fixed lint errors

swarms/server/async_parent_document_retriever.py

@@ -1,6 +1,8 @@
+""" AsyncParentDocumentRetriever is used by RAG
+to split up documents into smaller *and* larger related chunks. """
 import pickle
 import uuid
-from typing import ClassVar, Collection, List, Optional, Tuple
+from typing import Any, ClassVar, Collection, List, Optional, Tuple
 
 from langchain.callbacks.manager import (
     AsyncCallbackManagerForRetrieverRun,
@@ -161,6 +163,7 @@ class AsyncParentDocumentRetriever(ParentDocumentRetriever):
         documents: List[Document],
         ids: Optional[List[str]] = None,
         add_to_docstore: bool = True,
+        **kwargs: Any
     ) -> None:
         """Adds documents to the docstore and vectorstores.
 
@@ -215,6 +218,7 @@ class AsyncParentDocumentRetriever(ParentDocumentRetriever):
         documents: List[Document],
         ids: Optional[List[str]] = None,
         add_to_docstore: bool = True,
+        **kwargs: Any
     ) -> None:
         """Adds documents to the docstore and vectorstores.
 
@@ -251,7 +255,7 @@ class AsyncParentDocumentRetriever(ParentDocumentRetriever):
 
         if len(documents) < 1:
             return
-        
+
         for i, doc in enumerate(documents):
             _id = doc_ids[i]
             sub_docs = self.child_splitter.split_documents([doc])
@@ -275,4 +279,4 @@ class AsyncParentDocumentRetriever(ParentDocumentRetriever):
                 serialized_docs = [(id, pickle.dumps(doc)) for id, doc in full_docs]
                 self.docstore.mset(serialized_docs)
             else:
-                self.docstore.mset(full_docs)
+                self.docstore.mset(full_docs)

swarms/server/responses.py

@@ -1,22 +1,19 @@
-from typing import Any
+""" Customized Langchain StreamingResponse for Server-Side Events (SSE) """
 import asyncio
 from functools import partial
 from typing import Any
 
 from fastapi import status
 from langchain.chains.base import Chain
-from starlette.types import Send
-from fastapi import status
 from sse_starlette import ServerSentEvent
-from sse_starlette.sse import EventSourceResponse
+from sse_starlette.sse import EventSourceResponse, ensure_bytes
 from starlette.types import Send
 
 from swarms.server.utils import StrEnum
 
-from sse_starlette.sse import ensure_bytes
-
 
 class HTTPStatusDetail(StrEnum):
+    """ HTTP error descriptions. """
     INTERNAL_SERVER_ERROR = "Internal Server Error"
 
 
@@ -24,13 +21,14 @@ class StreamingResponse(EventSourceResponse):
     """`Response` class for streaming server-sent events.
 
     Follows the
-    [EventSource protocol](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events#interfaces)
+    [EventSource protocol]
+    (https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events#interfaces)
     """
 
     def __init__(
         self,
-        content: Any = iter(()),
         *args: Any,
+        content: Any = iter(()),
         **kwargs: dict[str, Any],
     ) -> None:
         """Constructor method.
@@ -97,10 +95,10 @@ class LangchainStreamingResponse(StreamingResponse):
 
     def __init__(
         self,
+        *args: Any,
         chain: Chain,
         config: dict[str, Any],
         run_mode: ChainRunMode = ChainRunMode.ASYNC,
-        *args: Any,
         **kwargs: dict[str, Any],
     ) -> None:
         """Constructor method.
@@ -146,8 +144,6 @@ class LangchainStreamingResponse(StreamingResponse):
                     callback.send = send
 
         try:
-            # TODO: migrate to `.ainvoke` when adding support
-            # for LCEL
             if self.run_mode == ChainRunMode.ASYNC:
                 async for outputs in self.chain.astream(input=self.config):
                     if 'answer' in outputs:
@@ -156,7 +152,11 @@ class LangchainStreamingResponse(StreamingResponse):
                         )
                         # Send each chunk with the appropriate body type
                         await send(
-                            {"type": "http.response.body", "body": ensure_bytes(chunk, None), "more_body": True}
+                            {
+                                "type": "http.response.body", 
+                                "body": ensure_bytes(chunk, None), 
+                                "more_body": True
+                            }
                         )
 
             else:
@@ -185,4 +185,4 @@ class LangchainStreamingResponse(StreamingResponse):
                 }
             )
 
