Update README.md

README.md

@@ -1,46 +1,4 @@
-title: Logbert Rca
-emoji: 🌖
-colorFrom: pink
-colorTo: pink
-sdk: docker
-pinned: false
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
-
-
-
-# RCA SQL Agent
-
-This project is an intelligent SQL agent that uses LangChain and Hugging Face SLM to generate and execute SQL queries on a PostgreSQL database.
 
-## Features
-- Natural language to SQL query generation using Hugging Face SLM via LangChain
-- Executes generated queries on a PostgreSQL database
-- Returns results to the user
-
-## Setup
-1. Install dependencies:
-   ```bash
-   pip install langchain[all] psycopg2-binary transformers langchain-huggingface
-   ```
-2. Set your PostgreSQL connection details in environment variables or update the script:
-   - `PG_HOST`, `PG_PORT`, `PG_USER`, `PG_PASSWORD`, `PG_DATABASE`
-3. Set your Hugging Face configuration in your environment (e.g., in a `.env` file):
-   - `HUGGINGFACEHUB_API_TOKEN` — your Hugging Face access token ([get one here](https://huggingface.co/settings/tokens))
-   - `HUGGINGFACE_MODEL` — the model repo id (e.g., `distilgpt2`, `microsoft/phi-2`, etc.)
-   - Optionally, set `HF_CACHE_DIR` for local model cache.
-
-## Usage
-Run the agent script and enter your question in natural language. The agent will generate and execute the SQL query, then display the results.
-
-```bash
-python sql_agent.py
-```
-
-Type your question (e.g., "How many users signed up last month?") and get the result from your Postgres database.
-
----
----
 title: Rca Sqlagent
 emoji: 👀
 colorFrom: yellow