fix: conflicts with main solved

README.md

@@ -14,17 +14,17 @@ A PostgreSQL MCP server and client system that accepts natural language queries
 
 ## Tech Stack
 
-| Layer             | Technology / Library               | Purpose                                                      |
-|-------------------|------------------------------------|--------------------------------------------------------------|
-| LLM Framework   | [LangChain](https://www.langchain.com/) | Manages agent behavior, memory, and tool interaction         |
-| LLM Provider   | Google Gemini (via LangChain)      | Converts natural language into SQL queries                   |
+| Layer       | Technology / Library               | Purpose                                                      |
+|-------------|------------------------------------|--------------------------------------------------------------|
+| LLM Framework | [LangChain](https://www.langchain.com/) | Manages agent behavior, memory, and tool interaction         |
+| LLM Provider | Google Gemini (via LangChain)      | Converts natural language into SQL queries                   |
 | Agent Runtime | LangGraph’s `create_react_agent`   | Runs the ReAct-style LLM agent                               |
-| Communication  | Modular Command Protocol (MCP)     | Handles communication between client and PostgreSQL backend|
-| Tooling        | `langchain_mcp_adapters`           | Loads and manages tools for the agent                        |
-|  Database       | PostgreSQL                         | Serves queried data                                          |
-| UI (optional)  | [Gradio](https://www.gradio.app/)  | Provides a lightweight web interface for querying            |
-| Memory         | `ConversationBufferMemory`         | Stores short-term in-session memory for conversation context |
-|  Language       | Python 3.10+                        | Core programming language used for development               |
+| Communication | Modular Command Protocol (MCP)     | Handles communication between client and PostgreSQL backend|
+| Tooling     | `langchain_mcp_adapters`           | Loads and manages tools for the agent                        |
+| Database    | PostgreSQL                         | Serves queried data                                          |
+| UI (optional) | [Gradio](https://www.gradio.app/)  | Provides a lightweight web interface for querying            |
+| Memory      | `FileChatMessageHistory`         | Stores short-term in-session memory for conversation context |
+| Language    | Python 3.10+                        | Core programming language used for development               |
 
 
 ## Installation
@@ -61,10 +61,6 @@ You can start by copying the example file provided:
 
 ### .env variables
 * API_KEY: Your Google Gemini API key
-* DSN: PostgreSQL connection string (used by MCP)
-* SCHEMA: Schema name to describe table structure
-### config variables
-* TABLE_SUMMARY_PATH: Path to the table descriptions file
 * MCP_SERVER_PATH: Path to the MCP server script (e.g. ./postgres_mcp_server.py)
 
