diff --git a/.gitattributes b/.gitattributes index a6344aac8c09253b3b630fb776ae94478aa0275b..288e54e855fb24d6580a1132f17f99e80cdce689 100644 --- a/.gitattributes +++ b/.gitattributes @@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text *.zip filter=lfs diff=lfs merge=lfs -text *.zst filter=lfs diff=lfs merge=lfs -text *tfevents* filter=lfs diff=lfs merge=lfs -text +software/** filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore index dc62faad07bc9a2e609141f982774914730fc77d..d6f4ebe57c969b2ad5ef5b7fdd52164b66618a5a 100644 --- a/.gitignore +++ b/.gitignore @@ -26,6 +26,8 @@ test/users/user_accounts.csv .env.prd .env.example +CLAUDE.md + erd/ playground/ playground_retriever.py @@ -33,4 +35,5 @@ playground_chat.py playground_flush_cache.py playground_create_user.py API_CONTRACT.md -context_engineering/ \ No newline at end of file +context_engineering/ +sample_file/ \ No newline at end of file diff --git a/main.py b/main.py index 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b/src/api/v1/db_client.py @@ -1,5 +1,357 @@ -from typing import Literal, Dict +"""API endpoints for user-registered database connections. +Credential schemas (DbType, PostgresCredentials, etc.) live in +`src/models/credentials.py` — they are imported below (with noqa: F401) so +FastAPI/Swagger picks them up for OpenAPI schema generation even though they +are not referenced by name in this file. +""" -dbtypes: Literal["postgresql", "mysql", "sqlite"] = Literal["postgresql", "mysql", "sqlite"] -creds: Dict[str, str] \ No newline at end of file +from typing import Any, Dict, List, Literal, Optional +from datetime import datetime + +from fastapi import APIRouter, Depends, HTTPException, Query, Request, status +from pydantic import BaseModel, Field +from sqlalchemy.ext.asyncio import AsyncSession + +from src.database_client.database_client_service import database_client_service +from src.db.postgres.connection import get_db +from src.middlewares.logging import get_logger, log_execution +from src.middlewares.rate_limit import limiter +from src.models.credentials import ( # noqa: F401 — re-exported for Swagger schema discovery + BigQueryCredentials, + CredentialSchemas, + DbType, + MysqlCredentials, + PostgresCredentials, + SnowflakeCredentials, + SqlServerCredentials, + SupabaseCredentials, +) +from src.pipeline.db_pipeline import db_pipeline_service +from src.utils.db_credential_encryption import decrypt_credentials_dict + +logger = get_logger("database_client_api") + +router = APIRouter(prefix="/api/v1", tags=["Database Clients"]) + + +# --------------------------------------------------------------------------- +# Request / Response schemas +# --------------------------------------------------------------------------- + + +class DatabaseClientCreate(BaseModel): + """ + Payload to register a new external database connection. + + The `credentials` object shape depends on `db_type`: + + | db_type | Required fields | + |-------------|----------------------------------------------------------| + | postgres | host, port, database, username, password, ssl_mode | + | mysql | host, port, database, username, password, ssl | + | sqlserver | host, port, database, username, password, driver? | + | supabase | host, port, database, username, password, ssl_mode | + | bigquery | project_id, dataset_id, location?, service_account_json | + | snowflake | account, warehouse, database, schema?, username, password, role? | + + Sensitive fields (`password`, `service_account_json`) are encrypted + at rest using Fernet symmetric encryption. + """ + + name: str = Field(..., description="Display name for this connection.", examples=["Production DB"]) + db_type: DbType = Field(..., description="Type of the database engine.", examples=["postgres"]) + credentials: Dict[str, Any] = Field( + ..., + description="Connection credentials. Shape depends on db_type. See schema descriptions above.", + examples=[ + { + "host": "db.example.com", + "port": 5432, + "database": "mydb", + "username": "admin", + "password": "s3cr3t!", + "ssl_mode": "require", + } + ], + ) + + +class DatabaseClientUpdate(BaseModel): + """ + Payload to update an existing database connection. + + All fields are optional — only provided fields will be updated. + If `credentials` is provided, it replaces the entire credentials object + and sensitive fields are re-encrypted. + """ + + name: Optional[str] = Field(None, description="New display name for this connection.", examples=["Staging DB"]) + credentials: Optional[Dict[str, Any]] = Field( + None, + description="Updated credentials object. Replaces existing credentials entirely if provided.", + examples=[{"host": "new-host.example.com", "port": 5432, "database": "mydb", "username": "admin", "password": "n3wP@ss!", "ssl_mode": "require"}], + ) + status: Optional[Literal["active", "inactive"]] = Field( + None, + description="Set to 'inactive' to soft-disable the connection without deleting it.", + examples=["inactive"], + ) + + +class DatabaseClientResponse(BaseModel): + """ + Database connection record returned by the API. + + Credentials are **never** included in the response for security reasons. + """ + + id: str = Field(..., description="Unique identifier of the database connection.") + user_id: str = Field(..., description="ID of the user who owns this connection.") + name: str = Field(..., description="Display name of the connection.") + db_type: str = Field(..., description="Database engine type.") + status: str = Field(..., description="Connection status: 'active' or 'inactive'.") + created_at: datetime = Field(..., description="Timestamp when the connection was registered.") + updated_at: Optional[datetime] = Field(None, description="Timestamp of the last update, if any.") + + model_config = {"from_attributes": True} + + +# --------------------------------------------------------------------------- +# Endpoints +# --------------------------------------------------------------------------- + + +@router.post( + "/database-clients", + response_model=DatabaseClientResponse, + status_code=status.HTTP_201_CREATED, + summary="Register a new database connection", + response_description="The newly created database connection record (credentials excluded).", + responses={ + 201: {"description": "Connection registered successfully."}, + 422: {"description": "Validation error — check the credentials shape for the given db_type."}, + 500: {"description": "Internal server error."}, + }, +) +@limiter.limit("10/minute") +@log_execution(logger) +async def create_database_client( + request: Request, + payload: DatabaseClientCreate, + user_id: str = Query(..., description="ID of the user registering the connection."), + db: AsyncSession = Depends(get_db), +): + """ + Register a new external database connection for a user. + + The `credentials` object must match the shape for the chosen `db_type` + (see **CredentialSchemas** in the schema section below for exact fields). + Sensitive fields (`password`, `service_account_json`) are encrypted + before being persisted — they are never returned in any response. + """ + try: + client = await database_client_service.create( + db=db, + user_id=user_id, + name=payload.name, + db_type=payload.db_type, + credentials=payload.credentials, + ) + return DatabaseClientResponse.model_validate(client) + except Exception as e: + logger.error(f"Failed to create database client for user {user_id}", error=str(e)) + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail=f"Failed to create database client: {str(e)}", + ) + + +@router.get( + "/database-clients/{user_id}", + response_model=List[DatabaseClientResponse], + summary="List all database connections for a user", + response_description="List of database connections (credentials excluded).", + responses={ + 200: {"description": "Returns an empty list if the user has no connections."