From d797d267e4df9c584f3729f242738e42b9bfd093 Mon Sep 17 00:00:00 2001 From: Joshua Kim Date: Tue, 27 Feb 2024 05:10:00 +1100 Subject: [PATCH] Blog regarding finite-state machine (#1622) * Initialization of fsm blog * Pre-commit pass * Pinyin name correction * Updated title * Updated title * Added summary of notebook and note about DAG * Update index.mdx * Update website/blog/2024-02-11-FSM-GroupChat/index.mdx Co-authored-by: Chi Wang * Update website/blog/2024-02-11-FSM-GroupChat/index.mdx Co-authored-by: Chi Wang * Removed outdated filename and followed SoM notebook format * Pre-commit pass * Update notebook link * Corrected link to rendered notebook * Removed agentchat_hierarchy_flow_using_select_speaker and modified agentchat_groupchat_finite_state_machine * Add notebook/agentchat_groupchat_finite_state_machine.ipynb to paths --------- Co-authored-by: freedeaths Co-authored-by: Chi Wang --- .github/workflows/openai.yml | 1 + ...elling_language_using_select_speaker.ipynb | 668 ------------------ ...tchat_groupchat_finite_state_machine.ipynb | 620 ++++++++++++++++ test/test_notebook.py | 13 +- .../img/FSM_logic.png | Bin 0 -> 28311 bytes .../img/FSM_of_multi-agents.png | Bin 0 -> 46898 bytes .../2024-02-11-FSM-GroupChat/img/teaser.jpg | Bin 0 -> 34283 bytes .../blog/2024-02-11-FSM-GroupChat/index.mdx | 288 ++++++++ website/blog/authors.yml | 14 +- 9 files changed, 924 insertions(+), 680 deletions(-) delete mode 100644 notebook/agentchat_graph_modelling_language_using_select_speaker.ipynb create mode 100644 notebook/agentchat_groupchat_finite_state_machine.ipynb create mode 100644 website/blog/2024-02-11-FSM-GroupChat/img/FSM_logic.png create mode 100644 website/blog/2024-02-11-FSM-GroupChat/img/FSM_of_multi-agents.png create mode 100644 website/blog/2024-02-11-FSM-GroupChat/img/teaser.jpg create mode 100644 website/blog/2024-02-11-FSM-GroupChat/index.mdx diff --git a/.github/workflows/openai.yml b/.github/workflows/openai.yml index 260f687803df..975045f4ce1c 100644 --- a/.github/workflows/openai.yml +++ b/.github/workflows/openai.yml @@ -11,6 +11,7 @@ on: - "test/**" - "notebook/agentchat_auto_feedback_from_code_execution.ipynb" - "notebook/agentchat_function_call.ipynb" + - "notebook/agentchat_groupchat_finite_state_machine.ipynb" - ".github/workflows/openai.yml" permissions: {} # actions: read diff --git a/notebook/agentchat_graph_modelling_language_using_select_speaker.ipynb b/notebook/agentchat_graph_modelling_language_using_select_speaker.ipynb deleted file mode 100644 index 9a706a6172fb..000000000000 --- a/notebook/agentchat_graph_modelling_language_using_select_speaker.ipynb +++ /dev/null @@ -1,668 +0,0 @@ -{ - "cells": [ - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\"Open" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Auto Generated Agent Chat: Graph Modeling Language with using select_speaker\n", - "\n", - "AutoGen offers conversable agents powered by LLM, tool, or human, which can be used to perform tasks collectively via automated chat. This framework allows tool use and human participation through multi-agent conversation.\n", - "Please find documentation about this feature [here](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat).\n", - "\n", - "This notebook is about using graphs to define the transition paths amongst speakers.\n", - "\n", - "Benefits\n", - "- This contribution fills the gap between the current modes of GroupChat Class (auto, manual, round_robin) and an expressive directed graph. See Motivation for more detailed discussion.