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* update intro * update intro * tutorial * update notebook * update notebooks * update * merge * add conversation patterns * rename; delete unused files. * Reorganize new guides * Improve intro, fix typos * add what is next * outline for code executor * initiate chats png * Improve language * Improve language of human in the loop tutorial * update * update * Update group chat * code executor * update convsersation patterns * update code executor section to use legacy code executor * update conversation pattern * redirect * update figures * update whats next * Break down chapter 2 into two chapters * udpate * fix website build * Minor corrections of typos and grammar. * remove broken links, update sidebar * code executor update * Suggest changes to the code executor section * update what is next * reorder * update getting started * title * update navbar * Delete website/docs/tutorial/what-is-next.ipynb * update conversable patterns * Improve language * Fix typo * minor fixes --------- Co-authored-by: Jack Gerrits <jack@jackgerrits.com> Co-authored-by: gagb <gagb@users.noreply.github.com> Co-authored-by: Joshua Kim <joshua@spectdata.com> Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
559 lines
22 KiB
Plaintext
559 lines
22 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Allowing Human Feedback in Agents\n",
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"\n",
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"In the last two chapters we introduced the `ConversableAgent` class and showed how you can use it to create autonomous (`human_input_mode=NEVER`) agents that can accomplish tasks. We also showed how to properly terminate a conversation between agents.\n",
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"\n",
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"But many applications may require putting humans in-the-loop with agents. For example, to allow human feedback to steer agents in the right direction, specify goals, etc. In this chapter, we will show how AutoGen supports human intervention."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Human Input Modes\n",
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"\n",
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"Currently AutoGen supports three modes for human input. The mode is specified through\n",
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"the `human_input_mode` argument of the `ConversableAgent`. The three modes are:\n",
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"\n",
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"1. `NEVER`: human input is never requested.\n",
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"2. `TERMINATE` (default): human input is only requested when a termination condition is\n",
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" met. Note that in this mode if the human chooses to intercept and reply, the conversation continues\n",
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" and the counter used by `max_consectuive_auto_reply` is reset.\n",
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"3. `ALWAYS`: human input is always requested and the human can choose to skip and trigger an auto-reply,\n",
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" intercept and provide feedback, or terminate the conversation. Note that in this mode\n",
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" termination based on `max_consecutive_auto_reply` is ignored.\n",
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"\n",
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"The previous chapters already showed many examples of the cases when `human_input_mode` is `NEVER`. \n",
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"Below we show one such example again and then show the differences when this mode is set to `ALWAYS` and `NEVER` instead."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"from autogen import ConversableAgent"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Human Input Mode = `NEVER`\n",
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"\n",
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"In this mode, human input is never requested and the termination conditions\n",
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"are used to terminate.\n",
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"This mode is useful when you want your agents to act fully autonomously.\n",
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"\n",
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"Here is an example of using this mode to run a simple guess-a-number game between\n",
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"two agents, with the maximum number of guesses set to 5 through\n",
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"`max_consecutive_auto_reply`, and the termination message set to check for the \n",
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"number that is the correct guess."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"I have a number between 1 and 100. Guess it!\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"50\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Too low.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"75\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"62\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"56\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"53\n",
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"\n",
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"--------------------------------------------------------------------------------\n"
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]
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}
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],
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"source": [
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"agent_with_number = ConversableAgent(\n",
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" \"agent_with_number\",\n",
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" system_message=\"You are playing a game of guess-my-number. You have the \"\n",
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" \"number 53 in your mind, and I will try to guess it. \"\n",
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" \"If I guess too high, say 'too high', if I guess too low, say 'too low'. \",\n",
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" llm_config={\"config_list\": [{\"model\": \"gpt-4\", \"api_key\": os.environ[\"OPENAI_API_KEY\"]}]},\n",
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" is_termination_msg=lambda msg: \"53\" in msg[\"content\"], # terminate if the number is guessed by the other agent\n",
