diff --git a/README.md b/README.md
index 8c3af2373..e1b48a08c 100644
--- a/README.md
+++ b/README.md
@@ -173,7 +173,6 @@ A `Microservices` can be created by using the decorator `register_microservice`.
 
 ```python
 from langchain_community.embeddings import HuggingFaceHubEmbeddings
-from langsmith import traceable
 
 from comps import register_microservice, EmbedDoc, ServiceType, TextDoc
 
@@ -187,7 +186,6 @@ from comps import register_microservice, EmbedDoc, ServiceType, TextDoc
     input_datatype=TextDoc,
     output_datatype=EmbedDoc,
 )
-@traceable(run_type="embedding")
 def embedding(input: TextDoc) -> EmbedDoc:
     embed_vector = embeddings.embed_query(input.text)
     res = EmbedDoc(text=input.text, embedding=embed_vector)
diff --git a/comps/agent/langchain/requirements.txt b/comps/agent/langchain/requirements.txt
index 16859ac2c..fa1c4423b 100644
--- a/comps/agent/langchain/requirements.txt
+++ b/comps/agent/langchain/requirements.txt
@@ -11,7 +11,6 @@ langchain-openai
 langchain_community
 langchainhub
 langgraph
-langsmith
 numpy
 
 # used by cloud native
diff --git a/comps/dataprep/milvus/prepare_doc_milvus.py b/comps/dataprep/milvus/prepare_doc_milvus.py
index 143010c06..a293963c4 100644
--- a/comps/dataprep/milvus/prepare_doc_milvus.py
+++ b/comps/dataprep/milvus/prepare_doc_milvus.py
@@ -22,7 +22,6 @@
 from langchain_core.documents import Document
 from langchain_milvus.vectorstores import Milvus
 from langchain_text_splitters import HTMLHeaderTextSplitter
-from langsmith import traceable
 from pyspark import SparkConf, SparkContext
 
 from comps import DocPath, opea_microservices, register_microservice
@@ -167,7 +166,6 @@ async def ingest_link_to_milvus(link_list: List[str]):
 
 
 @register_microservice(name="opea_service@prepare_doc_milvus", endpoint="/v1/dataprep", host="0.0.0.0", port=6010)
-@traceable(run_type="tool")
 async def ingest_documents(
     files: Optional[Union[UploadFile, List[UploadFile]]] = File(None),
     link_list: Optional[str] = Form(None),
@@ -239,7 +237,6 @@ def process_files_wrapper(files):
 @register_microservice(
     name="opea_service@prepare_doc_milvus_file", endpoint="/v1/dataprep/get_file", host="0.0.0.0", port=6011
 )
-@traceable(run_type="tool")
 async def rag_get_file_structure():
     print("[ dataprep - get file ] start to get file structure")
 
@@ -270,7 +267,6 @@ def delete_by_partition_field(my_milvus, partition_field):
 @register_microservice(
     name="opea_service@prepare_doc_milvus_del", endpoint="/v1/dataprep/delete_file", host="0.0.0.0", port=6012
 )
-@traceable(run_type="tool")
 async def delete_single_file(file_path: str = Body(..., embed=True)):
     """Delete file according to `file_path`.
 
diff --git a/comps/dataprep/milvus/requirements.txt b/comps/dataprep/milvus/requirements.txt
index cf088a1c0..48b8be1d9 100644
--- a/comps/dataprep/milvus/requirements.txt
+++ b/comps/dataprep/milvus/requirements.txt
@@ -9,7 +9,6 @@ langchain
 langchain-community
 langchain-text-splitters
 langchain_milvus
-langsmith
 markdown
 numpy
 openai
diff --git a/comps/dataprep/pgvector/langchain/prepare_doc_pgvector.py b/comps/dataprep/pgvector/langchain/prepare_doc_pgvector.py
index efb394991..f46e466ba 100644
--- a/comps/dataprep/pgvector/langchain/prepare_doc_pgvector.py
+++ b/comps/dataprep/pgvector/langchain/prepare_doc_pgvector.py
@@ -13,7 +13,6 @@
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.embeddings import HuggingFaceBgeEmbeddings, HuggingFaceHubEmbeddings
 from langchain_community.vectorstores import PGVector
-from langsmith import traceable
 
 from comps import DocPath, opea_microservices, register_microservice
 from comps.dataprep.utils import (
@@ -174,7 +173,6 @@ async def ingest_link_to_pgvector(link_list: List[str]):
     host="0.0.0.0",
     port=6007,
 )
-@traceable(run_type="tool")
 async def ingest_documents(
     files: Optional[Union[UploadFile, List[UploadFile]]] = File(None), link_list: Optional[str] = Form(None)
 ):
@@ -214,7 +212,6 @@ async def ingest_documents(
 @register_microservice(
     name="opea_service@prepare_doc_pgvector", endpoint="/v1/dataprep/get_file", host="0.0.0.0", port=6007
 )
-@traceable(run_type="tool")
 async def rag_get_file_structure():
     print("[ dataprep - get file ] start to get file structure")
 
@@ -229,7 +226,6 @@ async def rag_get_file_structure():
 @register_microservice(
     name="opea_service@prepare_doc_pgvector", endpoint="/v1/dataprep/delete_file", host="0.0.0.0", port=6007
 )
-@traceable(run_type="tool")
 async def delete_single_file(file_path: str = Body(..., embed=True)):
     """Delete file according to `file_path`.
