padding=True, truncation=True + ) + with torch.no_grad(): + outputs = self.sparse_model(**inputs) + + token_scores = outputs.logits.squeeze().max(dim=0)[0] + token_ids = inputs["input_ids"].squeeze() + + sparse_vector = { + int(token_id): float(score) + for token_id, score in zip(token_ids, token_scores) + if score > -5.0 + } + + sparse_vector = models.SparseVector( + indices=list(sparse_vector.keys()), + values=list(sparse_vector.values()), + ) + + return sparse_vector diff --git a/Api/app/modules/uploadDocument/controllers/__pycache__/FileUploadController.cpython-310.pyc b/Api/app/modules/documentHandeler/controllers/__pycache__/FileUploadController.cpython-310.pyc similarity index 100% rename from Api/app/modules/uploadDocument/controllers/__pycache__/FileUploadController.cpython-310.pyc rename to Api/app/modules/documentHandeler/controllers/__pycache__/FileUploadController.cpython-310.pyc diff --git a/Api/app/modules/documentHandeler/controllers/__pycache__/document_handeler_controller.cpython-310.pyc b/Api/app/modules/documentHandeler/controllers/__pycache__/document_handeler_controller.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..37446ad72c03bc2530015316f76c82772084f309 Binary files /dev/null and b/Api/app/modules/documentHandeler/controllers/__pycache__/document_handeler_controller.cpython-310.pyc differ diff --git a/Api/app/modules/documentHandeler/controllers/__pycache__/file_upload_controller.cpython-310.pyc b/Api/app/modules/documentHandeler/controllers/__pycache__/file_upload_controller.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..2005e9ddcf23b731153c708268ab8eeaae335bbb Binary files /dev/null and b/Api/app/modules/documentHandeler/controllers/__pycache__/file_upload_controller.cpython-310.pyc differ diff --git a/Api/app/modules/documentHandeler/controllers/document_handeler_controller.py b/Api/app/modules/documentHandeler/controllers/document_handeler_controller.py new file mode 100644 index 0000000000000000000000000000000000000000..3130eebda52e4fff97cdc6573311b68b5580eafb --- /dev/null +++ b/Api/app/modules/documentHandeler/controllers/document_handeler_controller.py @@ -0,0 +1,66 @@ +from fastapi import HTTPException, UploadFile +from fastapi.responses import JSONResponse + +from app.infrastructure.repository.document_handeler_repository import ( + DocumentHandelerRepository, +) +from app.modules.documentHandeler.features.createEmbeddings_feature import ( + CreateEmbeddingsFeature, +) +from app.modules.documentHandeler.features.deleteDocument_feature import ( + DeleteDocumentFeature, +) +from app.modules.documentHandeler.features.extractText_feature import ExtractTextFeature +from app.modules.documentHandeler.features.getAllChunkedText_feature import ( + GetAllChunkedTextFeature, +) + + +class DocumentHandelerController: + + def __init__( + self, + delete_document_feature: DeleteDocumentFeature, + create_embeddings_feature: CreateEmbeddingsFeature, + get_all_chunked_text_feature: GetAllChunkedTextFeature, + ): + self.create_embeddings_feature = create_embeddings_feature + self.delete_document_feature = delete_document_feature + self.get_all_chunked_text_feature = get_all_chunked_text_feature + + async def handle_file_upload(self, file: UploadFile) -> JSONResponse: + try: + + text_file = await ExtractTextFeature.extract_text_from_pdf(file) + result = await self.create_embeddings_feature.create_embeddings( + text_file, file.filename + ) + + return JSONResponse(status_code=200, content=result.model_dump()) + + except Exception as e: + raise HTTPException(status_code=500, detail="Probelm on controller") + + async def delete_document(self, text: str) -> JSONResponse: + try: + result = await self.delete_document_feature.delete_document_by_filename( + text + ) + if result: + return JSONResponse( + status_code=200, content={"message": "Document deleted"} + ) + return JSONResponse( + status_code=404, content={"message": "Document not found"} + ) + + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + async def get_all_chunks(self) -> JSONResponse: + try: + result = await self.get_all_chunked_text_feature.get_all_chunked_text() + return JSONResponse(status_code=200, content=result.model_dump()) + + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) diff --git a/Api/app/modules/documentHandeler/dependencies/__pycache__/dependencies.cpython-310.pyc b/Api/app/modules/documentHandeler/dependencies/__pycache__/dependencies.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..82af19266a289c97ae64e39b498698318e868ce4 Binary files /dev/null and b/Api/app/modules/documentHandeler/dependencies/__pycache__/dependencies.cpython-310.pyc differ diff --git a/Api/app/modules/documentHandeler/dependencies/dependencies.py b/Api/app/modules/documentHandeler/dependencies/dependencies.py new file mode 100644 index 0000000000000000000000000000000000000000..5bb8505920654ea2a9acba5308a5131e6861a715 --- /dev/null +++ b/Api/app/modules/documentHandeler/dependencies/dependencies.py @@ -0,0 +1,112 @@ +from fastapi import Depends, Request +from transformers import AutoModel, AutoModelForMaskedLM, AutoTokenizer + +from app.infrastructure.repository.document_handeler_repository import ( + DocumentHandelerRepository, +) +from app.modules.denseEmbeddings.denseEmbeddings import DenseEmbeddings +from app.modules.documentHandeler.controllers.document_handeler_controller import ( + DocumentHandelerController, +) +from app.modules.documentHandeler.features.createEmbeddings_feature import ( + CreateEmbeddingsFeature, +) +from app.modules.documentHandeler.features.deleteDocument_feature import ( + DeleteDocumentFeature, +) +from