}, + }, +) +@log_execution(logger) +async def list_database_clients( + user_id: str, + db: AsyncSession = Depends(get_db), +): + """ + Return all database connections registered by the specified user, + ordered by creation date (newest first). + + Credentials are never included in the response. + """ + clients = await database_client_service.get_user_clients(db, user_id) + return [DatabaseClientResponse.model_validate(c) for c in clients] + + +@router.get( + "/database-clients/{user_id}/{client_id}", + response_model=DatabaseClientResponse, + summary="Get a single database connection", + response_description="Database connection detail (credentials excluded).", + responses={ + 404: {"description": "Connection not found."}, + 403: {"description": "Access denied — user_id does not own this connection."}, + }, +) +@log_execution(logger) +async def get_database_client( + user_id: str, + client_id: str, + db: AsyncSession = Depends(get_db), +): + """ + Return the detail of a single database connection. + + Returns **403** if the `user_id` in the path does not match the owner + of the requested connection. + """ + client = await database_client_service.get(db, client_id) + + if not client: + raise HTTPException(status_code=404, detail="Database client not found") + + if client.user_id != user_id: + raise HTTPException(status_code=403, detail="Access denied") + + return DatabaseClientResponse.model_validate(client) + + +@router.put( + "/database-clients/{client_id}", + response_model=DatabaseClientResponse, + summary="Update a database connection", + response_description="Updated database connection record (credentials excluded).", + responses={ + 404: {"description": "Connection not found."}, + 403: {"description": "Access denied — user_id does not own this connection."}, + }, +) +@log_execution(logger) +async def update_database_client( + client_id: str, + payload: DatabaseClientUpdate, + user_id: str = Query(..., description="ID of the user who owns the connection."), + db: AsyncSession = Depends(get_db), +): + """ + Update an existing database connection. + + Only fields present in the request body are updated. + If `credentials` is provided it **replaces** the entire credentials object + and sensitive fields are re-encrypted automatically. + """ + client = await database_client_service.get(db, client_id) + + if not client: + raise HTTPException(status_code=404, detail="Database client not found") + + if client.user_id != user_id: + raise HTTPException(status_code=403, detail="Access denied") + + updated = await database_client_service.update( + db=db, + client_id=client_id, + name=payload.name, + credentials=payload.credentials, + status=payload.status, + ) + return DatabaseClientResponse.model_validate(updated) + + +@router.delete( + "/database-clients/{client_id}", + status_code=status.HTTP_200_OK, + summary="Delete a database connection", + responses={ + 200: {"description": "Connection deleted successfully."}, + 404: {"description": "Connection not found."}, + 403: {"description": "Access denied — user_id does not own this connection."}, + }, +) +@log_execution(logger) +async def delete_database_client( + client_id: str, + user_id: str = Query(..., description="ID of the user who owns the connection."), + db: AsyncSession = Depends(get_db), +): + """ + Permanently delete a database connection. + + This action is irreversible. The stored credentials are also removed. + """ + client = await database_client_service.get(db, client_id) + + if not client: + raise HTTPException(status_code=404, detail="Database client not found") + + if client.user_id != user_id: + raise HTTPException(status_code=403, detail="Access denied") + + await database_client_service.delete(db, client_id) + return {"status": "success", "message": "Database client deleted successfully"} + + +@router.post( + "/database-clients/{client_id}/ingest", + status_code=status.HTTP_200_OK, + summary="Ingest schema from a registered database into the vector store", + response_description="Count of chunks ingested.", + responses={ + 200: {"description": "Ingestion completed successfully."}, + 403: {"description": "Access denied — user_id does not own this connection."}, + 404: {"description": "Connection not found."}, + 501: {"description": "The connection's db_type is not yet supported by the pipeline."}, + 500: {"description": "Ingestion failed (connection error, profiling error, etc.)."}, + }, +) +@limiter.limit("5/minute") +@log_execution(logger) +async def ingest_database_client( + request: Request, + client_id: str, + user_id: str = Query(..., description="ID of the user who owns the connection."), + db: AsyncSession = Depends(get_db), +): + """ + Decrypt the stored credentials, connect to the user's database, introspect + its schema, profile each column, embed the descriptions, and store them in + the shared PGVector collection tagged with `source_type="database"`. + + Chunks become retrievable via the same retriever used for document chunks. + """ + client = await database_client_service.get(db, client_id) + + if not client: + raise HTTPException(status_code=404, detail="Database client not found") + + if client.user_id != user_id: + raise HTTPException(status_code=403, detail="Access denied") + + creds = decrypt_credentials_dict(client.credentials) + + try: + with db_pipeline_service.engine_scope( + db_type=client.db_type, + credentials=creds, + ) as engine: + total = await db_pipeline_service.run(user_id=user_id, engine=engine) + except NotImplementedError as e: + raise HTTPException(status_code=status.HTTP_501_NOT_IMPLEMENTED, detail=str(e)) + except Exception as e: + logger.error( + f"Ingestion failed for client {client_id}", user_id=user_id, error=str(e) + ) + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail=f"Ingestion failed: {e}", + ) + + return {"status": "success", "client_id": client_id, "chunks_ingested": total} diff --git a/src/api/v1/document.py b/src/api/v1/document.py index 9e7c3429b72ca50318dbaceee56b55e5d5046125..a6189cbe7fd9f1a7d4654f45427b2692a06fa379 100644 --- a/src/api/v1/document.py +++ b/src/api/v1/document.py @@ -1,21 +1,20 @@ """Document management API endpoints.""" - -from fastapi import APIRouter, Depends, HTTPException, Request, UploadFile, File, status + +from fastapi import APIRouter, Depends, HTTPException, Request, UploadFile, File from sqlalchemy.ext.asyncio import AsyncSession from src.db.postgres.connection import get_db from src.document.document_service import document_service -from src.knowledge.processing_service import knowledge_processor -from src.storage.az_blob.az_blob import blob_storage from src.middlewares.logging import get_logger, log_execution from src.middlewares.rate_limit import limiter +from src.pipeline.document_pipeline.document_pipeline import document_pipeline from pydantic import BaseModel from typing import List - + logger = get_logger("document_api") - + router = APIRouter(prefix="/api/v1", tags=["Documents"]) - - + + class DocumentResponse(BaseModel): id: str filename: str @@ -23,8 +22,8 @@ class DocumentResponse(BaseModel): file_size: int file_type: str created_at: str - - + + @router.get("/documents/{user_id}", response_model=List[DocumentResponse]) @log_execution(logger) async def list_documents( @@ -44,8 +43,8 @@ async def list_documents( ) for doc in documents ] - - + + @router.post("/document/upload") @limiter.limit("10/minute") @log_execution(logger) @@ -57,57 +56,12 @@ async def upload_document( ): """Upload a document.""" if not user_id: - raise HTTPException( - status_code=400, - detail="user_id is required" - ) - - try: - # Read file content - content = await file.read() - file_size = len(content) - - # Get file type - filename = file.filename - file_type = filename.split('.')