 ## Running the Project
@@ -85,11 +81,11 @@ Once you've installed the dependencies and configured the `.env` file, you're re
 .
 ├── gradio_app.py                # Gradio UI to interact with any client (LangChain or SmolAgent)
 ├── langchain_mcp_client.py      # Uses LangChain ReAct agent + ConversationBufferMemory (in-memory, also saves to memory.json)
-├── postgre_mcp_client.py        # Uses ReAct agent + custom memory class (in-session only), WIP: needs prompt fix
-├── postgre_smolagent_client.py  # Uses SmolAgent (lightweight), no memory support yet, WIP: output parsing + prompt building
+├── postgre_mcp_client.py        # Uses ReAct agent + custom memory class (in-session only), **WIP**: needs prompt fix
+├── postgre_smolagent_client.py  # Uses SmolAgent (lightweight), no memory support yet, **WIP**: output parsing + prompt building
 ├── postgre_mcp_server.py        # MCP server that handles actual PostgreSQL communication
 ├── conversation_memory.py       # Built-in memory class used by some clients
-├── memory.json                  # Keeps session memory. Needs to be deleted after each session
+├── chat_history.json                  # Keeps session memory. Needs to be deleted after each session
 ├── table_summary.txt            # Database table descriptions used to enrich tools
 ├── utils.py                     # Helper functions: intent classification, output parsing, etc.
 ├── .env.sample                  # Template for your environment config
@@ -97,34 +93,6 @@ Once you've installed the dependencies and configured the `.env` file, you're re
 └── README.md
 ```
 
-### Switching Clients in Gradio
-
-The `gradio_app.py` file is designed to work with **all three clients**.  
-To change the active one:
-
-1. Open `gradio_app.py`
-2. Replace the function call with one of the following:
-
-```python
-from langchain_mcp_client import lc_mcp_exec
-
-async def run_agent(request):
-    result = await lc_mcp_exec(request)
-    return result
-# or
-from postgre_mcp_client import pg_mcp_exec
-
-async def run_agent(request):
-    result = await pg_mcp_exec(request)
-    return result
-# or
-from postgre_smolagent_client import pg_mcp_smolagent_exec
-
-async def run_agent(request):
-    result = await pg_mcp_smolagent_exec(request)
-    return result
-```
-
 ### Work In Progress (WIP) Notes
 * postgre_mcp_client.py: 
    - needs improvement in build_prompt() function
@@ -136,6 +104,5 @@ async def run_agent(request):
    - Uses a different output format — not yet compatible with parse_mcp_output()
    
    - Also needs build_prompt() logic finalized
-* config file for the variables TABLE_SUMMARY_PATH and MCP_SERVER_PATH
 * gradio_app.py: 
    - Doesn't support conversation chat ui 

langchain_mcp_client.py

@@ -1,4 +1,5 @@
 import os.path
+import json
 from typing import Tuple, Any
 
 from mcp import ClientSession, StdioServerParameters
@@ -15,11 +16,10 @@ import logging
 from dotenv import load_dotenv
 
 
-load_dotenv()
-logger = logging.getLogger(__name__)
-
 
-async def lc_mcp_exec(request: str) -> tuple[Any, Any]:
+logger = logging.getLogger(__name__)
+load_dotenv()
+async def lc_mcp_exec(request: str, history) -> tuple[Any, Any]:
     """
     Execute the full PostgreSQL MCP pipeline with persistent memory.
     """
@@ -121,6 +121,7 @@ def load_table_summary(path: str) -> str:
 
 def get_server_params() -> StdioServerParameters:
     # TODO: give server params from config
+    load_dotenv()
     return StdioServerParameters(
         command="python",
         args=[os.environ["MCP_SERVER_PATH"]],
@@ -134,7 +135,6 @@ async def build_prompt(session, intent, request, tools, summary, chat_history):
     superset_prompt = await session.read_resource("resource://last_prompt")
     conversation_prompt = await session.read_resource("resource://base_prompt")
 
-
     if intent == "superset_request":
         template = superset_prompt.contents[0].text
         return template.format(

postgre_mcp_server.py

@@ -59,119 +59,128 @@ async def base_prompt_query() -> str:
 
     base_prompt = """
 
-                        ==========================
-                        # Your Role
-                        ==========================
+                    ==========================
+                    # Your Role
+                    ==========================
 
-                        You are an expert in generating and executing SQL queries and interacting with a PostgreSQL database using **FastMCP tools**. These tools allow you to:
+                    You are an expert in generating and executing SQL queries and interacting with a PostgreSQL database using **FastMCP tools**. These tools allow you to:
 
-                        - List available tables
-                        - Retrieve schema details
-                        - Execute SQL queries
+                    - List available tables
+                    - Retrieve schema details
+                    - Execute SQL queries
 
 
-                        Each tool may also return previews or summaries of table contents to help you better understand the data structure.
+                    Each tool may also return previews or summaries of table contents to help you better understand the data structure.
+                    
+                    ---
 
-                        You also have access to **short-term memory**, which stores relevant context from earlier queries. If memory contains the needed information, you **must use it** instead of repeating tool calls with the same input. Avoid redundant tool usage unless:
-                        - The memory is empty, or
-                        - A tool's output is outdated or missing
+                    ==========================
+                    # Your Objective
+                    ==========================
 
