Update configuration files and dependencies for improved functionality

.env.example

@@ -3,7 +3,7 @@ POSTGRES_PORT=5432
 POSTGRES_DB=postgres
 POSTGRES_USER=postgres
 POSTGRES_PASSWORD=postgres
-DB_SCHEMA=fa02_staging
+# DB_SCHEMA=fa02_staging
 
 KAFKA_NETWORK_NAME=fa-dae2-capstone_kafka_network
 
@@ -40,11 +40,11 @@ _AIRFLOW_WWW_USER_PASSWORD=airflow
 # _PIP_ADDITIONAL_REQUIREMENTS=
 
 # dbt Configuration (for Airflow)
-DBT_PROJECT_DIR=/opt/airflow/dbt_project
-DBT_PROFILES_DIR=/opt/airflow/dbt_project
+# DBT_PROJECT_DIR=/opt/airflow/dbt_project
+# DBT_PROFILES_DIR=/opt/airflow/dbt_project
 
 # Langfuse Configuration (for LLM observability)
 # Sign up at https://cloud.langfuse.com or self-host
 LANGFUSE_PUBLIC_KEY=pk-lf-...
 LANGFUSE_SECRET_KEY=sk-lf-...
-LANGFUSE_HOST=https://cloud.langfuse.com
+# LANGFUSE_HOST=https://cloud.langfuse.com

.gitignore

@@ -52,4 +52,7 @@ airflow/**/__pycache__/
 
 # SSH
 .ssh/
-.secret/
+.secret/
+
+notebook/eda_files/
+notebook/eda.html

chat_engine/agents/chart_generator.py

@@ -4,7 +4,7 @@
 """
 
 from typing import Literal
-from langchain.schema import HumanMessage
+from langchain_core.messages import HumanMessage
 from langgraph.prebuilt import create_react_agent
 from langgraph.types import Command
 from langfuse import observe

chat_engine/agents/cortex_analyst.py

@@ -7,7 +7,7 @@
 import os
 from typing import Literal, Type
 from dotenv import load_dotenv
-from langchain.schema import HumanMessage
+from langchain_core.messages import HumanMessage
 from langgraph.prebuilt import create_react_agent
 from langgraph.types import Command
 from langfuse import observe

chat_engine/agents/executor.py

@@ -5,7 +5,7 @@
 
 import json
 from typing import Literal, Any, Dict
-from langchain.schema import HumanMessage
+from langchain_core.messages import HumanMessage
 from langgraph.types import Command
 from langfuse import observe
 

chat_engine/agents/planner.py

@@ -5,7 +5,7 @@
 
 import json
 from typing import Literal, Any, Dict
-from langchain.schema import HumanMessage
+from langchain_core.messages import HumanMessage
 from langgraph.types import Command
 from langfuse import observe
 

chat_engine/agents/researcher.py

@@ -4,7 +4,7 @@
 """
 
 from typing import Literal
-from langchain.schema import HumanMessage
+from langchain_core.messages import HumanMessage
 from langchain_tavily import TavilySearch
 from langgraph.prebuilt import create_react_agent
 from langgraph.types import Command

chat_engine/agents/synthesizer.py

@@ -4,7 +4,7 @@
 """
 
 from typing import Literal
-from langchain.schema import HumanMessage
+from langchain_core.messages import HumanMessage
 from langgraph.graph import END
 from langgraph.types import Command
 from langfuse import observe

chat_engine/chat_engine.py

@@ -2,7 +2,7 @@
 from dotenv import load_dotenv
 
 load_dotenv(override=True)
-from langchain.schema import HumanMessage
+from langchain_core.messages import HumanMessage
 from langfuse import observe
 
 from langgraph.graph import StateGraph, START

chat_engine/chat_example.py

@@ -0,0 +1,29 @@
+from chat_engine.chat_engine import chat_engine
+
+
+def main():
+    """Main execution function with example queries."""
+    # query1 = "What is open stablecoin index?"
+    # print(f"Query: {query1}")
+    # chat_engine(query1)
+    # print("--------------------------------\n")
+
+    # query2 = "What are the top 3 minting addresses in fct_mint table?"
+    # print(f"Query: {query2}")
+    # chat_engine(query2)
+    # print("--------------------------------\n")
+
+    query3 = "Give me the chart of the top 3 minting addresses in the fct_mint table?"
+    # without saying fct_mint tracing: https://us.cloud.langfuse.com/project/cmkf6fdvf000rad07vt5hp9k0/traces/25a46aa42bf8dc0ff218ecdbc7eb4dcf?observation=8bcf14c9052b0daa&timestamp=2026-01-18T05:49:57.382Z
+    # final answer: I have been instructed to generate a chart using given data. Could you provide the minting data?
+
+    # with explicitly mentioning
+    # https://us.cloud.langfuse.com/project/cmkf6fdvf000rad07vt5hp9k0/traces?peek=0e635a5bef8004f14f20062df7212c29&timestamp=2026-01-18T05%3A54%3A00.793Z&observation=f8a1b0d333e8d659
+    print(f"Query: {query3}")
+    chat_engine(query3)
+    print("--------------------------------\n")
+
+
+if __name__ == "__main__":
+    main()
+    # visualize_graph("chat_engine_graph.png")

chat_engine/prompts.py

@@ -1,5 +1,5 @@
 from typing import Dict, Any, List
-from langchain.schema import HumanMessage  # type: ignore[import-not-found]
+from langchain_core.messages import HumanMessage  # type: ignore[import-not-found]
 import json
 from typing import Optional
 from langgraph.graph import MessagesState

pyproject.toml

@@ -28,10 +28,21 @@ dependencies = [
     "pyarrow>=21.0.0",
     "python-dotenv>=1.0.0",
     "requests>=2.32.0",
-    "rich>=14.1.0",
+    "rich>=13.6.0",
     "snowflake-connector-python>=3.17.4",
     "sqlalchemy>=2.0.43",
     "langfuse>=2.59.5",
+    "langchain>=1.2.6",
+    "langchain-openai>=1.1.7",
+    "langchain-core>=1.2.7",
+    "langgraph>=1.0.7",
+    "langchain-tavily>=0.2.17",
+    "langchain-experimental>=0.4.1",
+    "qdrant-client>=1.16.2",
+    "psycopg>=3.3.2",
+    "matplotlib>=3.10.8",
+    "snowflake-core>=1.11.0",
+    "snowflake-snowpark-python>=1.44.0",
 ]
 
 [project.scripts]