[BUG] Agentwith Pydantic BaseModel as Output Type

[evelynmitchell]

In colab after installing chromadb:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
[<ipython-input-7-075a5ba6bcf6>](https://localhost:8080/#) in <cell line: 27>()
     25 
     26 # Initialize the agent
---> 27 agent = Agent(
     28     agent_name="Person Information Generator",
     29     system_prompt=(

[/usr/local/lib/python3.10/dist-packages/swarms/structs/agent.py](https://localhost:8080/#) in __init__(self, id, llm, template, max_loops, stopping_condition, loop_interval, retry_attempts, retry_interval, return_history, stopping_token, dynamic_loops, interactive, dashboard, agent_name, agent_description, system_prompt, tools, dynamic_temperature_enabled, sop, sop_list, saved_state_path, autosave, context_length, user_name, self_healing_enabled, code_interpreter, multi_modal, pdf_path, list_of_pdf, tokenizer, long_term_memory, preset_stopping_token, traceback, traceback_handlers, streaming_on, docs, docs_folder, verbose, parser, best_of_n, callback, metadata, callbacks, logger_handler, search_algorithm, logs_to_filename, evaluator, output_json, stopping_func, custom_loop_condition, sentiment_threshold, custom_exit_command, sentiment_analyzer, limit_tokens_from_string, custom_tools_prompt, tool_schema, output_type, function_calling_type, output_cleaner, function_calling_format_type, list_base_models, metadata_output_type, state_save_file_type, chain_of_thoughts, algorithm_of_thoughts, tree_of_thoughts, tool_choice, execute_tool, rules, planning, planning_prompt, device, custom_planning_prompt, memory_chunk_size, agent_ops_on, *args, **kwargs)
    290         **kwargs,
    291     ):
--> 292         super().__init__(*args, **kwargs)
    293         self.id = id
    294         self.llm = llm

TypeError: BaseStructure.__init__() got an unexpected keyword argument 'list_tool_schemas'

Upvote & Fund

• We're using Polar.sh so you can upvote and help fund this issue.
• We receive the funding once the issue is completed & confirmed by you.
• Thank you in advance for helping prioritize & fund our backlog.