[-1].lower() if '.' in filename else 'txt' - - if file_type not in ['pdf', 'docx', 'txt']: - raise HTTPException( - status_code=400, - detail="Unsupported file type. Supported: pdf, docx, txt" - ) - - # Upload to blob storage - blob_name = await blob_storage.upload_file(content, filename, user_id) - - # Create document record - document = await document_service.create_document( - db=db, - user_id=user_id, - filename=filename, - blob_name=blob_name, - file_size=file_size, - file_type=file_type - ) - - return { - "status": "success", - "message": "Document uploaded successfully", - "data": { - "id": document.id, - "filename": document.filename, - "status": document.status - } - } - - except Exception as e: - logger.error(f"Upload failed for user {user_id}", error=str(e)) - raise HTTPException( - status_code=500, - detail=f"Upload failed: {str(e)}" - ) - - + raise HTTPException(status_code=400, detail="user_id is required") + + data = await document_pipeline.upload(file, user_id, db) + return {"status": "success", "message": "Document uploaded successfully", "data": data} + + @router.delete("/document/delete") @log_execution(logger) async def delete_document( @@ -116,31 +70,10 @@ async def delete_document( db: AsyncSession = Depends(get_db) ): """Delete a document.""" - document = await document_service.get_document(db, document_id) - - if not document: - raise HTTPException( - status_code=404, - detail="Document not found" - ) - - if document.user_id != user_id: - raise HTTPException( - status_code=403, - detail="Access denied" - ) - - success = await document_service.delete_document(db, document_id) - - if success: - return {"status": "success", "message": "Document deleted successfully"} - else: - raise HTTPException( - status_code=500, - detail="Failed to delete document" - ) - - + await document_pipeline.delete(document_id, user_id, db) + return {"status": "success", "message": "Document deleted successfully"} + + @router.post("/document/process") @log_execution(logger) async def process_document( @@ -149,45 +82,6 @@ async def process_document( db: AsyncSession = Depends(get_db) ): """Process document and ingest to vector index.""" - document = await document_service.get_document(db, document_id) - - if not document: - raise HTTPException( - status_code=404, - detail="Document not found" - ) - - if document.user_id != user_id: - raise HTTPException( - status_code=403, - detail="Access denied" - ) - - try: - # Update status to processing - await document_service.update_document_status(db, document_id, "processing") - - # Process document - chunks_count = await knowledge_processor.process_document(document, db) - - # Update status to completed - await document_service.update_document_status(db, document_id, "completed") - - return { - "status": "success", - "message": "Document processed successfully", - "data": { - "document_id": document_id, - "chunks_processed": chunks_count - } - } - - except Exception as e: - logger.error(f"Processing failed for document {document_id}", error=str(e)) - await document_service.update_document_status( - db, document_id, "failed", str(e) - ) - raise HTTPException( - status_code=500, - detail=f"Processing failed: {str(e)}" - ) + data = await document_pipeline.process(document_id, user_id, db) + return {"status": "success", "message": "Document processed successfully", "data": data} + \ No newline at end of file diff --git a/src/config/settings.py b/src/config/settings.py index 59a29e5c18d8e12700e523295c2699c0d39c5604..194e82000ae91b46083cb3c8617e6010ac7075b2 100644 --- a/src/config/settings.py +++ b/src/config/settings.py @@ -61,6 +61,11 @@ class Settings(BaseSettings): # Bcrypt salt (for users - existing) emarcal_bcrypt_salt: str = Field(alias="emarcal__bcrypt__salt", default="") + # DB credential encryption (Fernet key for user-registered database creds) + dataeyond_db_credential_key: str = Field( + alias="dataeyond__db__credential__key", default="" + ) + # Singleton instance settings = Settings() diff --git a/src/database_client/database_client_service.py b/src/database_client/database_client_service.py new file mode 100644 index 0000000000000000000000000000000000000000..9fdc7a9dca1b9e0cc7b096b14b16657d09c7e04f --- /dev/null +++ b/src/database_client/database_client_service.py @@ -0,0 +1,118 @@ +"""Service for managing user-registered external database connections.""" + +import uuid +from typing import List, Optional + +from sqlalchemy import delete, select +from sqlalchemy.ext.asyncio import AsyncSession + +from src.db.postgres.models import DatabaseClient +from src.middlewares.logging import get_logger +from src.utils.db_credential_encryption import ( + decrypt_credentials_dict, + encrypt_credentials_dict, +) + +logger = get_logger("database_client_service") + + +class DatabaseClientService: + """Service for managing user-registered external database connections.""" + + async def create( + self, + db: AsyncSession, + user_id: str, + name: str, + db_type: str, + credentials: dict, + ) -> DatabaseClient: + """Register a new database client connection. + + Credentials are encrypted before being stored. + """ + client = DatabaseClient( + id=str(uuid.uuid4()), + user_id=user_id, + name=name, + db_type=db_type, + credentials=encrypt_credentials_dict(credentials), + status="active", + ) + db.add(client) + await db.commit() + await db.refresh(client) + logger.info(f"Created database client {client.id} for user {user_id}") + return client + + async def get_user_clients( + self, + db: AsyncSession, + user_id: str, + ) -> List[DatabaseClient]: + """Return all active and inactive database clients for a user.""" + result = await db.execute( + select(DatabaseClient) + .where(DatabaseClient.user_id == user_id) + .order_by(DatabaseClient.created_at.desc()) + ) + return result.scalars().all() + + async def get( + self, + db: AsyncSession, + client_id: str, + ) -> Optional[DatabaseClient]: + """Return a single database client by its ID.""" + result = await db.execute( + select(DatabaseClient).where(DatabaseClient.id == client_id) + ) + return result.scalars().first() + + async def update( + self, + db: AsyncSession, + client_id: str, + name: Optional[str] = None, + credentials: Optional[dict] = None, + status: Optional[str] = None, + ) -> Optional[DatabaseClient]: + """Update an existing database client connection. + + Only non-None fields are updated. + Credentials are re-encrypted if provided. + """ + client = await self.get(db, client_id) + if not client: + return None + + if name is not None: + client.name = name + if credentials is not None: + client.credentials = encrypt_credentials_dict(credentials) + if status is not None: + client.status = status + + await db.commit() + await db.refresh(client) + logger.info(f"Updated database client {client_id}") + return client + + async def delete( + self, + db: AsyncSession, + client_id: str, + ) -> bool: + """Permanently delete a database client connection.""" + result = await db.execute( + delete(DatabaseClient).where(DatabaseClient.id == client_id) + ) + await