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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,169 @@ | ||
| --- | ||
| title: "SQL Agent" | ||
| sidebarTitle: "SQL Agent" | ||
| icon: "database" | ||
| description: "This guide provides detailed steps to create an agent that leverages | ||
| Composio to perform SQL queries and file operations to perform sql queries and | ||
| File operations and plot insightful graphs on the data in the db" | ||
| --- | ||
|
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||
| This project involves setting up and running a system of agents to conduct SQL queries, write the output to a file, and plot graphs based on the data. We use Composio to set up the tools and OpenAI GPT-4o to power the agents. Follow this guide to set up and run the project. | ||
|
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||
| <Steps> | ||
| <Step title="Setup Environment and Install Dependencies"> | ||
| > Ensure you have a `.env` file with your OpenAI and Composio API keys. | ||
| ```bash | ||
| # Install the required packages | ||
| pip install dotenv composio_langchain langchain_openai | ||
| ``` | ||
|
|
||
| Fill in the `.env` file with your API keys: | ||
| ``` | ||
| OPENAI_API_KEY=your_openai_api_key | ||
| COMPOSIO_API_KEY=your_composio_api_key | ||
| ``` | ||
| </Step> | ||
|
|
||
| <Step title="Imports and Environment Setup"> | ||
| In your Python script, import the necessary libraries and set up your environment variables. | ||
| <CodeGroup> | ||
| ```python | ||
| import os | ||
| import dotenv | ||
| from composio_langchain import App, ComposioToolSet | ||
| from langchain import hub | ||
| from langchain.agents import AgentExecutor, create_openai_functions_agent | ||
| from langchain_openai import ChatOpenAI | ||
| # Load environment variables | ||
| dotenv.load_dotenv() | ||
| ``` | ||
| </CodeGroup> | ||
| </Step> | ||
|
|
||
| <Step title="Initialize Language Model and Define Tools"> | ||
| Initialize the language model with OpenAI API key and model name, and set up the necessary tools for the agents. | ||
| <CodeGroup> | ||
| ```python | ||
| # Initialize the LLM with the OpenAI GPT-4o model and API key | ||
| llm = ChatOpenAI(model="gpt-4o", openai_api_key=os.getenv("OPENAI_API_KEY")) | ||
| # Initialize the Composio ToolSet with the API key | ||
| composio_toolset = ComposioToolSet(api_key=os.getenv("COMPOSIO_API_KEY")) | ||
| # Get tools for SQL and File operations | ||
| sql_file_tool = composio_toolset.get_tools(apps=[App.SQLTOOL, App.FILETOOL]) | ||
| # Get tools for SQL, File, and Code Interpreter operations | ||
| tools = composio_toolset.get_tools(apps=[App.SQLTOOL, App.FILETOOL, App.CODEINTERPRETER]) | ||
| ``` | ||
| </CodeGroup> | ||
| </Step> | ||
|
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||
| <Step title="Define the Task and Execute SQL Query"> | ||
| Define the task to execute a SQL query and write the output to a file. | ||
| <CodeGroup> | ||
| ```python | ||
| # Pull the prompt template for the agent | ||
| prompt = hub.pull("hwchase17/openai-functions-agent") | ||
| # Define the task to execute | ||
| query_task = ( | ||
| "Write sqlite query to get top 10 rows from the only table MOCK_DATA " | ||
| "and database company.db using sqltool, write the output in a file called log.txt and return the output" | ||
| ) | ||
| # Create the agent for SQL and File operations and execute the task | ||
| query_agent = create_openai_functions_agent(llm, sql_file_tool, prompt) | ||
| agent_executor = AgentExecutor(agent=query_agent, tools=sql_file_tool, verbose=True) | ||
| res = agent_executor.invoke({"input": query_task}) | ||
| ``` | ||
| </CodeGroup> | ||
| </Step> | ||
|
|
||
| <Step title="Define and Execute Code Interpreter Task"> | ||
| Create and execute the agent for Code Interpreter operations to plot a graph based on the extracted data. | ||
| <CodeGroup> | ||
| ```python | ||
| # Create the agent for Code Interpreter operations | ||
| code_tool = composio_toolset.get_tools(apps=[App.CODEINTERPRETER]) | ||
| code_agent = create_openai_functions_agent(llm, code_tool, prompt) | ||
| agent_executor = AgentExecutor(agent=code_agent, tools=code_tool, verbose=True) | ||
| # Define the task for plotting graphs | ||
| plot_task = ( | ||
| "Using the following extracted information, plot the graph between first name and salary: " | ||
| + res["output"] | ||
| ) | ||
| # Execute the plotting task | ||
| final_res = agent_executor.invoke({"input": plot_task}) | ||
| ``` | ||
| </CodeGroup> | ||
| </Step> | ||
|
|
||
| </Steps> | ||
|
|
||
| ## Putting it All Together | ||
| <CodeGroup> | ||
| ```python | ||
| import os | ||
| import dotenv | ||
| from composio_langchain import App, ComposioToolSet | ||
| from langchain import hub | ||
| from langchain.agents import AgentExecutor, create_openai_functions_agent | ||
| from langchain_openai import ChatOpenAI | ||
| # Load environment variables | ||
| dotenv.load_dotenv() | ||
| # Initialize the LLM with the OpenAI GPT-4o model and API key | ||
| llm = ChatOpenAI(model="gpt-4o", openai_api_key=os.getenv("OPENAI_API_KEY")) | ||
| # Initialize the Composio ToolSet with the API key | ||
| composio_toolset = ComposioToolSet(api_key=os.getenv("COMPOSIO_API_KEY")) | ||
| # Get tools for SQL and File operations | ||
| sql_file_tool = composio_toolset.get_tools(apps=[App.SQLTOOL, App.FILETOOL]) | ||
| # Get tools for SQL, File, and Code Interpreter operations | ||
| tools = composio_toolset.get_tools(apps=[App.SQLTOOL, App.FILETOOL, App.CODEINTERPRETER]) | ||
| # Pull the prompt template for the agent | ||
| prompt = hub.pull("hwchase17/openai-functions-agent") | ||
| # Define the task to execute | ||
| query_task = ( | ||
| "Write sqlite query to get top 10 rows from the only table MOCK_DATA " | ||
| "and database company.db using sqltool, write the output in a file called log.txt and return the output" | ||
| ) | ||
| # Create the agent for SQL and File operations and execute the task | ||
| query_agent = create_openai_functions_agent(llm, sql_file_tool, prompt) | ||
| agent_executor = AgentExecutor(agent=query_agent, tools=sql_file_tool, verbose=True) | ||
| res = agent_executor.invoke({"input": query_task}) | ||
| # Create the agent for Code Interpreter operations | ||
| code_tool = composio_toolset.get_tools(apps=[App.CODEINTERPRETER]) | ||
| code_agent = create_openai_functions_agent(llm, code_tool, prompt) | ||
| agent_executor = AgentExecutor(agent=code_agent, tools=code_tool, verbose=True) | ||
| # Define the task for plotting graphs | ||
| plot_task = ( | ||
| "Using the following extracted information, plot the graph between first name and salary: " | ||
| + res["output"] | ||
| ) | ||
| # Execute the plotting task | ||
| final_res = agent_executor.invoke({"input": plot_task}) | ||
| # Print the final result | ||
| print(final_res) | ||
| ``` | ||
|
|
||
| </CodeGroup> | ||
|
|
||
| ## Link to the Source Code | ||
| - [GitHub]() | ||
|
|
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introduction/foundations/components/integrations/custom-integration.mdx
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