diff --git a/wren-ai-service/.env.dev.example b/wren-ai-service/.env.dev.example
index a15ca71db..55faa58f8 100644
--- a/wren-ai-service/.env.dev.example
+++ b/wren-ai-service/.env.dev.example
@@ -44,8 +44,7 @@ DOCUMENT_STORE_PROVIDER=qdrant
 
 QDRANT_HOST=http://localhost:6333
 
-## ENGINE
-ENGINE=wren_ui
+ENGINE=wren_ui # wren_ui, wren_ibis, wren_engine
 
 ## when using wren_ui as the engine
 WREN_UI_ENDPOINT=http://localhost:3000
@@ -56,7 +55,10 @@ WREN_IBIS_SOURCE=bigquery
 ### this is a base64 encoded string of the MDL
 WREN_IBIS_MANIFEST= 
 ### this is a base64 encode string of the connection info
-WREN_IBIS_CONNECTION_INFO=e30= 
+WREN_IBIS_CONNECTION_INFO=
+
+## when using wren_engine as the engine
+WREN_ENGINE_ENDPOINT=http://localhost:8080
 
 # Evaluation
 DATASET_NAME=book_2
diff --git a/wren-ai-service/Makefile b/wren-ai-service/Makefile
index e05e6cfbf..2aaaaae1d 100644
--- a/wren-ai-service/Makefile
+++ b/wren-ai-service/Makefile
@@ -30,7 +30,10 @@ eval:
 	make dev-down
 
 demo:
-	cd demo; poetry run streamlit run app.py
+	poetry run streamlit run demo/app.py
+
+data_curation_app:
+	poetry run streamlit run eval/data_curation/app.py
 ## utilities related ##
 
 
diff --git a/wren-ai-service/README.md b/wren-ai-service/README.md
index 070304ebd..81c636917 100644
--- a/wren-ai-service/README.md
+++ b/wren-ai-service/README.md
@@ -28,16 +28,11 @@ The following commands can quickly start the service for development:
 
 ## Others
 
-### Pipeline Evaluation(Deprecated, will introduce new way to evaluate the speed in the future)
+### Pipeline Evaluation
 
-- install `psql`
-- fill in environment variables: `.env.dev` in the src folder and `config.properties` in the src/eval/wren-engine/etc folder
-- start the docker service
-- evaluation
-  - `make eval pipeline=ask args="--help"`
-  - `make eval pipeline=ask_details args="--help"`
-- `make eval_visualzation` to compare between the evaluation results
-- to run individual pipeline: `poetry run python -m src.pipelines.ask.[pipeline_name]` (e.g. `poetry run python -m src.pipelines.ask.retrieval_pipeline`)
+- evaluation dataset curation
+  - copy `.env.example` file to `.env` in the `eval/data_curation` folder and fill in the environment variables
+  - execute the command under the `wren-ai-service` folder: `make data_curation_app`
 
 ### Speed Evaluation(Deprecated, will introduce new way to evaluate the speed in the future)
 
diff --git a/wren-ai-service/demo/.env.example b/wren-ai-service/demo/.env.example
index ab0c93773..040660e59 100644
--- a/wren-ai-service/demo/.env.example
+++ b/wren-ai-service/demo/.env.example
@@ -1,6 +1,8 @@
-bigquery.project-id=wrenai
+bigquery.project-id=
+bigquery.dataset-id=
 bigquery.credentials-key=
-bigquery.location=asia-east1
+postgres.host=
+postgres.port=
+postgres.database=
 postgres.user=
-postgres.password=
-postgres.jdbc.url=jdbc:postgresql://localhost:5432/<database_name>
\ No newline at end of file
+postgres.password=
\ No newline at end of file
diff --git a/wren-ai-service/demo/app.py b/wren-ai-service/demo/app.py
index 70b0b16e3..40087c170 100644
--- a/wren-ai-service/demo/app.py
+++ b/wren-ai-service/demo/app.py
@@ -7,10 +7,8 @@ from utils import (
     DATA_SOURCES,
     ask,
     ask_details,
-    get_current_manifest,
     get_mdl_json,
     get_new_mdl_json,
-    is_current_manifest_available,
     prepare_duckdb,
     prepare_semantics,
     rerun_wren_engine,
@@ -59,11 +57,7 @@ if __name__ == "__main__":
     col1, col2 = st.columns([2, 4])
 
     with col1:
-        with st.expander("Current Deployed Model", expanded=True):
-            manifest_name, models, relationships = get_current_manifest()
-            st.markdown(f"Current Deployed Model: {manifest_name}")
-            show_er_diagram(models, relationships)
-        with st.expander("Deploy New Model"):
+        with st.expander("Deploy New Model", expanded=True):
             uploaded_file = st.file_uploader(
                 f"Upload an MDL json file, and the file name must be [xxx]_[datasource]_mdl.json, now we support these datasources: {DATA_SOURCES}",
                 type="json",
@@ -154,8 +148,7 @@ if __name__ == "__main__":
 
     query = st.chat_input(
         "Ask a question about the database",
-        disabled=(not is_current_manifest_available())
-        and st.session_state["semantics_preparation_status"] != "finished",
+        disabled=st.session_state["semantics_preparation_status"] != "finished",
     )
 
     with col2:
diff --git a/wren-ai-service/demo/pyproject.toml b/wren-ai-service/demo/pyproject.toml
deleted file mode 100644
index 0b9b1ad46..000000000
--- a/wren-ai-service/demo/pyproject.toml
+++ /dev/null
@@ -1,21 +0,0 @@
-[tool.poetry]
-name = "wren-ai-service-demo"
-version = "0.1.0"
-description = ""
-authors = ["Jimmy Yeh <jimmy.yeh@cannerdata.com>"]
-license = "AGPL-3.0"
-readme = "README.md"
-
-[tool.poetry.dependencies]
-python = "^3.12"
-requests = "^2.31.0"
-sqlparse = "^0.5.0"
-streamlit = "^1.32.2"
-watchdog = "^4.0.0"
-python-dotenv = "^1.0.1"
-orjson = "^3.10.3"
-
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
diff --git a/wren-ai-service/demo/utils.py b/wren-ai-service/demo/utils.py
index aa702e1f8..b3ae59a48 100644
--- a/wren-ai-service/demo/utils.py
+++ b/wren-ai-service/demo/utils.py
@@ -1,3 +1,4 @@
+import base64
 import json
 import os
 import re
@@ -14,43 +15,13 @@ from dotenv import load_dotenv
 
 WREN_AI_SERVICE_BASE_URL = "http://localhost:5556"
 WREN_ENGINE_API_URL = "http://localhost:8080"
+WREN_IBIS_API_URL = "http://localhost:8000"
 POLLING_INTERVAL = 0.5
 DATA_SOURCES = ["duckdb", "bigquery", "postgres"]
 
 load_dotenv()
 
 
-def get_current_manifest():
-    response = requests.get(
-        f"{WREN_ENGINE_API_URL}/v1/mdl",
-    )
-
-    assert response.status_code == 200
-
-    manifest = response.json()
-
-    if manifest["schema"] == "test_schema" and manifest["catalog"] == "test_catalog":
-        return "None", [], []
-
-    return (
-        f"{manifest['catalog']}.{manifest['schema']}",
-        manifest["models"],
-        manifest["relationships"],
-    )
-
-
-def is_current_manifest_available():
-    response = requests.get(
-        f"{WREN_ENGINE_API_URL}/v1/mdl",
-    )
-
-    assert response.status_code == 200
-
-    manifest = response.json()
-
-    return manifest["catalog"] != "text_catalog" and manifest["schema"] != "test_schema"
-
-
 def _update_wren_engine_configs(configs: list[dict]):
     response = requests.patch(
         f"{WREN_ENGINE_API_URL}/v1/config",
@@ -63,50 +34,78 @@ def _update_wren_engine_configs(configs: list[dict]):
 def rerun_wren_engine(mdl_json: Dict, dataset_type: str):
     assert dataset_type in DATA_SOURCES
 
-    if dataset_type == "bigquery":
-        BIGQUERY_CREDENTIALS = os.getenv("bigquery.credentials-key")
-        assert (
-            BIGQUERY_CREDENTIALS is not None
-        ), "bigquery.credentials-key is not set in .env"
+    if dataset_type == "duckdb":
+        # replace the values of ENGINE to wren-ui in ../.env.dev
+        with open(".env.dev", "r") as f:
+            lines = f.readlines()
+            for i, line in enumerate(lines):
+                if line.startswith("ENGINE"):
+                    lines[i] = "ENGINE=wren_engine\n"
+                    break
+        with open(".env.dev", "w") as f:
+            f.writelines(lines)
 
-        _update_wren_engine_configs(
-            [
-                {"name": "wren.datasource.type", "value": "bigquery"},
-                {
-                    "name": "bigquery.project-id",
-                    "value": os.getenv("bigquery.project-id"),
-                },
-                {"name": "bigquery.location", "value": os.getenv("bigquery.location")},
-                {"name": "bigquery.credentials-key", "value": BIGQUERY_CREDENTIALS},
-            ]
-        )
-    elif dataset_type == "duckdb":
         _update_wren_engine_configs(
             [{"name": "wren.datasource.type", "value": "duckdb"}]
         )
-    elif dataset_type == "postgresql":
-        _update_wren_engine_configs(
-            [
-                {"name": "wren.datasource.type", "value": "postgres"},
-                {"name": "postgres.user", "value": os.getenv("postgres.user")},
-                {"name": "postgres.password", "value": os.getenv("postgres.password")},
-                {"name": "postgres.jdbc.url", "value": os.getenv("postgres.jdbc.url")},
-            ]
+        st.toast("Wren Engine is being re-run", icon="⏳")
+
+        response = requests.post(
+            f"{WREN_ENGINE_API_URL}/v1/mdl/deploy",
+            json={
+                "manifest": mdl_json,
+                "version": "latest",
+            },
         )
 