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" human_input_mode=\"NEVER\", # never ask for human input\n",
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")\n",
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"\n",
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"agent_guess_number = ConversableAgent(\n",
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" \"agent_guess_number\",\n",
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" system_message=\"I have a number in my mind, and you will try to guess it. \"\n",
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" \"If I say 'too high', you should guess a lower number. If I say 'too low', \"\n",
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" \"you should guess a higher number. \",\n",
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" llm_config={\"config_list\": [{\"model\": \"gpt-4\", \"api_key\": os.environ[\"OPENAI_API_KEY\"]}]},\n",
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" human_input_mode=\"NEVER\",\n",
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")\n",
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"\n",
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"result = agent_with_number.initiate_chat(\n",
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" agent_guess_number,\n",
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" message=\"I have a number between 1 and 100. Guess it!\",\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Yay! The game is over. The guessing agent got the number correctly in exactly\n",
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"5 guesses using binary search -- very efficient!\n",
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"You can see that the conversation was terminated after the 5th guess which\n",
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"triggered both the counter-based and message-based termination conditions."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Human Input Mode = `ALWAYS`\n",
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"\n",
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"In this mode, human input is always requested and the human can choose to skip,\n",
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"intersecpt, or terminate the conversation.\n",
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"Let us see this mode in action by playing the same game as before with the agent with the number, but this time\n",
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"participating in the game as a human.\n",
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"We will be the agent that is guessing the number, and play against the agent\n",
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"with the number from before."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[33mhuman_proxy\u001b[0m (to agent_with_number):\n",
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"\n",
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"10\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to human_proxy):\n",
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"\n",
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"Too low.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33mhuman_proxy\u001b[0m (to agent_with_number):\n",
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"\n",
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"70\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to human_proxy):\n",
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"\n",
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"Too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33mhuman_proxy\u001b[0m (to agent_with_number):\n",
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"\n",
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"50\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to human_proxy):\n",
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"\n",
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"Too low.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33mhuman_proxy\u001b[0m (to agent_with_number):\n",
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"\n",
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"53\n",
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"\n",
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"--------------------------------------------------------------------------------\n"
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]
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}
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],
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"source": [
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"human_proxy = ConversableAgent(\n",
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" \"human_proxy\",\n",
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" llm_config=False, # no LLM used for human proxy\n",
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" human_input_mode=\"ALWAYS\", # always ask for human input\n",
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")\n",
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"\n",
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"# Start a chat with the agent with number with an initial guess.\n",
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"result = human_proxy.initiate_chat(\n",
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" agent_with_number, # this is the same agent with the number as before\n",
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" message=\"10\",\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"If you run the code above, you will be prompt to enter a response\n",
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"each time it is your turn to speak. You can see the human in the conversation\n",
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"was not very good at guessing the number... but hey the agent was nice enough\n",
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"to give out the number in the end."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Human Input Mode = `TERMINATE`\n",
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"\n",
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"In this mode, human input is only requested when a termination condition is\n",
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"met. **If the human choose to intercept and reply, the counter will be reset**; if \n",
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"the human choose to skip, automatic reply mechanism will be used; if the human\n",
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"choose to terminate, the conversation will be terminated.\n",
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"\n",