app.modules.documentHandeler.features.getAllChunkedText_feature import ( + GetAllChunkedTextFeature, +) +from app.qdrant import QdrantConnectionDb + + +def get_qdrant_connection_db() -> QdrantConnectionDb: + return QdrantConnectionDb() + + +def get_document_handeler_repository( + qdrant_connection_db: QdrantConnectionDb = Depends(get_qdrant_connection_db), +): + return DocumentHandelerRepository(qdrant_connection_db) + + +def get_dense_model(request: Request) -> AutoModel: + return request.scope["state"]["dense_model"] + + +def get_sparse_model(request: Request) -> AutoModelForMaskedLM: + return request.scope["state"]["sparse_model"] + + +def get_dense_tokenizer(request: Request) -> AutoTokenizer: + return request.scope["state"]["dense_tokenizer"] + + +def get_sparse_tokenizer(request: Request) -> AutoTokenizer: + return request.scope["state"]["sparse_tokenizer"] + + +def get_dense_embeddings( + dense_model: AutoModel = Depends(get_dense_model), + dense_tokenizer: AutoTokenizer = Depends(get_dense_tokenizer), + sparse_model: AutoModelForMaskedLM = Depends(get_sparse_model), + sparse_tokenizer: AutoTokenizer = Depends(get_sparse_tokenizer), +): + return DenseEmbeddings( + dense_model=dense_model, + dense_tokenizer=dense_tokenizer, + sparse_model=sparse_model, + sparse_tokenizer=sparse_tokenizer, + ) + + +def get_all_chunked_text_feature( + document_handeler_repository: DocumentHandelerRepository = Depends( + get_document_handeler_repository + ), +): + return GetAllChunkedTextFeature(document_handeler_repository) + + +def get_create_embeddings_feature( + dense_embeddings: DenseEmbeddings = Depends(get_dense_embeddings), + document_handeler_repository: DocumentHandelerRepository = Depends( + get_document_handeler_repository + ), +): + return CreateEmbeddingsFeature(dense_embeddings, document_handeler_repository) + + +def get_delete_document_feature( + document_handeler_repository: DocumentHandelerRepository = Depends( + get_document_handeler_repository + ), +): + return DeleteDocumentFeature(document_handeler_repository) + + +def get_document_handeler_controller( + delete_document_feature: DeleteDocumentFeature = Depends( + get_delete_document_feature + ), + create_embeddings_feature: CreateEmbeddingsFeature = Depends( + get_create_embeddings_feature + ), + get_all_chunked_text_feature: GetAllChunkedTextFeature = Depends( + get_all_chunked_text_feature + ), +): + return DocumentHandelerController( + delete_document_feature=delete_document_feature, + create_embeddings_feature=create_embeddings_feature, + get_all_chunked_text_feature=get_all_chunked_text_feature, + ) + + +def get_create_embeddings_feature( + dense_embeddings: DenseEmbeddings = Depends(get_dense_embeddings), + document_handeler_repository: DocumentHandelerRepository = Depends( + get_document_handeler_repository + ), +): + return CreateEmbeddingsFeature(dense_embeddings, document_handeler_repository) diff --git a/Api/app/modules/documentHandeler/features/__pycache__/createEmbeddings_feature.cpython-310.pyc b/Api/app/modules/documentHandeler/features/__pycache__/createEmbeddings_feature.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..c349cf430a140f148aa26f7440f5b17f4401983b Binary files /dev/null and b/Api/app/modules/documentHandeler/features/__pycache__/createEmbeddings_feature.cpython-310.pyc differ diff --git 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0000000000000000000000000000000000000000..57b14fdd10b2f9b87b4d69e34d0ca04afd4d4fd2 --- /dev/null +++ b/Api/app/modules/documentHandeler/features/createEmbeddings_feature.py @@ -0,0 +1,69 @@ +from typing import List +import uuid + +from qdrant_client.models import PointStruct + +from app.infrastructure.models.my_models import EmbeddingCreation +from app.infrastructure.repository.document_handeler_repository import ( + DocumentHandelerRepository, +) +from app.modules.denseEmbeddings.denseEmbeddings import DenseEmbeddings + + +class CreateEmbeddingsFeature: + + def __init__( + self, + dense_embeddings: DenseEmbeddings, + document_handeler_repository: DocumentHandelerRepository, + ): + self.dense_embeddings = dense_embeddings + self.document_handeler_repository = document_handeler_repository + + def chunk_text(self, text: str, chunk_size: int = 512) -> List[str]: + """ + Chunk text into smaller pieces + + :param text: str + :param chunk_size: int + :return: List[str] + """ + chunks = [text[i : i + chunk_size] for i in range(0, len(text), chunk_size)] + return chunks + + async def create_embeddings(self, text: str, filename: str) -> EmbeddingCreation: + """ + Create embeddings for the text + + :param text: str + :param filename: str + :return: EmbeddingCreation + """ + + chunks = self.chunk_text(text) + + document_id = filename.split(".")[0] + + points = [ + PointStruct( + id=str(uuid.uuid4()), + vector={ + "text-dense": self.dense_embeddings.get_dense_vector(chunk).vector, + "text-sparse": self.dense_embeddings.get_sparse_vector(chunk), + }, + payload={ + "document_id": document_id, + "chunk_index": i, + "filename": filename, + "chunk-text": chunk, + }, + ) + for i, chunk in enumerate(chunks) + ] + + result = self.document_handeler_repository.insert_points(points) + if result.status: + return EmbeddingCreation( + success=True, message="Embeddings created successfully" + ) + return EmbeddingCreation(success=False, message="Embeddings creation failed") diff --git a/Api/app/modules/documentHandeler/features/deleteDocument_feature.py b/Api/app/modules/documentHandeler/features/deleteDocument_feature.py new file mode 100644 index 0000000000000000000000000000000000000000..ba7e1a589e304ac281ae6b1660dd616ae19f4bf9 --- /dev/null +++ b/Api/app/modules/documentHandeler/features/deleteDocument_feature.py @@ -0,0 +1,18 @@ +from app.infrastructure.repository.document_handeler_repository import ( + DocumentHandelerRepository, +) + + +class DeleteDocumentFeature: + + def __init__(self, update_document_repository: DocumentHandelerRepository): + self.update_document_repository = update_document_repository + + async def delete_document_by_filename(self, document_name: str) -> bool: + document = self.update_document_repository.find_points_by_document_name( + document_name + ) + if document is None: + return False + self.update_document_repository.delete_document_by_id(document) + return True diff --git a/Api/app/modules/documentHandeler/features/extractText_feature.py b/Api/app/modules/documentHandeler/features/extractText_feature.py new file mode 100644 index 0000000000000000000000000000000000000000..dc42fad5867f0b1d5bfea763b71d5c896e3cea59 --- /dev/null +++ b/Api/app/modules/documentHandeler/features/extractText_feature.py @@ -0,0 +1,19 @@ +import io +import os + +from fastapi import UploadFile +import pdfplumber + + +class ExtractTextFeature: + + @staticmethod + async def extract_text_from_pdf(file: UploadFile) -> str: + + content = await file.read() + with pdfplumber.open(io.BytesIO(content)) as pdf: + text = "" + for page in pdf.pages: + text += page.extract_text() + + return text diff --git a/Api/app/modules/documentHandeler/features/getAllChunkedText_feature.py b/Api/app/modules/documentHandeler/features/getAllChunkedText_feature.py new file mode 100644 index 0000000000000000000000000000000000000000..3c733a4b6352919ca4d4d4d8f233318a3d3e03c5 --- /dev/null +++ b/Api/app/modules/documentHandeler/features/getAllChunkedText_feature.py @@ -0,0 +1,32 @@ +from app.infrastructure.models.my_models import ChunksResponse +from app.infrastructure.repository.document_handeler_repository import ( + DocumentHandelerRepository, +) + + +class GetAllChunkedTextFeature: + def __init__(self, document_handeler_repository: DocumentHandelerRepository): + self.document_handeler_repository = document_handeler_repository + + async def get_all_chunked_text(self): + + qdrant_response = self.document_handeler_repository.get_all_documents() + + transformed_data = {} + + for document in qdrant_response[0]: + document_id = document.payload["document_id"] + chunk_index = document.payload["chunk_index"] + text = document.payload["chunk-text"] + + if document_id not in transformed_data: + transformed_data[document_id] = [] + + transformed_data[document_id].append({"index": chunk_index, "text": text}) + + for doc in transformed_data: + transformed_data[doc] = sorted( + transformed_data[doc], key=lambda x: x["index"] + ) + + return ChunksResponse(data=transformed_data) diff --git a/Api/app/modules/documentHandeler/features/uploadDocument_feature.py b/Api/app/modules/documentHandeler/features/uploadDocument_feature.py new file mode 100644 index 0000000000000000000000000000000000000000..3aa4c94d8a9798bbc4e6bb4546eb058f1fcdd7e5 --- /dev/null +++ b/Api/app/modules/documentHandeler/features/uploadDocument_feature.py @@ -0,0 +1,26 @@ +# import os +# from typing import Dict + +# from fastapi import UploadFile +# from app.db_local_storage.files_db import FILES_DIRECTORY, FILES_NAMES_DATABASE +# from app.db_local_storage.documents_db import documents_db + + +# class UploadDocumentFeature: + +# @staticmethod +# async def uploadFile(document: UploadFile) -> Dict[str, str]: +# """ +# Upload a file to the server +# :param document: the file to upload +# :return: a message to confirm the upload +# """ + +# data = { +# "id": len(documents_db) + 1, +# "filename": document.filename, +# } + +# documents_db.append(data) + +# return {"message": "Document Updated"} diff --git a/Api/app/modules/documentHandeler/routes/__pycache__/document_handeler_route.cpython-310.pyc b/Api/app/modules/documentHandeler/routes/__pycache__/document_handeler_route.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..5b7b07076c121e4a29ea894fe56a85b0c2890d58 Binary files /dev/null and b/Api/app/modules/documentHandeler/routes/__pycache__/document_handeler_route.cpython-310.pyc differ diff --git a/Api/app/modules/documentHandeler/routes/__pycache__/uploadDocument_route.cpython-310.pyc b/Api/app/modules/documentHandeler/routes/__pycache__/uploadDocument_route.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..c590a403fe17a2aaf1eb488e666906c5c66508f4 Binary files /dev/null and b/Api/app/modules/documentHandeler/routes/__pycache__/uploadDocument_route.cpython-310.pyc differ diff --git a/Api/app/modules/documentHandeler/routes/document_handeler_route.py b/Api/app/modules/documentHandeler/routes/document_handeler_route.py new file mode 100644 index 0000000000000000000000000000000000000000..b28740511640f75b27d80066ec57ed7cbfda1b9e --- /dev/null +++ b/Api/app/modules/documentHandeler/routes/document_handeler_route.py @@ -0,0 +1,31 @@ +from fastapi import APIRouter, Depends, File, UploadFile + +from app.modules.documentHandeler.controllers.document_handeler_controller import \ + DocumentHandelerController +from app.modules.documentHandeler.dependencies.dependencies import \ + get_document_handeler_controller + +router = APIRouter() + + +@router.get("/get_chunks") +async def get_all_documents( + controller: DocumentHandelerController = Depends(get_document_handeler_controller), +): + return await controller.get_all_chunks() + + +@router.delete("/delete_document/{filename}") +async def delete_document( + filename: str, + controller: DocumentHandelerController = Depends(get_document_handeler_controller), +): + return await controller.delete_document(filename) + + +@router.post("/upload_file") +async def upload_file( + file: UploadFile = File(...), + controller: DocumentHandelerController = Depends(get_document_handeler_controller), +): + return await controller.handle_file_upload(file) diff --git a/Api/app/modules/uploadDocument/schemas/uploadDocument_schema.py b/Api/app/modules/documentHandeler/schemas/uploadDocument_schema.py similarity index 100% rename from Api/app/modules/uploadDocument/schemas/uploadDocument_schema.py rename to Api/app/modules/documentHandeler/schemas/uploadDocument_schema.py diff --git a/Api/app/modules/hybridSearcher/__pycache__/hybridSearcher.cpython-310.pyc b/Api/app/modules/hybridSearcher/__pycache__/hybridSearcher.