 
diff --git a/comps/dataprep/pgvector/langchain/requirements.txt b/comps/dataprep/pgvector/langchain/requirements.txt
index 84fd48e52..b5b4f168b 100644
--- a/comps/dataprep/pgvector/langchain/requirements.txt
+++ b/comps/dataprep/pgvector/langchain/requirements.txt
@@ -8,7 +8,6 @@ huggingface_hub
 langchain
 langchain-community
 langchain-text-splitters
-langsmith
 markdown
 numpy
 opentelemetry-api
diff --git a/comps/dataprep/pinecone/prepare_doc_pinecone.py b/comps/dataprep/pinecone/prepare_doc_pinecone.py
index ec0e200a2..cbee8cd94 100644
--- a/comps/dataprep/pinecone/prepare_doc_pinecone.py
+++ b/comps/dataprep/pinecone/prepare_doc_pinecone.py
@@ -14,7 +14,6 @@
 from langchain_community.embeddings import HuggingFaceBgeEmbeddings, HuggingFaceEmbeddings, HuggingFaceHubEmbeddings
 from langchain_pinecone import PineconeVectorStore
 from langchain_text_splitters import HTMLHeaderTextSplitter
-from langsmith import traceable
 from pinecone import Pinecone, ServerlessSpec
 
 from comps import DocPath, opea_microservices, opea_telemetry, register_microservice
@@ -172,7 +171,6 @@ async def ingest_link_to_pinecone(link_list: List[str]):
 
 
 @register_microservice(name="opea_service@prepare_doc_pinecone", endpoint="/v1/dataprep", host="0.0.0.0", port=6007)
-@traceable(run_type="tool")
 async def ingest_documents(
     files: Optional[Union[UploadFile, List[UploadFile]]] = File(None),
     link_list: Optional[str] = Form(None),
@@ -223,7 +221,6 @@ async def ingest_documents(
 @register_microservice(
     name="opea_service@prepare_doc_pinecone_file", endpoint="/v1/dataprep/get_file", host="0.0.0.0", port=6008
 )
-@traceable(run_type="tool")
 async def rag_get_file_structure():
     print("[ dataprep - get file ] start to get file structure")
 
@@ -238,7 +235,6 @@ async def rag_get_file_structure():
 @register_microservice(
     name="opea_service@prepare_doc_pinecone_del", endpoint="/v1/dataprep/delete_file", host="0.0.0.0", port=6009
 )
-@traceable(run_type="tool")
 async def delete_all(file_path: str = Body(..., embed=True)):
     """Delete file according to `file_path`.
 
diff --git a/comps/dataprep/pinecone/requirements.txt b/comps/dataprep/pinecone/requirements.txt
index a2d5c4298..06ab12ecd 100644
--- a/comps/dataprep/pinecone/requirements.txt
+++ b/comps/dataprep/pinecone/requirements.txt
@@ -10,7 +10,6 @@ langchain-community
 langchain-openai
 langchain-pinecone
 langchain-text-splitters
-langsmith
 markdown
 numpy
 opentelemetry-api
diff --git a/comps/dataprep/redis/langchain_ray/prepare_doc_redis_on_ray.py b/comps/dataprep/redis/langchain_ray/prepare_doc_redis_on_ray.py
index c55165061..07ad81da8 100644
--- a/comps/dataprep/redis/langchain_ray/prepare_doc_redis_on_ray.py
+++ b/comps/dataprep/redis/langchain_ray/prepare_doc_redis_on_ray.py
@@ -26,7 +26,6 @@
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.embeddings import HuggingFaceBgeEmbeddings, HuggingFaceHubEmbeddings
 from langchain_community.vectorstores import Redis
-from langsmith import traceable
 
 cur_path = pathlib.Path(__file__).parent.resolve()
 comps_path = os.path.join(cur_path, "../../../../")
@@ -322,7 +321,6 @@ async def ingest_documents(files: List[UploadFile] = File(None), link_list: str
 @register_microservice(
     name="opea_service@prepare_doc_redis_file", endpoint="/v1/dataprep/get_file", host="0.0.0.0", port=6008
 )
-@traceable(run_type="tool")
 async def rag_get_file_structure():
     print("[ get_file_structure] ")
 
@@ -337,7 +335,6 @@ async def rag_get_file_structure():
 @register_microservice(
     name="opea_service@prepare_doc_redis_del", endpoint="/v1/dataprep/delete_file", host="0.0.0.0", port=6009
 )
-@traceable(run_type="tool")
 async def delete_single_file(file_path: str = Body(..., embed=True)):
     """Delete file according to `file_path`.
 
diff --git a/comps/dataprep/redis/langchain_ray/requirements.txt b/comps/dataprep/redis/langchain_ray/requirements.txt
index 50d57b20e..a77ba5c4d 100644
--- a/comps/dataprep/redis/langchain_ray/requirements.txt
+++ b/comps/dataprep/redis/langchain_ray/requirements.txt
@@ -7,7 +7,6 @@ fastapi
 huggingface_hub
 langchain
 langchain-community
-langsmith
 numpy
 opentelemetry-api
 opentelemetry-exporter-otlp
diff --git a/comps/dataprep/redis/llama_index/prepare_doc_redis.py b/comps/dataprep/redis/llama_index/prepare_doc_redis.py
index da176555b..ae4d00461 100644
--- a/comps/dataprep/redis/llama_index/prepare_doc_redis.py
+++ b/comps/dataprep/redis/llama_index/prepare_doc_redis.py
@@ -8,7 +8,6 @@
 
 from config import EMBED_MODEL, INDEX_NAME, REDIS_URL
 from fastapi import Body, File, HTTPException, UploadFile
-from langsmith import traceable
 from llama_index.core import SimpleDirectoryReader, StorageContext, VectorStoreIndex
 from llama_index.core.settings import Settings
 from llama_index.embeddings.huggingface import HuggingFaceEmbedding
@@ -55,7 +54,6 @@ async def ingest_data_to_redis(doc_path: DocPath):
 
 
 @register_microservice(name="opea_service@prepare_doc_redis", endpoint="/v1/dataprep", host="0.0.0.0", port=6007)
-@traceable(run_type="tool")
 # llama index only support upload files now
 async def ingest_documents(files: Optional[Union[UploadFile, List[UploadFile]]] = File(None)):
     print(f"files:{files}")
@@ -81,7 +79,6 @@ async def ingest_documents(files: Optional[Union[UploadFile, List[UploadFile]]]
 @register_microservice(
     name="opea_service@prepare_doc_redis_file", endpoint="/v1/dataprep/get_file", host="0.0.0.0", port=6008
 )
-@traceable(run_type="tool")
 async def rag_get_file_structure():
     print("[ get_file_structure] ")
 
@@ -96,7 +93,6 @@ async def rag_get_file_structure():
 @register_microservice(
     name="opea_service@prepare_doc_redis_del", endpoint="/v1/dataprep/delete_file", host="0.0.0.0", port=6009
 )
-@traceable(run_type="tool")
 async def delete_single_file(file_path: str = Body(..., embed=True)):
     """Delete file according to `file_path`.