-                        ---
+                    When a user submits a request, you must:
 
-                        ==========================
-                        # Your Objective
-                        ==========================
+                    1. **Analyze the request** to determine the required data or action.
+                    2. **Use FastMCP tools** to gather any necessary information (e.g., list tables or retrieve schema).
+                    3. **Generate a valid SQL SELECT query**, if needed, and clearly show the full query.
+                    4. **Execute the SQL query** and return the results.
+                    5. **Chain tools logically**, such as: List Tables → Get Schema → Write and Run Query.
+                    6. **Explain your reasoning and each step taken** to ensure clarity and transparency.
 
-                        When a user submits a request, follow these steps:
+                    ---
 
-                        1. Analyze the request to determine the desired data or action.
-                        2. Use tools to gather any necessary information (e.g., list tables, get schema).
-                        3. Generate a valid SQL query (such as **SELECT**, **COUNT**, or other read-only operations) and clearly display the full query.
-                        4. Execute the query and **return the execution result of the query**.
-                        5. **Chain tools logically to build toward the answer.**
-                        6. Explain your reasoning at every step for clarity and transparency.
-                        7. Show the result of the **execute_query** in your final answer. 
+                    ==========================
+                    # Your Objective
+                    ==========================
 
-                        ---
+                    When a user submits a request, follow these steps:
 
-                        ==========================
-                        # Critical Rules
-                        ==========================
+                    1. Analyze the request to determine the desired data or action.
+                    2. Use tools to gather any necessary information (e.g., list tables, get schema).
+                    3. Generate a valid SQL query (such as **SELECT**, **COUNT**, or other read-only operations) and clearly display the full query.
+                    4. Execute the query and **return the execution result of the query**.
+                    5. **Chain tools logically to build toward the answer.**
+                    6. Explain your reasoning at every step for clarity and transparency.
+                    7. Show the result of the **execute_query** in your final answer. 
 
-                        - Only use **read-only** SQL queries such as **SELECT**, **COUNT**, or queries with **GROUP BY**, **ORDER BY**, etc.
-                        - **Never** use destructive operations like **DELETE**, **UPDATE**, **INSERT**, or **DROP**.
-                        - Always show the SQL query you generate along with the execution result.
-                        - Validate SQL syntax before execution.
-                        - Never assume table or column names. Use tools to confirm structure.
-                        - Use memory efficiently. Don’t rerun a tool unless necessary.
-                        - If you generate a SQL query, immediately call the **execute_query** tool using that query. Do not delay or wait for user confirmation.
+                    ---
 
+                    ==========================
+                    # Critical Rules
+                    ==========================
 
-                        ---
+                    - Only use **read-only** SQL queries such as **SELECT**, **COUNT**, or queries with **GROUP BY**, **ORDER BY**, etc.
+                    - **Never** use destructive operations like **DELETE**, **UPDATE**, **INSERT**, or **DROP**.
+                    - Always show the SQL query you generate along with the execution result.
+                    - Validate SQL syntax before execution.
+                    - Never assume table or column names. Use tools to confirm structure.
+                    - Use memory efficiently. Don’t rerun a tool unless necessary.
+                    - If you generate a SQL query, immediately call the **execute_query** tool using that query. Do not delay or wait for user confirmation.
 
-                        ==========================
-                        # Short-Term Memory
-                        ==========================
+                    ---
+                    
+                    ==========================
+                    # Database Description
+                    ==========================
+                    
+                    {descriptions}
+                    
+                    ---
 
-                        You have access to the following memory from this conversation. Use it if applicable for the current request.
+                    ==========================
+                    # Tools
+                    ==========================
 
-                        {chat_history}
+                    You can use the following FastMCP tools. These allow you to create **read-only** queries, such as `SELECT`, `COUNT`, or queries with `GROUP BY`, `ORDER BY`, and similar clauses. You may chain tools together to gather the necessary information before generating your SQL query.
 
-                        ---
+                    {tools}
 
-                        ==========================
-                        # Tools
-                        ==========================
+                    ---
 