-    st.toast("Wren Engine is being re-run", icon="⏳")
+        assert response.status_code == 202, response.json()
 
-    response = requests.post(
-        f"{WREN_ENGINE_API_URL}/v1/mdl/deploy",
-        json={
-            "manifest": mdl_json,
-            "version": "latest",
-        },
-    )
+        st.toast("Wren Engine is ready", icon="🎉")
+    else:
+        WREN_IBIS_SOURCE = dataset_type
+        WREN_IBIS_MANIFEST = base64.b64encode(orjson.dumps(mdl_json)).decode()
+        if dataset_type == "bigquery":
+            WREN_IBIS_CONNECTION_INFO = base64.b64encode(
+                orjson.dumps(
+                    {
+                        "project_id": os.getenv("bigquery.project-id"),
+                        "dataset_id": os.getenv("bigquery.dataset-id"),
+                        "credentials": os.getenv("bigquery.credentials-key"),
+                    }
+                )
+            ).decode()
+        elif dataset_type == "postgres":
+            WREN_IBIS_CONNECTION_INFO = base64.b64encode(
+                orjson.dumps(
+                    {
+                        "host": os.getenv("postgres.host"),
+                        "port": int(os.getenv("postgres.port")),
+                        "database": os.getenv("postgres.database"),
+                        "user": os.getenv("postgres.user"),
+                        "password": os.getenv("postgres.password"),
+                    }
+                )
+            ).decode()
 
-    assert response.status_code == 202
+        # replace the values of WREN_IBIS_xxx to ../.env.dev
+        with open(".env.dev", "r") as f:
+            lines = f.readlines()
+            for i, line in enumerate(lines):
+                if line.startswith("ENGINE"):
+                    lines[i] = "ENGINE=wren-ibis\n"
+                elif line.startswith("WREN_IBIS_SOURCE"):
+                    lines[i] = f"WREN_IBIS_SOURCE={WREN_IBIS_SOURCE}\n"
+                elif line.startswith("WREN_IBIS_MANIFEST"):
+                    lines[i] = f"WREN_IBIS_MANIFEST={WREN_IBIS_MANIFEST}\n"
+                elif line.startswith("WREN_IBIS_CONNECTION_INFO"):
+                    lines[
+                        i
+                    ] = f"WREN_IBIS_CONNECTION_INFO={WREN_IBIS_CONNECTION_INFO}\n"
+        with open(".env.dev", "w") as f:
+            f.writelines(lines)
 
-    st.toast("Wren Engine is ready", icon="🎉")
+    # wait for wren-ai-service to restart
+    time.sleep(5)
 
 
 def save_mdl_json_file(file_name: str, mdl_json: Dict):
@@ -120,7 +119,7 @@ def save_mdl_json_file(file_name: str, mdl_json: Dict):
 def get_mdl_json(database_name: str):
     assert database_name in ["music", "nba", "ecommerce"]
 
-    with open(f"sample_dataset/{database_name}_duckdb_mdl.json", "r") as f:
+    with open(f"demo/sample_dataset/{database_name}_duckdb_mdl.json", "r") as f:
         mdl_json = json.load(f)
 
     return mdl_json
@@ -146,20 +145,62 @@ def get_new_mdl_json(chosen_models: List[str]):
 
 
 @st.cache_data
-def get_data_from_wren_engine(sql: str):
-    response = requests.get(
-        f"{WREN_ENGINE_API_URL}/v1/mdl/preview",
-        json={
-            "sql": sql,
-        },
-    )
+def get_data_from_wren_engine(sql: str, dataset_type: str):
+    assert dataset_type in DATA_SOURCES
 
-    assert response.status_code == 200
+    if dataset_type == "duckdb":
+        response = requests.get(
+            f"{WREN_ENGINE_API_URL}/v1/mdl/preview",
+            json={
+                "sql": sql,
+            },
+        )
 
-    data = response.json()
-    column_names = [f'{i}_{col["name"]}' for i, col in enumerate(data["columns"])]
+        if response.status_code != 200:
+            st.error(response.json())
+            st.stop()
 
-    return pd.DataFrame(data["data"], columns=column_names)
+        data = response.json()
+        column_names = [f'{i}_{col["name"]}' for i, col in enumerate(data["columns"])]
+
+        return pd.DataFrame(data["data"], columns=column_names)
+    else:
+        connection_info = {
+            "bigquery": {
+                "project_id": os.getenv("bigquery.project-id"),
+                "dataset_id": os.getenv("bigquery.dataset-id"),
+                "credentials": os.getenv("bigquery.credentials-key"),
+            },
+            "postgres": {
+                "host": os.getenv("postgres.host"),
+                "port": int(os.getenv("postgres.port"))
+                if os.getenv("postgres.port")
+                else 5432,
+                "database": os.getenv("postgres.database"),
+                "user": os.getenv("postgres.user"),
+                "password": os.getenv("postgres.password"),
+            },
+        }
+
+        response = requests.post(
+            f"{WREN_IBIS_API_URL}/v2/ibis/{dataset_type}/query",
+            json={
+                "sql": sql,
+                "manifestStr": base64.b64encode(
+                    orjson.dumps(st.session_state["mdl_json"])
+                ).decode(),
+                "connectionInfo": connection_info[dataset_type],
+            },
+        )
+
+        if response.status_code != 200:
+            st.error(response.json())
+            st.stop()
+
+        data = response.json()
+        column_names = [f"{i}_{col}" for i, col in enumerate(data["columns"])]
+
+        return pd.DataFrame(data["data"], columns=column_names)
 
 
 # ui related
@@ -319,6 +360,7 @@ def show_asks_details_results():
             st.dataframe(
                 get_data_from_wren_engine(
                     st.session_state["preview_sql"],
+                    st.session_state["dataset_type"],
                 )
             )
 
diff --git a/wren-ai-service/docker/Dockerfile b/wren-ai-service/docker/Dockerfile
index 392cdaa41..ede8861bd 100644
--- a/wren-ai-service/docker/Dockerfile
+++ b/wren-ai-service/docker/Dockerfile
@@ -12,7 +12,7 @@ WORKDIR /app
 
 COPY pyproject.toml ./
 
-RUN poetry install --without dev --no-root && rm -rf $POETRY_CACHE_DIR
+RUN poetry install --without dev,eval,demo --no-root && rm -rf $POETRY_CACHE_DIR
 