 
diff --git a/comps/dataprep/redis/llama_index/requirements.txt b/comps/dataprep/redis/llama_index/requirements.txt
index ad75869c1..2f808e534 100644
--- a/comps/dataprep/redis/llama_index/requirements.txt
+++ b/comps/dataprep/redis/llama_index/requirements.txt
@@ -1,7 +1,6 @@
 docarray[full]
 fastapi
 huggingface_hub
-langsmith
 llama-index
 llama-index-embeddings-huggingface==0.2.0
 llama-index-readers-file
diff --git a/comps/embeddings/langchain-mosec/embedding_mosec.py b/comps/embeddings/langchain-mosec/embedding_mosec.py
index f13c23eca..702b1937c 100644
--- a/comps/embeddings/langchain-mosec/embedding_mosec.py
+++ b/comps/embeddings/langchain-mosec/embedding_mosec.py
@@ -6,7 +6,6 @@
 from typing import List, Optional
 
 from langchain_community.embeddings import OpenAIEmbeddings
-from langsmith import traceable
 
 from comps import (
     EmbedDoc,
@@ -53,7 +52,6 @@ def empty_embedding() -> List[float]:
     input_datatype=TextDoc,
     output_datatype=EmbedDoc,
 )
-@traceable(run_type="embedding")
 @register_statistics(names=["opea_service@embedding_mosec"])
 def embedding(input: TextDoc) -> EmbedDoc:
     start = time.time()
diff --git a/comps/embeddings/langchain/embedding_tei.py b/comps/embeddings/langchain/embedding_tei.py
index 6a5fbc614..a318ff0bf 100644
--- a/comps/embeddings/langchain/embedding_tei.py
+++ b/comps/embeddings/langchain/embedding_tei.py
@@ -6,7 +6,6 @@
 from typing import Union
 
 from langchain_huggingface import HuggingFaceEndpointEmbeddings
-from langsmith import traceable
 
 from comps import (
     EmbedDoc,
@@ -32,7 +31,6 @@
     host="0.0.0.0",
     port=6000,
 )
-@traceable(run_type="embedding")
 @register_statistics(names=["opea_service@embedding_tei_langchain"])
 def embedding(
     input: Union[TextDoc, EmbeddingRequest, ChatCompletionRequest]
diff --git a/comps/embeddings/langchain/requirements.txt b/comps/embeddings/langchain/requirements.txt
index 8f0dd3ad4..1bfe6f44c 100644
--- a/comps/embeddings/langchain/requirements.txt
+++ b/comps/embeddings/langchain/requirements.txt
@@ -3,7 +3,6 @@ fastapi
 huggingface_hub
 langchain
 langchain_huggingface
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/embeddings/llama_index/embedding_tei.py b/comps/embeddings/llama_index/embedding_tei.py
index 4f3920d32..9042a61a7 100644
--- a/comps/embeddings/llama_index/embedding_tei.py
+++ b/comps/embeddings/llama_index/embedding_tei.py
@@ -3,7 +3,6 @@
 
 import os
 
-from langsmith import traceable
 from llama_index.embeddings.text_embeddings_inference import TextEmbeddingsInference
 
 from comps import EmbedDoc, ServiceType, TextDoc, opea_microservices, register_microservice
@@ -18,7 +17,6 @@
     input_datatype=TextDoc,
     output_datatype=EmbedDoc,
 )
-@traceable(run_type="embedding")
 def embedding(input: TextDoc) -> EmbedDoc:
     embed_vector = embeddings._get_query_embedding(input.text)
     res = EmbedDoc(text=input.text, embedding=embed_vector)
diff --git a/comps/embeddings/llama_index/local_embedding.py b/comps/embeddings/llama_index/local_embedding.py
index f6a69afaf..53cc30e15 100644
--- a/comps/embeddings/llama_index/local_embedding.py
+++ b/comps/embeddings/llama_index/local_embedding.py
@@ -1,7 +1,6 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-from langsmith import traceable
 from llama_index.embeddings.huggingface_api import HuggingFaceInferenceAPIEmbedding
 
 from comps import EmbedDoc, ServiceType, TextDoc, opea_microservices, register_microservice
@@ -16,7 +15,6 @@
     input_datatype=TextDoc,
     output_datatype=EmbedDoc,
 )
-@traceable(run_type="embedding")
 def embedding(input: TextDoc) -> EmbedDoc:
     embed_vector = embeddings.get_text_embedding(input.text)
     res = EmbedDoc(text=input.text, embedding=embed_vector)
diff --git a/comps/embeddings/llama_index/requirements.txt b/comps/embeddings/llama_index/requirements.txt
index 908c38b06..4f1457e4a 100644
--- a/comps/embeddings/llama_index/requirements.txt
+++ b/comps/embeddings/llama_index/requirements.txt
@@ -1,7 +1,6 @@
 docarray[full]
 fastapi
 huggingface_hub
-langsmith
 llama-index-embeddings-huggingface-api
 llama-index-embeddings-text-embeddings-inference
 opentelemetry-api
diff --git a/comps/guardrails/llama_guard/guardrails_tgi.py b/comps/guardrails/llama_guard/guardrails_tgi.py
index b415876ed..93b046e97 100644
--- a/comps/guardrails/llama_guard/guardrails_tgi.py
+++ b/comps/guardrails/llama_guard/guardrails_tgi.py
@@ -7,7 +7,6 @@
 from langchain_community.utilities.requests import JsonRequestsWrapper
 from langchain_huggingface import ChatHuggingFace
 from langchain_huggingface.llms import HuggingFaceEndpoint
-from langsmith import traceable
 
 from comps import GeneratedDoc, ServiceType, TextDoc, opea_microservices, register_microservice
 
@@ -63,7 +62,6 @@ def get_tgi_service_model_id(endpoint_url, default=DEFAULT_MODEL):
     input_datatype=Union[GeneratedDoc, TextDoc],
     output_datatype=TextDoc,
 )
-@traceable(run_type="llm")
 def safety_guard(input: Union[GeneratedDoc, TextDoc]) -> TextDoc:
