Patched patchwork/steps/DatabaseAgent/README.md

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patchwork/steps/DatabaseAgent/README.md

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+# Documentation: DatabaseAgent Module
+
+## Overview
+
+The `DatabaseAgent` module is designed to facilitate interaction with a database by generating and executing appropriate SQL queries. It uses machine learning to understand and interpret user tasks and generates an execution plan to gather and process necessary data from a database using the specified database dialect (e.g., SQL).
+
+The main functionality is encapsulated within a class called `DatabaseAgent`, which leverages the `AgenticStrategyV2` to dynamically generate responses to user tasks. This agent uses the `AioLlmClient` and `DatabaseQueryTool` to perform its operations, geared towards summarizing conversations and fetching data based on user prompts.
+
+## Inputs
+
+### DatabaseAgent Inputs Class
+
+In the file `typed.py`, the `DatabaseAgentInputs` class defines the input structure that the `DatabaseAgent` expects:
+
+- **task (str):** A string describing the task that needs completion.
+- **db_dialect (str):** Specifies the type of SQL dialect the database uses (e.g., MySQL, PostgreSQL).
+- **db_driver (str):** The database driver used for connections.
+- **db_username (str):** Username for database authentication.
+- **db_password (str):** Password for database authentication.
+- **db_host (str):** Host address of the database.
+- **db_port (int):** Port number for database connection.
+- **db_name (str):** Name of the database.
+- **db_params (dict):** Additional connection parameters.
+- **db_driver_args (dict):** Additional driver-specific arguments.
+- **prompt_value (Dict[str, Any]):** Dictionary holding values for prompt customization.
+- **max_llm_calls (int):** Configures the maximum number of large language model calls.
+- **openai_api_key (str):** API key for OpenAI services.
+- **anthropic_api_key (str):** API key for Anthropic services.
+- **google_api_key (str):** API key for Google services.
+- **example_json (str):** A JSON example to guide response structure.
+
+## Outputs
+
+### DatabaseAgent Outputs Class
+
+Within `typed.py`, the `DatabaseAgentOutputs` class is introduced to outline the expected output format:
+
+- **request_tokens (int):** Number of tokens used in the request.
+- **response_tokens (int):** Number of tokens received in the response.
+
+## DatabaseAgent Implementation
+
+### Core Functionality
+
+In `DatabaseAgent.py`, the `DatabaseAgent` class derives from the `Step` class and uses both `DatabaseAgentInputs` and `DatabaseAgentOutputs`. The class:
+
+- Initializes an agentic strategy to process user-provided tasks and database information.
+- Sets up database query configurations through the `DatabaseQueryTool`.
+- Employs the `mustache_render` utility to tailor command-line interactions and strategy prompts.
+- Executes the task, restricting output operation to a maximum of ten results (`limit=10`).
+
+### `run` Method
+
+The `run` function executes the agent's strategy to fetch requested data and append execution usage metrics from the `AgenticStrategyV2`.
+
+By employing this module, users can expect an automated task execution environment, where high-level natural language prompts can seamlessly translate into concrete database operations. This setup is particularly useful for data analysis and management tasks that require flexible and interactive database querying capabilities.