DuckDb Agent

Example

duckdb_agent.py

import json
from phi.agent.duckdb import DuckDbAgent

tables = [
    {
        "name": "movies",
        "description": "Contains information about movies from IMDB.",
        "path": "s3://phidata-public/demo_data/IMDB-Movie-Data.csv",
    },
]

duckdb_agent = DuckDbAgent(
    show_function_calls=True,
    semantic_model=json.dumps({"tables": tables}, indent=4),
)

duckdb_agent.print_response("What is the average rating of movies?")

DuckDbAgent Params

Parameter	Type	Default	Description
`name`	`str`	`"DuckDbAgent"`	Name of the agent.
`semantic_model`	`str`	`None`	Semantic model for the agent. Use this to describe the available tables, their description, data path and relations between tables.
`add_chat_history_to_messages`	`bool`	`True`	If the chat history should be added to the messages.
`num_history_messages`	`int`	`6`	Number of history messages to add to the response.
`followups`	`bool`	`False`	If the DuckDbAgent is allowed to run followup queries.
`read_tool_call_history`	`bool`	`True`	If the DuckDbAgent is allowed to read the tool call history.
`db_path`	`str`	`None`	Path to the DuckDb database file.
`connection`	`DuckDBPyConnection`	`None`	Provide an existing duckdb connection.
`init_commands`	`List[str]`	`None`	Commands ran when the duckdb connection is initialized.
`read_only`	`bool`	`False`	If the database is read-only.
`config`	`dict`	`None`	Database config used to initialize the duckdb connection.
`run_queries`	`bool`	`True`	If the DuckDbAgent is allowed to run queries.
`inspect_queries`	`bool`	`True`	If the DuckDbAgent is allowed to inspect queries.
`create_tables`	`bool`	`True`	If the DuckDbAgent is allowed to create tables.
`summarize_tables`	`bool`	`True`	If the DuckDbAgent is allowed to summarize tables.
`export_tables`	`bool`	`True`	If the DuckDbAgent is allowed to export tables.
`base_dir`	`Path`	`.`	Where to save SQL files if needed.
`save_files`	`bool`	`True`	If the DuckDbAgent is allowed to save SQL files.
`read_files`	`bool`	`False`	If the DuckDbAgent is allowed to read SQL files.
`list_files`	`bool`	`False`	If the DuckDbAgent is allowed to list SQL files.