     if isinstance(input, GeneratedDoc):
         messages = [{"role": "user", "content": input.prompt}, {"role": "assistant", "content": input.text}]
diff --git a/comps/guardrails/llama_guard/requirements.txt b/comps/guardrails/llama_guard/requirements.txt
index 5eda60170..9f35ee74d 100644
--- a/comps/guardrails/llama_guard/requirements.txt
+++ b/comps/guardrails/llama_guard/requirements.txt
@@ -4,7 +4,6 @@ fastapi
 huggingface-hub<=0.24.0
 langchain-community
 langchain-huggingface
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/guardrails/pii_detection/pii_detection.py b/comps/guardrails/pii_detection/pii_detection.py
index feecf3baf..1ae0dddae 100644
--- a/comps/guardrails/pii_detection/pii_detection.py
+++ b/comps/guardrails/pii_detection/pii_detection.py
@@ -8,7 +8,6 @@
 from pathlib import Path
 
 from fastapi import File, Form, HTTPException, UploadFile
-from langsmith import traceable
 
 cur_path = pathlib.Path(__file__).parent.resolve()
 comps_path = os.path.join(cur_path, "../../../")
diff --git a/comps/guardrails/pii_detection/requirements.txt b/comps/guardrails/pii_detection/requirements.txt
index e9bb7ba66..bc95de0fd 100644
--- a/comps/guardrails/pii_detection/requirements.txt
+++ b/comps/guardrails/pii_detection/requirements.txt
@@ -8,7 +8,6 @@ gibberish-detector
 huggingface_hub
 langchain
 langchain-community
-langsmith
 numpy
 opentelemetry-api
 opentelemetry-exporter-otlp
diff --git a/comps/knowledgegraphs/langchain/knowledge_graph.py b/comps/knowledgegraphs/langchain/knowledge_graph.py
index 9ed2c5b65..01d1a5a5a 100755
--- a/comps/knowledgegraphs/langchain/knowledge_graph.py
+++ b/comps/knowledgegraphs/langchain/knowledge_graph.py
@@ -22,7 +22,6 @@
 from langchain_community.graphs import Neo4jGraph
 from langchain_community.llms import HuggingFaceEndpoint
 from langchain_community.vectorstores.neo4j_vector import Neo4jVector
-from langsmith import traceable
 
 from comps import GeneratedDoc, GraphDoc, ServiceType, opea_microservices, register_microservice
 
diff --git a/comps/knowledgegraphs/requirements.txt b/comps/knowledgegraphs/requirements.txt
index ecb5228af..39b351530 100755
--- a/comps/knowledgegraphs/requirements.txt
+++ b/comps/knowledgegraphs/requirements.txt
@@ -8,7 +8,6 @@ langchain
 langchain_community==0.2.5
 langchain_openai
 langchainhub
-langsmith
 neo4j
 numpy
 opentelemetry-api
diff --git a/comps/llms/faq-generation/tgi/llm.py b/comps/llms/faq-generation/tgi/llm.py
index af23a74af..beaa5700b 100644
--- a/comps/llms/faq-generation/tgi/llm.py
+++ b/comps/llms/faq-generation/tgi/llm.py
@@ -9,12 +9,10 @@
 from langchain.prompts import PromptTemplate
 from langchain.text_splitter import CharacterTextSplitter
 from langchain_community.llms import HuggingFaceEndpoint
-from langsmith import traceable
 
 from comps import GeneratedDoc, LLMParamsDoc, ServiceType, opea_microservices, register_microservice
 
 
-@traceable(run_type="tool")
 def post_process_text(text: str):
     if text == " ":
         return "data: @#$\n\n"
@@ -33,7 +31,6 @@ def post_process_text(text: str):
     host="0.0.0.0",
     port=9000,
 )
-@traceable(run_type="llm")
 def llm_generate(input: LLMParamsDoc):
     llm_endpoint = os.getenv("TGI_LLM_ENDPOINT", "http://localhost:8080")
     llm = HuggingFaceEndpoint(
diff --git a/comps/llms/faq-generation/tgi/requirements.txt b/comps/llms/faq-generation/tgi/requirements.txt
index 623a8f667..fbe54af95 100644
--- a/comps/llms/faq-generation/tgi/requirements.txt
+++ b/comps/llms/faq-generation/tgi/requirements.txt
@@ -3,7 +3,6 @@ fastapi
 huggingface_hub
 langchain==0.1.16
 langserve
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/llms/summarization/tgi/llm.py b/comps/llms/summarization/tgi/llm.py
index a9db6248d..43a583a96 100644
--- a/comps/llms/summarization/tgi/llm.py
+++ b/comps/llms/summarization/tgi/llm.py
@@ -8,12 +8,10 @@
 from langchain.docstore.document import Document
 from langchain.text_splitter import CharacterTextSplitter
 from langchain_huggingface import HuggingFaceEndpoint
-from langsmith import traceable
 
 from comps import GeneratedDoc, LLMParamsDoc, ServiceType, opea_microservices, register_microservice
 
 
-@traceable(run_type="tool")
 def post_process_text(text: str):
     if text == " ":
         return "data: @#$\n\n"
@@ -32,7 +30,6 @@ def post_process_text(text: str):
     host="0.0.0.0",
     port=9000,
 )
-@traceable(run_type="llm")
 def llm_generate(input: LLMParamsDoc):
     llm_endpoint = os.getenv("TGI_LLM_ENDPOINT", "http://localhost:8080")
     llm = HuggingFaceEndpoint(
diff --git a/comps/llms/summarization/tgi/requirements.txt b/comps/llms/summarization/tgi/requirements.txt
index c6c151f6e..e074ba8c8 100644
--- a/comps/llms/summarization/tgi/requirements.txt
+++ b/comps/llms/summarization/tgi/requirements.txt
@@ -6,7 +6,6 @@ langchain-huggingface
 langchain-openai
 langchain_community
 langchainhub
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/llms/text-generation/ollama/llm.py b/comps/llms/text-generation/ollama/llm.py