\n", - "\n", - "\n", - "## Requirements\n", - "\n", - "AutoGen requires `Python>=3.8`. To run this notebook example, please install:\n", - "```bash\n", - "pip install pyautogen\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%%capture --no-stderr\n", - "# %pip install \"pyautogen>=0.2.3\"\n", - "%pip install pyautogen[graph]" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "import random # noqa E402\n", - "\n", - "import matplotlib.pyplot as plt # noqa E402\n", - "import networkx as nx # noqa E402\n", - "\n", - "import autogen # noqa E402\n", - "from autogen.agentchat.conversable_agent import ConversableAgent # noqa E402\n", - "from autogen.agentchat.assistant_agent import AssistantAgent # noqa E402\n", - "from autogen.agentchat.groupchat import GroupChat # noqa E402\n", - "from autogen.graph_utils import visualize_speaker_transitions_dict # noqa E402" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.2.5\n" - ] - } - ], - "source": [ - "print(autogen.__version__)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Motivation\n", - "\n", - "\n", - "The current GroupChat class allows transition to any agent (without or without the decision of LLM), some use case might demand for more control over transition. A graph is a possible way to control the transition paths, where each node represents an agent and each directed edge represent possible transition path. Let's illustrate the current transition paths for a GroupChat with five agents." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# The default config list in notebook.\n", - "config_list_gpt4 = autogen.config_list_from_json(\n", - " \"OAI_CONFIG_LIST\",\n", - " filter_dict={\n", - " \"model\": [\"gpt-4\", \"gpt-4-0314\", \"gpt4\", \"gpt-4-32k\", \"gpt-4-32k-0314\", \"gpt-4-32k-v0314\"],\n", - " },\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "agents = [ConversableAgent(name=f\"Agent{i}\", llm_config=False) for i in range(5)]\n", - "allowed_speaker_transitions_dict = {agent: [other_agent for other_agent in agents] for agent in agents}\n", - "\n", - "visualize_speaker_transitions_dict(allowed_speaker_transitions_dict, agents)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Possibly interesting transition paths\n", - "1. Hub and Spoke\n", - "2. Sequential Team Operations\n", - "3. Think aloud and debate" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "agents = [ConversableAgent(name=f\"Agent{i}\", llm_config=False) for i in range(5)]\n", - "allowed_speaker_transitions_dict = {\n", - " agents[0]: [agents[1], agents[2], agents[3], agents[4]],\n", - " agents[1]: [agents[0]],\n", - " agents[2]: [agents[0]],\n", - " agents[3]: [agents[0]],\n", - " agents[4]: [agents[0]],\n", - "}\n", - "\n", - "visualize_speaker_transitions_dict(allowed_speaker_transitions_dict, agents)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Sequential Team Operations\n", - "# Create an empty directed graph\n", - "\n", - "speaker_transitions_dict = {}\n", - "teams = [\"A\", \"B\", \"C\"]\n", - "team_size = 5\n", - "\n", - "\n", - "def get_agent_of_name(agents, name) -> ConversableAgent:\n", - " for agent in agents:\n", - " if agent.name == name:\n", - " return agent\n", - "\n", - "\n", - "# Create a list of 15 agents 3 teams x 5 agents\n", - "agents = [ConversableAgent(name=f\"{team}{i}\", llm_config=False) for team in teams for i in range(team_size)]\n", - "\n", - "# Loop through each team and add members and their connections\n", - "for team in teams:\n", - " for i in range(team_size):\n", - " member = f\"{team}{i}\"\n", - " # Connect each member to other members of the same team\n", - " speaker_transitions_dict[get_agent_of_name(agents, member)] = [\n", - " get_agent_of_name(agents, name=f\"{team}{j}\") for j in range(team_size) if j != i\n", - " ]\n", - "\n", - "# Team leaders connection\n", - "print(get_agent_of_name(agents, name=\"B0\"))\n", - "speaker_transitions_dict[get_agent_of_name(agents, \"A0\")].append(get_agent_of_name(agents, name=\"B0\"))\n", - "speaker_transitions_dict[get_agent_of_name(agents, \"B0\")].append(get_agent_of_name(agents, name=\"C0\"))\n", - "\n", - "visualize_speaker_transitions_dict(speaker_transitions_dict, agents)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "agents = [ConversableAgent(name=f\"Agent{i}\", llm_config=False) for i in range(2)]\n", - "allowed_speaker_transitions_dict = {\n", - " agents[0]: [agents[0], agents[1]],\n", - " agents[1]: [agents[0], agents[1]],\n", - "}\n", - "\n", - "visualize_speaker_transitions_dict(allowed_speaker_transitions_dict, agents)" - ] - }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Set your API Endpoint\n", - "\n", - "The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "# The default config list in notebook.