-        await send({"type": "http.response.body", "body": b"", "more_body": False})
+        await send({"type": "http.response.body", "body": b"", "more_body": False})

swarms/server/server_models.py

@@ -1,3 +1,4 @@
+""" Chatbot Server API Models """
 try:
     from enum import StrEnum
 except ImportError:
@@ -7,45 +8,48 @@ from pydantic import BaseModel
 from swarms.prompts import QA_PROMPT_TEMPLATE_STR as DefaultSystemPrompt
 
 class AIModel(BaseModel):
+    """ Defines the model a user selected. """
     id: str
     name: str
     maxLength: int
     tokenLimit: int
 
 
-class AIModels(BaseModel):
-    models: list[AIModel]
-
-
 class State(StrEnum):
-    Unavailable = "Unavailable"
-    InProcess = "InProcess"
-    Processed = "Processed"
+    """ State of RAGFile that's been uploaded. """
+    UNAVAILABLE = "UNAVAILABLE"
+    PROCESSING = "PROCESSING"
+    PROCESSED = "PROCESSED"
 
 
 class RAGFile(BaseModel):
+    """ Defines a file uploaded by the users for RAG processing. """
     filename: str
     title: str
     username: str
-    state: State = State.Unavailable
+    state: State = State.UNAVAILABLE
 
 
 class RAGFiles(BaseModel):
+    """ Defines a list of RAGFile objects. """
     files: list[RAGFile]
 
 
 class Role(StrEnum):
+    """ The role of a message in a conversation. """
     SYSTEM = "system"
     ASSISTANT = "assistant"
     USER = "user"
 
 
 class Message(BaseModel):
+    """ Defines the type of a Message with a role and content. """
     role: Role
     content: str
 
 
 class ChatRequest(BaseModel):
+    """ The model for a ChatRequest expected by the Chatbot Chat POST endpoint. """
     id: str
     model: AIModel = AIModel(
         id="llama-2-70b.Q5_K_M",
@@ -61,28 +65,3 @@ class ChatRequest(BaseModel):
     temperature: float = 0
     prompt: str = DefaultSystemPrompt
     file: RAGFile = RAGFile(filename="None", title="None", username="None")
-
-
-class LogMessage(BaseModel):
-    message: str
-
-
-class ConversationRequest(BaseModel):
-    id: str
-    name: str
-    title: RAGFile
-    messages: list[Message]
-    model: AIModel
-    prompt: str
-    temperature: float
-    folderId: str | None = None
-
-
-class ProcessRAGFileRequest(BaseModel):
-    filename: str
-    username: str
-
-
-class GetRAGFileStateRequest(BaseModel):
-    filename: str
-    username: str

swarms/server/utils.py

@@ -1,20 +1,10 @@
-# modified from Lanarky source https://github.com/auxon/lanarky
+""" modified from Lanarky source https://github.com/auxon/lanarky """
 from typing import Any
- 
 import pydantic
 from pydantic.fields import FieldInfo
- 
-try:
-    from enum import StrEnum  # type: ignore
-except ImportError:
-    from enum import Enum
- 
-    class StrEnum(str, Enum): ...
- 
- 
 PYDANTIC_V2 = pydantic.VERSION.startswith("2.")
- 
- 
+
+
 def model_dump(model: pydantic.BaseModel, **kwargs) -> dict[str, Any]:
     """Dump a pydantic model to a dictionary.
  
@@ -23,10 +13,10 @@ def model_dump(model: pydantic.BaseModel, **kwargs) -> dict[str, Any]:
     """
     if PYDANTIC_V2:
         return model.model_dump(**kwargs)
-    else:
-        return model.dict(**kwargs)
- 
- 
+
+    return model.dict(**kwargs)
+
+
 def model_dump_json(model: pydantic.BaseModel, **kwargs) -> str:
     """Dump a pydantic model to a JSON string.
  
@@ -35,10 +25,10 @@ def model_dump_json(model: pydantic.BaseModel, **kwargs) -> str:
     """
     if PYDANTIC_V2:
         return model.model_dump_json(**kwargs)
-    else:
-        return model.json(**kwargs)
- 
- 
+
+    return model.json(**kwargs)
+
+
 def model_fields(model: pydantic.BaseModel) -> dict[str, FieldInfo]:
     """Get the fields of a pydantic model.
  
@@ -47,5 +37,5 @@ def model_fields(model: pydantic.BaseModel) -> dict[str, FieldInfo]:
     """
     if PYDANTIC_V2:
         return model.model_fields
-    else:
-        return model.__fields__
+
+    return model.__fields__