~/Projects/AutoAgent on main !1 ───────────────────────────────────────────────────────── Py autoagent at 16:11:40
❯ auto main
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│ ╔═══ 𝒞𝓇𝑒𝒶𝓉𝑒 𝒜𝑔𝑒𝓃𝓉𝒾𝒸 𝒜ℐ 𝓊𝓈𝒾𝓃𝑔 ℒ𝒶𝓃𝑔𝓊𝒶𝑔𝑒 ═══╗ │
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║ Version ║ 0.2.0 ║
║ Author ║ AutoAgent Team@HKU ║
║ License ║ MIT ║
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╭──────────────────────────────────────────────── Important Notes ────────────────────────────────────────────────╮
│ │
│ • Choose user mode if you just want to let a general yet powerful AI Assistant to help you │
│ • Choose agent editor to create your own AI Agent with language. │
│ • Choose workflow editor to create your own AI Workflow with language. │
│ • Choose exit to exit the program │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Tell me what do you want to create with `Agent Chain`? (type "exit" to quit, press "Enter" to continue): Help me fi
nd iOS and android adoption rates, % who want to learn another language, and change in mobile penetration, over the
past 10 years, for top 10 developed and top 10 developing countries by GDP. Lay this info out in a table and separ
ate stats into columns, and include recommendations on markets to target for a new iOS translation app from ChatGPT
, focusing on markets ChatGPT is currently active in.
Your request: Help me find iOS and android adoption rates, % who want to learn another language, and change in
mobile penetration, over the past 10 years, for top 10 developed and top 10 developing countries by GDP. Lay this
info out in a table and separate stats into columns, and include recommendations on markets to target for a new iOS
translation app from ChatGPT, focusing on markets ChatGPT is currently active in.
@Agent Former Agent will help you, be patient...
16:13:13 - LiteLLM:INFO: utils.py:2777 -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:13:13,359 - INFO -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:13:34,891 - INFO - HTTP Request: POST https://api.bianxie.ai/v1/chat/completions "HTTP/1.1 200 OK"
16:13:34 - LiteLLM:INFO: utils.py:902 - Wrapper: Completed Call, calling success_handler
2025-10-15 16:13:34,907 - INFO - Wrapper: Completed Call, calling success_handler
@Agent Former Agent has created agent form successfully with the following details:
<agents>
<system_input>
Request for adoption rates of iOS and Android, percentage of people interested in learning another
language, and changes in mobile penetration over the past 10 years for top 10 developed and top 10 developing
countries by GDP, along with recommendations for markets to target for a new iOS translation app based on ChatGPT's
active markets.
</system_input>
<system_output>
<key>market_analysis_report</key>
<description>A table containing the adoption rates, language learning percentages, mobile penetration
changes, and targeted market recommendations for the iOS translation app.</description>
</system_output>
<agent>
<name>Market Analysis Agent</name>
<description>The market analysis agent is responsible for analyzing market potential and generating
recommendations.</description>
<instructions>You are the Market Analysis Agent tasked with analyzing the collected data and generating
recommendations for the iOS translation app.</instructions>
<tools category="existing">
<tool>
<name>get_adoption_rates</name>
<description>Retrieve the adoption rates for iOS and Android in top developed and developing
countries.</description>
</tool>
<tool>
<name>get_language_interest_stats</name>
<description>Gather statistics on the percentage of people who want to learn another language in
different countries.</description>
</tool>
<tool>
<name>get_mobile_penetration_data</name>
<description>Execute queries to retrieve changes in mobile penetration over the past 10
years.</description>
</tool>
<tool>
<name>generate_recommendations</name>
<description>Create market recommendations based on the analysis of the data for the new iOS
translation app.</description>
</tool>
</tools>
<agent_input>
<key>country_data</key>
<description>Dataset including country names, GDP, and other relevant information for the
analysis.</description>
</agent_input>
<agent_output>
<key>market_analysis_report</key>
<description>A table containing the adoption rates, language learning percentages, mobile penetration
changes, and targeted market recommendations for the iOS translation app.</description>
</agent_output>
</agent>
<agent>
<name>Market Strategy Agent</name>
<description>The market strategy agent analyzes collected data and generates recommendations for targeting
appropriate markets for the new iOS translation app.</description>
<instructions>You are the Market Strategy Agent. Your task is to analyze the data table provided by the
Market Analysis Agent and generate recommendations for the iOS translation app based on market
potential.</instructions>
<tools category="existing">
<tool>
<name>evaluate_market_potential</name>
<description>Evaluate the potential of different markets for the iOS translation app based on
collected data.</description>
</tool>
<tool>
<name>generate_recommendation_report</name>
<description>Create a comprehensive report with recommendations for market targeting.</description>
</tool>
</tools>
<agent_input>
<key>analysis_report</key>
<description>The comprehensive report generated by the Market Analysis Agent containing relevant
statistics and data for analysis.</description>
</agent_input>
<agent_output>
<key>market_recommendations</key>
<description>A list of recommendations for target markets for the new iOS translation
app.</description>
</agent_output>
</agent>
</agents>
It is time to create the desired tools, do you have any suggestions for creating the tools? (type "exit" to quit, p
ress "Enter" to continue):
Your request:
@Tool Editor Agent will help you, be patient...