db.commit() + deleted = result.rowcount > 0 + if deleted: + logger.info(f"Deleted database client {client_id}") + return deleted + + +database_client_service = DatabaseClientService() + \ No newline at end of file diff --git a/src/db/postgres/init_db.py b/src/db/postgres/init_db.py index b4713f8909a3349e807b8f75e68d8cc81095e733..7925b236534e85c078490d1b2db8b89e08342b1c 100644 --- a/src/db/postgres/init_db.py +++ b/src/db/postgres/init_db.py @@ -2,7 +2,14 @@ from sqlalchemy import text from src.db.postgres.connection import engine, Base -from src.db.postgres.models import Document, Room, ChatMessage, User, MessageSource +from src.db.postgres.models import ( + ChatMessage, + DatabaseClient, + Document, + MessageSource, + Room, + User, +) async def init_db(): diff --git a/src/db/postgres/models.py b/src/db/postgres/models.py index 3aa25f87fa18a76b249e9bbdeec32a7eac2a9ace..62c542bbffc22be43653ea22a096746ac982e1a4 100644 --- a/src/db/postgres/models.py +++ b/src/db/postgres/models.py @@ -4,6 +4,7 @@ from uuid import uuid4 from sqlalchemy import Column, String, DateTime, Text, Integer, ForeignKey from sqlalchemy.orm import relationship from sqlalchemy.sql import func +from sqlalchemy.dialects.postgresql import JSONB from src.db.postgres.connection import Base @@ -81,3 +82,18 @@ class MessageSource(Base): created_at = Column(DateTime(timezone=True), server_default=func.now()) message = relationship("ChatMessage", back_populates="sources") + + +class DatabaseClient(Base): + """User-registered external database connections.""" + __tablename__ = "databases" + + id = Column(String, primary_key=True, default=lambda: str(uuid4())) + user_id = Column(String, nullable=False, index=True) + name = Column(String, nullable=False) # display name, e.g. "Prod DB" + db_type = Column(String, nullable=False) # postgres|mysql|sqlserver|supabase|bigquery|snowflake + credentials = Column(JSONB, nullable=False) # per-type JSON; sensitive fields Fernet-encrypted + status = Column(String, nullable=False, default="active") # active | inactive + created_at = Column(DateTime(timezone=True), server_default=func.now()) + updated_at = Column(DateTime(timezone=True), onupdate=func.now()) + \ No newline at end of file diff --git a/src/knowledge/processing_service.py b/src/knowledge/processing_service.py index b9d7fbf2391078523129bbdb2493e3b0aa37a9f2..761a4b4a719c44b0213e9417ac5dbaf783c4f686 100644 --- a/src/knowledge/processing_service.py +++ b/src/knowledge/processing_service.py @@ -5,14 +5,14 @@ from langchain_core.documents import Document as LangChainDocument from src.db.postgres.vector_store import get_vector_store from src.storage.az_blob.az_blob import blob_storage from src.db.postgres.models import Document as DBDocument -from src.config.settings import settings from sqlalchemy.ext.asyncio import AsyncSession from src.middlewares.logging import get_logger -from azure.ai.documentintelligence.aio import DocumentIntelligenceClient -from azure.core.credentials import AzureKeyCredential from typing import List -import pypdf +import sys import docx +import pandas as pd +import pytesseract +from pdf2image import convert_from_bytes from io import BytesIO logger = get_logger("knowledge_processing") @@ -40,6 +40,10 @@ class KnowledgeProcessingService: if db_doc.file_type == "pdf": documents = await self._build_pdf_documents(content, db_doc) + elif db_doc.file_type == "csv": + documents = self._build_csv_documents(content, db_doc) + elif db_doc.file_type == "xlsx": + documents = self._build_excel_documents(content, db_doc) else: text = self._extract_text(content, db_doc.file_type) if not text.strip(): @@ -49,10 +53,14 @@ class KnowledgeProcessingService: LangChainDocument( page_content=chunk, metadata={ - "document_id": db_doc.id, "user_id": db_doc.user_id, - "filename": db_doc.filename, - "chunk_index": i, + "source_type": "document", + "data": { + "document_id": db_doc.id, + "filename": db_doc.filename, + "file_type": db_doc.file_type, + "chunk_index": i, + }, } ) for i, chunk in enumerate(chunks) @@ -74,62 +82,98 @@ class KnowledgeProcessingService: async def _build_pdf_documents( self, content: bytes, db_doc: DBDocument ) -> List[LangChainDocument]: - """Build LangChain documents from PDF with page_label metadata. - - Uses Azure Document Intelligence (per-page) when credentials are present, - falls back to pypdf (also per-page) otherwise. - """ + """Build LangChain documents from PDF with page_label metadata using Tesseract OCR.""" documents: List[LangChainDocument] = [] - if settings.azureai_docintel_endpoint and settings.azureai_docintel_key: - async with DocumentIntelligenceClient( - endpoint=settings.azureai_docintel_endpoint, - credential=AzureKeyCredential(settings.azureai_docintel_key), - ) as client: - poller = await client.begin_analyze_document( - model_id="prebuilt-read", - body=BytesIO(content), - content_type="application/pdf", - ) - result = await poller.result() - logger.info(f"Azure DI extracted {len(result.pages or [])} pages") - - for page in result.pages or []: - page_text = "\n".join( - line.content for line in (page.lines or []) - ) - if not page_text.strip(): - continue - for chunk in self.text_splitter.split_text(page_text): - documents.append(LangChainDocument( - page_content=chunk, - metadata={ - "document_id": db_doc.id, - "user_id": db_doc.user_id, - "filename": db_doc.filename, - "chunk_index": len(documents), - "page_label": page.page_number, - } - )) - else: - logger.warning("Azure DI not configured, using pypdf") - pdf_reader = pypdf.PdfReader(BytesIO(content)) - for page_num, page in enumerate(pdf_reader.pages, start=1): - page_text = page.extract_text() or "" - if not page_text.strip(): - continue - for chunk in self.text_splitter.split_text(page_text): - documents.append(LangChainDocument( - page_content=chunk, - metadata={ + poppler_path = None + if sys.platform == "win32": + pytesseract.pytesseract.tesseract_cmd = r"./software/Tesseract-OCR/tesseract.exe" + poppler_path = "./software/poppler-24.08.0/Library/bin" + + images = convert_from_bytes(content, poppler_path=poppler_path) + logger.info(f"Tesseract OCR: converting {len(images)} pages") + + for page_num, image in enumerate(images, start=1): + page_text = pytesseract.image_to_string(image) + if not page_text.strip(): + continue + for chunk in self.text_splitter.split_text(page_text): + documents.append(LangChainDocument( + page_content=chunk, + metadata={ + "user_id": db_doc.user_id, + "source_type": "document", + "data": { "document_id": db_doc.id, - "user_id": db_doc.user_id, "filename": db_doc.filename, + "file_type": db_doc.file_type, "chunk_index": len(documents), "page_label": page_num, - } - )) + }, + } + )) + + return documents + + def _profile_dataframe( + self, df: pd.DataFrame, source_name: str, db_doc: DBDocument + ) -> List[LangChainDocument]: + """Profile each column of a dataframe → one chunk per column.""" + documents = [] + row_count = len(df) + + for col_name in df.columns: + col = df[col_name] + is_numeric = pd.api.types.is_numeric_dtype(col) + null_count = int(col.isnull().sum()) + distinct_count = int(col.nunique()) + distinct_ratio = distinct_count / row_count if row_count > 0 else 0 + + text = f"Source: {source_name} ({row_count} rows)\n" + text += f"Column: {col_name} ({col.dtype})\n" + text += f"Null count: {null_count}\n" + text += f"Distinct count: {distinct_count} ({distinct_ratio:.1%})\n" + + if is_numeric: + text += f"Min: {col.min()}, Max: {col.max()}\n" + text += f"Mean: {col.mean():.4f}, Median: {col.median():.4f}\n" + + if 0 < distinct_ratio <= 0.05: + top_values = col.value_counts().head(10) + top_str = ", ".join(f"{v} ({c})" for v, c in top_values.items()) + text += f"Top values: {top_str}\n" + + text += f"Sample values: {col.dropna().head(5).tolist()}" + + documents.append(LangChainDocument( + page_content=text, + metadata={ + "user_id": db_doc.user_id, + "source_type": "document", + "data": { + "document_id": db_doc.id, + "filename": db_doc.filename, + "file_type": db_doc.file_type, + "source": source_name, + "column_name": col_name, + "column_type": str(col.dtype), + } + } + )) + return documents + def _build_csv_documents(self, content: bytes, db_doc: DBDocument) -> List[LangChainDocument]: + """Profile each column of a CSV file.""" + df = pd.read_csv(BytesIO(content)) + return self._profile_dataframe(df, db_doc.filename, db_doc) + + def _build_excel_documents(self, content: bytes, db_doc: DBDocument) -> List[LangChainDocument]: + """Profile each column of every sheet in an Excel file.""" + sheets = pd.read_excel(BytesIO(content), sheet_name=None) + documents = [] + for sheet_name, df in sheets.items(): + source_name = f"{db_doc.filename} / sheet: {sheet_name}" + documents.extend(self._profile_dataframe(df, source_name, db_doc)) return documents def _extract_text(self, content: bytes, file_type: str) -> str: diff --git a/src/models/credentials.py b/src/models/credentials.py new file mode 100644 index 0000000000000000000000000000000000000000..01eb0f9ed3c717587cd92ce37104ca7dcd4b2084 --- /dev/null +++ b/src/models/credentials.py @@ -0,0 +1,164 @@ +"""Pydantic credential schemas for user-registered external databases. + +Imported by the `/database-clients` API router (`src/api/v1/db_client.py`) and, +via `DbType`, by the db pipeline connector (`src/pipeline/db_pipeline/connector.py`). + +Sensitive fields (`password`, `service_account_json`) are Fernet-encrypted by +the database_client service before being stored in the JSONB column; these +schemas describe the plaintext wire format, not the stored shape. +""" + +from typing import Literal, Optional, Union + +from pydantic import BaseModel, Field + +# --------------------------------------------------------------------------- +# Supported DB types +# --------------------------------------------------------------------------- + +DbType = Literal["postgres", "mysql", "sqlserver", "supabase", "bigquery", "snowflake"] + + +# --------------------------------------------------------------------------- +# Typed credential schemas per DB type +# --------------------------------------------------------------------------- + + +class PostgresCredentials(BaseModel): + """Connection credentials for PostgreSQL.""" + + host: str = Field(..., description="Hostname or IP address of the PostgreSQL server.", examples=["db.example.com"]) + port: int = Field(5432, description="Port number (default: 5432).", examples=[5432]) + database: str = Field(..., description="Name of the target database.", examples=["mydb"]) + username: str = Field(..., description="Database username.", examples=["admin"]) + password: str = Field(..., description="Database password. Will be encrypted at rest.", examples=["s3cr3t!"]) + ssl_mode: Literal["disable", "require", "verify-ca", "verify-full"] = Field( + "require", + description="SSL mode for the connection.", + examples=["require"], + ) + + +class MysqlCredentials(BaseModel): + """Connection credentials for MySQL.""" + + host: str = Field(..., description="Hostname or IP address of the MySQL server.", examples=["db.example.com"]) + port: int = Field(3306, description="Port number (default: 3306).", examples=[3306]) + database: str = Field(..., description="Name of the target database.", examples=["mydb"]) + username: str = Field(..., description="Database username.", examples=["admin"]) + password: str = Field(..., description="Database password. Will be encrypted at rest.", examples=["s3cr3t!"]) + ssl: bool = Field(True, description="Enable SSL for the connection.", examples=[True]) + + +class SqlServerCredentials(BaseModel): + """Connection credentials for Microsoft SQL Server.""" + + host: str = Field(..., description="Hostname or IP address of the SQL Server.", examples=["sqlserver.example.com"]) + port: int = Field(1433, description="Port number (default: 1433).", examples=[1433]) + database: str = Field(..., description="Name of the target database.", examples=["mydb"]) + username: str = Field(..., description="Database username.", examples=["sa"]) + password: str = Field(..., description="Database password. Will be encrypted at rest.", examples=["s3cr3t!"]) + driver: Optional[str] = Field( + None, + description="ODBC driver name. Leave empty to use the default driver.", + examples=["ODBC Driver 17 for SQL Server"], + ) + + +class SupabaseCredentials(BaseModel): + """Connection credentials for Supabase (PostgreSQL-based). + + Use the connection string details from your Supabase project dashboard + under Settings > Database. + """ + + host: str = Field( + ..., + description="Supabase database host (e.g. db..supabase.co, or the pooler host).", + examples=["db.xxxx.supabase.co"], + ) + port: int = Field( + 5432, + description="Port number. Use 5432 for direct connection, 6543 for the connection pooler.", + examples=[5432], + ) + database: str = Field("postgres", description="Database name (always 'postgres' for Supabase).", examples=["postgres"]) + username: str = Field( + ..., + description="Database user. Use 'postgres' for direct connection, or 'postgres.' for the pooler.", + examples=["postgres"], + ) + password: str = Field(..., description="Database password (set in Supabase dashboard). Will be encrypted at rest.", examples=["s3cr3t!"]) + ssl_mode: Literal["require", "verify-ca", "verify-full"] = Field( + "require", + description="SSL mode. Supabase always requires SSL.", + examples=["require"], + ) + + +class BigQueryCredentials(BaseModel): + """Connection credentials for Google BigQuery. + + Requires a GCP Service Account with at least BigQuery Data Viewer + and BigQuery Job User roles. + """ + + project_id: str = Field(..., description="GCP project ID where the BigQuery dataset resides.", examples=["my-gcp-project"]) + dataset_id: str = Field(..., description="BigQuery dataset name to connect to.", examples=["my_dataset"]) + location: Optional[str] = Field( + "US", + description="Dataset location/region (default: US).", + examples=["US", "EU", "asia-southeast1"], + ) + service_account_json: str = Field( + ..., + description=( + "Full content of the GCP Service Account key JSON file as a string. " + "Will be encrypted at rest." + ), + examples=['{"type":"service_account","project_id":"my-gcp-project","private_key_id":"..."