 FROM python:3.12.0-slim-bookworm as runtime
 
diff --git a/wren-ai-service/eval/.gitignore b/wren-ai-service/eval/.gitignore
new file mode 100644
index 000000000..2eea525d8
--- /dev/null
+++ b/wren-ai-service/eval/.gitignore
@@ -0,0 +1 @@
+.env
\ No newline at end of file
diff --git a/wren-ai-service/eval/data_curation/.env.example b/wren-ai-service/eval/data_curation/.env.example
new file mode 100644
index 000000000..e203bf033
--- /dev/null
+++ b/wren-ai-service/eval/data_curation/.env.example
@@ -0,0 +1,6 @@
+OPENAI_API_KEY=
+WREN_IBIS_ENDPOINT=http://localhost:8000
+WREN_ENGINE_ENDPOINT=http://localhost:8080
+bigquery.project-id=
+bigquery.dataset-id=
+bigquery.credentials-key=
\ No newline at end of file
diff --git a/wren-ai-service/eval/data_curation/__init__.py b/wren-ai-service/eval/data_curation/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/wren-ai-service/eval/data_curation/app.py b/wren-ai-service/eval/data_curation/app.py
new file mode 100644
index 000000000..4d49b5ddd
--- /dev/null
+++ b/wren-ai-service/eval/data_curation/app.py
@@ -0,0 +1,461 @@
+import asyncio
+import os
+import re
+import uuid
+from datetime import datetime
+
+import orjson
+import pandas as pd
+import streamlit as st
+import tomlkit
+from openai import AsyncClient
+from streamlit_tags import st_tags
+from utils import (
+    DATA_SOURCES,
+    get_contexts_from_sqls,
+    get_data_from_wren_engine,
+    get_eval_dataset_in_toml_string,
+    get_openai_client,
+    get_question_sql_pairs,
+    is_sql_valid,
+    prettify_sql,
+)
+
+st.set_page_config(layout="wide")
+st.title("WrenAI Data Curation App")
+
+
+LLM_OPTIONS = ["gpt-3.5-turbo", "gpt-4-turbo", "gpt-4o"]
+
+llm_client = get_openai_client()
+
+
+# session states
+if "llm_model" not in st.session_state:
+    st.session_state["llm_model"] = LLM_OPTIONS[0]
+if "deployment_id" not in st.session_state:
+    st.session_state["deployment_id"] = str(uuid.uuid4())
+if "mdl_json" not in st.session_state:
+    st.session_state["mdl_json"] = None
+if "custom_instructions_for_llm" not in st.session_state:
+    st.session_state["custom_instructions_for_llm"] = ""
+if "llm_question_sql_pairs" not in st.session_state:
+    st.session_state["llm_question_sql_pairs"] = []
+if "user_question_sql_pair" not in st.session_state:
+    st.session_state["user_question_sql_pair"] = {}
+if "candidate_dataset" not in st.session_state:
+    st.session_state["candidate_dataset"] = []
+if "data_source" not in st.session_state:
+    st.session_state["data_source"] = None
+if "connection_info" not in st.session_state:
+    st.session_state["connection_info"] = None
+
+
+# widget callbacks
+def on_change_upload_eval_dataset():
+    doc = tomlkit.parse(st.session_state.uploaded_eval_file.getvalue().decode("utf-8"))
+    assert (
+        doc["mdl"] == st.session_state["mdl_json"]
+    ), "The model in the uploaded dataset is different from the deployed model"
+    st.session_state["candidate_dataset"] = doc["eval_dataset"]
+
+
+def on_change_custom_instructions_for_llm():
+    st.session_state["custom_instructions_for_llm"] = st.session_state[
+        "custom_instructions_text_area"
+    ]
+
+
+def on_click_generate_question_sql_pairs(llm_client: AsyncClient):
+    st.toast("Generating question-sql-pairs...")
+    st.session_state["llm_question_sql_pairs"] = asyncio.run(
+        get_question_sql_pairs(
+            llm_client,
+            st.session_state["llm_model"],
+            st.session_state["mdl_json"],
+            st.session_state["custom_instructions_for_llm"],
+            st.session_state["data_source"],
+            st.session_state["connection_info"],
+        )
+    )
+
+
+def on_click_setup_uploaded_file():
+    uploaded_file = st.session_state.get("uploaded_mdl_file")
+    if uploaded_file:
+        match = re.match(
+            r".+_(" + "|".join(DATA_SOURCES) + r")_mdl\.json$",
+            uploaded_file.name,
+        )
+        if not match:
+            st.error(
+                f"the file name must be [xxx]_[datasource]_mdl.json, now we support these datasources: {DATA_SOURCES}"
+            )
+            st.stop()
+
+        data_source = match.group(1)
+        st.session_state["data_source"] = data_source
+        st.session_state["mdl_json"] = orjson.loads(
+            uploaded_file.getvalue().decode("utf-8")
+        )
+
+        st.session_state["connection_info"] = {
+            "project_id": os.getenv("bigquery.project-id"),
+            "dataset_id": os.getenv("bigquery.dataset-id"),
+            "credentials": os.getenv("bigquery.credentials-key"),
+        }
+    else:
+        st.session_state["data_source"] = None
+        st.session_state["mdl_json"] = None
+        st.session_state["connection_info"] = None
+
+
+def on_change_llm_model():
+    st.toast(f"Switching LLM model to {st.session_state["select_llm_model"]}")
+    st.session_state["llm_model"] = st.session_state["select_llm_model"]
+
+
+def on_change_sql(i: int, key: str):
+    sql = st.session_state[key]
+
+    valid, error = asyncio.run(
+        is_sql_valid(
+            sql,
+            st.session_state["data_source"],
+            st.session_state["mdl_json"],
+            st.session_state["connection_info"],
+        )
+    )
+    if valid:
+        new_context = asyncio.run(
+            get_contexts_from_sqls([sql], st.session_state["mdl_json"])
+        )
+    if i != -1:
+        st.session_state["llm_question_sql_pairs"][i]["sql"] = sql
+        st.session_state["llm_question_sql_pairs"][i]["is_valid"] = valid
+        st.session_state["llm_question_sql_pairs"][i]["error"] = error
+        if valid:
+            st.session_state["llm_question_sql_pairs"][i]["context"] = new_context
+    else:
+        st.session_state["user_question_sql_pair"]["sql"] = sql
+        st.session_state["user_question_sql_pair"]["is_valid"] = valid
+        st.session_state["user_question_sql_pair"]["error"] = error
+        if valid:
+            st.session_state["user_question_sql_pair"]["context"] = new_context
+
+
+def on_click_add_candidate_dataset(i: int, categories: list):
+    if i != -1:
+        dataset_to_add = {
+            "categories": categories,
+            "question": st.session_state["llm_question_sql_pairs"][i]["question"],
+            "context": st.session_state["llm_question_sql_pairs"][i]["context"],
+            "sql": st.session_state["llm_question_sql_pairs"][i]["sql"],
+        }
+    else:
+        dataset_to_add = {
+            "categories": categories,
+            "question": st.session_state["user_question_sql_pair"]["question"],
+            "context": st.session_state["user_question_sql_pair"]["context"],
+            "sql": st.session_state["user_question_sql_pair"]["sql"],
+        }
+
+        # reset input for user question sql pair
+        st.session_state["user_question_sql_pair"] = {}
+        st.session_state["user_question"] = ""
+        st.session_state["user_sql"] = ""
+
+    should_add = True
+    for dataset in st.session_state["candidate_dataset"]:
+        if dataset == dataset_to_add:
+            should_add = False
+            break
+
+    if should_add:
+        st.session_state["candidate_dataset"].append(dataset_to_add)
+
+
+def on_change_user_question():
+    if not st.session_state["user_question_sql_pair"]:
+        st.session_state["user_question_sql_pair"] = {
+            "question": st.session_state["user_question"],
+            "context": [],
+            "sql": "",
+            "is_valid": False,
+            "error": "",
+        }
+    else:
+        st.session_state["user_question_sql_pair"] = {
+            **st.session_state["user_question_sql_pair"],
+            "question": st.session_state["user_question"],
+        }
+
+
+def on_click_remove_candidate_dataset_button(i: int):
+    st.session_state["candidate_dataset"].pop(i)
+
+
+st.file_uploader(
+    f"Upload an MDL json file, and the file name must be [xxx]_[datasource]_mdl.json, now we support these datasources: {DATA_SOURCES}",
+    type="json",
+    key="uploaded_mdl_file",
+    on_change=on_click_setup_uploaded_file,
+)
+
+st.selectbox(
+    label="Select which LLM model you want to use",
+    options=LLM_OPTIONS,
+    index=0,
+    key="select_llm_model",
+    on_change=on_change_llm_model,
+)
+
+tab_create_dataset, tab_modify_dataset = st.tabs(
+    ["Create New Evaluation Dataset", "Modify Saved Evaluation Dataset"]
+)
+with tab_create_dataset:
+    st.markdown(
+        """
+        ### Usage Guide
+        1. Upload an MDL json file first
+        2. Get question-sql-pairs given by LLM or you manually enter question and corresponding sql
+        3. Do validation on each group of question, context and SQL, and move it to the candidate dataset if you think it's valid
+        3. Save the candidate dataset by clicking the "Save as Evaluation Dataset" button.
+        """
+    )
+
+with tab_modify_dataset:
+    st.markdown(
+        """
+        ### Usage Guide
+        1. Upload an MDL json file first
+        2. Upload the evaluation dataset(`.toml` file) you want to modify, and please make sure the model in the dataset is the same as the deployed model
+        3. Modify the evaluation dataset the same as you create a new one
+        4. Save the candidate dataset by clicking the "Save as Evaluation Dataset" button.
+        """
+    )
+
+    st.warning(
+        "WARNING: Uploading the evaluation dataset will overwrite the current candidate dataset"
+    )
+    st.file_uploader(
+        "Upload Evaluation Dataset",
+        type="toml",
+        key="uploaded_eval_file",
+        on_change=on_change_upload_eval_dataset,
+        disabled=st.session_state["mdl_json"] is None,
+    )
+
+if st.session_state["mdl_json"] is not None:
+    col1, col2 = st.columns(2)
+    with col1:
+        st.markdown("### Question SQL Pairs")
+        tab_generated_by_llm, tab_generated_by_user = st.tabs(
+            ["Generated by LLM", "Generated by User"]
+        )
+
+        with tab_generated_by_llm:
+            st.text_area(
+                "Custom Instructions for generating question-sql-pairs (Optional)",
+                key="custom_instructions_text_area",
+                value=st.session_state["custom_instructions_for_llm"],
+                placeholder="You can specify the custom instructions on how LLM should generate question-sql-pairs here, for example: what type of questions you want to generate.",
+                on_change=on_change_custom_instructions_for_llm,
+            )
+
+            st.button(
+                "Generate 10 question-sql-pairs",
+                key="generate_question_sql_pairs",
+                on_click=on_click_generate_question_sql_pairs,
+                args=(llm_client,),
+            )
+
+            with st.container(border=True, height=550):
+                for i, question_sql_pair in enumerate(
+                    st.session_state["llm_question_sql_pairs"]
+                ):
+                    st.text_input(
+                        f"Question {i}",
+                        question_sql_pair["question"],
+                        disabled=True,
+                        key=f"question_{i}",
+                    )
+                    categories = st_tags(
+                        label=f"Categories {i}",
+                        text="Press enter to add more",
+                        value=[],
+                        key=f"categories_{i}",
+                    )
+                    st.multiselect(
+                        label=f"Context {i}",
+                        options=question_sql_pair["context"],
+                        default=question_sql_pair["context"],
+                        key=f"context_{i}",
+                        help="Contexts are automatically generated based on the SQL once you save the changes of the it(ctrl+enter or command+enter)",
+                        disabled=True,
+                    )
+                    st.text_area(
+                        f"SQL {i}",
+                        prettify_sql(question_sql_pair["sql"]),
+                        key=f"sql_{i}",
+                        height=250,
+                        on_change=on_change_sql,
+                        args=(i, f"sql_{i}"),
+                    )
+                    if st.session_state["llm_question_sql_pairs"][i]["is_valid"]:
+                        st.success("SQL is valid")
+                        st.dataframe(
+                            pd.DataFrame(
+                                question_sql_pair["data"]["data"],
+                                columns=question_sql_pair["data"]["columns"],
+                            )
+                        )
+                    else:
+                        st.error(
+                            f"SQL is invalid: {st.session_state["llm_question_sql_pairs"][i]["error"]}"
+                        )
+
+                    st.button(
+                        "Move it to the candidate dataset",
+                        key=f"move_to_dataset_{i}",
+                        disabled=(
+                            not st.session_state["llm_question_sql_pairs"][i][
+                                "is_valid"
+                            ]
+                            or not st.session_state[f"context_{i}"]
+                            or not categories
+                        ),
+                        on_click=on_click_add_candidate_dataset,
+                        args=(
+                            i,
+                            categories,
+                        ),
+                    )
+
+                    st.markdown("---")
+
+        with tab_generated_by_user:
+            with st.container(border=True, height=550):
+                st.text_input(
+                    "Question",
+                    disabled=False,
+                    key="user_question",
+                    on_change=on_change_user_question,
+                )
+                categories = st_tags(
+                    label="Categories",
+                    text="Press enter to add more",
+                    value=[],
+                    key="user_categories",
+                )
+                st.multiselect(
+                    label="Context",
+                    options=st.session_state.get("user_question_sql_pair", {}).get(
+                        "context", []
+                    ),
+                    default=st.session_state.get("user_question_sql_pair", {}).get(
+                        "context", []
+                    ),
+                    key="user_context",
+                    help="Contexts are automatically generated based on the SQL once you save the changes of the it(ctrl+enter or command+enter)",
+                    disabled=True,
+                )
+                st.text_area(
+                    "SQL",
+                    key="user_sql",
+                    height=250,
+                    on_change=on_change_sql,
+                    args=(-1, "user_sql"),
