[pre-commit.ci] auto fixes from pre-commit.com hooks

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Author: pre-commit-ci[bot]

EdgeCraftRAG/README.md

@@ -110,6 +110,7 @@ docker pull intelanalytics/ipex-llm-serving-xpu:0.8.3-b18
 ```
 
 Generate your nginx config file
+
 ```bash
 export HOST_IP=#your host ip
 export NGINX_PORT=8086 #set port for nginx
@@ -149,6 +150,7 @@ export SELECTED_XPU_1=<which GPU to select to run for container 1>
 ```
 
 start with compose_vllm_multi-arc.yaml
+
 ```bash
 docker compose -f docker_compose/intel/gpu/arc/compose_vllm_multi-arc.yaml --profile ${CONTAINER_COUNT} up -d
 ```

EdgeCraftRAG/chatqna.py

@@ -43,7 +43,7 @@ def add_remote_service(self):
     async def handle_request(self, request: Request):
         input = await request.json()
         stream_opt = input.get("stream", False)
-        input["user"] = request.headers.get("sessionid",None)
+        input["user"] = request.headers.get("sessionid", None)
         chat_request = ChatCompletionRequest.parse_obj(input)
         parameters = LLMParams(
             max_tokens=chat_request.max_tokens if chat_request.max_tokens else 1024,

EdgeCraftRAG/docker_compose/intel/gpu/arc/compose_vllm_multi-arc.yaml

@@ -1,6 +1,6 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
- 
+
 services:
   server:
     image: ${REGISTRY:-opea}/edgecraftrag-server:${TAG:-latest}
@@ -150,4 +150,4 @@ services:
       - multi_container
 networks:
   default:
-    driver: bridge
+    driver: bridge

EdgeCraftRAG/docker_compose/intel/gpu/arc/set_env.sh

@@ -25,4 +25,3 @@ export NGINX_CONFIG_PATH=${NGINX_CONFIG_PATH}
 export SELECTED_XPU_0=${SELECTED_XPU_0}
 export SELECTED_XPU_1=${SELECTED_XPU_1}
 export vLLM_ENDPOINT=${vLLM_ENDPOINT}
-

EdgeCraftRAG/edgecraftrag/api/v1/chatqna.py

@@ -63,4 +63,4 @@ async def ragqna(request: ChatCompletionRequest):
         ragout = RagOut(query=request.messages, contexts=serialized_contexts, response=str(res))
         return ragout
     except Exception as e:
-        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))
+        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))

EdgeCraftRAG/edgecraftrag/api/v1/data.py

@@ -95,7 +95,7 @@ async def delete_file(name):
 
 # Upload & save a file from UI
 @data_app.post(path="/v1/data/file/{file_name}")
-async def upload_file(file_name: str,file: UploadFile = File(...)):
+async def upload_file(file_name: str, file: UploadFile = File(...)):
     if ctx.get_pipeline_mgr().get_active_pipeline() is None:
         raise HTTPException(
             status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Please activate pipeline and upload the file"

EdgeCraftRAG/edgecraftrag/api/v1/knowledge_base.py

@@ -1,8 +1,12 @@
-from fastapi import FastAPI, HTTPException,status
-from edgecraftrag.context import ctx  
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import os
+
 from edgecraftrag.api.v1.data import add_data
 from edgecraftrag.api_schema import DataIn, KnowledgeBaseCreateIn
-import os
+from edgecraftrag.context import ctx
+from fastapi import FastAPI, HTTPException, status
 
 kb_app = FastAPI()
 
@@ -23,11 +27,11 @@ async def get_knowledge_base(knowledge_name: str):
     return kb
 
 
-# Create a new knowledge base 
+# Create a new knowledge base
 @kb_app.post(path="/v1/knowledge")
 async def create_knowledge_base(knowledge: KnowledgeBaseCreateIn):
     try:
-        kb =  ctx.knowledgemgr.create_knowledge_base(knowledge)
+        kb = ctx.knowledgemgr.create_knowledge_base(knowledge)
         if kb.active:
             await update_knowledge_base_handler(kb.get_file_paths())
         return "Create knowledge base successfully"
@@ -60,48 +64,48 @@ async def update_knowledge_base(knowledge: KnowledgeBaseCreateIn):
 
 # Add a files to the  knowledge base
 @kb_app.post(path="/v1/knowledge/{knowledge_name}/files")
-async def add_file_to_knowledge_base(knowledge_name ,file_path: DataIn):
+async def add_file_to_knowledge_base(knowledge_name, file_path: DataIn):
     try:
         kb = ctx.knowledgemgr.get_knowledge_base_by_name_or_id(knowledge_name)
-        if  os.path.isdir(file_path.local_path) :
+        if os.path.isdir(file_path.local_path):
             for root, _, files in os.walk(file_path.local_path):
                 for file in files:
                     file_full_path = os.path.join(root, file)
                     if file_full_path not in kb.get_file_paths():
                         kb.add_file_path(file_full_path)
                     else:
                         raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail="File upload failed")
-        elif os.path.isfile(file_path.local_path)  and file_path.local_path not in kb.get_file_paths():