-                        You can use the following FastMCP tools. These allow you to create **read-only** queries, such as `SELECT`, `COUNT`, or queries with `GROUP BY`, `ORDER BY`, and similar clauses. You may chain tools together to gather the necessary information before generating your SQL query.
 
-                        {tools}
+                    ### Invalid Example — DELETE Operation (Not Allowed):
+                    **User Request:** "Delete all customers from Germany."
 
-                        ---
+                    **Response Guidance:**
+                    - **Do not generate or execute** destructive queries such as `DELETE`.
+                    - Instead, respond with a message like:
+                      > Destructive operations such as `DELETE` are not permitted. I can help you retrieve the customers from Germany using a `SELECT` query instead:
+                      > ```sql
+                      > SELECT * FROM customers WHERE country = 'Germany';
+                      > ```
 
+==========================
+# Output Format
+==========================
 
-                        ### Invalid Example — DELETE Operation (Not Allowed):
-                        **User Request:** "Delete all customers from Germany."
+Present your final answer using the following structure **exactly**. When necessary, bold the important parts of your answer or use `` inline code blocks.:
 
-                        **Response Guidance:**
-                        - **Do not generate or execute** destructive queries such as `DELETE`.
-                        - Instead, respond with a message like:
-                          > Destructive operations such as `DELETE` are not permitted. I can help you retrieve the customers from Germany using a `SELECT` query instead:
-                          > ```sql
-                          > SELECT * FROM customers WHERE country = 'Germany';
-                          > ```
+```markdown
+# Result
+{{Take the result from the execute_query tool and format it nicely using Markdown. Use a Markdown table for tabular data (rows and columns) including headers. Use bullet points or items in markdown for answers that include lists of names or descriptions. Use plain text for single values or simple messages. Ensure data alignment and clarity.}}
 
-                        ---
-                        ==========================
-                        # Output Format
-                        ==========================
-                        
-                        Present your final answer using the following structure **exactly**. When necessary, bold the important parts of your answer or use `` inline code blocks.:
-                        
-                        ```markdown
-                        # Result
-                        {{Take the result from the execute_query tool and format it nicely using Markdown. Use a Markdown table for tabular data (rows and columns) including headers. Use bullet points or items in markdown for answers that include lists of names or descriptions. Use plain text for single values or simple messages. Ensure data alignment and clarity.}}
-                        
-                        # Explanation
-                        {{Provide a concise explanation or interpretation of the results in 1-3 sentences. Explain what the data in the 'Result' section represents in the context of the user's request.}}
-                        
-                        # Query
-                        ```sql
-                        {{Display the exact SQL query you generated and executed here to answer the user's request.}}
-    
-                        **Reminder:** 
-                        **Every time you generate a SQL query, call **execute_query** right after and include the result in your final response.**
-                        **If you do not execute the generated SQL query, this will be the violation of the instructions**
-                        **Your final answer cannot be only a SQL query, you will have to call **execute_query** and give the result of the call with the SQL query.** 
-                        ---
-                        =========================
-                        # New User Request
-                        =========================
+# Explanation
+{{Provide a concise explanation or interpretation of the results in 1-3 sentences. Explain what the data in the 'Result' section represents in the context of the user's request.}}
 
-                        Please fulfill the following request based on the above context:
+# Query
+```sql
+{{Display the exact SQL query you generated and executed here to answer the user's request.}}
 
-                        {new_request}
-                        """
+                    **Reminder:** 
+                    **Every time you generate a SQL query, call **execute_query** right after and include the result in your final response.**
+                    **If you do not execute the generated SQL query, this will be the violation of the instructions**
+                    **Your final answer cannot be only a SQL query, you will have to call **execute_query** and give the result of the call with the SQL query.** 
+                    ---
+                    {chat_history}
+                    ---
+                    =========================
+                    # New User Request
+                    =========================
+
+                    Please fulfill the following request based on the above context:
+
+                    {new_request}
+                    """
 
     return base_prompt
 
@@ -442,7 +451,6 @@ async def test_connection(ctx: Context) -> str:
         return f"Connection failed: {str(e)}"
 
 
-
 @mcp.tool(description="Executes a read-only SQL SELECT query and returns formatted results or an error message.")
 async def execute_query(
         query: str = Field(description="SQL query to execute (SELECT only)"),