index aadb2e2fa..1f6d330c8 100644
--- a/comps/llms/text-generation/ollama/llm.py
+++ b/comps/llms/text-generation/ollama/llm.py
@@ -5,7 +5,6 @@
 
 from fastapi.responses import StreamingResponse
 from langchain_community.llms import Ollama
-from langsmith import traceable
 
 from comps import GeneratedDoc, LLMParamsDoc, ServiceType, opea_microservices, register_microservice
 
@@ -17,7 +16,6 @@
     host="0.0.0.0",
     port=9000,
 )
-@traceable(run_type="llm")
 def llm_generate(input: LLMParamsDoc):
     ollama = Ollama(
         base_url=ollama_endpoint,
diff --git a/comps/llms/text-generation/ollama/requirements.txt b/comps/llms/text-generation/ollama/requirements.txt
index e224aaaa5..78b323c73 100644
--- a/comps/llms/text-generation/ollama/requirements.txt
+++ b/comps/llms/text-generation/ollama/requirements.txt
@@ -2,7 +2,6 @@ docarray[full]
 fastapi
 huggingface_hub
 langchain==0.1.16
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/llms/text-generation/ray_serve/llm.py b/comps/llms/text-generation/ray_serve/llm.py
new file mode 100644
index 000000000..c86025625
--- /dev/null
+++ b/comps/llms/text-generation/ray_serve/llm.py
@@ -0,0 +1,82 @@
+# Copyright (c) 2024 Intel Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+from fastapi.responses import StreamingResponse
+from langchain_openai import ChatOpenAI
+
+from comps import GeneratedDoc, LLMParamsDoc, ServiceType, opea_microservices, register_microservice
+
+
+def post_process_text(text: str):
+    if text == " ":
+        return "data: @#$\n\n"
+    if text == "\n":
+        return "data: <br/>\n\n"
+    if text.isspace():
+        return None
+    new_text = text.replace(" ", "@#$")
+    return f"data: {new_text}\n\n"
+
+
+@register_microservice(
+    name="opea_service@llm_ray",
+    service_type=ServiceType.LLM,
+    endpoint="/v1/chat/completions",
+    host="0.0.0.0",
+    port=9000,
+)
+def llm_generate(input: LLMParamsDoc):
+    llm_endpoint = os.getenv("RAY_Serve_ENDPOINT", "http://localhost:8080")
+    llm_model = os.getenv("LLM_MODEL", "Llama-2-7b-chat-hf")
+    if "/" in llm_model:
+        llm_model = llm_model.split("/")[-1]
+    llm = ChatOpenAI(
+        openai_api_base=llm_endpoint + "/v1",
+        model_name=llm_model,
+        openai_api_key=os.getenv("OPENAI_API_KEY", "not_needed"),
+        max_tokens=input.max_new_tokens,
+        temperature=input.temperature,
+        streaming=input.streaming,
+        request_timeout=600,
+    )
+
+    if input.streaming:
+
+        async def stream_generator():
+            chat_response = ""
+            async for text in llm.astream(input.query):
+                text = text.content
+                chat_response += text
+                processed_text = post_process_text(text)
+                if text and processed_text:
+                    if "</s>" in text:
+                        res = text.split("</s>")[0]
+                        if res != "":
+                            yield res
+                        break
+                    yield processed_text
+            print(f"[llm - chat_stream] stream response: {chat_response}")
+            yield "data: [DONE]\n\n"
+
+        return StreamingResponse(stream_generator(), media_type="text/event-stream")
+    else:
+        response = llm.invoke(input.query)
+        response = response.content
+        return GeneratedDoc(text=response, prompt=input.query)
+
+
+if __name__ == "__main__":
+    opea_microservices["opea_service@llm_ray"].start()
diff --git a/comps/llms/text-generation/ray_serve/requirements.txt b/comps/llms/text-generation/ray_serve/requirements.txt
new file mode 100644
index 000000000..d97ce32e2
--- /dev/null
+++ b/comps/llms/text-generation/ray_serve/requirements.txt
@@ -0,0 +1,13 @@
+docarray[full]
+fastapi
+huggingface_hub
+langchain==0.1.16
+langchain_openai
+openai
+opentelemetry-api
+opentelemetry-exporter-otlp
+opentelemetry-sdk
+prometheus-fastapi-instrumentator
+ray[serve]>=2.10
+shortuuid
+transformers
diff --git a/comps/llms/text-generation/tgi/llm.py b/comps/llms/text-generation/tgi/llm.py
index c202aede7..6597d5b57 100644
--- a/comps/llms/text-generation/tgi/llm.py
+++ b/comps/llms/text-generation/tgi/llm.py
@@ -8,7 +8,6 @@
 from fastapi.responses import StreamingResponse
 from huggingface_hub import AsyncInferenceClient
 from langchain_core.prompts import PromptTemplate
-from langsmith import traceable
 from openai import OpenAI
 from template import ChatTemplate
 
@@ -37,7 +36,6 @@
     host="0.0.0.0",
     port=9000,
 )
-@traceable(run_type="llm")
 @register_statistics(names=["opea_service@llm_tgi"])
 async def llm_generate(input: Union[LLMParamsDoc, ChatCompletionRequest]):
 
diff --git a/comps/llms/text-generation/tgi/requirements.txt b/comps/llms/text-generation/tgi/requirements.txt
index 9670813d6..6b6f11ee4 100644
--- a/comps/llms/text-generation/tgi/requirements.txt
+++ b/comps/llms/text-generation/tgi/requirements.txt