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..0e0d1602954736f7efeeac8f9ef211c036f0bdc7 Binary files /dev/null and b/Api/app/modules/hybridSearcher/__pycache__/hybridSearcher.cpython-310.pyc differ diff --git a/Api/app/modules/hybridSearcher/hybridSearcher.py b/Api/app/modules/hybridSearcher/hybridSearcher.py new file mode 100644 index 0000000000000000000000000000000000000000..361cef040959c4eeca458e9af55fe6f0a36a6fb6 --- /dev/null +++ b/Api/app/modules/hybridSearcher/hybridSearcher.py @@ -0,0 +1,71 @@ +from qdrant_client import models +from qdrant_client.conversions import common_types as types +from qdrant_client.models import NamedVector, SparseVector + +from app.infrastructure.models.my_models import HybridSearchResponse +from app.infrastructure.repository.query_search_repository import QuerySearchRepository +from app.modules.denseEmbeddings.denseEmbeddings import DenseEmbeddings +from app.qdrant import QdrantConnectionDb + + +class HybridSearcher: + + def __init__( + self, + dense_embeddings: DenseEmbeddings, + query_search_repository: QuerySearchRepository, + ): + self.dense_embeddings = dense_embeddings + self.query_search_repository = query_search_repository + + def sparse_dense_rrf_prefetch( + self, sparse_vector: SparseVector, dense_vector: NamedVector + ) -> models.Prefetch: + result = models.Prefetch( + prefetch=[ + models.Prefetch( + query=dense_vector.vector, + using="text-dense", + limit=10, + ), + models.Prefetch( + query=sparse_vector, + using="text-sparse", + limit=10, + ), + ], + query=models.FusionQuery( + fusion=models.Fusion.RRF, + ), + ) + + return result + + def hybrid_search(self, user_query: str) -> types.QueryResponse: + """ + Hybrid search + + :param user_query: str + :return: types.QueryResponse + """ + try: + sparse_vector = self.dense_embeddings.get_sparse_vector(user_query) + dense_vector = self.dense_embeddings.get_dense_vector(user_query) + + prefetch_context = self.sparse_dense_rrf_prefetch( + sparse_vector, dense_vector + ) + + result = self.query_search_repository.find_text_by_hybrid_search( + prefetch_context, dense_vector + ) + + response_data = [ + {"chunk-text": point.payload["chunk-text"]} for point in result.points + ] + return HybridSearchResponse(success=True, data=response_data) + + except Exception as e: + return HybridSearchResponse( + success=False, message=f"Database operation failed: {str(e)}" + ) diff --git a/Api/app/modules/model.py b/Api/app/modules/model.py deleted file mode 100644 index bb0bd4993c02a5be2cadc691f31e963c05c9ea98..0000000000000000000000000000000000000000 --- a/Api/app/modules/model.py +++ /dev/null @@ -1,6 +0,0 @@ -from sentence_transformers import SentenceTransformer -from transformers import pipeline - - -model = SentenceTransformer("paraphrase-MiniLM-L6-v2") -qa_pipeline = pipeline("question-answering", model="deepset/roberta-base-squad2") diff --git a/Api/app/modules/querySearch/__pycache__/dependecies.cpython-310.pyc b/Api/app/modules/querySearch/__pycache__/dependecies.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..2743aa14325d39fe280b117af36a3e456df00e07 Binary files /dev/null and b/Api/app/modules/querySearch/__pycache__/dependecies.cpython-310.pyc differ diff --git a/Api/app/modules/querySearch/controllers/__pycache__/querySearch_controller.cpython-310.pyc b/Api/app/modules/querySearch/controllers/__pycache__/querySearch_controller.cpython-310.pyc index 8956047ae70b03aa6682b5f88a8e0e776a417545..0bcb6222020dae6d1dfaf7b885767e0993ae6f88 100644 Binary files a/Api/app/modules/querySearch/controllers/__pycache__/querySearch_controller.cpython-310.pyc and b/Api/app/modules/querySearch/controllers/__pycache__/querySearch_controller.cpython-310.pyc differ diff --git a/Api/app/modules/querySearch/controllers/querySearch_controller.py b/Api/app/modules/querySearch/controllers/querySearch_controller.py index 041242cd8d80f34a077880e5d0c5a35a2cf3e310..4856936f520d85ba43a9e0c459c6b9ab5fc4249d 100644 --- a/Api/app/modules/querySearch/controllers/querySearch_controller.py +++ b/Api/app/modules/querySearch/controllers/querySearch_controller.py @@ -1,4 +1,3 @@ -from typing import Any from fastapi import HTTPException from fastapi.responses import JSONResponse @@ -10,13 +9,12 @@ class QuerySearchController: def __init__(self, query_search_feature: QuerySearchFeature): self.query_search_feature = query_search_feature - async def handle_query_search(self, q: str) -> Any: + async def handle_query_search(self, query: str) -> JSONResponse: try: - result = await self.query_search_feature.query_search(q) - message = result.get("message", "No message provided") + result = await self.query_search_feature.query_search(query) - return JSONResponse(status_code=200, content={"message": message}) + return JSONResponse(status_code=200, content=result.model_dump()) except Exception as e: raise HTTPException(status_code=500, detail=str(e)) diff --git a/Api/app/modules/querySearch/dependecies.py b/Api/app/modules/querySearch/dependecies.py