@Tool Editor Agent has created tools successfully with the following details:
Case resolved. ALL desired tools are created and tested successfully.
It is time to create the desired agent(s), do you have any suggestions for creating the agent(s)? (type "exit" to q
uit, press "Enter" to continue):
Your request:
@Agent Creator Agent will help you, be patient...
It is time to create the desired agent(s), what task do you want to complete with the agent(s)? (Press Enter if non
e):
16:14:25 - LiteLLM:INFO: utils.py:2777 -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:14:25,849 - INFO -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:14:29,552 - INFO - HTTP Request: POST https://api.bianxie.ai/v1/chat/completions "HTTP/1.1 200 OK"
16:14:29 - LiteLLM:INFO: utils.py:902 - Wrapper: Completed Call, calling success_handler
2025-10-15 16:14:29,557 - INFO - Wrapper: Completed Call, calling success_handler
16:14:35 - LiteLLM:INFO: utils.py:2777 -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:14:35,230 - INFO -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:14:39,119 - INFO - HTTP Request: POST https://api.bianxie.ai/v1/chat/completions "HTTP/1.1 200 OK"
16:14:39 - LiteLLM:INFO: utils.py:902 - Wrapper: Completed Call, calling success_handler
2025-10-15 16:14:39,121 - INFO - Wrapper: Completed Call, calling success_handler
16:14:43 - LiteLLM:INFO: utils.py:2777 -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:14:43,850 - INFO -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:14:47,625 - INFO - HTTP Request: POST https://api.bianxie.ai/v1/chat/completions "HTTP/1.1 200 OK"
16:14:47 - LiteLLM:INFO: utils.py:902 - Wrapper: Completed Call, calling success_handler
2025-10-15 16:14:47,629 - INFO - Wrapper: Completed Call, calling success_handler
16:14:53 - LiteLLM:INFO: utils.py:2777 -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:14:53,141 - INFO -
LiteLLM completion() model= gpt-4o-mini; provider = openai
2025-10-15 16:14:56,628 - INFO - HTTP Request: POST https://api.bianxie.ai/v1/chat/completions "HTTP/1.1 200 OK"
16:14:56 - LiteLLM:INFO: utils.py:902 - Wrapper: Completed Call, calling success_handler
2025-10-15 16:14:56,630 - INFO - Wrapper: Completed Call, calling success_handler
Traceback (most recent call last):
File "/Users/icyfeather/miniconda3/envs/autoagent/bin/auto", line 7, in <module>
sys.exit(cli())
^^^^^
File "/Users/icyfeather/miniconda3/envs/autoagent/lib/python3.12/site-packages/click/core.py", line 1462, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/icyfeather/miniconda3/envs/autoagent/lib/python3.12/site-packages/click/core.py", line 1383, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/Users/icyfeather/miniconda3/envs/autoagent/lib/python3.12/site-packages/click/core.py", line 1850, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/icyfeather/miniconda3/envs/autoagent/lib/python3.12/site-packages/click/core.py", line 1246, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/icyfeather/miniconda3/envs/autoagent/lib/python3.12/site-packages/click/core.py", line 814, in invoke
return callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/icyfeather/Projects/AutoAgent/autoagent/cli.py", line 227, in main
meta_agent(model, context_variables, False)
File "/Users/icyfeather/Projects/AutoAgent/autoagent/cli_utils/metachain_meta_agent.py", line 248, in meta_agent
agent_response, messages = agent_editing(agent_creator_agent, client, messages, context_variables, agent_form, output_xml_form, requirements, task, debug, suggestions)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/icyfeather/Projects/AutoAgent/autoagent/cli_utils/metachain_meta_agent.py", line 138, in agent_editing
response = client.run(agent_creator_agent, messages, context_variables, debug=debug)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/icyfeather/Projects/AutoAgent/autoagent/core.py", line 482, in run
partial_response = self.handle_tool_calls(
^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/icyfeather/Projects/AutoAgent/autoagent/core.py", line 269, in handle_tool_calls
raw_result = function_map[name](**args)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/icyfeather/Projects/AutoAgent/autoagent/tools/meta/edit_agents.py", line 260, in create_orchestrator_agent
sub_agent_info = [agent_dict[sub_agent["name"]] for sub_agent in sub_agents]
~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
KeyError: 'Market Analysis Agent'