@@ -3,7 +3,6 @@ docarray[full]
 fastapi
 httpx
 huggingface_hub
-langsmith
 openai==1.35.13
 opentelemetry-api
 opentelemetry-exporter-otlp
diff --git a/comps/llms/text-generation/vllm-ray/llm.py b/comps/llms/text-generation/vllm-ray/llm.py
index 6d8abd028..d3de026e0 100644
--- a/comps/llms/text-generation/vllm-ray/llm.py
+++ b/comps/llms/text-generation/vllm-ray/llm.py
@@ -16,7 +16,6 @@
 
 from fastapi.responses import StreamingResponse
 from langchain_openai import ChatOpenAI
-from langsmith import traceable
 
 from comps import GeneratedDoc, LLMParamsDoc, ServiceType, opea_microservices, register_microservice
 
@@ -28,7 +27,6 @@
     host="0.0.0.0",
     port=9000,
 )
-@traceable(run_type="llm")
 def llm_generate(input: LLMParamsDoc):
     llm_endpoint = os.getenv("vLLM_RAY_ENDPOINT", "http://localhost:8006")
     llm_model = os.getenv("LLM_MODEL", "meta-llama/Llama-2-7b-chat-hf")
diff --git a/comps/llms/text-generation/vllm-ray/requirements.txt b/comps/llms/text-generation/vllm-ray/requirements.txt
index 083a2910b..1f9020583 100644
--- a/comps/llms/text-generation/vllm-ray/requirements.txt
+++ b/comps/llms/text-generation/vllm-ray/requirements.txt
@@ -4,7 +4,6 @@ huggingface_hub
 langchain==0.1.16
 langchain_openai
 langserve
-langsmith
 openai
 opentelemetry-api
 opentelemetry-exporter-otlp
diff --git a/comps/llms/text-generation/vllm-xft/llm.py b/comps/llms/text-generation/vllm-xft/llm.py
index 02446baa6..2c479d90b 100644
--- a/comps/llms/text-generation/vllm-xft/llm.py
+++ b/comps/llms/text-generation/vllm-xft/llm.py
@@ -5,7 +5,6 @@
 
 from fastapi.responses import StreamingResponse
 from langchain_community.llms import VLLMOpenAI
-from langsmith import traceable
 
 from comps import GeneratedDoc, LLMParamsDoc, ServiceType, opea_microservices, register_microservice
 
@@ -17,7 +16,6 @@
     host="0.0.0.0",
     port=9000,
 )
-@traceable(run_type="llm")
 def llm_generate(input: LLMParamsDoc):
     llm_endpoint = os.getenv("vLLM_LLM_ENDPOINT", "http://localhost:18688")
     llm = VLLMOpenAI(
diff --git a/comps/llms/text-generation/vllm-xft/requirements.txt b/comps/llms/text-generation/vllm-xft/requirements.txt
index bc9f457c4..a4accaed2 100644
--- a/comps/llms/text-generation/vllm-xft/requirements.txt
+++ b/comps/llms/text-generation/vllm-xft/requirements.txt
@@ -1,7 +1,6 @@
 docarray[full]
 fastapi
 langchain==0.1.16
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/llms/text-generation/vllm/llm.py b/comps/llms/text-generation/vllm/llm.py
index ea8691f1a..61bebbe27 100644
--- a/comps/llms/text-generation/vllm/llm.py
+++ b/comps/llms/text-generation/vllm/llm.py
@@ -5,7 +5,6 @@
 
 from fastapi.responses import StreamingResponse
 from langchain_community.llms import VLLMOpenAI
-from langsmith import traceable
 
 from comps import GeneratedDoc, LLMParamsDoc, ServiceType, opea_microservices, opea_telemetry, register_microservice
 
@@ -29,7 +28,6 @@ def post_process_text(text: str):
     host="0.0.0.0",
     port=9000,
 )
-@traceable(run_type="llm")
 def llm_generate(input: LLMParamsDoc):
     llm_endpoint = os.getenv("vLLM_ENDPOINT", "http://localhost:8008")
     model_name = os.getenv("LLM_MODEL", "meta-llama/Meta-Llama-3-8B-Instruct")
diff --git a/comps/ragas/tgi/llm.py b/comps/ragas/tgi/llm.py
index 895705703..03c214d30 100644
--- a/comps/ragas/tgi/llm.py
+++ b/comps/ragas/tgi/llm.py
@@ -11,7 +11,6 @@
     HuggingFaceInstructEmbeddings,
 )
 from langchain_community.llms import HuggingFaceEndpoint
-from langsmith import traceable
 from ragas import evaluate
 from ragas.metrics import answer_relevancy, context_precision, context_recall, faithfulness
 
@@ -30,7 +29,6 @@
     input_datatype=RAGASParams,
     output_datatype=RAGASScores,
 )
-@traceable(run_type="llm")
 def llm_generate(input: RAGASParams):
     llm_endpoint = os.getenv("TGI_LLM_ENDPOINT", "http://localhost:8080")
 
diff --git a/comps/ragas/tgi/requirements.txt b/comps/ragas/tgi/requirements.txt
index 2c8fad29f..7839ef15d 100644
--- a/comps/ragas/tgi/requirements.txt
+++ b/comps/ragas/tgi/requirements.txt
@@ -3,7 +3,6 @@ docarray[full]
 fastapi
 huggingface_hub
 langchain==0.1.16
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/reranks/fastrag/local_reranking.py b/comps/reranks/fastrag/local_reranking.py
index f11ebc1f9..4548ef9a7 100644
--- a/comps/reranks/fastrag/local_reranking.py
+++ b/comps/reranks/fastrag/local_reranking.py
@@ -4,7 +4,6 @@
 from config import RANKER_MODEL
 from fastrag.rankers import IPEXBiEncoderSimilarityRanker
 from haystack import Document
-from langsmith import traceable
 
 from comps.cores.mega.micro_service import ServiceType, opea_microservices, register_microservice
 from comps.cores.proto.docarray import RerankedDoc, SearchedDoc, TextDoc
@@ -19,7 +18,6 @@
     input_datatype=SearchedDoc,
     output_datatype=RerankedDoc,
 )
-@traceable(run_type="llm")
 def reranking(input: SearchedDoc) -> RerankedDoc:
     documents = []
     for i, d in enumerate(input.retrieved_docs):