new file mode 100644 index 0000000000000000000000000000000000000000..3978a08f3825404624e789d3bde1fe6043e50f0d --- /dev/null +++ b/Api/app/modules/querySearch/dependecies.py @@ -0,0 +1,85 @@ +from fastapi import Depends, Request +from transformers import (AutoModel, AutoModelForMaskedLM, AutoTokenizer, + pipeline) + +from app.infrastructure.repository.query_search_repository import \ + QuerySearchRepository +from app.modules.denseEmbeddings.denseEmbeddings import DenseEmbeddings +from app.modules.hybridSearcher.hybridSearcher import HybridSearcher +from app.modules.querySearch.controllers.querySearch_controller import \ + QuerySearchController +from app.modules.querySearch.features.querySearch_feature import \ + QuerySearchFeature +from app.modules.questionAnswer.questionAnswer import QuestionAnswering +from app.qdrant import QdrantConnectionDb + + +def get_qdrant_connection_db() -> QdrantConnectionDb: + return QdrantConnectionDb() + + +def get_query_search_repository( + qdrant_connection_db: QdrantConnectionDb = Depends(get_qdrant_connection_db), +): + return QuerySearchRepository(qdrant_connection_db) + + +def get_dense_model(request: Request) -> AutoModel: + return request.scope["state"]["dense_model"] + + +def get_sparse_model(request: Request) -> AutoModelForMaskedLM: + return request.scope["state"]["sparse_model"] + + +def get_dense_tokenizer(request: Request) -> AutoTokenizer: + return request.scope["state"]["dense_tokenizer"] + + +def get_sparse_tokenizer(request: Request) -> AutoTokenizer: + return request.scope["state"]["sparse_tokenizer"] + + +def get_dense_embeddings( + dense_model: AutoModel = Depends(get_dense_model), + dense_tokenizer: AutoTokenizer = Depends(get_dense_tokenizer), + sparse_model: AutoModelForMaskedLM = Depends(get_sparse_model), + sparse_tokenizer: AutoTokenizer = Depends(get_sparse_tokenizer), +): + return DenseEmbeddings( + dense_model=dense_model, + dense_tokenizer=dense_tokenizer, + sparse_model=sparse_model, + sparse_tokenizer=sparse_tokenizer, + ) + + +def get_qa_pipeline(request: Request): + return request.scope["state"]["qa_pipeline"] + + +def get_question_ansering(qa_pipline: pipeline = Depends(get_qa_pipeline)): + return QuestionAnswering(qa_pipline) + + +def get_hybrid_searcher( + dense_embeddings: DenseEmbeddings = Depends(get_dense_embeddings), + query_search_repository: QuerySearchRepository = Depends( + get_query_search_repository + ), +): + return HybridSearcher(dense_embeddings, query_search_repository) + + +def get_query_search_feature( + qa_pipeline: pipeline = Depends(get_qa_pipeline), + hybrid_searcher: HybridSearcher = Depends(get_hybrid_searcher), + question_answering: QuestionAnswering = Depends(get_question_ansering), +): + return QuerySearchFeature(qa_pipeline, hybrid_searcher, question_answering) + + +def get_query_search_controller( + query_search_feature: QuerySearchFeature = Depends(get_query_search_feature), +): + return QuerySearchController(query_search_feature) diff --git a/Api/app/modules/querySearch/features/__pycache__/querySearch_feature.cpython-310.pyc b/Api/app/modules/querySearch/features/__pycache__/querySearch_feature.cpython-310.pyc index 61190420a531e23ce279156a801a4d1a6f1035a7..e487da84d54e2b794a09cf5b932933f2244f5285 100644 Binary files a/Api/app/modules/querySearch/features/__pycache__/querySearch_feature.cpython-310.pyc and b/Api/app/modules/querySearch/features/__pycache__/querySearch_feature.cpython-310.pyc differ diff --git a/Api/app/modules/querySearch/features/querySearch_feature.py b/Api/app/modules/querySearch/features/querySearch_feature.py index 87a857481ff06ff10ddf00277aacb62ec6265f2e..30ef6f12267acb0b17e7cdcb5500d560d63922df 100644 --- a/Api/app/modules/querySearch/features/querySearch_feature.py +++ b/Api/app/modules/querySearch/features/querySearch_feature.py @@ -1,89 +1,51 @@ -import json -from typing import List, Tuple +from qdrant_client.conversions import common_types as types -import numpy as np -# from fastapi.responses import JSONResponse -# from sentence_transformers import SentenceTransformer -# from transformers import pipeline - -from app.db_local_storage.vector_files_db import vector_files_db -from app.db_local_storage.files_db import VECTOR_FILES_DIRECTORY from app.db_local_storage.in_memory_db import query_response_storage - +from app.infrastructure.models.my_models import HybridSearchResponse, ModelResponse +from app.modules.hybridSearcher.hybridSearcher import HybridSearcher +from app.modules.questionAnswer.questionAnswer import QuestionAnswering +from transformers import pipeline class QuerySearchFeature: - def __init__(self, model, qa_pipeline): - self.model = model + def __init__( + self, + qa_pipeline: pipeline, + hybrid_searcher: HybridSearcher, + question_answering: QuestionAnswering, + ): self.qa_pipeline = qa_pipeline + self.hybrid_searcher = hybrid_searcher + self.question_answering = question_answering - async def query_search(self, query: str) -> dict: - - user_query = { - "text": query, - "isSender": True, - } - - query_response_storage.append(user_query) + async def query_search(self, query: str) -> ModelResponse: - # dataBase = await QuerySearchFeature.load_data() - dataBase = vector_files_db - text_data, embeddings = await QuerySearchFeature.split_dataBase(dataBase) - - lexical_results = await QuerySearchFeature.lexical_search(query, text_data) - semantic_results = await QuerySearchFeature.semantic_search( - query, text_data, embeddings, self.model + query_response_storage.append( + { + "text": query, + "isSender": True, + } ) - combined_results = list(set(lexical_results + semantic_results)) - context = await