+                )
+
+                if st.session_state.get("user_question_sql_pair", {}).get(
+                    "is_valid", False
+                ):
+                    st.success("SQL is valid")
+                    data = asyncio.run(
+                        get_data_from_wren_engine(
+                            [st.session_state["user_question_sql_pair"]["sql"]],
+                            st.session_state["data_source"],
+                        )
+                    )[0]
+                    st.dataframe(
+                        pd.DataFrame(
+                            data["data"],
+                            columns=data["columns"],
+                        )
+                    )
+                else:
+                    st.error(
+                        f"SQL is invalid: {st.session_state.get("user_question_sql_pair", {}).get('error', '')}"
+                    )
+
+                st.button(
+                    "Move it to the candidate dataset",
+                    key="move_to_dataset",
+                    disabled=(
+                        not st.session_state.get("user_question_sql_pair", {}).get(
+                            "is_valid", False
+                        )
+                        or not st.session_state["user_context"]
+                        or not st.session_state["user_question"]
+                        or not categories
+                    ),
+                    on_click=on_click_add_candidate_dataset,
+                    args=(
+                        -1,
+                        categories,
+                    ),
+                )
+    with col2:
+        st.markdown("### Candidate Dataset")
+
+        with st.container(border=True, height=600):
+            for i, dataset in enumerate(st.session_state["candidate_dataset"]):
+                st.text_input(
+                    f"Question {i}",
+                    dataset["question"],
+                    disabled=True,
+                    key=f"candidate_dataset_question_{i}",
+                )
+                st.multiselect(
+                    f"Categories {i}",
+                    options=dataset["categories"],
+                    default=dataset["categories"],
+                    disabled=True,
+                    key=f"candidate_dataset_categories_{i}",
+                )
+                st.multiselect(
+                    f"Context {i}",
+                    options=dataset["context"],
+                    default=dataset["context"],
+                    disabled=True,
+                    key=f"candidate_dataset_context_{i}",
+                )
+                st.markdown(f"SQL {i}")
+                st.code(prettify_sql(dataset["sql"]), language="sql", line_numbers=True)
+                st.button(
+                    "Remove",
+                    key=f"remove_{i}",
+                    on_click=on_click_remove_candidate_dataset_button,
+                    args=(i,),
+                )
+                st.markdown("---")
+
+        with st.popover("Save as Evaluation Dataset", use_container_width=True):
+            file_name = st.text_input(
+                "File Name",
+                f'eval_dataset_{datetime.today().strftime("%Y_%m_%d")}.toml',
+                key="eval_dataset_file_name",
+            )
+            download_btn = st.download_button(
+                "Download",
+                get_eval_dataset_in_toml_string(
+                    st.session_state["mdl_json"],
+                    st.session_state["candidate_dataset"],
+                ),
+                file_name=file_name,
+                key="download_eval_dataset_confirmed",
+                disabled=not st.session_state["candidate_dataset"],
+            )
+            if download_btn:
+                st.toast("Downloading the evaluation dataset...")
diff --git a/wren-ai-service/eval/data_curation/utils.py b/wren-ai-service/eval/data_curation/utils.py
new file mode 100644
index 000000000..0b6ab8166
--- /dev/null
+++ b/wren-ai-service/eval/data_curation/utils.py
@@ -0,0 +1,326 @@
+import asyncio
+import base64
+import os
+import sys
+from datetime import datetime
+from pathlib import Path
+from typing import List, Tuple
+
+import aiohttp
+import orjson
+import sqlglot
+import sqlparse
+import streamlit as st
+import tomlkit
+from dotenv import load_dotenv
+from openai import AsyncClient
+
+# in order to import the DDLConverter class from the indexing module
+sys.path.append(f"{Path().parent.parent.resolve()}")
+from src.pipelines.indexing.indexing import DDLConverter
+
+load_dotenv()
+
+WREN_IBIS_ENDPOINT = os.getenv("WREN_IBIS_ENDPOINT", "http://localhost:8000")
+WREN_ENGINE_ENDPOINT = os.getenv("WREN_ENGINE_ENDPOINT", "http://localhost:8080")
+DATA_SOURCES = ["bigquery"]
+TIMEOUT_SECONDS = 60
+ddl_converter = DDLConverter()
+
+
+def get_openai_client(
+    api_key: str = os.getenv("OPENAI_API_KEY"), timeout: float = TIMEOUT_SECONDS
+) -> AsyncClient:
+    return AsyncClient(
+        api_key=api_key,
+        timeout=timeout,
+    )
+
+
+def add_quotes(sql: str) -> str:
+    return sqlglot.transpile(sql, read="trino", identify=True)[0]
+
+
+async def is_sql_valid(
+    sql: str,
+    data_source: str,
+    mdl_json: dict,
+    connection_info: dict,
+    api_endpoint: str = WREN_IBIS_ENDPOINT,
+    timeout: float = TIMEOUT_SECONDS,
+) -> Tuple[bool, str]:
+    sql = sql[:-1] if sql.endswith(";") else sql
+    async with aiohttp.request(
+        "POST",
+        f"{api_endpoint}/v2/connector/{data_source}/query?dryRun=true",
+        json={
+            "sql": add_quotes(sql),
+            "manifestStr": base64.b64encode(orjson.dumps(mdl_json)).decode(),
+            "connectionInfo": connection_info,
+        },
+        timeout=aiohttp.ClientTimeout(total=timeout),
+    ) as response:
+        if response.status == 204:
+            return True, None
+        res = await response.text()
+
+        return False, res
+
+
+async def get_validated_question_sql_pairs(
+    question_sql_pairs: list[dict],
+    data_source: str,
+    mdl_json: dict,
+    connection_info: dict,
+) -> list[dict]:
+    tasks = []
+
+    async with aiohttp.ClientSession():
+        for question_sql_pair in question_sql_pairs:
+            task = asyncio.ensure_future(
+                is_sql_valid(
+                    question_sql_pair["sql"],
+                    data_source,
+                    mdl_json,
+                    connection_info,
+                )
+            )
+            tasks.append(task)
+
+        results = await asyncio.gather(*tasks)
+        return [
+            {
+                **question_sql_pairs[i],
+                "context": [],
+                "is_valid": valid,
+                "error": error,
+            }
+            for i, (valid, error) in enumerate(results)
+        ]
+
+
+async def get_sql_analysis(
+    sql: str,
+    mdl_json: dict,
+    api_endpoint: str = WREN_ENGINE_ENDPOINT,
+    timeout: float = TIMEOUT_SECONDS,
+) -> List[dict]:
+    sql = sql[:-1] if sql.endswith(";") else sql
+    async with aiohttp.request(
+        "GET",
+        f"{api_endpoint}/v1/analysis/sql",
+        json={
+            "sql": add_quotes(sql),
+            "manifest": mdl_json,
+        },
+        timeout=aiohttp.ClientTimeout(total=timeout),
+    ) as response:
+        return await response.json()
+
+
+async def get_contexts_from_sqls(
+    sqls: list[str],
+    mdl_json: dict,
+) -> list[str]:
+    def _compose_contexts_of_select_type(select_items: list[dict]):
+        return [
+            f'{expr_source['sourceDataset']}.{expr_source['expression']}'
+            for select_item in select_items
+            for expr_source in select_item["exprSources"]
+        ]
+
+    def _compose_contexts_of_filter_type(filter: dict):
+        contexts = []
+        if filter["type"] == "EXPR":
+            contexts += [
+                f'{expr_source["sourceDataset"]}.{expr_source["expression"]}'
+                for expr_source in filter["exprSources"]
+            ]
+        elif filter["type"] in ("AND", "OR"):
+            contexts += _compose_contexts_of_filter_type(filter["left"])
+            contexts += _compose_contexts_of_filter_type(filter["right"])
+
+        return contexts
+
+    def _compose_contexts_of_groupby_type(groupby_keys: list[list[dict]]):
+        contexts = []
+        for groupby_key_list in groupby_keys:
+            contexts += [
+                f'{expr_source["sourceDataset"]}.{expr_source["expression"]}'
+                for groupby_key in groupby_key_list
+                for expr_source in groupby_key["exprSources"]
+            ]
+        return contexts
+
+    def _compose_contexts_of_sorting_type(sortings: list[dict]):
+        return [
+            f'{expr_source["sourceDataset"]}.{expr_source["expression"]}'
+            for sorting in sortings
+            for expr_source in sorting["exprSources"]
+        ]
+
+    def _get_contexts_from_sql_analysis_results(sql_analysis_results: list[dict]):
+        contexts = []
+        for result in sql_analysis_results:
+            if "selectItems" in result:
+                contexts += _compose_contexts_of_select_type(result["selectItems"])
+            if "filter" in result:
+                contexts += _compose_contexts_of_filter_type(result["filter"])
+            if "groupByKeys" in result:
+                contexts += _compose_contexts_of_groupby_type(result["groupByKeys"])
+            if "sortings" in result:
+                contexts += _compose_contexts_of_sorting_type(result["sortings"])
+
+        # print(
+        #     f'SQL ANALYSIS RESULTS: {orjson.dumps(sql_analysis_results, option=orjson.OPT_INDENT_2).decode("utf-8")}'
+        # )
+        # print(f"CONTEXTS: {sorted(set(contexts))}")
+        # print("\n\n")
+
+        return sorted(set(contexts))
+
+    async with aiohttp.ClientSession():
+        tasks = []
+        for sql in sqls:
+            task = asyncio.ensure_future(get_sql_analysis(sql, mdl_json))
+            tasks.append(task)
+
+        results = await asyncio.gather(*tasks)
+
+        return [_get_contexts_from_sql_analysis_results(result) for result in results]
+
+
+async def get_question_sql_pairs(
+    llm_client: AsyncClient,
+    llm_model: str,
+    mdl_json: dict,
+    custom_instructions: str,
+    data_source: str,
+    connection_info: dict,
+    num_pairs: int = 10,
+) -> list[dict]:
+    messages = [
+        {
+            "role": "system",
+            "content": "",
+        },
+        {
+            "role": "user",
+            "content": f"""
+### TASK ###
+Given the database DDL, generate {num_pairs} of the questions and corresponding SQL queries.
+
+### Output Format ###
+{{
+    "results": [
+        {{
+            "question": <question_string>,
+            "sql": <sql_query_string>
+        }},
+        {{
+            "question": <question_string>,
+            "sql": <sql_query_string>
+        }},
+        ...
+    ]
+}}
+
+### Custom Instructions ###
+
+{custom_instructions}
+
+### Input ###
+Data Model: {"\n\n".join(ddl_converter.get_ddl_commands(mdl_json))}
+
+Generate {num_pairs} of the questions and corresponding SQL queries according to the Output Format in JSON
+Think step by step
+""",
+        },
+    ]
+
+    try:
+        response = await llm_client.chat.completions.create(
+            model=llm_model,
+            messages=messages,
+            response_format={"type": "json_object"},
+            max_tokens=4096,
+            temperature=0,
+        )
+
+        results = orjson.loads(response.choices[0].message.content)["results"]
+        question_sql_pairs = await get_validated_question_sql_pairs(
+            results,
+            data_source=data_source,
+            mdl_json=mdl_json,
+            connection_info=connection_info,
+        )
+        sqls = [question_sql_pair["sql"] for question_sql_pair in question_sql_pairs]
+        contexts = await get_contexts_from_sqls(sqls, mdl_json)
+        sqls_data = await get_data_from_wren_engine(sqls, data_source)
+        return [
+            {**quesiton_sql_pair, "context": context, "data": sql_data}
+            for quesiton_sql_pair, context, sql_data in zip(
+                question_sql_pairs, contexts, sqls_data
+            )
+        ]
+    except Exception as e:
+        st.error(f"Error generating question-sql-pairs: {e}")
+        return []
+
+
+def prettify_sql(sql: str) -> str:
+    return sqlparse.format(
+        sql,
+        reindent=True,
+        keyword_case="upper",
+    )
+
+
+async def get_data_from_wren_engine(
+    sqls: List[str],
+    data_source: str,
+    api_endpoint: str = WREN_IBIS_ENDPOINT,
+    data_sources: list[str] = DATA_SOURCES,
+    timeout: float = TIMEOUT_SECONDS,
+) -> List[dict]:
+    assert data_source in data_sources, f"Invalid data source: {data_source}"
+
+    async def _get_data(sql: str, data_source: str):
+        async with aiohttp.request(
+            "POST",
+            f"{api_endpoint}/v2/connector/{data_source}/query",
+            json={
+                "sql": add_quotes(sql),
+                "manifestStr": base64.b64encode(
+                    orjson.dumps(st.session_state["mdl_json"])
+                ).decode(),
+                "connectionInfo": st.session_state["connection_info"],
+            },
+            timeout=aiohttp.ClientTimeout(total=timeout),
+        ) as response:
+            if response.status != 200:
+                return {"data": [], "columns": []}
+
+            data = await response.json()
+            column_names = [f"{i}_{col}" for i, col in enumerate(data["columns"])]
+
+            return {"data": data["data"], "columns": column_names}
+
+    async with aiohttp.ClientSession():
+        tasks = []
+        for sql in sqls:
+            task = asyncio.ensure_future(_get_data(sql, data_source))
+            tasks.append(task)
+
+        return await asyncio.gather(*tasks)
+
+
+@st.cache_data
+def get_eval_dataset_in_toml_string(mdl: dict, dataset: list) -> str:
+    doc = tomlkit.document()
+
+    doc.add("date", datetime.today().strftime("%Y_%m_%d"))
+    doc.add("mdl", mdl)
+    doc.add("eval_dataset", dataset)
+
+    return tomlkit.dumps(doc)
diff --git a/wren-ai-service/poetry.lock b/wren-ai-service/poetry.lock
index a96fa40d1..bf85df856 100644
--- a/wren-ai-service/poetry.lock
+++ b/wren-ai-service/poetry.lock
@@ -1,5 +1,19 @@
 # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
+[[package]]
+name = "aiodns"
+version = "3.2.0"
+description = "Simple DNS resolver for asyncio"
+optional = false
+python-versions = "*"
+files = [
+    {file = "aiodns-3.2.0-py3-none-any.whl", hash = "sha256:e443c0c27b07da3174a109fd9e736d69058d808f144d3c9d56dbd1776964c5f5"},
+    {file = "aiodns-3.2.0.tar.gz", hash = "sha256:62869b23409349c21b072883ec8998316b234c9a9e36675756e8e317e8768f72"},
+]
+
+[package.dependencies]
+pycares = ">=4.0.0"
+
 [[package]]
 name = "aiohttp"
 version = "3.9.5"
@@ -86,8 +100,11 @@ files = [
 ]
 