\n", - "config_list = autogen.config_list_from_json(\n", - " \"OAI_CONFIG_LIST\",\n", - " file_location=\".\",\n", - " filter_dict={\n", - " \"model\": [\"gpt-3.5-turbo\", \"gpt-35-turbo\", \"gpt-35-turbo-0613\", \"gpt-4\", \"gpt4\", \"gpt-4-32k\"],\n", - " },\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It first looks for environment variable \"OAI_CONFIG_LIST\" which needs to be a valid json string. If that variable is not found, it then looks for a json file named \"OAI_CONFIG_LIST\". It filters the configs by models (you can filter by other keys as well). Only the gpt-4 models are kept in the list based on the filter condition.\n", - "\n", - "The config list looks like the following:\n", - "```python\n", - "config_list = [\n", - " {\n", - " 'model': 'gpt-4',\n", - " 'api_key': '',\n", - " },\n", - " {\n", - " 'model': 'gpt-4',\n", - " 'api_key': '',\n", - " 'base_url': '',\n", - " 'api_type': 'azure',\n", - " 'api_version': '2024-02-15-preview',\n", - " },\n", - " {\n", - " 'model': 'gpt-4-32k',\n", - " 'api_key': '',\n", - " 'base_url': '',\n", - " 'api_type': 'azure',\n", - " 'api_version': '2024-02-15-preview',\n", - " },\n", - "]\n", - "```\n", - "\n", - "If you open this notebook in colab, you can upload your files by clicking the file icon on the left panel and then choosing \"upload file\" icon.\n", - "\n", - "You can set the value of config_list in other ways you prefer, e.g., loading from a YAML file." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Demonstration" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`GroupChat` now takes in two optional arguments.\n", - "- speaker_transitions_dict: a dictionary of keys and list as values. The keys are the names of the agents, and the values are the agents that the key agent can transition to. Default is None, in which case a fully connected graph is assumed.\n", - "- is_allowed_graph: whether the speaker_transitions_dict is a list of allowed agents or disallowed agents. Default is True, in which case the speaker_transitions_dict is a list of allowed agents. If set to False, then the speaker_transitions_dict is a list of disallowed agents." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Team Operations\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# llm config\n", - "llm_config = {\"config_list\": config_list_gpt4, \"cache_seed\": 100}\n", - "\n", - "# Create an empty directed graph\n", - "agents = []\n", - "speaker_transitions_dict = {}\n", - "secret_values = {}\n", - "\n", - "# Outer loop for prefixes 'A', 'B', 'C'\n", - "for prefix in [\"A\", \"B\", \"C\"]:\n", - " # Add 3 nodes with each prefix to the graph using a for loop\n", - " for i in range(3):\n", - " node_id = f\"{prefix}{i}\"\n", - " secret_value = random.randint(1, 5) # Generate a random secret value\n", - " secret_values[node_id] = secret_value\n", - "\n", - " # Create an AssistantAgent for each node (assuming AssistantAgent is a defined class)\n", - " agents.append(\n", - " AssistantAgent(\n", - " name=node_id,\n", - " system_message=f\"\"\"Your name is {node_id}.\n", - " Do not respond as the speaker named in the NEXT tag if your name is not in the NEXT tag. Instead, suggest a relevant team leader to handle the mis-tag, with the NEXT: tag.\n", - "\n", - " You have {secret_value} chocolates.\n", - "\n", - " The list of players are [A0, A1, A2, B0, B1, B2, C0, C1, C2].