fix deprecated langchain stuff

swarms/prompts/conversational_RAG.py

@@ -1,3 +1,4 @@
+""" Prompt templates for Swarms Chatbot """
 from langchain.prompts.prompt import PromptTemplate
 
 B_INST, E_INST = "[INST]", "[/INST]"
@@ -11,7 +12,7 @@ QA_CONDENSE_TEMPLATE_STR = (
     " with the new Standalone Question. \n"
     "Chat History: \n"
     "{chat_history} \n"
-    "Follow Up Question: {input} \n"
+    "Follow Up Question: {question} \n"
     "Standalone Question:"
 )
 
@@ -28,7 +29,7 @@ QA_PROMPT_TEMPLATE_STR = (
     "don't try to make up an answer. \n\n"
     "{context}\n"
     "{chat_history}\n"
-    "{input}\n\n"
+    "{question}\n\n"
     "AI:  Here is the most relevant sentence in the context:  \n"
 )
 
@@ -75,4 +76,4 @@ _SUMMARIZER_INST_TEMPLATE = (
 
 SUMMARY_PROMPT_TEMPLATE = PromptTemplate.from_template(
     template=(_SUMMARIZER_SYS_TEMPLATE + "\n" + _SUMMARIZER_INST_TEMPLATE).strip()
-)
+)

swarms/server/async_parent_document_retriever.py

@@ -11,7 +11,8 @@ from langchain.callbacks.manager import (
 from langchain.retrievers import ParentDocumentRetriever
 from langchain.schema.document import Document
 from langchain.schema.storage import BaseStore
-from langchain.storage import LocalFileStore, RedisStore
+from langchain.storage import LocalFileStore
+from langchain_community.storage import RedisStore
 from langchain.vectorstores.base import VectorStore
 
 

swarms/server/server.py

@@ -113,21 +113,20 @@ langchain.verbose = True
 @asynccontextmanager
 async def lifespan(app: FastAPI):
     """Initializes the vector store in a background task."""
-    print(f"Initializing vector store retrievers for {app.title}.")
     asyncio.create_task(vector_store.init_retrievers())
     yield
 
 
-chatbot = FastAPI(title="Chatbot", lifespan=lifespan)
+app = FastAPI(title="Chatbot", lifespan=lifespan)
 router = APIRouter()
 
 current_dir = os.path.dirname(__file__)
 print("current_dir: " + current_dir)
 static_dir = os.path.join(current_dir, "static")
 print("static_dir:  " + static_dir)
-chatbot.mount(static_dir, StaticFiles(directory=static_dir), name="static")
+app.mount(static_dir, StaticFiles(directory=static_dir), name="static")
 
-chatbot.add_middleware(
+app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
     allow_credentials=True,
@@ -170,7 +169,7 @@ async def create_chain(
     # if llm is VLLMAsync:
     #     llm.max_tokens = max_tokens_to_gen
 
-    retriever = await vector_store.get_retriever()
+    retriever = await vector_store.get_retriever("swarms")
 
     chat_memory = ChatMessageHistory()
     for message in messages:
@@ -222,11 +221,7 @@ async def create_chain(
         verbose=True,
     )
 
-
-router = APIRouter()
-
-
-@router.post(
+@app.post(
     "/chat",
     summary="Chatbot",
     description="Chatbot AI Service",
@@ -252,25 +247,22 @@ async def chat(request: ChatRequest):
         # ],
     }
     return LangchainStreamingResponse(
-        chain,
+        chain=chain,
         config=json_config,
+        run_mode="async"
     )
 
-
-chatbot.include_router(router, tags=["chat"])
-
-
-@chatbot.get("/")
+@app.get("/")
 def root():
     """Swarms Chatbot API Root"""
     return {"message": "Swarms Chatbot API"}
 