 [package.dependencies]
+aiodns = {version = "*", optional = true, markers = "(sys_platform == \"linux\" or sys_platform == \"darwin\") and extra == \"speedups\""}
 aiosignal = ">=1.1.2"
 attrs = ">=17.3.0"
+Brotli = {version = "*", optional = true, markers = "platform_python_implementation == \"CPython\" and extra == \"speedups\""}
+brotlicffi = {version = "*", optional = true, markers = "platform_python_implementation != \"CPython\" and extra == \"speedups\""}
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
 yarl = ">=1.0,<2.0"
@@ -340,15 +357,54 @@ files = [
     {file = "Brotli-1.1.0.tar.gz", hash = "sha256:81de08ac11bcb85841e440c13611c00b67d3bf82698314928d0b676362546724"},
 ]
 
+[[package]]
+name = "brotlicffi"
+version = "1.1.0.0"
+description = "Python CFFI bindings to the Brotli library"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "brotlicffi-1.1.0.0-cp37-abi3-macosx_10_9_x86_64.whl", hash = "sha256:9b7ae6bd1a3f0df532b6d67ff674099a96d22bc0948955cb338488c31bfb8851"},
+    {file = "brotlicffi-1.1.0.0-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:19ffc919fa4fc6ace69286e0a23b3789b4219058313cf9b45625016bf7ff996b"},
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+]
+
+[package.dependencies]
+cffi = ">=1.0.0"
+
 [[package]]
 name = "cachetools"
-version = "5.3.3"
+version = "5.4.0"
 description = "Extensible memoizing collections and decorators"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "cachetools-5.3.3-py3-none-any.whl", hash = "sha256:0abad1021d3f8325b2fc1d2e9c8b9c9d57b04c3932657a72465447332c24d945"},
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 ]
 
 [[package]]
@@ -657,37 +713,37 @@ typing-inspect = ">=0.4.0,<1"
 
 [[package]]
 name = "datasets"
-version = "2.20.0"
+version = "2.19.1"
 description = "HuggingFace community-driven open-source library of datasets"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "datasets-2.20.0-py3-none-any.whl", hash = "sha256:76ac02e3bdfff824492e20678f0b6b1b6d080515957fe834b00c2ba8d6b18e5e"},
-    {file = "datasets-2.20.0.tar.gz", hash = "sha256:3c4dbcd27e0f642b9d41d20ff2efa721a5e04b32b2ca4009e0fc9139e324553f"},
+    {file = "datasets-2.19.1-py3-none-any.whl", hash = "sha256:f7a78d15896f45004ccac1c298f3c7121f92f91f6f2bfbd4e4f210f827e6e411"},
+    {file = "datasets-2.19.1.tar.gz", hash = "sha256:0df9ef6c5e9138cdb996a07385220109ff203c204245578b69cca905eb151d3a"},
 ]
 
 [package.dependencies]
 aiohttp = "*"
 dill = ">=0.3.0,<0.3.9"
 filelock = "*"
-fsspec = {version = ">=2023.1.0,<=2024.5.0", extras = ["http"]}
+fsspec = {version = ">=2023.1.0,<=2024.3.1", extras = ["http"]}
 huggingface-hub = ">=0.21.2"
 multiprocess = "*"
 numpy = ">=1.17"
 packaging = "*"
 pandas = "*"
-pyarrow = ">=15.0.0"
+pyarrow = ">=12.0.0"
 pyarrow-hotfix = "*"
 pyyaml = ">=5.1"
-requests = ">=2.32.2"
-tqdm = ">=4.66.3"
+requests = ">=2.19.0"
+tqdm = ">=4.62.1"
 xxhash = "*"
 
 [package.extras]
 apache-beam = ["apache-beam (>=2.26.0)"]
 audio = ["librosa", "soundfile (>=0.12.1)"]
 benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"]
-dev = ["Pillow (>=9.4.0)", "absl-py", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "ruff (>=0.3.0)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.6.0)", "tiktoken", "torch", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
+dev = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "ruff (>=0.3.0)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.6.0)", "tiktoken", "torch", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
 docs = ["s3fs", "tensorflow (>=2.6.0)", "torch", "transformers"]
 jax = ["jax (>=0.3.14)", "jaxlib (>=0.3.14)"]
 metrics-tests = ["Werkzeug (>=1.0.1)", "accelerate", "bert-score (>=0.3.6)", "jiwer", "langdetect", "mauve-text", "nltk", "requests-file (>=1.5.1)", "rouge-score", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "spacy (>=3.0.0)", "texttable (>=1.6.3)", "tldextract", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "typer (<0.5.0)"]
@@ -695,9 +751,9 @@ quality = ["ruff (>=0.3.0)"]
 s3 = ["s3fs"]
 tensorflow = ["tensorflow (>=2.6.0)"]
 tensorflow-gpu = ["tensorflow (>=2.6.0)"]
-tests = ["Pillow (>=9.4.0)", "absl-py", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.6.0)", "tiktoken", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
+tests = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.6.0)", "tiktoken", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
 torch = ["torch"]
-vision = ["Pillow (>=9.4.0)"]
+vision = ["Pillow (>=6.2.1)"]
 