\n", - "\n", - " Your first character of your name is your team, and your second character denotes that you are a team leader if it is 0.\n", - " CONSTRAINTS: Team members can only talk within the team, whilst team leader can talk to team leaders of other teams but not team members of other teams.\n", - "\n", - " You can use NEXT: to suggest the next speaker. You have to respect the CONSTRAINTS, and can only suggest one player from the list of players, i.e., do not suggest A3 because A3 is not from the list of players.\n", - " Team leaders must make sure that they know the sum of the individual chocolate count of all three players in their own team, i.e., A0 is responsible for team A only.\n", - "\n", - " Keep track of the player's tally using a JSON format so that others can check the total tally. Use\n", - " A0:?, A1:?, A2:?,\n", - " B0:?, B1:?, B2:?,\n", - " C0:?, C1:?, C2:?\n", - "\n", - " If you are the team leader, you should aggregate your team's total chocolate count to cooperate.\n", - " Once the team leader know their team's tally, they can suggest another team leader for them to find their team tally, because we need all three team tallys to succeed.\n", - " Use NEXT: to suggest the next speaker, e.g., NEXT: A0.\n", - "\n", - " Once we have the total tally from all nine players, sum up all three teams' tally, then terminate the discussion using TERMINATE.\n", - "\n", - " \"\"\",\n", - " llm_config=llm_config,\n", - " )\n", - " )\n", - " speaker_transitions_dict[agents[-1]] = []\n", - "\n", - " # Add edges between nodes with the same prefix using a nested for loop\n", - " for source_node in range(3):\n", - " source_id = f\"{prefix}{source_node}\"\n", - " for target_node in range(3):\n", - " target_id = f\"{prefix}{target_node}\"\n", - " if source_node != target_node: # To avoid self-loops\n", - " speaker_transitions_dict[get_agent_of_name(agents, source_id)].append(\n", - " get_agent_of_name(agents, name=target_id)\n", - " )\n", - "\n", - "\n", - "# Adding edges between teams\n", - "speaker_transitions_dict[get_agent_of_name(agents, \"A0\")].append(get_agent_of_name(agents, name=\"B0\"))\n", - "speaker_transitions_dict[get_agent_of_name(agents, \"A0\")].append(get_agent_of_name(agents, name=\"C0\"))\n", - "speaker_transitions_dict[get_agent_of_name(agents, \"B0\")].append(get_agent_of_name(agents, name=\"A0\"))\n", - "speaker_transitions_dict[get_agent_of_name(agents, \"B0\")].append(get_agent_of_name(agents, name=\"C0\"))\n", - "speaker_transitions_dict[get_agent_of_name(agents, \"C0\")].append(get_agent_of_name(agents, name=\"A0\"))\n", - "speaker_transitions_dict[get_agent_of_name(agents, \"C0\")].append(get_agent_of_name(agents, name=\"B0\"))\n", - "\n", - "\n", - "# Visualization only\n", - "\n", - "graph = nx.DiGraph()\n", - "\n", - "# Add nodes\n", - "graph.add_nodes_from([agent.name for agent in agents])\n", - "\n", - "# Add edges\n", - "for key, value in speaker_transitions_dict.items():\n", - " for agent in value:\n", - " graph.add_edge(key.name, agent.name)\n", - "\n", - "# Visualize\n", - "\n", - "\n", - "# Draw the graph with secret values annotated\n", - "plt.figure(figsize=(12, 10))\n", - "pos = nx.spring_layout(graph) # positions for all nodes\n", - "\n", - "# Draw nodes with their colors\n", - "nx.draw(graph, pos, with_labels=True, font_weight=\"bold\")\n", - "\n", - "# Annotate secret values\n", - "for node, (x, y) in pos.items():\n", - " secret_value = secret_values[node]\n", - " plt.text(x, y + 0.1, s=f\"Secret: {secret_value}\", horizontalalignment=\"center\")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "# Termination message detection\n", - "\n", - "\n", - "def is_termination_msg(content) -> bool:\n", - " have_content = content.get(\"content\", None) is not None\n", - " if have_content and \"TERMINATE\" in content[\"content\"]:\n", - " return True\n", - " return False\n", - "\n", - "\n", - "# Terminates the conversation when TERMINATE is detected.