}'], + ) + + +class SnowflakeCredentials(BaseModel): + """Connection credentials for Snowflake.""" + + account: str = Field( + ..., + description="Snowflake account identifier, including region if applicable (e.g. myaccount.us-east-1).", + examples=["myaccount.us-east-1"], + ) + warehouse: str = Field(..., description="Name of the virtual warehouse to use for queries.", examples=["COMPUTE_WH"]) + database: str = Field(..., description="Name of the target Snowflake database.", examples=["MY_DB"]) + db_schema: Optional[str] = Field("PUBLIC", alias="schema", description="Schema name (default: PUBLIC).", examples=["PUBLIC"]) + username: str = Field(..., description="Snowflake username.", examples=["admin"]) + password: str = Field(..., description="Snowflake password. Will be encrypted at rest.", examples=["s3cr3t!"]) + role: Optional[str] = Field(None, description="Snowflake role to assume for the session.", examples=["SYSADMIN"]) + + +# Union of all credential shapes — reserved for future typed validation on +# DatabaseClientCreate.credentials (currently Dict[str, Any]). Kept exported +# so downstream code can reference it without re-declaring. +CredentialsUnion = Union[ + PostgresCredentials, + MysqlCredentials, + SqlServerCredentials, + SupabaseCredentials, + BigQueryCredentials, + SnowflakeCredentials, +] + + +# Doc-only helper: surfaces per-type credential shapes in the Swagger "Schemas" +# panel so API consumers can discover the exact field set for each db_type. +# Not referenced by any endpoint — importing it in db_client.py is enough for +# FastAPI's OpenAPI generator to pick it up. +class CredentialSchemas(BaseModel): + """Reference schemas for `credentials` per `db_type` (Swagger-only, not used by endpoints).""" + + postgres: PostgresCredentials + mysql: MysqlCredentials + sqlserver: SqlServerCredentials + supabase: SupabaseCredentials + bigquery: BigQueryCredentials + snowflake: SnowflakeCredentials diff --git a/src/pipeline/db_pipeline/__init__.py b/src/pipeline/db_pipeline/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..0ba26e75a2664a43b346a216599827176a5f354b --- /dev/null +++ b/src/pipeline/db_pipeline/__init__.py @@ -0,0 +1,3 @@ +from src.pipeline.db_pipeline.db_pipeline_service import DbPipelineService, db_pipeline_service + +__all__ = ["DbPipelineService", "db_pipeline_service"] diff --git a/src/pipeline/db_pipeline/db_pipeline_service.py b/src/pipeline/db_pipeline/db_pipeline_service.py new file mode 100644 index 0000000000000000000000000000000000000000..837a33fb50f93a04239a7318cf1cbae6611f8d50 --- /dev/null +++ b/src/pipeline/db_pipeline/db_pipeline_service.py @@ -0,0 +1,197 @@ +"""Service for ingesting a user's external database into the vector store. + +End-to-end flow: connect -> introspect schema -> profile columns -> build text +-> embed + store in the shared PGVector collection (tagged with +`source_type="database"`, retrievable via the same retriever used for docs). + +Sync DB work (SQLAlchemy inspect, pandas read_sql) runs in a threadpool; +async vector writes stay on the event loop. +""" + +import asyncio +from contextlib import contextmanager +from typing import Any, Iterator, Optional + +from langchain_core.documents import Document as LangChainDocument +from sqlalchemy import URL, create_engine +from sqlalchemy.engine import Engine + +from src.db.postgres.vector_store import get_vector_store +from src.middlewares.logging import get_logger +from src.models.credentials import DbType +from src.pipeline.db_pipeline.extractor import get_schema, profile_table + +logger = get_logger("db_pipeline") + + +class DbPipelineService: + """End-to-end DB ingestion: connect -> introspect -> profile -> embed -> store.""" + + def connect(self, db_type: DbType, credentials: dict[str, Any]) -> Engine: + """Build a SQLAlchemy engine for the user's database. + + `credentials` is the plaintext dict matching the per-type schema in + `src/models/credentials.py`. BigQuery/Snowflake auth models differ + from host/port/user/pass, so every shape flows through one dict. + + Optional driver imports (snowflake-sqlalchemy, json for BigQuery) are + done lazily so an env missing one driver doesn't break module import. + """ + logger.info("connecting to user db", db_type=db_type) + + if db_type in ("postgres", "supabase"): + query = ( + {"sslmode": credentials["ssl_mode"]} if credentials.get("ssl_mode") else {} + ) + url = URL.create( + drivername="postgresql+psycopg2", + username=credentials["username"], + password=credentials["password"], + host=credentials["host"], + port=credentials["port"], + database=credentials["database"], + query=query, + ) + return create_engine(url) + + if db_type == "mysql": + url = URL.create( + drivername="mysql+pymysql", + username=credentials["username"], + password=credentials["password"], + host=credentials["host"], + port=credentials["port"], + database=credentials["database"], + ) + # pymysql only activates TLS when the `ssl` dict is truthy + # (empty dict is falsy and silently disables TLS). Use system- + # default CAs via certifi + hostname verification — required by + # managed MySQL providers like TiDB Cloud / PlanetScale / Aiven. + if credentials.get("ssl", True): + import certifi + + connect_args = { + "ssl": { + "ca": certifi.where(), + "check_hostname": True, + } + } + else: + connect_args = {} + return create_engine(url, connect_args=connect_args) + + if db_type == "sqlserver": + # `driver` applies to pyodbc only; we ship pymssql. Accept-and-ignore + # keeps the credential schema stable. + if credentials.get("driver"): + logger.info( + "sqlserver driver hint ignored (using pymssql)", + driver=credentials["driver"], + ) + url = URL.create( + drivername="mssql+pymssql", + username=credentials["username"], + password=credentials["password"], + host=credentials["host"], + port=credentials["port"], + database=credentials["database"], + ) + return create_engine(url) + + if db_type == "bigquery": + import json + + sa_info = json.loads(credentials["service_account_json"]) + # sqlalchemy-bigquery URL shape: bigquery:/// + url = f"bigquery://{credentials['project_id']}/{credentials['dataset_id']}" + return create_engine( + url, + credentials_info=sa_info, + location=credentials.get("location", "US"), + ) + + if db_type == "snowflake": + from snowflake.sqlalchemy import URL as SnowflakeURL + + url = SnowflakeURL( + account=credentials["account"], + user=credentials["username"], + password=credentials["password"], + database=credentials["database"], + schema=( + credentials.get("db_schema") + or credentials.get("schema") + or "PUBLIC" + ), + warehouse=credentials["warehouse"], + role=credentials.get("role") or "", + ) + return create_engine(url) + + raise ValueError(f"Unsupported db_type: {db_type}") + + @contextmanager + def engine_scope( + self, db_type: DbType, credentials: dict[str, Any] + ) -> Iterator[Engine]: + """Yield a connected Engine and dispose its pool on exit. + + API callers should prefer this over raw `connect(...)` so user DB + connection pools do not leak between pipeline runs. + """ + engine = self.connect(db_type, credentials) + try: + yield engine + finally: + engine.dispose() + + def _to_document( + self, user_id: str, table_name: str, entry: dict + ) -> LangChainDocument: + col = entry["col"] + return LangChainDocument( + page_content=entry["text"], + metadata={ + "user_id": user_id, + "source_type": "database", + "data": { + "table_name": table_name, + "column_name": col["name"], + "column_type": col["type"], + "is_primary_key": col.get("is_primary_key", False), + "foreign_key": col.get("foreign_key"), + }, + }, + ) + + async def run( + self, + user_id: str, + engine: Engine, + exclude_tables: Optional[frozenset[str]] = None, + ) -> int: + """Introspect the user's DB, profile columns, embed descriptions, store in PGVector. + + Returns: + Total number of chunks ingested. + """ + vector_store = get_vector_store() + logger.info("db pipeline start", user_id=user_id) + + schema = await asyncio.to_thread(get_schema, engine, exclude_tables) + + total = 0 + for table_name, columns in schema.items(): + logger.info("profiling table", table=table_name, columns=len(columns)) + entries = await asyncio.to_thread(profile_table, engine, table_name, columns) + docs = [self._to_document(user_id, table_name, e) for e in entries] + if docs: + await vector_store.aadd_documents(docs) + total += len(docs) + logger.info("ingested