+        elif os.path.isfile(file_path.local_path) and file_path.local_path not in kb.get_file_paths():
             kb.add_file_path(file_path.local_path)
         else:
             raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="File upload failed")
-        
+
         active_kb = ctx.knowledgemgr.get_active_knowledge_base()
         if active_kb:
-            if active_kb.name == knowledge_name  or active_kb.idx == knowledge_name:  
+            if active_kb.name == knowledge_name or active_kb.idx == knowledge_name:
                 await update_knowledge_base_handler(file_path, add_file=True)
 
-        return "File upload successfully" 
+        return "File upload successfully"
     except ValueError as e:
         raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(e))
 
 
 # Remove a file from the knowledge base
 @kb_app.delete(path="/v1/knowledge/{knowledge_name}/files")
-async def remove_file_from_knowledge_base(knowledge_name ,file_path: DataIn):
+async def remove_file_from_knowledge_base(knowledge_name, file_path: DataIn):
     try:
         kb = ctx.knowledgemgr.get_knowledge_base_by_name_or_id(knowledge_name)
-        if  file_path.local_path in kb.get_file_paths():
+        if file_path.local_path in kb.get_file_paths():
             kb.remove_file_path(file_path.local_path)
         else:
             raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="File remove failure")
 
         file_path = kb.get_file_paths()
         active_kb = ctx.knowledgemgr.get_active_knowledge_base()
         if active_kb:
-            if active_kb.name == knowledge_name  or active_kb.idx == knowledge_name:
+            if active_kb.name == knowledge_name or active_kb.idx == knowledge_name:
                 await update_knowledge_base_handler(file_path)
-        return f"File deleted successfully"
+        return "File deleted successfully"
     except ValueError as e:
         raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(e))
 
@@ -110,10 +114,10 @@ async def remove_file_from_knowledge_base(knowledge_name ,file_path: DataIn):
 async def update_knowledge_base_handler(file_path=None, add_file: bool = False):
     if ctx.get_pipeline_mgr().get_active_pipeline() is None:
         raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Please activate pipeline")
-    
+
     if add_file and file_path:
         return await add_data(file_path)
-        
+
     elif file_path:
         pl = ctx.get_pipeline_mgr().get_active_pipeline()
         ctx.get_node_mgr().del_nodes_by_np_idx(pl.node_parser.idx)
@@ -123,10 +127,10 @@ async def update_knowledge_base_handler(file_path=None, add_file: bool = False):
             request = DataIn(local_path=file)
             await add_data(request)
         return "Done"
-    
+
     else:
         pl = ctx.get_pipeline_mgr().get_active_pipeline()
         ctx.get_node_mgr().del_nodes_by_np_idx(pl.node_parser.idx)
         pl.indexer.reinitialize_indexer()
         pl.update_indexer_to_retriever()
-        return "Done"
+        return "Done"

EdgeCraftRAG/edgecraftrag/api/v1/prompt.py

@@ -1,6 +1,9 @@
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from edgecraftrag.api_schema import PromptIn
 from edgecraftrag.context import ctx
 from fastapi import FastAPI, File, HTTPException, UploadFile, status
-from edgecraftrag.api_schema import PromptIn
 
 prompt_app = FastAPI()
 
@@ -52,4 +55,4 @@ async def reset_prompt():
             generator.reset_prompt()
             return "Reset LLM Prompt Successfully"
     except Exception as e:
-        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))
+        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))

EdgeCraftRAG/edgecraftrag/api_schema.py

@@ -1,7 +1,7 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-from typing import Optional, Any
+from typing import Any, Optional
 
 from pydantic import BaseModel
 
@@ -76,4 +76,4 @@ class PromptIn(BaseModel):
 class KnowledgeBaseCreateIn(BaseModel):
     name: str
     description: Optional[str] = None
-    active: Optional[bool] = None
+    active: Optional[bool] = None

EdgeCraftRAG/edgecraftrag/components/data.py

@@ -54,7 +54,7 @@ def convert_text_to_documents(text) -> List[Document]:
 def convert_file_to_documents(file_path) -> List[Document]:
     from llama_index.core import SimpleDirectoryReader
 
-    supported_exts = [".pdf", ".txt", ".doc", ".docx", ".pptx", ".ppt", ".csv", ".md", ".html", ".rst",".epub"]
+    supported_exts = [".pdf", ".txt", ".doc", ".docx", ".pptx", ".ppt", ".csv", ".md", ".html", ".rst", ".epub"]
     if file_path.is_dir():
         docs = SimpleDirectoryReader(input_dir=file_path, recursive=True, required_exts=supported_exts).load_data()
     elif file_path.is_file():