diff --git a/comps/reranks/fastrag/requirements.txt b/comps/reranks/fastrag/requirements.txt
index c4ded91c8..e8166a77a 100644
--- a/comps/reranks/fastrag/requirements.txt
+++ b/comps/reranks/fastrag/requirements.txt
@@ -2,7 +2,6 @@ docarray[full]
 fastapi
 haystack-ai
 langchain
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/reranks/langchain-mosec/reranking_mosec_xeon.py b/comps/reranks/langchain-mosec/reranking_mosec_xeon.py
index 4640433af..da3d7854a 100644
--- a/comps/reranks/langchain-mosec/reranking_mosec_xeon.py
+++ b/comps/reranks/langchain-mosec/reranking_mosec_xeon.py
@@ -22,7 +22,6 @@
 
 import requests
 from langchain_core.prompts import ChatPromptTemplate
-from langsmith import traceable
 
 from comps import (
     LLMParamsDoc,
@@ -44,7 +43,6 @@
     input_datatype=SearchedDoc,
     output_datatype=LLMParamsDoc,
 )
-@traceable(run_type="llm")
 @register_statistics(names=["opea_service@reranking_mosec_xeon"])
 def reranking(input: SearchedDoc) -> LLMParamsDoc:
     print("reranking input: ", input)
diff --git a/comps/reranks/requirements.txt b/comps/reranks/requirements.txt
index 67503038f..7260862a3 100644
--- a/comps/reranks/requirements.txt
+++ b/comps/reranks/requirements.txt
@@ -2,7 +2,6 @@ aiohttp
 docarray[full]
 fastapi
 httpx
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/reranks/tei/local_reranking.py b/comps/reranks/tei/local_reranking.py
index d0fa8a79c..f02a95823 100644
--- a/comps/reranks/tei/local_reranking.py
+++ b/comps/reranks/tei/local_reranking.py
@@ -1,7 +1,6 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-from langsmith import traceable
 from sentence_transformers import CrossEncoder
 
 from comps import RerankedDoc, SearchedDoc, ServiceType, TextDoc, opea_microservices, register_microservice
@@ -16,7 +15,6 @@
     input_datatype=SearchedDoc,
     output_datatype=RerankedDoc,
 )
-@traceable(run_type="llm")
 def reranking(input: SearchedDoc) -> RerankedDoc:
     query_and_docs = [(input.initial_query, doc.text) for doc in input.retrieved_docs]
     scores = reranker_model.predict(query_and_docs)
diff --git a/comps/reranks/tei/reranking_tei.py b/comps/reranks/tei/reranking_tei.py
index 2440f800a..5575aa88f 100644
--- a/comps/reranks/tei/reranking_tei.py
+++ b/comps/reranks/tei/reranking_tei.py
@@ -9,7 +9,6 @@
 from typing import Union
 
 import requests
-from langsmith import traceable
 
 from comps import (
     LLMParamsDoc,
@@ -37,7 +36,6 @@
     input_datatype=SearchedDoc,
     output_datatype=LLMParamsDoc,
 )
-@traceable(run_type="llm")
 @register_statistics(names=["opea_service@reranking_tgi_gaudi"])
 def reranking(
     input: Union[SearchedDoc, RerankingRequest, ChatCompletionRequest]
diff --git a/comps/retrievers/haystack/qdrant/requirements.txt b/comps/retrievers/haystack/qdrant/requirements.txt
index 9b99c00fb..24458a6fb 100644
--- a/comps/retrievers/haystack/qdrant/requirements.txt
+++ b/comps/retrievers/haystack/qdrant/requirements.txt
@@ -3,7 +3,6 @@ easyocr
 fastapi
 haystack-ai==2.2.4
 langchain_community
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/retrievers/haystack/qdrant/retriever_qdrant.py b/comps/retrievers/haystack/qdrant/retriever_qdrant.py
index c2cc8735b..30d1bd72d 100644
--- a/comps/retrievers/haystack/qdrant/retriever_qdrant.py
+++ b/comps/retrievers/haystack/qdrant/retriever_qdrant.py
@@ -4,7 +4,6 @@
 from haystack.components.embedders import HuggingFaceTEITextEmbedder, SentenceTransformersTextEmbedder
 from haystack_integrations.components.retrievers.qdrant import QdrantEmbeddingRetriever
 from haystack_integrations.document_stores.qdrant import QdrantDocumentStore
-from langsmith import traceable
 from qdrant_config import EMBED_DIMENSION, EMBED_ENDPOINT, EMBED_MODEL, INDEX_NAME, QDRANT_HOST, QDRANT_PORT
 
 from comps import EmbedDoc, SearchedDoc, ServiceType, TextDoc, opea_microservices, register_microservice
@@ -28,7 +27,6 @@ def initialize_qdrant_retriever() -> QdrantEmbeddingRetriever:
     host="0.0.0.0",
     port=7000,
 )
-@traceable(run_type="retriever")
 def retrieve(input: EmbedDoc) -> SearchedDoc:
     search_res = retriever.run(query_embedding=input.embedding)["documents"]
     searched_docs = [TextDoc(text=r.content) for r in search_res if r.content]
diff --git a/comps/retrievers/langchain/milvus/retriever_milvus.py b/comps/retrievers/langchain/milvus/retriever_milvus.py
index 1625eed0a..0c81e76ce 100644
--- a/comps/retrievers/langchain/milvus/retriever_milvus.py
+++ b/comps/retrievers/langchain/milvus/retriever_milvus.py
@@ -15,9 +15,8 @@
     MODEL_ID,
     MOSEC_EMBEDDING_ENDPOINT,
 )
-from langchain_community.embeddings import HuggingFaceBgeEmbeddings, HuggingFaceHubEmbeddings, OpenAIEmbeddings
+from langchain_community.embeddings import HuggingFaceBgeEmbeddings, OpenAIEmbeddings
 from langchain_milvus.vectorstores import Milvus
-from langsmith import traceable
 
 from comps import (
     EmbedDoc,
@@ -63,7 +62,6 @@ def empty_embedding() -> List[float]:
     host="0.0.0.0",
     port=7000,
 )