chunks", table=table_name, count=len(docs)) + + logger.info("db pipeline complete", user_id=user_id, total=total) + return total + + +db_pipeline_service = DbPipelineService() diff --git a/src/pipeline/db_pipeline/extractor.py b/src/pipeline/db_pipeline/extractor.py new file mode 100644 index 0000000000000000000000000000000000000000..3de4444d09ab9b2a63a412a0aed98bdcfb1fa5a3 --- /dev/null +++ b/src/pipeline/db_pipeline/extractor.py @@ -0,0 +1,213 @@ +"""Schema introspection and per-column profiling for a user's database. + +Identifiers (table/column names) are quoted via the engine's dialect preparer, +which handles reserved words, mixed case, and embedded quotes correctly across +dialects. Values used in SQL come from SQLAlchemy inspection of the DB itself, +not user input. +""" + +from typing import Optional + +import pandas as pd +from sqlalchemy import Float, Integer, Numeric, inspect +from sqlalchemy.engine import Engine + +from src.middlewares.logging import get_logger + +logger = get_logger("db_extractor") + +TOP_VALUES_THRESHOLD = 0.05 # show top values if distinct_ratio <= 5% + +# Dialects where PERCENTILE_CONT(...) WITHIN GROUP is supported as an aggregate. +# MySQL has no percentile aggregate; BigQuery has PERCENTILE_CONT only as an +# analytic (window) function — both drop median and keep min/max/mean. +_MEDIAN_DIALECTS = frozenset({"postgresql", "mssql", "snowflake"}) + + +def _supports_median(engine: Engine) -> bool: + return engine.dialect.name in _MEDIAN_DIALECTS + + +def _head_query( + engine: Engine, + select_clause: str, + from_clause: str, + n: int, + order_by: str = "", +) -> str: + """LIMIT/TOP-equivalent head query for the engine's dialect.""" + if engine.dialect.name == "mssql": + return f"SELECT TOP {n} {select_clause} FROM {from_clause} {order_by}".strip() + return f"SELECT {select_clause} FROM {from_clause} {order_by} LIMIT {n}".strip() + + +def _qi(engine: Engine, name: str) -> str: + """Dialect-correct identifier quoting (schema.table also handled if dotted).""" + preparer = engine.dialect.identifier_preparer + if "." in name: + schema, _, table = name.partition(".") + return f"{preparer.quote(schema)}.{preparer.quote(table)}" + return preparer.quote(name) + + +def get_schema( + engine: Engine, exclude_tables: Optional[frozenset[str]] = None +) -> dict[str, list[dict]]: + """Returns {table_name: [{name, type, is_numeric, is_primary_key, foreign_key}, ...]}.""" + exclude = exclude_tables or frozenset() + inspector = inspect(engine) + schema = {} + for table_name in inspector.get_table_names(): + if table_name in exclude: + continue + + pk = inspector.get_pk_constraint(table_name) + pk_cols = set(pk["constrained_columns"]) if pk else set() + + fk_map = {} + for fk in inspector.get_foreign_keys(table_name): + for col, ref_col in zip(fk["constrained_columns"], fk["referred_columns"]): + fk_map[col] = f"{fk['referred_table']}.{ref_col}" + + cols = inspector.get_columns(table_name) + schema[table_name] = [ + { + "name": c["name"], + "type": str(c["type"]), + "is_numeric": isinstance(c["type"], (Integer, Numeric, Float)), + "is_primary_key": c["name"] in pk_cols, + "foreign_key": fk_map.get(c["name"]), + } + for c in cols + ] + logger.info("extracted schema", table_count=len(schema)) + return schema + + +def get_row_count(engine: Engine, table_name: str) -> int: + return pd.read_sql(f"SELECT COUNT(*) FROM {_qi(engine, table_name)}", engine).iloc[0, 0] + + +def profile_column( + engine: Engine, + table_name: str, + col_name: str, + is_numeric: bool, + row_count: int, +) -> dict: + """Returns null_count, distinct_count, min/max, top values, and sample values.""" + if row_count == 0: + return { + "null_count": 0, + "distinct_count": 0, + "distinct_ratio": 0.0, + "sample_values": [], + } + + qt = _qi(engine, table_name) + qc = _qi(engine, col_name) + + # Combined stats query: null_count, distinct_count, and min/max (if numeric). + # One round-trip instead of two. + select_cols = [ + f"COUNT(*) - COUNT({qc}) AS nulls", + f"COUNT(DISTINCT {qc}) AS distincts", + ] + if is_numeric: + select_cols.append(f"MIN({qc}) AS min_val") + select_cols.append(f"MAX({qc}) AS max_val") + select_cols.append(f"AVG({qc}) AS mean_val") + if _supports_median(engine): + select_cols.append( + f"PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY {qc}) AS median_val" + ) + stats = pd.read_sql(f"SELECT {', '.join(select_cols)} FROM {qt}", engine) + + null_count = int(stats.iloc[0]["nulls"]) + distinct_count = int(stats.iloc[0]["distincts"]) + distinct_ratio = distinct_count / row_count if row_count > 0 else 0 + + profile = { + "null_count": null_count, + "distinct_count": distinct_count, + "distinct_ratio": round(distinct_ratio, 4), + } + + if is_numeric: + profile["min"] = stats.iloc[0]["min_val"] + profile["max"] = stats.iloc[0]["max_val"] + profile["mean"] = stats.iloc[0]["mean_val"] + if _supports_median(engine): + profile["median"] = stats.iloc[0]["median_val"] + + if 0 < distinct_ratio <= TOP_VALUES_THRESHOLD: + top_sql = _head_query( + engine, + select_clause=f"{qc}, COUNT(*) AS cnt", + from_clause=f"{qt} GROUP BY {qc}", + n=10, + order_by="ORDER BY cnt DESC", + ) + top = pd.read_sql(top_sql, engine) + profile["top_values"] = list(zip(top[col_name].tolist(), top["cnt"].tolist())) + + sample = pd.read_sql(_head_query(engine, qc, qt, 5), engine) + profile["sample_values"] = sample[col_name].tolist() + + return profile + + +def profile_table(engine: Engine, table_name: str, columns: list[dict]) -> list[dict]: + """Profile every column in a table. Returns [{col, profile, text}, ...]. + + Per-column errors are logged and skipped so one bad column doesn't abort + the whole table. + """ + row_count = get_row_count(engine, table_name) + if row_count == 0: + logger.info("skipping empty table", table=table_name) + return [] + + results = [] + for col in columns: + try: + profile = profile_column( + engine, table_name, col["name"], col.get("is_numeric", False), row_count + ) + text = build_text(table_name, row_count, col, profile) + results.append({"col": col, "profile": profile, "text": text}) + except Exception as e: + logger.error( + "column profiling failed", + table=table_name, + column=col["name"], + error=str(e), + ) + continue + return results + + +def build_text(table_name: str, row_count: int, col: dict, profile: dict) -> str: + col_name = col["name"] + col_type = col["type"] + + key_label = "" + if col.get("is_primary_key"): + key_label = " [PRIMARY KEY]" + elif col.get("foreign_key"): + key_label = f" [FK -> {col['foreign_key']}]" + + text = f"Table: {table_name} ({row_count} rows)\n" + text += f"Column: {col_name} ({col_type}){key_label}\n" + text += f"Null count: {profile['null_count']}\n" + text += f"Distinct count: {profile['distinct_count']} ({profile['distinct_ratio']:.1%})\n" + if "min" in profile: + text += f"Min: {profile['min']}, Max: {profile['max']}\n" + text += f"Mean: {profile['mean']}\n" + if profile.get("median") is not None: + text += f"Median: {profile['median']}\n" + if "top_values" in profile: + top_str = ", ".join(f"{v} ({c})" for v, c in profile["top_values"]) + text += f"Top values: {top_str}\n" + text += f"Sample values: {profile['sample_values']}" + return text diff --git a/src/pipeline/document_pipeline/__init__.py b/src/pipeline/document_pipeline/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/src/pipeline/document_pipeline/document_pipeline.py b/src/pipeline/document_pipeline/document_pipeline.py new file mode 100644 index 0000000000000000000000000000000000000000..5a40a0bf68038538342766916c6f97093346bc85 --- /dev/null +++ b/src/pipeline/document_pipeline/document_pipeline.py @@ -0,0 +1,80 @@ +"""Document upload and processing pipeline.""" + +from fastapi import HTTPException, UploadFile +from sqlalchemy.ext.asyncio import AsyncSession + +from src.document.document_service import document_service +from src.knowledge.processing_service import knowledge_processor +from src.middlewares.logging import get_logger +from src.storage.az_blob.az_blob import blob_storage + +logger = get_logger("document_pipeline") + +SUPPORTED_FILE_TYPES = ["pdf", "docx", "txt", "csv", "xlsx"] + + +class DocumentPipeline: + """Orchestrates the full document upload, process, and delete flows.""" + + async def upload(self, file: UploadFile, user_id: str, db: AsyncSession) -> dict: + """Validate → upload to blob → save to DB.""" + content = await file.read() + file_type = file.filename.split(".")