 [[package]]
 name = "dill"
@@ -910,13 +966,13 @@ files = [
 
 [[package]]
 name = "fsspec"
-version = "2024.5.0"
+version = "2024.3.1"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fsspec-2024.5.0-py3-none-any.whl", hash = "sha256:e0fdbc446d67e182f49a70b82cf7889028a63588fde6b222521f10937b2b670c"},
-    {file = "fsspec-2024.5.0.tar.gz", hash = "sha256:1d021b0b0f933e3b3029ed808eb400c08ba101ca2de4b3483fbc9ca23fcee94a"},
+    {file = "fsspec-2024.3.1-py3-none-any.whl", hash = "sha256:918d18d41bf73f0e2b261824baeb1b124bcf771767e3a26425cd7dec3332f512"},
+    {file = "fsspec-2024.3.1.tar.gz", hash = "sha256:f39780e282d7d117ffb42bb96992f8a90795e4d0fb0f661a70ca39fe9c43ded9"},
 ]
 
 [package.dependencies]
@@ -927,7 +983,7 @@ abfs = ["adlfs"]
 adl = ["adlfs"]
 arrow = ["pyarrow (>=1)"]
 dask = ["dask", "distributed"]
-dev = ["pre-commit", "ruff"]
+devel = ["pytest", "pytest-cov"]
 dropbox = ["dropbox", "dropboxdrivefs", "requests"]
 full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
 fuse = ["fusepy"]
@@ -944,9 +1000,6 @@ s3 = ["s3fs"]
 sftp = ["paramiko"]
 smb = ["smbprotocol"]
 ssh = ["paramiko"]
-test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
-test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
-test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
 tqdm = ["tqdm"]
 
 [[package]]
@@ -1536,13 +1589,13 @@ socks = ["socksio (==1.*)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "0.23.4"
+version = "0.23.5"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "huggingface_hub-0.23.4-py3-none-any.whl", hash = "sha256:3a0b957aa87150addf0cc7bd71b4d954b78e749850e1e7fb29ebbd2db64ca037"},
-    {file = "huggingface_hub-0.23.4.tar.gz", hash = "sha256:35d99016433900e44ae7efe1c209164a5a81dbbcd53a52f99c281dcd7ce22431"},
+    {file = "huggingface_hub-0.23.5-py3-none-any.whl", hash = "sha256:d7a7d337615e11a45cc14a0ce5a605db6b038dc24af42866f731684825226e90"},
+    {file = "huggingface_hub-0.23.5.tar.gz", hash = "sha256:67a9caba79b71235be3752852ca27da86bd54311d2424ca8afdb8dda056edf98"},
 ]
 
 [package.dependencies]
@@ -1705,18 +1758,18 @@ referencing = ">=0.31.0"
 
 [[package]]
 name = "langchain"
-version = "0.2.7"
+version = "0.2.8"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain-0.2.7-py3-none-any.whl", hash = "sha256:98e79e0b9a60a9c740b44d5b0135c85f649219308f30d373cf5f10d0efe18b87"},
-    {file = "langchain-0.2.7.tar.gz", hash = "sha256:8742f363d2890854501e0075af04fcb470600f201dec251c9bd5841e1990e73d"},
+    {file = "langchain-0.2.8-py3-none-any.whl", hash = "sha256:53e7dfe50294a14200f33bec22b4e14cb63857ccf0a5500b0d18b0fd51285d58"},
+    {file = "langchain-0.2.8.tar.gz", hash = "sha256:7fecb309e3558cde4e5cf7e9ffb7c1ab3f07121c40a7ff3b0c27135f8120c296"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
-langchain-core = ">=0.2.12,<0.3.0"
+langchain-core = ">=0.2.19,<0.3.0"
 langchain-text-splitters = ">=0.2.0,<0.3.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = {version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""}
@@ -1751,13 +1804,13 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.2.17"
+version = "0.2.20"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.2.17-py3-none-any.whl", hash = "sha256:f8b4f64c95b381bd3ac4322bafa9ecee3ca3970aa0aa2829ef11175bcad27249"},
-    {file = "langchain_core-0.2.17.tar.gz", hash = "sha256:f9b8d0f7b5f339ac62e11c417181e87f54e9282af82d1a64c8a7427f3d5d9118"},
+    {file = "langchain_core-0.2.20-py3-none-any.whl", hash = "sha256:16cc4da6f7ebf33accea7af45a70480733dc852ab291030fb6924865bd7caf76"},
+    {file = "langchain_core-0.2.20.tar.gz", hash = "sha256:a66c439e085d8c75f822f7650a5551d17bada4003521173c763d875d949e4ed5"},
 ]
 
 [package.dependencies]
@@ -1827,13 +1880,13 @@ openai = ["openai (>=0.27.8)"]
 
 [[package]]
 name = "langsmith"
-version = "0.1.85"
+version = "0.1.88"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.85-py3-none-any.whl", hash = "sha256:c1f94384f10cea96f7b4d33fd3db7ec180c03c7468877d50846f881d2017ff94"},
-    {file = "langsmith-0.1.85.tar.gz", hash = "sha256:acff31f9e53efa48586cf8e32f65625a335c74d7c4fa306d1655ac18452296f6"},
+    {file = "langsmith-0.1.88-py3-none-any.whl", hash = "sha256:460ebb7de440afd150fcea8f54ca8779821f2228cd59e149e5845c9dbe06db16"},
+    {file = "langsmith-0.1.88.tar.gz", hash = "sha256:28a07dec19197f4808aa2628d5a3ccafcbe14cc137aef0e607bbd128e7907821"},
 ]
 
 [package.dependencies]
@@ -2631,13 +2684,13 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "portalocker"
-version = "2.10.0"
+version = "2.10.1"
 description = "Wraps the portalocker recipe for easy usage"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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 description = "Python library for Apache Arrow"
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 ]
 
 [package.dependencies]
 numpy = ">=1.16.6"
 
+[package.extras]
+test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
+
 [[package]]
 name = "pyarrow-hotfix"
 version = "0.6"
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 ]
 
+[[package]]
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+version = "4.4.0"
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+    {file = "pycares-4.4.0-cp312-cp312-win_amd64.whl", hash = "sha256:db24c4e7fea4a052c6e869cbf387dd85d53b9736cfe1ef5d8d568d1ca925e977"},
+    {file = "pycares-4.4.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:21a5a0468861ec7df7befa69050f952da13db5427ae41ffe4713bc96291d1d95"},
+    {file = "pycares-4.4.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:22c00bf659a9fa44d7b405cf1cd69b68b9d37537899898d8cbe5dffa4016b273"},
+    {file = "pycares-4.4.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:23aa3993a352491a47fcf17867f61472f32f874df4adcbb486294bd9fbe8abee"},
+    {file = "pycares-4.4.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:813d661cbe2e37d87da2d16b7110a6860e93ddb11735c6919c8a3545c7b9c8d8"},
+    {file = "pycares-4.4.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:77cf5a2fd5583c670de41a7f4a7b46e5cbabe7180d8029f728571f4d2e864084"},
+    {file = "pycares-4.4.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:3eaa6681c0a3e3f3868c77aca14b7760fed35fdfda2fe587e15c701950e7bc69"},
+    {file = "pycares-4.4.0-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:ad58e284a658a8a6a84af2e0b62f2f961f303cedfe551854d7bd40c3cbb61912"},
+    {file = "pycares-4.4.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:bfb89ca9e3d0a9b5332deeb666b2ede9d3469107742158f4aeda5ce032d003f4"},
+    {file = "pycares-4.4.0-cp38-cp38-win32.whl", hash = "sha256:f36bdc1562142e3695555d2f4ac0cb69af165eddcefa98efc1c79495b533481f"},
+    {file = "pycares-4.4.0-cp38-cp38-win_amd64.whl", hash = "sha256:902461a92b6a80fd5041a2ec5235680c7cc35e43615639ec2a40e63fca2dfb51"},
+    {file = "pycares-4.4.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:7bddc6adba8f699728f7fc1c9ce8cef359817ad78e2ed52b9502cb5f8dc7f741"},
+    {file = "pycares-4.4.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:cb49d5805cd347c404f928c5ae7c35e86ba0c58ffa701dbe905365e77ce7d641"},
+    {file = "pycares-4.4.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:56cf3349fa3a2e67ed387a7974c11d233734636fe19facfcda261b411af14d80"},
+    {file = "pycares-4.4.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8bf2eaa83a5987e48fa63302f0fe7ce3275cfda87b34d40fef9ce703fb3ac002"},
+    {file = "pycares-4.4.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:82bba2ab77eb5addbf9758d514d9bdef3c1bfe7d1649a47bd9a0d55a23ef478b"},
+    {file = "pycares-4.4.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:c6a8bde63106f162fca736e842a916853cad3c8d9d137e11c9ffa37efa818b02"},
+    {file = "pycares-4.4.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:f5f646eec041db6ffdbcaf3e0756fb92018f7af3266138c756bb09d2b5baadec"},
+    {file = "pycares-4.4.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:9dc04c54c6ea615210c1b9e803d0e2d2255f87a3d5d119b6482c8f0dfa15b26b"},
+    {file = "pycares-4.4.0-cp39-cp39-win32.whl", hash = "sha256:97892cced5794d721fb4ff8765764aa4ea48fe8b2c3820677505b96b83d4ef47"},
+    {file = "pycares-4.4.0-cp39-cp39-win_amd64.whl", hash = "sha256:917f08f0b5d9324e9a34211e68d27447c552b50ab967044776bbab7e42a553a2"},
+    {file = "pycares-4.4.0.tar.gz", hash = "sha256:f47579d508f2f56eddd16ce72045782ad3b1b3b678098699e2b6a1b30733e1c2"},
+]
+
+[package.dependencies]
+cffi = ">=1.5.0"
+
+[package.extras]
+idna = ["idna (>=2.1)"]
+
 [[package]]
 name = "pycparser"
 version = "2.22"
@@ -3513,13 +3622,13 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.32.3"
+version = "2.31.0"
 description = "Python HTTP for Humans."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7"
 files = [
-    {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
-    {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
+    {file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
+    {file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
 ]
 
