update engine path - Adithya S Kolavi

backend/app/api/admin/route.py

@@ -17,7 +17,7 @@
 from llama_index.core.ingestion import IngestionPipeline
 from llama_index.core.node_parser import SentenceSplitter
 from llama_index.core.settings import Settings
-from app.engine.vectordb import get_vector_store
+from app.api.chat.engine.vectordb import get_vector_store
 from llama_index.core import SimpleDirectoryReader
 from llama_index.core.schema import Document
 

backend/app/api/chat/chat_config.py

@@ -11,16 +11,6 @@
 logger = logging.getLogger("uvicorn")
 
 
-# @r.get("")
-# async def chat_config() -> ChatConfig:
-#     starter_questions = None
-#     # conversation_starters = os.getenv("CONVERSATION_STARTERS")
-#     conversation_starters = "Tell me about CognitiveLab \n What are some open source projects  \n Tell me about Open Source AI \n What are AI Agents"
-#     if conversation_starters and conversation_starters.strip():
-#         starter_questions = conversation_starters.strip().split("\n")
-#     return ChatConfig(starter_questions=starter_questions)
-
-
 @r.get("")
 async def chat_config() -> ChatConfig:
     return await config_service.get_chat_config()

backend/app/engine/engine.py → backend/app/api/chat/engine/engine.py

@@ -1,7 +1,7 @@
 import os
 
-from app.engine.index import get_index
-from app.engine.node_postprocessors import NodeCitationProcessor
+from app.api.chat.engine.index import get_index
+from app.api.chat.engine.node_postprocessors import NodeCitationProcessor
 from fastapi import HTTPException
 from llama_index.core.chat_engine import CondensePlusContextChatEngine
 

backend/app/engine/generate.py → backend/app/api/chat/engine/generate.py

@@ -6,8 +6,8 @@
 import logging
 import os
 
-from app.engine.loaders import get_documents
-from app.engine.vectordb import get_vector_store
+from app.api.chat.engine.loaders import get_documents
+from app.api.chat.engine.vectordb import get_vector_store
 from app.settings import init_settings
 from llama_index.core.ingestion import IngestionPipeline
 from llama_index.core.node_parser import SentenceSplitter

backend/app/engine/index.py → backend/app/api/chat/engine/index.py

@@ -1,6 +1,6 @@
 import logging
 from llama_index.core.indices import VectorStoreIndex
-from app.engine.vectordb import get_vector_store
+from app.api.chat.engine.vectordb import get_vector_store
 
 
 logger = logging.getLogger("uvicorn")

backend/app/engine/loaders/__init__.py → backend/app/api/chat/engine/loaders/__init__.py

@@ -1,9 +1,9 @@
 import logging
 
 import yaml
-from app.engine.loaders.db import DBLoaderConfig, get_db_documents
-from app.engine.loaders.file import FileLoaderConfig, get_file_documents
-from app.engine.loaders.web import WebLoaderConfig, get_web_documents
+from app.api.chat.engine.loaders.db import DBLoaderConfig, get_db_documents
+from app.api.chat.engine.loaders.file import FileLoaderConfig, get_file_documents
+from app.api.chat.engine.loaders.web import WebLoaderConfig, get_web_documents
 
 logger = logging.getLogger(__name__)
 

backend/app/api/chat/route.py

@@ -20,8 +20,8 @@
     SourceNodes,
 )
 from app.api.chat.vercel_response import VercelStreamResponse
-from app.engine import get_chat_engine
-from app.engine.query_filter import generate_filters
+from app.api.chat.engine import get_chat_engine
+from app.api.chat.engine.query_filter import generate_filters
 from app.models.user_model import User
 from app.core.user import get_current_user
 from app.api.chat.summary import summary_generator
@@ -184,7 +184,7 @@ async def enhanced_content_generator():
 # ):
 #     try:
 #         # Start background tasks to download documents from LlamaCloud if needed
-#         from app.engine.service import LLamaCloudFileService
+#         from app.api.chat.engine.service import LLamaCloudFileService
 
 #         LLamaCloudFileService.download_files_from_nodes(nodes, background_tasks)
 #     except ImportError:

backend/app/api/chat/services/file.py

@@ -6,7 +6,7 @@
 from typing import Any, List, Tuple
 
 
-from app.engine.index import get_index
+from app.api.chat.engine.index import get_index
 from llama_index.core import VectorStoreIndex
 from llama_index.core.ingestion import IngestionPipeline
 from llama_index.core.readers.file.base import (
@@ -18,8 +18,8 @@
 
 
 def get_llamaparse_parser():
-    from app.engine.loaders import load_configs
-    from app.engine.loaders.file import FileLoaderConfig, llama_parse_parser
+    from app.api.chat.engine.loaders import load_configs
+    from app.api.chat.engine.loaders.file import FileLoaderConfig, llama_parse_parser
 
     config = load_configs()
     file_loader_config = FileLoaderConfig(**config["file"])
@@ -81,7 +81,7 @@ def process_file(file_name: str, base64_content: str, params: Any) -> List[str]:
 
         # Insert the documents into the index
         if isinstance(current_index, LlamaCloudIndex):
-            from app.engine.service import LLamaCloudFileService
+            from app.api.chat.engine.service import LLamaCloudFileService
 
             project_id = current_index._get_project_id()
             pipeline_id = current_index._get_pipeline_id()

backend/app/core/config.py

@@ -10,10 +10,10 @@ class Settings(BaseSettings):
     JWT_SECRET_KEY: str = config("JWT_SECRET_KEY", cast=str)
     JWT_REFRESH_SECRET_KEY: str = config("JWT_REFRESH_SECRET_KEY", cast=str)
     ALGORITHM: ClassVar[str] = "HS256"
-    ACCESS_TOKEN_EXPIRE_MINUTES: int = 60
+    ACCESS_TOKEN_EXPIRE_MINUTES: int = 60 * 24
     REFRESH_TOKEN_EXPIRE_MINUTES: int = 60 * 24 * 7  # 7 days
     BACKEND_CORS_ORIGINS: List[AnyHttpUrl] = ["http://localhost:3000"]
-    PROJECT_NAME: str = "FODOIST"
+    PROJECT_NAME: str = "RAGSAAS"
     COOKIE_SECURE: bool = False
 
     # Database

backend/pyproject.toml

@@ -7,7 +7,7 @@ authors = [ "Adithya S K <Adithyaskolavi@gmail.com>" ]
 readme = "README.md"
 
 [tool.poetry.scripts]
-generate = "app.engine.generate:generate_datasource"
+generate = "app.api.chat.engine.generate:generate_datasource"
 
 [tool.poetry.dependencies]
 python = ">=3.11,<3.12"