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"Let us see this mode in action by playing the same game again, but this time\n",
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"the agent with the number will choose a new number and the game will restart."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"I have a number between 1 and 100. Guess it!\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"50\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Too low.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"75\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"62\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"56\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"53\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Correct! You've guessed my number.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"Great! This was a fun game. Let's play again sometime.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"10\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"Your guess is too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Okay, let's try 5.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"Your guess is too high.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Okay, how about 2?\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"Your guess is too low.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Alright, then it must be 3.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"Yes, correct! The number was 3. Good job guessing it!\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Thank you! That was indeed a fun game. I look forward to playing again with you.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"I'm glad you enjoyed it! I'm always here for a good game. Don't hesitate to come back when you want to play again.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Surely, I will. This was fun. Thanks for playing with me. See you next time!\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"You're welcome! I'm glad you had fun. Looking forward to our next game. See you next time!\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"Lets play again\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"Sure! I'll think of a number between 1 and 100. Let's start guessing!\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
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"\n",
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"I'll start with 50.\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
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"\n",
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"The guess is too low.\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n",
|
|
"\u001b[31m\n",
|
|
">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
|
|
"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
|
|
"\n",
|
|
"Okay, let's try 75.\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n",
|
|
"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
|
|
"\n",
|
|
"The guess is too high.\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n",
|
|
"\u001b[31m\n",
|
|
">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
|
|
"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
|
|
"\n",
|
|
"How about 62?\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n",
|
|
"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
|
|
"\n",
|
|
"The guess is too low.\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n",
|
|
"\u001b[31m\n",
|
|
">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
|
|
"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
|
|
"\n",
|
|
"Then, let's try 68.\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n",
|
|
"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
|
|
"\n",
|
|
"The guess is too high.\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n",
|
|
"\u001b[31m\n",
|
|
">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
|
|
"\u001b[33magent_with_number\u001b[0m (to agent_guess_number):\n",
|
|
"\n",
|
|
"Okay, how about 65?\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n",
|
|
"\u001b[33magent_guess_number\u001b[0m (to agent_with_number):\n",
|
|
"\n",
|
|
"Yes, correct! The number was 65. Good job guessing it!\n",
|
|
"\n",
|
|
"--------------------------------------------------------------------------------\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"agent_with_number = ConversableAgent(\n",
|
|
" \"agent_with_number\",\n",
|
|
" system_message=\"You are playing a game of guess-my-number. \"\n",
|
|
" \"In the first game, you have the \"\n",
|
|
" \"number 53 in your mind, and I will try to guess it. \"\n",
|
|
" \"If I guess too high, say 'too high', if I guess too low, say 'too low'. \",\n",
|
|
" llm_config={\"config_list\": [{\"model\": \"gpt-4\", \"api_key\": os.environ[\"OPENAI_API_KEY\"]}]},\n",
|
|
" max_consecutive_auto_reply=5,\n",
|
|
" human_input_mode=\"TERMINATE\", # ask for human input until the game is terminated\n",
|
|
")\n",
|
|
"\n",
|
|
"agent_guess_number = ConversableAgent(\n",
|
|
" \"agent_guess_number\",\n",
|
|
" system_message=\"I have a number in my mind, and you will try to guess it. \"\n",
|
|
" \"If I say 'too high', you should guess a lower number. If I say 'too low', \"\n",
|
|
" \"you should guess a higher number. \",\n",
|
|
" llm_config={\"config_list\": [{\"model\": \"gpt-4\", \"api_key\": os.environ[\"OPENAI_API_KEY\"]}]},\n",
|
|
" human_input_mode=\"NEVER\",\n",
|
|
")\n",
|
|
"\n",
|
|
"result = agent_with_number.initiate_chat(\n",
|
|
" agent_guess_number,\n",
|
|
" message=\"I have a number between 1 and 100. Guess it!\",\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"In the previous conversation, we were asked to provide human input first time\n",
|
|
"when the counter-based termination condition was met. We intercepted the\n",
|
|
"message and replied \"Let's play again\". The conversation continued and the\n",
|
|
"counter was reset. The game continued until the counter-based termination\n",
|
|
"condition was met again, and this time we chose to skip. The conversation\n",
|
|
"continued again but human input was requested at every turn since, and we\n",
|
|
"chose to skip each time until the game was over."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Summary\n",
|
|
"\n",
|
|
"In this chapter, we showed you how to use the human-in-the-loop component\n",
|
|
"to provide human feedback to agent and to terminate conversation.\n",
|
|
"We also showed you the different human input modes and how they affect\n",
|
|
"the behavior of the human-in-the-loop component.\n",
|
|
"\n",
|
|
"The next chapter will be all about code executor -- the most powerful\n",
|
|
"component second only to LLMs."
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "autogen",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.13"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|