 [package.dependencies]
@@ -3926,6 +4035,20 @@ watchdog = {version = ">=2.1.5", markers = "platform_system != \"Darwin\""}
 [package.extras]
 snowflake = ["snowflake-connector-python (>=2.8.0)", "snowflake-snowpark-python (>=0.9.0)"]
 
+[[package]]
+name = "streamlit-tags"
+version = "1.2.8"
+description = "Tags custom component for Streamlit"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "streamlit_tags-1.2.8-py3-none-any.whl", hash = "sha256:c71b10666f3fce67d8e0b3c089aa50dc48830d310223fb88005b08f157586f95"},
+    {file = "streamlit_tags-1.2.8.tar.gz", hash = "sha256:9ea46b21f206dc73164e59e3c800a96c863c90af57afde20115f001a6d986583"},
+]
+
+[package.dependencies]
+streamlit = ">=0.63"
+
 [[package]]
 name = "tenacity"
 version = "8.5.0"
@@ -4004,6 +4127,17 @@ files = [
     {file = "toml-0.10.2.tar.gz", hash = "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f"},
 ]
 
+[[package]]
+name = "tomlkit"
+version = "0.12.5"
+description = "Style preserving TOML library"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tomlkit-0.12.5-py3-none-any.whl", hash = "sha256:af914f5a9c59ed9d0762c7b64d3b5d5df007448eb9cd2edc8a46b1eafead172f"},
+    {file = "tomlkit-0.12.5.tar.gz", hash = "sha256:eef34fba39834d4d6b73c9ba7f3e4d1c417a4e56f89a7e96e090dd0d24b8fb3c"},
+]
+
 [[package]]
 name = "toolz"
 version = "0.12.1"
@@ -4797,4 +4931,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.12.*, <4.0"
-content-hash = "4592f4cc15dcf7566fc314c127df2d649f20ecc05c2a672d2c982ad5df5174e1"
+content-hash = "7159216c0183970d94b3b819c5460bac914e8ddbbdc96bb618791c5978899b64"
diff --git a/wren-ai-service/pyproject.toml b/wren-ai-service/pyproject.toml
index 58894d574..b659ed1e5 100644
--- a/wren-ai-service/pyproject.toml
+++ b/wren-ai-service/pyproject.toml
@@ -21,7 +21,7 @@ sqlparse = "==0.5.0"
 sqlglot = "==22.5.0"
 orjson = "==3.10.3"
 sf-hamilton = {version = "==1.63.0", extras = ["visualization"]}
-aiohttp = "==3.9.5"
+aiohttp = {extras = ["speedups"], version = "==3.9.5"}
 ollama-haystack = "==0.0.6"
 langfuse = "==2.35.0"
 ollama = "==0.2.1"
@@ -40,6 +40,13 @@ psycopg2-binary = "==2.9.9"
 setuptools = "==70.0.0"
 locust = "==2.28.0"
 
+[tool.poetry.group.eval.dependencies]
+tomlkit = "==0.12.5"
+streamlit-tags = "==1.2.8"
+
+[tool.poetry.group.demo.dependencies]
+requests = "==2.31.0"
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
diff --git a/wren-ai-service/src/core/engine.py b/wren-ai-service/src/core/engine.py
index e1c999efc..d315ff98e 100644
--- a/wren-ai-service/src/core/engine.py
+++ b/wren-ai-service/src/core/engine.py
@@ -15,7 +15,6 @@ class Engine(metaclass=ABCMeta):
         self,
         sql: str,
         session: aiohttp.ClientSession,
-        properties: Dict[str, Any] = {},
     ) -> Tuple[bool, Optional[Dict[str, Any]]]:
         ...
 
diff --git a/wren-ai-service/src/force_deploy.py b/wren-ai-service/src/force_deploy.py
index ee5c4381f..2cf129d5b 100644
--- a/wren-ai-service/src/force_deploy.py
+++ b/wren-ai-service/src/force_deploy.py
@@ -1,12 +1,13 @@
 import asyncio
 import os
+from pathlib import Path
 
 import aiohttp
 import backoff
+from dotenv import load_dotenv
 
-from src.utils import load_env_vars
-
-load_env_vars()
+if Path(".env.dev").exists():
+    load_dotenv(".env.dev", override=True)
 
 
 @backoff.on_exception(backoff.expo, aiohttp.ClientError, max_time=60, max_tries=3)
diff --git a/wren-ai-service/src/pipelines/ask/followup_generation.py b/wren-ai-service/src/pipelines/ask/followup_generation.py
index 76d7c489e..e0620676b 100644
--- a/wren-ai-service/src/pipelines/ask/followup_generation.py
+++ b/wren-ai-service/src/pipelines/ask/followup_generation.py
@@ -17,7 +17,7 @@ from src.pipelines.ask.components.prompts import (
     TEXT_TO_SQL_RULES,
     text_to_sql_system_prompt,
 )
-from src.utils import async_timer, init_providers, timer
+from src.utils import async_timer, timer
 from src.web.v1.services.ask import AskRequest
 
 logger = logging.getLogger("wren-ai-service")
@@ -234,7 +234,7 @@ class FollowUpGeneration(BasicPipeline):
 if __name__ == "__main__":
     from langfuse.decorators import langfuse_context
 
-    from src.utils import init_langfuse, load_env_vars
+    from src.utils import init_langfuse, init_providers, load_env_vars
 
     load_env_vars()
     init_langfuse()
diff --git a/wren-ai-service/src/pipelines/ask/generation.py b/wren-ai-service/src/pipelines/ask/generation.py
index 29e521b8b..5b9741902 100644
--- a/wren-ai-service/src/pipelines/ask/generation.py
+++ b/wren-ai-service/src/pipelines/ask/generation.py
@@ -19,7 +19,7 @@ from src.pipelines.ask.components.prompts import (
     TEXT_TO_SQL_RULES,
     text_to_sql_system_prompt,
 )
-from src.utils import async_timer, init_providers, timer
+from src.utils import async_timer, timer
 
 logger = logging.getLogger("wren-ai-service")
 
@@ -192,7 +192,7 @@ class Generation(BasicPipeline):
 if __name__ == "__main__":
     from langfuse.decorators import langfuse_context
 
-    from src.utils import init_langfuse, load_env_vars
+    from src.utils import init_langfuse, init_providers, load_env_vars
 
     load_env_vars()
     init_langfuse()
diff --git a/wren-ai-service/src/pipelines/ask/historical_question.py b/wren-ai-service/src/pipelines/ask/historical_question.py
index 47059f1b9..321892858 100644
--- a/wren-ai-service/src/pipelines/ask/historical_question.py
+++ b/wren-ai-service/src/pipelines/ask/historical_question.py
@@ -13,7 +13,6 @@ from src.core.pipeline import BasicPipeline, async_validate
 from src.core.provider import DocumentStoreProvider, EmbedderProvider
 from src.utils import (
     async_timer,
-    init_providers,
     timer,
 )
 
@@ -149,7 +148,7 @@ class HistoricalQuestion(BasicPipeline):
 if __name__ == "__main__":
     from langfuse.decorators import langfuse_context
 
-    from src.utils import init_langfuse, load_env_vars
+    from src.utils import init_langfuse, init_providers, load_env_vars
 
     load_env_vars()
     init_langfuse()
diff --git a/wren-ai-service/src/pipelines/ask/retrieval.py b/wren-ai-service/src/pipelines/ask/retrieval.py
index 152b6ad2e..eee0c7be3 100644
--- a/wren-ai-service/src/pipelines/ask/retrieval.py
+++ b/wren-ai-service/src/pipelines/ask/retrieval.py
@@ -9,7 +9,7 @@ from langfuse.decorators import observe
 
 from src.core.pipeline import BasicPipeline, async_validate
 from src.core.provider import DocumentStoreProvider, EmbedderProvider
-from src.utils import async_timer, init_providers
+from src.utils import async_timer
 
 logger = logging.getLogger("wren-ai-service")
 
@@ -83,7 +83,7 @@ class Retrieval(BasicPipeline):
 if __name__ == "__main__":
     from langfuse.decorators import langfuse_context
 
-    from src.utils import init_langfuse, load_env_vars
+    from src.utils import init_langfuse, init_providers, load_env_vars
 
     load_env_vars()
     init_langfuse()
diff --git a/wren-ai-service/src/pipelines/ask/sql_correction.py b/wren-ai-service/src/pipelines/ask/sql_correction.py
index b6cd76d36..38b189a03 100644
--- a/wren-ai-service/src/pipelines/ask/sql_correction.py
+++ b/wren-ai-service/src/pipelines/ask/sql_correction.py
@@ -17,7 +17,7 @@ from src.pipelines.ask.components.prompts import (
     TEXT_TO_SQL_RULES,
     text_to_sql_system_prompt,
 )
-from src.utils import async_timer, init_providers, timer
+from src.utils import async_timer, timer
 
 logger = logging.getLogger("wren-ai-service")
 