-@traceable(run_type="retriever")
 @register_statistics(names=["opea_service@retriever_milvus"])
 def retrieve(input: EmbedDoc) -> SearchedDoc:
     vector_db = Milvus(
diff --git a/comps/retrievers/langchain/pgvector/requirements.txt b/comps/retrievers/langchain/pgvector/requirements.txt
index 18609d361..d3d95dee9 100644
--- a/comps/retrievers/langchain/pgvector/requirements.txt
+++ b/comps/retrievers/langchain/pgvector/requirements.txt
@@ -2,7 +2,6 @@ docarray[full]
 easyocr
 fastapi
 langchain_community
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/retrievers/langchain/pgvector/retriever_pgvector.py b/comps/retrievers/langchain/pgvector/retriever_pgvector.py
index 2fba1f1c0..014a616a5 100644
--- a/comps/retrievers/langchain/pgvector/retriever_pgvector.py
+++ b/comps/retrievers/langchain/pgvector/retriever_pgvector.py
@@ -7,7 +7,6 @@
 from config import EMBED_MODEL, INDEX_NAME, PG_CONNECTION_STRING, PORT
 from langchain_community.embeddings import HuggingFaceBgeEmbeddings, HuggingFaceHubEmbeddings
 from langchain_community.vectorstores import PGVector
-from langsmith import traceable
 
 from comps import (
     EmbedDoc,
@@ -30,7 +29,6 @@
     host="0.0.0.0",
     port=PORT,
 )
-@traceable(run_type="retriever")
 @register_statistics(names=["opea_service@retriever_pgvector"])
 def retrieve(input: EmbedDoc) -> SearchedDoc:
     start = time.time()
diff --git a/comps/retrievers/langchain/pinecone/requirements.txt b/comps/retrievers/langchain/pinecone/requirements.txt
index 32df7f40f..7536f591c 100644
--- a/comps/retrievers/langchain/pinecone/requirements.txt
+++ b/comps/retrievers/langchain/pinecone/requirements.txt
@@ -6,7 +6,6 @@ huggingface_hub
 langchain
 langchain-community
 langchain-pinecone
-langsmith
 numpy
 opentelemetry-api
 opentelemetry-exporter-otlp
diff --git a/comps/retrievers/langchain/pinecone/retriever_pinecone.py b/comps/retrievers/langchain/pinecone/retriever_pinecone.py
index ba8e6526f..73e77d111 100644
--- a/comps/retrievers/langchain/pinecone/retriever_pinecone.py
+++ b/comps/retrievers/langchain/pinecone/retriever_pinecone.py
@@ -7,7 +7,6 @@
 from config import EMBED_MODEL, PINECONE_API_KEY, PINECONE_INDEX_NAME
 from langchain_community.embeddings import HuggingFaceBgeEmbeddings, HuggingFaceHubEmbeddings
 from langchain_pinecone import PineconeVectorStore
-from langsmith import traceable
 from pinecone import Pinecone, ServerlessSpec
 
 from comps import (
@@ -31,7 +30,6 @@
     host="0.0.0.0",
     port=7000,
 )
-@traceable(run_type="retriever")
 @register_statistics(names=["opea_service@retriever_pinecone"])
 def retrieve(input: EmbedDoc) -> SearchedDoc:
     start = time.time()
diff --git a/comps/retrievers/langchain/redis/requirements.txt b/comps/retrievers/langchain/redis/requirements.txt
index 3720190d3..c68c3d274 100644
--- a/comps/retrievers/langchain/redis/requirements.txt
+++ b/comps/retrievers/langchain/redis/requirements.txt
@@ -2,7 +2,6 @@ docarray[full]
 easyocr
 fastapi
 langchain_community
-langsmith
 opentelemetry-api
 opentelemetry-exporter-otlp
 opentelemetry-sdk
diff --git a/comps/retrievers/langchain/redis/retriever_redis.py b/comps/retrievers/langchain/redis/retriever_redis.py
index 43f3e0c05..a4ab5dc4e 100644
--- a/comps/retrievers/langchain/redis/retriever_redis.py
+++ b/comps/retrievers/langchain/redis/retriever_redis.py
@@ -7,7 +7,6 @@
 
 from langchain_community.embeddings import HuggingFaceBgeEmbeddings, HuggingFaceHubEmbeddings
 from langchain_community.vectorstores import Redis
-from langsmith import traceable
 from redis_config import EMBED_MODEL, INDEX_NAME, REDIS_URL
 
 from comps import (
@@ -37,7 +36,6 @@
     host="0.0.0.0",
     port=7000,
 )
-@traceable(run_type="retriever")
 @register_statistics(names=["opea_service@retriever_redis"])
 def retrieve(
     input: Union[EmbedDoc, RetrievalRequest, ChatCompletionRequest]
diff --git a/comps/retrievers/llamaindex/requirements.txt b/comps/retrievers/llamaindex/requirements.txt
index 236ea9af8..83228c259 100644
--- a/comps/retrievers/llamaindex/requirements.txt
+++ b/comps/retrievers/llamaindex/requirements.txt
@@ -3,7 +3,6 @@ docarray[full]
 easyocr
 fastapi
 httpx
-langsmith
 llama-index-vector-stores-redis
 llama_index
 opentelemetry-api
diff --git a/comps/retrievers/llamaindex/retriever_redis.py b/comps/retrievers/llamaindex/retriever_redis.py
index 4999a7235..3c387010e 100644
--- a/comps/retrievers/llamaindex/retriever_redis.py
+++ b/comps/retrievers/llamaindex/retriever_redis.py
@@ -3,7 +3,6 @@
 
 import os
 
-from langsmith import traceable
 from llama_index.core.vector_stores.types import VectorStoreQuery
 from llama_index.vector_stores.redis import RedisVectorStore
 from redis_config import INDEX_NAME, REDIS_URL
@@ -20,7 +19,6 @@
     host="0.0.0.0",
     port=7000,
 )
-@traceable(run_type="retriever")
 def retrieve(input: EmbedDoc) -> SearchedDoc:
     vector_store_query = VectorStoreQuery(query_embedding=input.embedding)
     search_res = vector_store.query(query=vector_store_query)