\n", - "user_proxy = autogen.UserProxyAgent(\n", - " name=\"User_proxy\",\n", - " system_message=\"Terminator admin.\",\n", - " code_execution_config=False,\n", - " is_termination_msg=is_termination_msg,\n", - " human_input_mode=\"NEVER\",\n", - ")\n", - "\n", - "agents.append(user_proxy)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:Warning: There are agents in self.agents not in graph.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[33mA0\u001b[0m (to chat_manager):\n", - "\n", - "\n", - " There are 9 players in this game, split equally into Teams A, B, C. Therefore each team has 3 players, including the team leader.\n", - " The task is to find out the sum of chocolate count from all nine players. I will now start with my team.\n", - " NEXT: A1\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mA1\u001b[0m (to chat_manager):\n", - "\n", - "Sure, I, A1, have 3 chocolates. NEXT: A2\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mA2\u001b[0m (to chat_manager):\n", - "\n", - "As A2, I have 5 chocolates.\n", - "\n", - "So currently our tally is:\n", - "A0:?, A1:3, A2:5, B0:?, B1:?, B2:?, C0:?, C1:?, C2:?\n", - " \n", - "NEXT: A0\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mA0\u001b[0m (to chat_manager):\n", - "\n", - "Okay, as A0, I have 1 chocolate.\n", - "\n", - "Therefore, total chocolate count of team A is: \n", - "1 (A0's chocolates) + 3 (A1's chocolates) + 5 (A2's chocolates) = 9 chocolates \n", - "\n", - "The running tally is:\n", - "A0:1, A1:3, A2:5, \n", - "B0:?, B1:?, B2:?, \n", - "C0:?, C1:?, C2:?\n", - "\n", - "I suggest we move on to the next team. \n", - "\n", - "NEXT: B0\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mB0\u001b[0m (to chat_manager):\n", - "\n", - "As B0, I need to gather the count from my team members. \n", - "\n", - "NEXT: B1\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mB1\u001b[0m (to chat_manager):\n", - "\n", - "As B1, I have 1 chocolate. \n", - "\n", - "NEXT: B2\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mB2\u001b[0m (to chat_manager):\n", - "\n", - "As B2, I have 4 chocolates. \n", - "\n", - "So currently, our team B tally is:\n", - "B0:?, B1:1, B2:4 \n", - "\n", - "NEXT: B0\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mB0\u001b[0m (to chat_manager):\n", - "\n", - "As B0, I have 1 chocolate. So, the total chocolate count for team B is:\n", - "1 (B0's chocolates) + 1 (B1's chocolates) + 4 (B2's chocolates) = 6 chocolates.\n", - "\n", - "The updated tally is:\n", - "A0:1, A1:3, A2:5, \n", - "B0:1, B1:1, B2:4, \n", - "C0:?, C1:?, C2:?\n", - "\n", - "I suggest we move on to the next team.\n", - "\n", - "NEXT: C0\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mC0\u001b[0m (to chat_manager):\n", - "\n", - "As C0, I will now gather the count from my team members. \n", - "\n", - "NEXT: C1\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mC1\u001b[0m (to chat_manager):\n", - "\n", - "As C1, I have 2 chocolates.\n", - "\n", - "NEXT: C2\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mC2\u001b[0m (to chat_manager):\n", - "\n", - "As C2, I have 1 chocolate.\n", - "\n", - "So currently, our team C tally is:\n", - "C0:?, C1:2, C2:1\n", - "\n", - "NEXT: C0\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mC0\u001b[0m (to chat_manager):\n", - "\n", - "As C0, I'm the team leader and I have 1 chocolate. So, the total chocolate count for team C is:\n", - "1 (C0's chocolates) + 2 (C1's chocolates) + 1 (C2's chocolates) = 4 chocolates.\n", - "\n", - "The final tally is:\n", - "A0:1, A1:3, A2:5, \n", - "B0:1, B1:1, B2:4, \n", - "C0:1, C1:2, C2:1\n", - "\n", - "Now, the sum of chocolates from all nine players is:\n", - "9 (team A's chocolates) + 6 (team B's chocolates) + 4 (team C's chocolates) = 19 chocolates.\n", - "\n", - "TERMINATE.