@@ -158,7 +158,7 @@ class SQLCorrection(BasicPipeline):
 if __name__ == "__main__":
     from langfuse.decorators import langfuse_context
 
-    from src.utils import init_langfuse, load_env_vars
+    from src.utils import init_langfuse, init_providers, load_env_vars
 
     load_env_vars()
     init_langfuse()
diff --git a/wren-ai-service/src/pipelines/ask_details/generation.py b/wren-ai-service/src/pipelines/ask_details/generation.py
index ad0933fdf..5caca7f5f 100644
--- a/wren-ai-service/src/pipelines/ask_details/generation.py
+++ b/wren-ai-service/src/pipelines/ask_details/generation.py
@@ -24,7 +24,6 @@ from src.pipelines.ask_details.components.prompts import (
 )
 from src.utils import (
     async_timer,
-    init_providers,
     timer,
 )
 
@@ -197,7 +196,7 @@ class Generation(BasicPipeline):
 if __name__ == "__main__":
     from langfuse.decorators import langfuse_context, observe
 
-    from src.utils import init_langfuse, load_env_vars
+    from src.utils import init_langfuse, init_providers, load_env_vars
 
     load_env_vars()
     init_langfuse()
diff --git a/wren-ai-service/src/pipelines/indexing/indexing.py b/wren-ai-service/src/pipelines/indexing/indexing.py
index bd16049e3..25f77848f 100644
--- a/wren-ai-service/src/pipelines/indexing/indexing.py
+++ b/wren-ai-service/src/pipelines/indexing/indexing.py
@@ -17,7 +17,7 @@ from tqdm import tqdm
 
 from src.core.pipeline import BasicPipeline, async_validate
 from src.core.provider import DocumentStoreProvider, EmbedderProvider
-from src.utils import async_timer, init_providers, timer
+from src.utils import async_timer, timer
 
 logger = logging.getLogger("wren-ai-service")
 
@@ -124,6 +124,25 @@ class DDLConverter:
 
         logger.debug(f"original mdl_json: {mdl}")
 
+        ddl_commands = self.get_ddl_commands(mdl)
+
+        return {
+            "documents": [
+                Document(
+                    id=str(i),
+                    meta={"id": str(i)},
+                    content=ddl_command,
+                )
+                for i, ddl_command in enumerate(
+                    tqdm(
+                        ddl_commands,
+                        desc="indexing ddl commands into the ddl store",
+                    )
+                )
+            ]
+        }
+
+    def get_ddl_commands(self, mdl: Dict[str, Any]) -> List[str]:
         semantics = {
             "models": [],
             "relationships": mdl["relationships"],
@@ -159,7 +178,7 @@ class DDLConverter:
                 }
             )
 
-        ddl_commands = (
+        return (
             self._convert_models_and_relationships(
                 semantics["models"], semantics["relationships"]
             )
@@ -167,22 +186,6 @@ class DDLConverter:
             + self._convert_views(semantics["views"])
         )
 
-        return {
-            "documents": [
-                Document(
-                    id=str(i),
-                    meta={"id": str(i)},
-                    content=ddl_command,
-                )
-                for i, ddl_command in enumerate(
-                    tqdm(
-                        ddl_commands,
-                        desc="indexing ddl commands into the ddl store",
-                    )
-                )
-            ]
-        }
-
     # TODO: refactor this method
     def _convert_models_and_relationships(
         self, models: List[Dict[str, Any]], relationships: List[Dict[str, Any]]
@@ -458,7 +461,7 @@ class Indexing(BasicPipeline):
 if __name__ == "__main__":
     from langfuse.decorators import langfuse_context
 
-    from src.utils import init_langfuse, load_env_vars
+    from src.utils import init_langfuse, init_providers, load_env_vars
 
     load_env_vars()
     init_langfuse()
diff --git a/wren-ai-service/src/prepare_mdl_json.py b/wren-ai-service/src/prepare_mdl_json.py
deleted file mode 100644
index cfe34b06a..000000000
--- a/wren-ai-service/src/prepare_mdl_json.py
+++ /dev/null
@@ -1,37 +0,0 @@
-import argparse
-import os
-import shutil
-from pathlib import Path
-
-from .utils import load_env_vars
-
-load_env_vars()
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Prepare the MDL JSON file for the Wren engine using the Spider dataset"
-    )
-    parser.add_argument(
-        "--dataset_name",
-        type=str,
-        default=os.getenv("DATASET_NAME"),
-        help="Database name of the Spider dataset",
-    )
-    args = parser.parse_args()
-
-    dataset_name = args.dataset_name
-
-    assert Path(
-        f"src/eval/data/{dataset_name}_mdl.json"
-    ).exists(), f"File not found in src/eval/data: {dataset_name}_mdl.json"
-
-    # remove all files in src/eval/wren-engine/etc/mdl
-    os.system("rm -rf tools/dev/etc/mdl/*")
-    os.makedirs("tools/dev/etc/mdl", exist_ok=True)
-
-    # move the file to src/eval/wren-engine/etc/mdl
-    shutil.copyfile(
-        f"src/eval/data/{dataset_name}_mdl.json",
-        f"tools/dev/etc/mdl/{dataset_name}_mdl.json",
-    )
diff --git a/wren-ai-service/src/providers/engine/wren.py b/wren-ai-service/src/providers/engine/wren.py
index d186abb6e..7e470f8e8 100644
--- a/wren-ai-service/src/providers/engine/wren.py
+++ b/wren-ai-service/src/providers/engine/wren.py
@@ -21,7 +21,6 @@ class WrenUI(Engine):
         self,
         sql: str,
         session: aiohttp.ClientSession,
-        properties: Dict[str, Any] = {},
     ) -> Tuple[bool, Optional[Dict[str, Any]]]:
         async with session.post(
             f"{self._endpoint}/api/graphql",
@@ -46,27 +45,25 @@ class WrenUI(Engine):
 class WrenIbis(Engine):
     def __init__(self, endpoint: str = os.getenv("WREN_IBIS_ENDPOINT")):
         self._endpoint = endpoint
+        self._source = os.getenv("WREN_IBIS_SOURCE")
+        self._manifest = os.getenv("WREN_IBIS_MANIFEST")
+        self._connection_info = (
+            orjson.loads(base64.b64decode(os.getenv("WREN_IBIS_CONNECTION_INFO")))
+            if os.getenv("WREN_IBIS_CONNECTION_INFO")
+            else {}
+        )
 
     async def dry_run_sql(
         self,
         sql: str,
         session: aiohttp.ClientSession,
-        properties: Dict[str, Any] = {
-            "source": os.getenv("WREN_IBIS_SOURCE"),
-            "manifest": os.getenv("WREN_IBIS_MANIFEST"),
-            "connection_info": orjson.loads(
-                base64.b64decode(os.getenv("WREN_IBIS_CONNECTION_INFO"))
-            )
-            if os.getenv("WREN_IBIS_CONNECTION_INFO")
-            else {},
-        },
     ) -> Tuple[bool, Optional[Dict[str, Any]]]:
         async with session.post(
-            f"{self._endpoint}/v2/connector/{properties.get('source', '')}/query?dryRun=true",
+            f"{self._endpoint}/v2/connector/{self._source}/query?dryRun=true",
             json={
                 "sql": remove_limit_statement(add_quotes(sql)),
-                "manifestStr": properties.get("manifest", ""),
-                "connectionInfo": properties.get("connection_info", {}),
+                "manifestStr": self._manifest,
+                "connectionInfo": self._connection_info,
             },
         ) as response:
             if response.status == 204:
@@ -74,3 +71,23 @@ class WrenIbis(Engine):
             res = await response.text()
 
             return False, res
+
+
+@provider("wren_engine")
+class WrenEngine(Engine):
+    def __init__(self, endpoint: str = os.getenv("WREN_ENGINE_ENDPOINT")):
+        self._endpoint = endpoint
+
+    async def dry_run_sql(
+        self,
+        sql: str,
+        session: aiohttp.ClientSession,
+    ) -> Tuple[bool, Optional[Dict[str, Any]]]:
+        async with session.get(
+            f"{self._endpoint}/v1/mdl/dry-run",
+            json={"sql": remove_limit_statement(add_quotes(sql)), "limit": 1},
+        ) as response:
+            if response.status == 200:
+                return True, None
+            res = await response.text()
+            return False, res
diff --git a/wren-ai-service/tests/pytest/providers/test_loader.py b/wren-ai-service/tests/pytest/providers/test_loader.py
index 50deb557b..5c6fe910f 100644
--- a/wren-ai-service/tests/pytest/providers/test_loader.py
+++ b/wren-ai-service/tests/pytest/providers/test_loader.py
@@ -3,7 +3,7 @@ from src.providers import loader
 
 def test_import_mods():
     loader.import_mods("src.providers")
-    assert len(loader.PROVIDERS) == 9
+    assert len(loader.PROVIDERS) == 10
 
 
 def test_get_provider():
@@ -39,3 +39,6 @@ def test_get_provider():
 
     provider = loader.get_provider("wren_ibis")
     assert provider.__name__ == "WrenIbis"
+
+    provider = loader.get_provider("wren_engine")
+    assert provider.__name__ == "WrenEngine"
diff --git a/wren-ai-service/tools/dev/docker-compose-dev.yaml b/wren-ai-service/tools/dev/docker-compose-dev.yaml
index 3a3f0273d..1cbfea987 100644
--- a/wren-ai-service/tools/dev/docker-compose-dev.yaml
+++ b/wren-ai-service/tools/dev/docker-compose-dev.yaml
@@ -28,6 +28,7 @@ services:
       - ${IBIS_SERVER_PORT}:${IBIS_SERVER_PORT}
     environment:
       WREN_ENGINE_ENDPOINT: http://engine:${WREN_ENGINE_PORT}
+      LOG_LEVEL: DEBUG
     networks:
       - wren