[-1].lower() if "." in file.filename else "txt" + + if file_type not in SUPPORTED_FILE_TYPES: + raise HTTPException( + status_code=400, + detail=f"Unsupported file type. Supported: {SUPPORTED_FILE_TYPES}", + ) + + blob_name = await blob_storage.upload_file(content, file.filename, user_id) + document = await document_service.create_document( + db=db, + user_id=user_id, + filename=file.filename, + blob_name=blob_name, + file_size=len(content), + file_type=file_type, + ) + + logger.info(f"Uploaded document {document.id} for user {user_id}") + return {"id": document.id, "filename": document.filename, "status": document.status} + + async def process(self, document_id: str, user_id: str, db: AsyncSession) -> dict: + """Validate ownership → extract text → chunk → ingest to vector store.""" + document = await document_service.get_document(db, document_id) + + if not document: + raise HTTPException(status_code=404, detail="Document not found") + if document.user_id != user_id: + raise HTTPException(status_code=403, detail="Access denied") + + try: + await document_service.update_document_status(db, document_id, "processing") + chunks_count = await knowledge_processor.process_document(document, db) + await document_service.update_document_status(db, document_id, "completed") + + logger.info(f"Processed document {document_id}: {chunks_count} chunks") + return {"document_id": document_id, "chunks_processed": chunks_count} + + except Exception as e: + logger.error(f"Processing failed for document {document_id}", error=str(e)) + await document_service.update_document_status(db, document_id, "failed", str(e)) + raise HTTPException(status_code=500, detail=f"Processing failed: {str(e)}") + + async def delete(self, document_id: str, user_id: str, db: AsyncSession) -> dict: + """Validate ownership → delete from blob and DB.""" + document = await document_service.get_document(db, document_id) + + if not document: + raise HTTPException(status_code=404, detail="Document not found") + if document.user_id != user_id: + raise HTTPException(status_code=403, detail="Access denied") + + await document_service.delete_document(db, document_id) + + logger.info(f"Deleted document {document_id} for user {user_id}") + return {"document_id": document_id} + + +document_pipeline = DocumentPipeline() diff --git a/src/utils/db_credential_encryption.py b/src/utils/db_credential_encryption.py new file mode 100644 index 0000000000000000000000000000000000000000..04c1b98cd5babbc69ffcf200075b4dbb87c7eac0 --- /dev/null +++ b/src/utils/db_credential_encryption.py @@ -0,0 +1,70 @@ +"""Fernet encryption utilities for user-registered database credentials. + +Encryption key is sourced from `dataeyond__db__credential__key` env variable, +intentionally separate from the user-auth bcrypt salt (`emarcal__bcrypt__salt`). + +Usage: + from src.utils.db_credential_encryption import encrypt_credentials_dict, decrypt_credentials_dict + + # Before INSERT: + safe_creds = encrypt_credentials_dict(raw_credentials) + + # After SELECT: + plain_creds = decrypt_credentials_dict(row.credentials) +""" + +from cryptography.fernet import Fernet +from src.config.settings import settings + +# Sensitive credential field names that must be encrypted at rest. +# Covers all supported DB types: +# - password : postgres, mysql, sqlserver, supabase, snowflake +# - service_account_json : bigquery +SENSITIVE_FIELDS: frozenset[str] = frozenset({"password", "service_account_json"}) + + +def _get_cipher() -> Fernet: + key = settings.dataeyond_db_credential_key + if not key: + raise ValueError( + "dataeyond__db__credential__key is not set. " + "Generate one with: Fernet.generate_key().decode()" + ) + return Fernet(key.encode()) + + +def encrypt_credential(value: str) -> str: + """Encrypt a single credential string value.""" + return _get_cipher().encrypt(value.encode()).decode() + + +def decrypt_credential(value: str) -> str: + """Decrypt a single Fernet-encrypted credential string.""" + return _get_cipher().decrypt(value.encode()).decode() + + +def encrypt_credentials_dict(creds: dict) -> dict: + """Return a copy of the credentials dict with sensitive fields encrypted. + + Call this before inserting a new DatabaseClient record. + """ + cipher = _get_cipher() + result = dict(creds) + for field in SENSITIVE_FIELDS: + if result.get(field): + result[field] = cipher.encrypt(result[field].encode()).decode() + return result + + +def decrypt_credentials_dict(creds: dict) -> dict: + """Return a copy of the credentials dict with sensitive fields decrypted. + + Call this after fetching a DatabaseClient record from DB. + """ + cipher = _get_cipher() + result = dict(creds) + for field in SENSITIVE_FIELDS: + if result.get(field): + result[field] = cipher.decrypt(result[field].encode()).decode() + return result + \ No newline at end of file diff --git a/uv.lock b/uv.lock index 60ad7363ccd77db05cac154b504a0e6b6e1aeb35..eaee70247eccf1228c95d317d122fd3866b47a72 100644 --- a/uv.lock +++ b/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 2 +revision = 3 requires-python = "==3.12.*" resolution-markers = [ "python_full_version >= '3.12.4'", @@ -49,6 +49,8 @@ dependencies = [ { name = "pydantic" }, { name = "pydantic-settings" }, { name = "pymongo" }, + { name = "pymssql" }, + { name = "pymysql" }, { name = "pypdf" }, { name = "python-docx" }, { name = "python-dotenv" }, @@ -57,8 +59,10 @@ dependencies = [ { name = "redis" }, { name = "sentence-transformers" }, { name = "slowapi" }, + { name = "snowflake-sqlalchemy" }, { name = "spacy" }, { name = "sqlalchemy", extra = ["asyncio"] }, + { name = "sqlalchemy-bigquery" }, { name = "sse-starlette" }, { name = "starlette" }, { name = "structlog" }, @@ -131,6 +135,8 @@ requires-dist = [ { name = "pydantic", specifier = "==2.10.3" }, { name = "pydantic-settings", specifier = "==2.7.0" }, { name = "pymongo", specifier = ">=4.14.0" }, + { name = "pymssql", specifier = ">=2.3.0" }, + { name = "pymysql", specifier = ">=1.1.1" }, { name = "pypdf", specifier = "==5.1.0" }, { name = "pytest", marker = "extra == 'dev'", specifier = "==8.3.4" }, { name = "pytest-asyncio", marker = "extra == 'dev'", specifier = "==0.24.0" }, @@ -143,8 +149,10 @@ requires-dist = [ { name = "ruff", marker = "extra == 'dev'", specifier = "==0.8.4" }, { name = "sentence-transformers", specifier = "==3.3.1" }, { name = "slowapi", specifier = "==0.1.9" }, + { name = "snowflake-sqlalchemy", specifier = ">=1.7.0" }, { name = "spacy", specifier = "==3.8.3" }, { name = "sqlalchemy", extras = ["asyncio"], specifier = "==2.0.36" }, + { name = "sqlalchemy-bigquery", specifier = ">=1.11.0" }, { 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