QuerySearchFeature.get_context(combined_results) - - response = self.qa_pipeline(question=query, context=context) - - response_query = { - "text": response["answer"], - "isSender": False, - } + result = self.hybrid_searcher.hybrid_search(query) + context = self.get_and_join_context(result) + model_response = self.question_answering.answer_question(query, context) - query_response_storage.append(response_query) - - return { - "message": response["answer"], - "context_used": context, - "chunks": context, - } - - @staticmethod - async def semantic_search( - query: str, chunks: List[str], embeddings: np.ndarray, model - ) -> List[str]: - query_embedding = model.encode([query]) - similarities = np.dot(embeddings, query_embedding.T).flatten() - top_indices = np.argsort(-similarities)[:3] - return [chunks[i] for i in top_indices] - - @staticmethod - async def lexical_search(query: str, chunks: List[str]) -> List[str]: - return [chunk for chunk in chunks if query.lower() in chunk.lower()] - - @staticmethod - async def load_data(): - with open(VECTOR_FILES_DIRECTORY, "r") as file: - dataBase = json.load(file) - return dataBase - - @staticmethod - async def split_dataBase(db) -> Tuple[List[str], np.ndarray]: - text_data = [] - embeddings = [] + # TODO: Manage memory for display messages + query_response_storage.append( + { + "text": model_response, + "isSender": False, + } + ) - for document in db.values(): - for page in document["data"]: - text_data.append(page["metadata"]["original_text"]) - embeddings.append(page["embedding"]) - return text_data, embeddings + return ModelResponse( + text=model_response, + isSender=False, + message="success", + ) - @staticmethod - async def get_context(chunks: List[str]) -> str: - return " ".join(chunks) + def get_and_join_context(self, search_result: HybridSearchResponse) -> str: + contexts = [point["chunk-text"] for point in search_result.data] + return ", ".join(contexts) diff --git a/Api/app/modules/querySearch/features/querySearch_feature_v2.py b/Api/app/modules/querySearch/features/querySearch_feature_v2.py new file mode 100644 index 0000000000000000000000000000000000000000..e7ad6070962649f0f295f16e5fa070675474d8cf --- /dev/null +++ b/Api/app/modules/querySearch/features/querySearch_feature_v2.py @@ -0,0 +1,87 @@ +import json +from typing import List, Tuple + +import numpy as np +# from fastapi.responses import JSONResponse +# from sentence_transformers import SentenceTransformer +# from transformers import pipeline + +from app.db_local_storage.in_memory_db import query_response_storage + + + +class QuerySearchFeature: + + def __init__(self, model, qa_pipeline): + self.model = model + self.qa_pipeline = qa_pipeline + + async def query_search(self, query: str) -> dict: + + user_query = { + "text": query, + "isSender": True, + } + + query_response_storage.append(user_query) + + # dataBase = await QuerySearchFeature.load_data() + dataBase = vector_files_db + text_data, embeddings = await QuerySearchFeature.split_dataBase(dataBase) + + lexical_results = await QuerySearchFeature.lexical_search(query, text_data) + semantic_results = await QuerySearchFeature.semantic_search( + query, text_data, embeddings, self.model + ) + + combined_results = list(set(lexical_results + semantic_results)) + context = await QuerySearchFeature.get_context(combined_results) + + response = self.qa_pipeline(question=query, context=context) + + response_query = { + "text": response["answer"], + "isSender": False, + } + + query_response_storage.append(response_query) + + return { + "message": response["answer"], + "context_used": context, + "chunks": context, + } + + @staticmethod + async def semantic_search( + query: str, chunks: List[str], embeddings: np.ndarray, model + ) -> List[str]: + query_embedding = model.encode([query]) + similarities = np.dot(embeddings, query_embedding.T).flatten() + top_indices = np.argsort(-similarities)[:3] + return [chunks[i] for i in top_indices] + + @staticmethod + async def lexical_search(query: str, chunks: List[str]) -> List[str]: + return [chunk for chunk in chunks if query.lower() in chunk.lower()] + + @staticmethod + async def load_data(): + with open(VECTOR_FILES_DIRECTORY, "r") as file: + dataBase = json.load(file) + return dataBase + + @staticmethod + async def split_dataBase(db) -> Tuple[List[str], np.ndarray]: + text_data = [] + embeddings = [] + + for document in db.values(): + for page in document["data"]: + text_data.append(page["metadata"]["original_text"]) + embeddings.append(page["embedding"]) + return text_data, embeddings + + @staticmethod + async def get_context(chunks: List[str]) -> str: + return " ".join(chunks) diff --git a/Api/app/modules/querySearch/routes/__pycache__/querySearch_route.cpython-310.pyc b/Api/app/modules/querySearch/routes/__pycache__/querySearch_route.cpython-310.pyc index 5ecac8e639c5c6a26b9f3e307cca87163499f88c..71ab6fbb17e024813d19ba98fa2ef64db73ad0e7 100644 Binary files a/Api/app/modules/querySearch/routes/__pycache__/querySearch_route.cpython-310.pyc and b/Api/app/modules/querySearch/routes/__pycache__/querySearch_route.cpython-310.pyc differ diff --git a/Api/app/modules/querySearch/routes/querySearch_route.py b/Api/app/modules/querySearch/routes/querySearch_route.py index 0ac465e41c8525d5985a8db1d2bca15c22bdd20b..98717a91b1ab8f243a300fe4c3437a1902279028 100644 --- a/Api/app/modules/querySearch/routes/querySearch_route.py +++ b/Api/app/modules/querySearch/routes/querySearch_route.py @@ -1,28 +1,22 @@ -from fastapi import APIRouter, Form, HTTPException +from fastapi import APIRouter, Depends, Form from fastapi.responses import JSONResponse -# from sentence_transformers