Agent Reference

DuckDbAgent is a subclass of the Agent class and has access to the same params

Parameter	Type	Default	Description
`llm`	`LLM`	-	LLM to use for this Agent
`introduction`	`str`	-	Agent introduction. This is added to the chat history when a run is started.
`name`	`str`	-	Agent name
`agent_data`	`Dict[str, Any]`	-	Metadata associated with this agent
`run_id`	`str`	-	Run UUID (autogenerated if not set)
`run_name`	`str`	-	Run name
`run_data`	`Dict[str, Any]`	-	Metadata associated with this run
`user_id`	`str`	-	ID of the user participating in this run
`user_data`	`Dict[str, Any]`	-	Metadata associated the user participating in this run
`memory`	`AgentMemory`	`AgentMemory()`	Agent Memory
`add_chat_history_to_messages`	`bool`	`False`	Add chat history to the messages sent to the LLM.
`add_chat_history_to_prompt`	`bool`	`False`	Add chat history to the prompt sent to the LLM.
`num_history_messages`	`int`	`6`	Number of previous messages to add to prompt or messages sent to the LLM.
`knowledge_base`	`AgentKnowledge`	-	Agent Knowledge Base
`add_references_to_prompt`	`bool`	`False`	Enable RAG by adding references from the knowledge base to the prompt.
`storage`	`AgentStorage`	-	Agent Storage
`db_row`	`AgentRun`	-	AgentRun from the database: DO NOT SET MANUALLY
`tools`	`List[Union[Tool, ToolRegistry, Callable, Dict, Function]]`	-	A list of tools provided to the LLM. Tools are functions the model may generate JSON inputs for. If you provide a dict, it is not called by the model.
`show_tool_calls`	`bool`	`False`	Show tool calls in LLM messages.
`tool_call_limit`	`int`	-	Maximum number of tool calls allowed.
`tool_choice`	`Union[str, Dict[str, Any]]`	-	Controls which (if any) tool is called by the model. "none" means the model will not call a tool and instead generates a message. "auto" means the model can pick between generating a message or calling a tool. Specifying a particular function via `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that tool. "none" is the default when no tools are present. "auto" is the default if tools are present.
`read_chat_history`	`bool`	`False`	If True, adds a tool that allows the LLM to get the chat history.
`search_knowledge`	`bool`	`False`	If True, adds a tool that allows the LLM to search the knowledge base.
`update_knowledge`	`bool`	`False`	If True, adds a tool that allows the LLM to update the knowledge base.
`read_tool_call_history`	`bool`	`False`	If True, adds a tool that allows the LLM to get the tool call history.
`use_tools`	`bool`	`False`	Allow the agent to use tools
`additional_messages`	`List[Union[Dict, Message]]`	-	List of additional messages added to the messages list after the system prompt. Use these for few-shot learning or to provide additional context to the LLM.
`system_prompt`	`str`	-	Provide the system prompt as a string
`system_prompt_template`	`PromptTemplate`	-	Provide the system prompt as a PromptTemplate
`build_default_system_prompt`	`Callable[..., Optional[str]]`	-	If True, build a default system prompt using instructions and extra_instructions
`description`	`str`	-	Agent description for the default system prompt
`task`	`str`	-	Agent task
`instructions`	`List[str]`	-	List of instructions for the default system prompt
`extra_instructions`	`List[str]`	-	List of extra_instructions for the default system prompt Use these when you want to use the default prompt but also add some extra instructions
`expected_output`	`str`	-	Expected output added to the system prompt
`add_to_system_prompt`	`str`	-	Add a string to the end of the default system prompt
`add_knowledge_base_instructions`	`bool`	`True`	If True, add instructions for using the knowledge base to the default system prompt if knowledge base is provided
`prevent_hallucinations`	`bool`	`False`	If True, add instructions for letting the user know that the agent does not know the answer
`prevent_prompt_injection`	`bool`	`False`	If True, add instructions to prevent prompt injection attacks
`limit_tool_access`	`bool`	`False`	If True, add instructions for limiting tool access to the default system prompt if tools are provided
`add_datetime_to_instructions`	`bool`	`False`	If True, add the current datetime to the prompt to give the agent a sense of time This allows for relative times like "tomorrow" to be used in the prompt
`markdown`	`bool`	`False`	If markdown=true, formats the output using markdown
`user_prompt`	`Union[List[Dict], str]`	-	Provides the user prompt as a string. Note: this will ignore the input message provided to the run function
`user_prompt_template`	`PromptTemplate`	-	Provides the user prompt as a PromptTemplate
`build_default_user_prompt`	`bool`	`True`	If True, build a default user prompt using references and chat history
`references_function`	`Callable[..., Optional[str]]`	-	Function to build references for the default `user_prompt`. This function, if provided, is called when `add_references_to_prompt` is True
`references_format`	`Literal['json', 'yaml']`	`json`	Format of the references
`chat_history_function`	`Callable[..., Optional[str]]`	-	Function to build the chat_history for the default `user_prompt`. This function, if provided, is called when `add_chat_history_to_prompt` is True
`output_model`	`Union[str, List, Type[BaseModel]]`	-	Provide an output model for the responses
`parse_output`	`bool`	`True`	If True, the output is converted into the output_model (pydantic model or json dict)
`output`	`Any`	-	Final LLM response i.e. the final output of this agent
`save_output_to_file`	`Str`	-	Save the output to a file
`task_data`	`Dict[str, Any]`	-	Metadata associated with the agent tasks
`team`	`List['Agent']`	-	Agent team.
`role`	`str`	-	When the agent is part of a team, this is the role of the agent in the team
`add_delegation_instructions`	`bool`	`True`	Add instructions for delegating tasks to another agents
`debug_mode`	`bool`	`False`	If True, show debug logs
`monitoring`	`bool`	`False`	If True, logs Agent runs on phidata.com

Building Blocks

Command Line

Example

DuckDbAgent Params

Agent Reference

Building Blocks

Command Line

​Example

​DuckDbAgent Params

​Agent Reference

Example

DuckDbAgent Params

Agent Reference