 
-@chatbot.get("/favicon.ico")
+@app.get("/favicon.ico")
 def favicon():
     """ Returns a favicon """
     file_name = "favicon.ico"
-    file_path = os.path.join(chatbot.root_path, "static", file_name)
+    file_path = os.path.join(app.root_path, "static", file_name)
     return FileResponse(
         path=file_path,
         headers={
@@ -282,12 +274,12 @@ def favicon():
 logging.basicConfig(level=logging.ERROR)
 
 
-@chatbot.exception_handler(HTTPException)
-async def http_exception_handler(r: Request, exc: HTTPException):
-    """Log and return exception details in response."""
-    logging.error(
-        "HTTPException: %s executing request: %s", exc.detail, r.base_url
-    )
-    return JSONResponse(
-        status_code=exc.status_code, content={"detail": exc.detail}
-    )
+# @app.exception_handler(HTTPException)
+# async def http_exception_handler(r: Request, exc: HTTPException):
+#     """Log and return exception details in response."""
+#     logging.error(
+#         "HTTPException: %s executing request: %s", exc.detail, r.base_url
+#     )
+#     return JSONResponse(
+#         status_code=exc.status_code, content={"detail": exc.detail}
+#     )

swarms/server/server_models.py

@@ -1,8 +1,5 @@
 """ Chatbot Server API Models """
-try:
-    from enum import StrEnum
-except ImportError:
-    from strenum import StrEnum
+from strenum import StrEnum
 
 from pydantic import BaseModel
 from swarms.prompts import QA_PROMPT_TEMPLATE_STR as DefaultSystemPrompt

swarms/server/vector_store.py

@@ -1,21 +1,22 @@
 """ Vector storage with RAG (Retrieval Augmented Generation) support for Markdown."""
 
 import asyncio
+import glob
 import json
 import os
-import glob
 from datetime import datetime
 from typing import Dict
+
 from chromadb.config import Settings
-from langchain.document_loaders.markdown import UnstructuredMarkdownLoader
-from langchain.embeddings import HuggingFaceBgeEmbeddings
+from langchain_community.document_loaders import UnstructuredMarkdownLoader
+from langchain_community.embeddings import HuggingFaceBgeEmbeddings
+from langchain.schema import BaseRetriever
 from langchain.storage import LocalFileStore
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.vectorstores.chroma import Chroma
-from langchain.schema import BaseRetriever
-from swarms.server.async_parent_document_retriever import (
-    AsyncParentDocumentRetriever,
-)
+from langchain_chroma import Chroma
+
+from swarms.server.async_parent_document_retriever import \
+    AsyncParentDocumentRetriever
 
 STORE_TYPE = "local"  # "redis" or "local"
 
@@ -39,8 +40,8 @@ class VectorStorage:
             chunk_size=2000, chunk_overlap=200
         )
         if STORE_TYPE == "redis":
-            from langchain.storage import RedisStore
-            from langchain.utilities.redis import get_client
+            from langchain_community.storage import RedisStore
+            from langchain_community.storage.redis import get_client
 
             username = r"username"
             password = r"password"
@@ -60,9 +61,7 @@ class VectorStorage:
         self.client = self.vectorstore._client
         self.retrievers: Dict[str, BaseRetriever] = {}
         # default retriever for when no collection title is specified
-        self.retrievers[
-            str(self.vectorstore._LANGCHAIN_DEFAULT_COLLECTION_NAME)
-        ] = self.vectorstore.as_retriever()
+        self.retrievers["swarms"] = self.vectorstore.as_retriever()
 
     async def init_retrievers(self, directories: list[str] | None = None):
         """Initializes the vector storage retrievers."""
@@ -235,7 +234,7 @@ class VectorStorage:
     def get_vector_store(self, collection_name: str | None = None) -> Chroma:
         """ get a specific vector store for a collection """
         if collection_name is None or "" or "None":
-            collection_name = "langchain"
+            collection_name = "swarms"
         print("collection_name: " + collection_name)
         vectorstore = Chroma(
             client_settings=self.settings,