import SentenceTransformer -# from transformers import pipeline from app.db_local_storage.in_memory_db import query_response_storage from app.modules.querySearch.controllers.querySearch_controller import ( QuerySearchController, ) -from app.modules.model import model, qa_pipeline -from app.modules.querySearch.features.querySearch_feature import QuerySearchFeature +from app.modules.querySearch.dependecies import get_query_search_controller router = APIRouter() -# model = SentenceTransformer("paraphrase-MiniLM-L6-v2") -# qa_pipeline = pipeline("question-answering", model="deepset/roberta-base-squad2") - -querySearchFeature = QuerySearchFeature(model, qa_pipeline) -querySearchController = QuerySearchController(querySearchFeature) - @router.post("/query_search") -async def handle_query_search(q: str = Form(...)): +async def handle_query_search( + q: str = Form(...), + controller: QuerySearchController = Depends(get_query_search_controller), +): - return await querySearchController.handle_query_search(q) + return await controller.handle_query_search(q) @router.get("/get_messages") diff --git a/Api/app/modules/questionAnswer/__pycache__/questionAnswer.cpython-310.pyc b/Api/app/modules/questionAnswer/__pycache__/questionAnswer.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..75c83e87fea8ff5b2b079b8f85943d10c832bf90 Binary files /dev/null and b/Api/app/modules/questionAnswer/__pycache__/questionAnswer.cpython-310.pyc differ diff --git a/Api/app/modules/questionAnswer/questionAnswer.py b/Api/app/modules/questionAnswer/questionAnswer.py new file mode 100644 index 0000000000000000000000000000000000000000..3747c88aea7922324144684ed4ad0ca44b658590 --- /dev/null +++ b/Api/app/modules/questionAnswer/questionAnswer.py @@ -0,0 +1,10 @@ +from transformers import pipeline + + +class QuestionAnswering: + def __init__(self, qa_pipeline: pipeline): + self.qa_pipeline = qa_pipeline + + def answer_question(self, question: str, context: str) -> str: + result = self.qa_pipeline(question=question, context=context) + return result["answer"] diff --git a/Api/app/modules/uploadDocument/controllers/__pycache__/file_upload_controller.cpython-310.pyc b/Api/app/modules/uploadDocument/controllers/__pycache__/file_upload_controller.cpython-310.pyc deleted file mode 100644 index 0139ae4ccb0523f2bfd7e16eb78fd5b2b913c34b..0000000000000000000000000000000000000000 Binary files a/Api/app/modules/uploadDocument/controllers/__pycache__/file_upload_controller.cpython-310.pyc and /dev/null differ diff --git a/Api/app/modules/uploadDocument/controllers/file_upload_controller.py b/Api/app/modules/uploadDocument/controllers/file_upload_controller.py deleted file mode 100644 index 3551c3e4774f809d955e3bfc396a4341292c1d90..0000000000000000000000000000000000000000 --- a/Api/app/modules/uploadDocument/controllers/file_upload_controller.py +++ /dev/null @@ -1,30 +0,0 @@ -from typing import Any - -from fastapi import HTTPException, UploadFile -from fastapi.responses import JSONResponse - -from app.modules.uploadDocument.features.createEmbeddings_feature import ( - CreateEmbeddingsFeature, -) -from app.modules.uploadDocument.features.extractText_feature import ExtractTextFeature -from app.modules.uploadDocument.features.uploadDocument_feature import ( - UploadDocumentFeature, -) - - -class FileUploadController: - - async def handle_file_upload(self, file: UploadFile) -> Any: - try: - - text_file = await ExtractTextFeature.extract_text_from_pdf(file) - - await CreateEmbeddingsFeature.create_embeddings(text_file, file.filename) - - result = await UploadDocumentFeature.uploadFile(file) - message = result.get("message", "No message provided") - - return JSONResponse(status_code=200, content={"message": message}) - - except Exception as e: - raise HTTPException(status_code=500, detail=str(e)) diff --git a/Api/app/modules/uploadDocument/features/__pycache__/createEmbeddings_feature.cpython-310.pyc b/Api/app/modules/uploadDocument/features/__pycache__/createEmbeddings_feature.cpython-310.pyc deleted file mode 100644 index 608a62b700128c29b30050cd5e9a9a66d9737b99..0000000000000000000000000000000000000000 Binary files a/Api/app/modules/uploadDocument/features/__pycache__/createEmbeddings_feature.cpython-310.pyc and /dev/null differ diff --git a/Api/app/modules/uploadDocument/features/__pycache__/extractText_feature.cpython-310.pyc b/Api/app/modules/uploadDocument/features/__pycache__/extractText_feature.cpython-310.pyc deleted file mode 100644 index 38fdbd24625d5e6fb6ae99bacfac48fdbc4c7191..0000000000000000000000000000000000000000 Binary files a/Api/app/modules/uploadDocument/features/__pycache__/extractText_feature.cpython-310.pyc and /dev/null differ diff --git a/Api/app/modules/uploadDocument/features/createEmbeddings_feature.py b/Api/app/modules/uploadDocument/features/createEmbeddings_feature.py deleted file mode 100644 index ddddd3048614500f82445e2ac36a676e850db9f8..0000000000000000000000000000000000000000 --- a/Api/app/modules/uploadDocument/features/createEmbeddings_feature.py +++ /dev/null @@ -1,39 +0,0 @@ -import json -from typing import List - -from app.db_local_storage.vector_files_db import vector_files_db as EMBEDDING_DATA -from app.modules.model import model, qa_pipeline - - -class CreateEmbeddingsFeature: - - @staticmethod - async def chunk_text(text: str, chunk_size: int = 512) -> List[str]: - chunks = [text[i : i + chunk_size] for i in range(0, len(text), chunk_size)] - return chunks - - @staticmethod - async def create_embeddings(text: str, filename: str) -> List: - - chunks = await CreateEmbeddingsFeature.chunk_text(text) - - id = len(EMBEDDING_DATA) + 1 - docoument_index = f"document_{id}" - EMBEDDING_DATA[docoument_index] = { - "metadata": {"id": id, "filename": filename, "chunks": len(chunks)}, - "data": [], - } - - for i, chunk in enumerate(chunks): - embedding = model.encode(chunk).tolist() - embedding_entry = { - "embedding": embedding, - "metadata": { - "chunk_index": i, - "original_text": chunk, - "document_id": docoument_index, - }, - } - EMBEDDING_DATA[docoument_index]["data"].append(embedding_entry) - - return diff --git a/Api/app/modules/uploadDocument/features/extractText_feature.py b/Api/app/modules/uploadDocument/features/extractText_feature.py deleted file mode 100644 index 12a6924b029cb9eba05dd407a91b8006423ca064..0000000000000000000000000000000000000000 --- a/Api/app/modules/uploadDocument/features/extractText_feature.py +++ /dev/null @@ -1,56 +0,0 @@ -import io -import os - -from fastapi import UploadFile -import pdfplumber - -from app.db_local_storage.files_db import TEXT_FILES_DIRECTORY -from app.db_local_storage.documents_db import documents_text - - -class ExtractTextFeature: - - # @staticmethod - # def ensure_directory_exists(folder_path: str) -> None: - # """Ensure that the directory exists.""" - # if not os.path.exists(folder_path): - # os.makedirs(folder_path) - - # @staticmethod - # async def saveFile(content, filename, directory: str) -> str: - # """Save the uploaded file to the specified directory.""" - # file_path = os.path.join(directory, filename) - # with open(file_path, "w") as file: - # file.write(content) - # return file_path - - # @staticmethod - # async def save_text_from_pdf(file: UploadFile, text) -> str: - - # ExtractTextFeature.ensure_directory_exists(TEXT_FILES_DIRECTORY) - # await ExtractTextFeature.saveFile(text, file.filename, TEXT_FILES_DIRECTORY) - - # return text - - @staticmethod - async def extract_text_from_pdf(file: UploadFile) -> str: - - content = await file.read() - with pdfplumber.open(io.BytesIO(content)) as pdf: - text = "" - for page in pdf.pages: - text += page.extract_text() - - for document in documents_text: - if document["filename"] == file.filename: - return {"message": "Document already exists"} - - data = { - "id": len(documents_text) + 1, - "filename": file.filename, - "text": text, - } - - documents_text.append(data) - - return text diff --git a/Api/app/modules/uploadDocument/features/uploadDocument_feature.py b/Api/app/modules/uploadDocument/features/uploadDocument_feature.py deleted file mode 100644 index 407de782185c824637afc571cf60953eb4599def..0000000000000000000000000000000000000000 --- a/Api/app/modules/uploadDocument/features/uploadDocument_feature.py +++ /dev/null @@ -1,51 +0,0 @@ -import os -from typing import Dict - -from fastapi import UploadFile -from app.db_local_storage.files_db import FILES_DIRECTORY, FILES_NAMES_DATABASE -from app.db_local_storage.documents_db import documents_db - - -class UploadDocumentFeature: - - # @staticmethod - # def ensure_directory_exists(folder_path: str) -> None: - # """Ensure that the directory exists.""" - # if not os.path.exists(folder_path): - # os.makedirs(folder_path) - - # @staticmethod - # async def saveFile(document: UploadFile, directory: str) -> str: - # """Save the uploaded file to the specified directory.""" - # file_path = os.path.join(directory, document.filename) - # with open(file_path, "wb") as file: - # content = await document.read() - # file.write(content) - # return file - - # @staticmethod - # async def SaveFileMemory(document: UploadFile) -> str: - # """Save the uploaded file to memory.""" - # UploadDocumentFeature.ensure_directory_exists(FILES_DIRECTORY) - # id = len(FILES_NAMES_DATABASE) + 1 - # FILES_NAMES_DATABASE[id] = document.filename - - # file = await UploadDocumentFeature.saveFile(document, FILES_DIRECTORY) - # return file - - @staticmethod - async def uploadFile(document: UploadFile) -> Dict[str, str]: - """ - Upload a file to the server - :param document: the file to upload - :return: a message to confirm the upload - """ - - data = { - "id": len(documents_db) + 1, - "filename": document.filename, - } - - documents_db.append(data) - - return {"message": "Document Updated"} diff --git a/Api/app/modules/uploadDocument/routes/__pycache__/uploadDocument_route.cpython-310.pyc b/Api/app/modules/uploadDocument/routes/__pycache__/uploadDocument_route.cpython-310.pyc deleted file mode 100644 index 27ed42794e8fb24d1cf5cc7290db3e8a11d17b83..0000000000000000000000000000000000000000 Binary files a/Api/app/modules/uploadDocument/routes/__pycache__/uploadDocument_route.cpython-310.pyc and /dev/null differ diff --git a/Api/app/modules/uploadDocument/routes/uploadDocument_route.py b/Api/app/modules/uploadDocument/routes/uploadDocument_route.py deleted file mode 100644 index 7c763bc42d79513bd52aee1dab76bd394ca40778..0000000000000000000000000000000000000000 --- a/Api/app/modules/uploadDocument/routes/uploadDocument_route.py +++ /dev/null @@ -1,58 +0,0 @@ -from fastapi import APIRouter, File, HTTPException, UploadFile -from fastapi.responses import JSONResponse -from app.db_local_storage.vector_files_db import vector_files_db -from app.modules.uploadDocument.controllers.file_upload_controller import ( - FileUploadController, -) -from app.db_local_storage.documents_db import documents_db - -router = APIRouter() -fileUploadController = FileUploadController() - - -@router.get("/get_documents") -async def get_all_documents(): - return JSONResponse(status_code=200, content={"data": documents_db}) - - -@router.get("/get_embeddings") -async def get_all_embeddings(): - return JSONResponse(status_code=200, content={"data": vector_files_db}) - - 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