\n", - "\n", - "\n", - "--------------------------------------------------------------------------------\n" - ] - } - ], - "source": [ - "group_chat = GroupChat(\n", - " agents=agents,\n", - " messages=[],\n", - " max_round=20,\n", - " allowed_or_disallowed_speaker_transitions=speaker_transitions_dict,\n", - " speaker_transitions_type=\"allowed\",\n", - ")\n", - "\n", - "\n", - "# Create the manager\n", - "manager = autogen.GroupChatManager(\n", - " groupchat=group_chat, llm_config=llm_config, code_execution_config=False, is_termination_msg=is_termination_msg\n", - ")\n", - "\n", - "\n", - "# Initiates the chat with Alice\n", - "agents[0].initiate_chat(\n", - " manager,\n", - " message=\"\"\"\n", - " There are 9 players in this game, split equally into Teams A, B, C. Therefore each team has 3 players, including the team leader.\n", - " The task is to find out the sum of chocolate count from all nine players. I will now start with my team.\n", - " NEXT: A1\"\"\",\n", - ")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "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": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/notebook/agentchat_groupchat_finite_state_machine.ipynb b/notebook/agentchat_groupchat_finite_state_machine.ipynb new file mode 100644 index 000000000000..3a05af2805f8 --- /dev/null +++ b/notebook/agentchat_groupchat_finite_state_machine.ipynb @@ -0,0 +1,620 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "# FSM - User can input speaker transition contraints.\n", + "\n", + "AutoGen offers conversable agents powered by LLM, tool, or human, which can be used to perform tasks collectively via automated chat. This framework allows tool use and human participation through multi-agent conversation.\n", + "Please find documentation about this feature [here](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat).\n", + "\n", + "This notebook is about using graphs to define the transition paths amongst speakers.\n", + "\n", + "Benefits\n", + "- This contribution fills the gap between the current modes of GroupChat Class (auto, manual, round_robin) and an expressive directed graph. See Motivation for more detailed discussion.\n", + "\n", + "\n", + "````{=mdx}\n", + ":::info Requirements\n", + "Install `pyautogen`:\n", + "```bash\n", + "pip install pyautogen\n", + "```\n", + "\n", + "For more information, please refer to the [installation guide](/docs/installation/).\n", + ":::\n", + "````" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.0\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "%%capture --no-stderr\n", + "%pip install pyautogen[graph]>=0.2.11" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import random # noqa E402\n", + "\n", + "import matplotlib.pyplot as plt # noqa E402\n", + "import networkx as nx # noqa E402\n", + "\n", + "import autogen # noqa E402\n", + "from autogen.agentchat.conversable_agent import ConversableAgent # noqa E402\n", + "from autogen.agentchat.assistant_agent import AssistantAgent # noqa E402\n", + "from autogen.agentchat.groupchat import GroupChat # noqa E402\n", + "from autogen.graph_utils import visualize_speaker_transitions_dict # noqa E402" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.2.14\n" + ] + } + ], + "source": [ + "print(autogen.__version__)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Motivation\n", + "\n", + "\n", + "The current GroupChat class allows transition to any agent (without or without the decision of LLM), some use case might demand for more control over transition. A graph is a possible way to control the transition paths, where each node represents an agent and each directed edge represent possible transition path. Let's illustrate the current transition paths for a GroupChat with five agents." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "config_list_gpt4 = {\n", + " \"timeout\": 600,\n", + " \"cache_seed\": 44, # change the seed for different trials\n", + " \"config_list\": autogen.config_list_from_json(\n", + " \"OAI_CONFIG_LIST\",\n", + " filter_dict={\"model\": [\"gpt-4\", \"gpt-4-0613\", \"gpt-4-32k\", \"gpt-4-32k-0613\", \"gpt-4-1106-preview\"]},\n", + " ),\n", + " \"temperature\": 0,\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "agents = [ConversableAgent(name=f\"Agent{i}\", llm_config=False) for i in range(5)]\n", + "allowed_speaker_transitions_dict = {agent: [other_agent for other_agent in agents] for agent in agents}\n", + "\n", + "visualize_speaker_transitions_dict(allowed_speaker_transitions_dict, agents)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Possibly interesting transition paths\n", + "1. Hub and Spoke\n", + "2. Sequential Team Operations\n", + "3. Think aloud and debate" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "agents = [ConversableAgent(name=f\"Agent{i}\", llm_config=False) for i in range(5)]\n", + "allowed_speaker_transitions_dict = {\n", + " agents[0]: [agents[1], agents[2], agents[3], agents[4]],\n", + " agents[1]: [agents[0]],\n", + " agents[2]: [agents[0]],\n", + " agents[3]: [agents[0]],\n", + " agents[4]: [agents[0]],\n", + "}\n", + "\n", + "visualize_speaker_transitions_dict(allowed_speaker_transitions_dict, agents)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Sequential Team Operations\n", + "# Create an empty directed graph\n", + "\n", + "speaker_transitions_dict = {}\n", + "teams = [\"A\", \"B\", \"C\"]\n", + "team_size = 5\n", + "\n", + "\n", + "def get_agent_of_name(agents, name) -> ConversableAgent:\n", + " for agent in agents:\n", + " if agent.name == name:\n", + " return agent\n", + "\n", + "\n", + "# Create a list of 15 agents 3 teams x 5 agents\n", + "agents = [ConversableAgent(name=f\"{team}{i}\", llm_config=False) for team in teams for i in range(team_size)]\n", + "\n", + "# Loop through each team and add members and their connections\n", + "for team in teams:\n", + " for i in range(team_size):\n", + " member = f\"{team}{i}\"\n", + " # Connect each member to other members of the same team\n", + " speaker_transitions_dict[get_agent_of_name(agents, member)] = [\n", + " get_agent_of_name(agents, name=f\"{team}{j}\") for j in range(team_size) if j != i\n", + " ]\n", + "\n", + "# Team leaders connection\n", + "print(get_agent_of_name(agents, name=\"B0\"))\n", + "speaker_transitions_dict[get_agent_of_name(agents, \"A0\")].append(get_agent_of_name(agents, name=\"B0\"))\n", + "speaker_transitions_dict[get_agent_of_name(agents, \"B0\")].append(get_agent_of_name(agents, name=\"C0\"))\n", + "\n", + "visualize_speaker_transitions_dict(speaker_transitions_dict, agents)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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JTk5OSk1NVadOna7b/mReseauSlLCsXOq5+jwk8Hy+9f9u7bSgkm+Nr3MfS0CJQAAsBupqakKDAzUmTNn1KNHD8XFxenXv/611q9fr6eeekqLFy/+8ffmXNTSHZmKPZqrzPPFujZAOUjyaumi4G7umjHYS13dm9T6Z7EkBEoAAGAX3n77bb300kuqrKzUiy++qDfffFPS1QuM//Wvf9Wf/vQntWrV6pb2delKuU6cv6TScrMaODmqU0vXqjvg2CMCJQAAsGlFRUUaMWKEduzYoWbNmikyMlIDBw40eiybwlneAADAZkVERMjDw0M7duzQ6NGjlZOTQ5isBQRKAABgc8xms2bNmqXRo0errKxMS5Ys0caNG9WgQQOjR7NJ9rvYDwAAbFJ6err8/f11+vRp+fj4KD4+Xp6enkaPZdNoKAEAgM1YtGiRfHx8lJWVpeeee05Hjx4lTNYBGkoAAGD1iouLNXLkSG3btk1NmzbVpk2bNHjwYKPHshs0lAAAwKpFR0fL3d1d27Zt08iRI5Wbm0uYrGMESgAAYJXMZrMee+wxjRgxQleuXNHHH3+syMhITrwxAEveAADA6mRkZMjf318nT56Ut7e34uPj1bZtW6PHsls0lAAAwKq8++678vb21smTJzVnzhwdO3aMMGkwGkoAAGAVSkpKFBYWpoSEBLm5uSk8PFzDhg0zeiyIhhIAAFiBuLg4tW7dWgkJCQoJCVFubi5h0oIQKAEAgEWbPXu2goODVVJSoo8++kjR0dFq2LCh0WPhGix5AwAAi5SZmamAgABlZGSoc+fOio+PV/v27Y0eCzdBQwkAACzOhx9+KG9vb2VkZOjJJ5/U8ePHCZMWjIYSAABYjJKSEo0ePVomk0lNmjTRhg0b5O/vb/RY+BkESgAAYBG2bNmisWPH6uLFiwoMDNSmTZvk7Oxs9Fi4BSx5AwAAwz355JPy9/dXcXGx3nvvPcXFxREmrQgNJQAAMMypU6cUEBCg9PR0dezYUSaTSR07djR6LNwmGkoAAGCI//znP+rcubPS09P1+OOPV4VKWB8aSgAAUKdKS0s1ZswYxcTEqHHjxlq3bp2CgoKMHgvVQKAEAAB1Ztu2bRozZowKCws1fPhwRUREyMXFxeixUE0seQMAgDrx9NNPa9iwYbp06ZIWL16shIQEwqSNoKEEAAC1KisrSwEBAUpLS1OHDh0UHx+vTp06GT0WahANJQAAqDWffvqpOnbsqLS0ND366KM6ceIEYdIG0VACAIAaV1paqnvuuUdRUVFydXXVpk2bFBoaavRYqCUESgAAUKN27NihUaNGqaCgQEOHDlVUVBTflbRxLHkDAIAa8/zzz2vIkCEqKirSwoULtXXrVsKkHaChBAAA1Zadna2AgAClpqaqXbt2io+PV5cuXYweC3WEhhIAAFTL559/Li8vL6WmpmrmzJnKzMwkTNoZGkoAAHBHysvLde+992rTpk1ycXHR+vXrFRYWZvRYMACBEgAA3LbExESFhYUpPz9fgwYN0ubNm9W4cWOjx4JBWPIGAAC35fe//70GDRqkwsJCvfXWW/ruu+8Ik3aOhhIAANyS3NxcBQYGKjk5WW3btlVcXJx8fHyMHgsWgIYSAAD8rKVLl6pDhw5KTk7WjBkzdPLkScIkqtBQAgCAH1VeXq6JEydqw4YNatSokcLDwzVmzBijx4KFIVACAICb2rNnj0aOHKm8vDwNGDBA0dHRcnNzM3osWCCWvAEAwA3++Mc/asCAAcrPz9cbb7yhxMREwiR+FA0lAACocu7cOQUGBurw4cPy9PRUXFycunfvbvRYsHA0lAAAQJK0fPlytWvXTocPH9b06dN1+vRpwiRuCQ0lAAB2rry8XFOnTtWaNWvk7OystWvX6t577zV6LFgRAiUAAHbswIEDCgkJ0fnz59W/f3/FxsbyXUncNpa8AQCwU6+++qr69u2rCxcu6PXXX9fu3bsJk7gjNJQAANiZvLw8BQUFKSkpSe7u7oqNjVWvXr2MHgtWjIYSAAA7smLFCrVt21ZJSUmaNm2azpw5Q5hEtdFQAgBgB8xms6ZNm6aVK1eqYcOGWrVqlSZOnGj0WLARBEoAAGzcwYMHFRISorNnz6pv376KjY1Vs2bNjB4LNoQlbwAAbNj8+fPl5+enc+fOaf78+dq7dy9hEjWOhhIAABuUn5+voKAg7d+/X61bt1ZMTIz69Olj9FiwUTSUAADYmFWrVqlNmzbav3+/pkyZouzsbMIkahWBEgAAG/H9iTeTJ09WZWWlVqxYoRUrVsjRkb/uUbtY8gYAwAYcOXJEQUFBys3Nla+vr+Li4tSiRQujx4Kd4H9ZAACwcq+//rr69Omjs2fP6tVXX9WBAwcIk6hTNJQAAFipwsJCBQUFae/evWrZsqViYmLk5+dn9FiwQzSUAABYobVr18rDw0N79+7VhAkTlJ2dTZiEYQiUAABYEbPZrOnTp2vChAkym81atmyZVq9eLScnFh1hHP7tAwDASqSkpCgoKEjZ2dnq3bu34uLi1KpVK6PHAmgoAQCwBn//+9/Vq1cv5eTkaO7cuTp48CBhEhaDhhIAAAtWWFiokJAQ7d69Wy1atFBUVJT69+9v9FjAdWgoAQCwUOHh4fL09NTu3bt1zz33KCcnhzAJi0SgBADAwpjNZs2YMUPjxo1TRUWFli5dqnXr1nHiDSwW/2YCAGBBUlNTFRgYqDNnzqhHjx4ymUxyd3c3eizgJ9FQAgBgId5++2316NFD2dnZeumll3TkyBHCJKwCDSUAAAYrKipSaGiodu7cqebNmysyMlIDBgwweizgltFQAgBgoIiICHl4eGjnzp0aM2aMcnNzCZOwOgRKAAAMYDabNXPmTI0ePVplZWX6/PPPFR4ezok3sEr8WwsAQB1LT0+Xv7+/Tp8+rW7duik+Pl4eHh5GjwXcMRpKAADq0KJFi+Tj46OsrCw9//zzSklJIUzC6tFQAgBQB4qLizVixAht375dTZs2VUREhAYNGmT0WECNoKEEAKCWRUdHy93dXdu3b1dYWJhyc3MJk7ApBEoAAGqJ2WzWr3/9a40YMUKlpaX69NNPFRERoQYNGhg9GlCjWPIGAKAWZGRkyN/fXydPnlTXrl0VHx+vNm3aGD0WUCtoKAEAqGHvvvuuvL29dfLkST399NNKTU0lTMKm0VACAFBDiouLNWrUKG3ZskVubm7auHGjhg4davRYQK2joQQAoAbExcXJ3d1dW7ZsUWhoqM6ePUuYhN0gUAIAUA1ms1lPPPGEgoODdeXKFf373//W5s2bOfEGdoUlbwAA7lBmZqYCAgKUkZGhLl26yGQyqX379kaPBdQ5GkoAAO7A+++/L29vb2VkZOipp55SWloaYRJ2i4YSAIDbUFJSotGjR8tkMqlJkyYKDw/X8OHDjR4LMBQNJQAAtyg+Pl7u7u4ymUwKCgpSbm4uYRIQgRIAgFvy5JNPKjAwUJcvX9YHH3yg2NhYOTs7Gz0WYBFY8gYA4CecOnVKAQEBSk9PV6dOnWQymeTl5WX0WIBFoaEEAOBHfPTRR+rcubPS09P1xBNPKD09nTAJ3AQNJQAAP1BaWqoxY8YoJiZGjRs31rp16xQUFGT0WIDFIlACAHCNrVu3auzYsSosLJS/v78iIyP5riTwM1jyBgDgf+bMmaPhw4fr0qVLevfddxUfH0+YBG4BDSUAwO5lZWUpICBAaWlp8vLyUnx8vDp27Gj0WIDVoKEEANi1Tz/9VB07dlRaWpoee+wxpaenEyaB20RDCQCwS6WlpRo3bpw2b94sV1dXbdq0SaGhoUaPBVglAiUAwO7s2LFDo0aNUkFBgYYNG6bIyEi5uLgYPRZgtVjyBgDYleeee05DhgxRUVGRFi1apC1bthAmgWqioQQA2IXs7GwFBAQoNTVV7du3V3x8vDp37mz0WIBNoKEEANi8zz//XF5eXkpNTdWsWbOUkZFBmARqEA0lAMBmlZaWavz48YqIiJCLi4s2bNigkSNHGj0WYHMIlAAAm5SYmKiwsDDl5+dr8ODBioqKUuPGjY0eC7BJLHkDAGzOSy+9pEGDBqmwsFBvv/22tm/fTpgEahENJQDAZuTm5iowMFDJyclq27atTCaTunbtavRYgM2joQQA2ISlS5eqQ4cOSk5O1sMPP6yTJ08SJoE6QkMJALBq5eXlmjBhgsLDw9WoUSOFh4drzJgxRo8F2BUCJQDAau3Zs0cjRozQhQsXNHDgQMXExPBdScAALHkDAKzS3LlzNWDAABUUFOjNN9/Uzp07CZOAQWgoAQBW5dy5cwoMDNThw4fl6ekpk8mkbt26GT0WYNdoKAEAVmP58uVq166dDh8+rAceeECnT58mTAIWgIYSAGDxysvLNWXKFK1du1bOzs5at26d7rnnHqPHAvA/BEoAgEXbt2+fRowYofPnz+sXv/iFYmJi5ObmZvRYAK7BkjcAwGK9+uqr6t+/vy5cuKAFCxZo165dhEnAAtFQAgAsTl5enoKCgpSUlCQPDw/FxsaqZ8+eRo8F4EfQUAIALMqKFSvUtm1bJSUl6b777lNWVhZhErBwNJQAAItgNps1depUrVq1Ss7Ozlq9erUmTJhg9FgAbgGBEgBguIMHDyo4OFjnzp1T3759FRsbq2bNmhk9FoBbxJI3AMBQ8+fPl5+fn/Ly8vSXv/xFe/fuJUwCVoaGEgBgiPz8fAUGBurAgQNq3bq1YmJi1KdPH6PHAnAHaCgBAHVu1apVatOmjQ4cOKApU6YoOzubMAlYMQIlAKDOmM1mTZs2TZMnT1ZlZaVWrFihFStWyNGRv44Aa8aSNwCgThw6dEghISHKzc2Vn5+fYmNj1aJFC6PHAlAD+F9CAECte/311+Xn56ezZ8/qtdde0/79+wmTgA2hoQQA1JrCwkIFBQVp7969atWqlaKjo+Xn52f0WABqGA0lAKBWrF27Vh4eHtq7d68mTpyoM2fOECYBG0WgBADUKLPZrOnTp2vChAmqrKzU8uXLtWrVKjk5sSgG2Cr+6wYA1JiUlBQFBQVVXQYoLi5OLVu2NHosALWMhhIAUCPeeOMN9erVSzk5OZo7d66SkpIIk4CdoKEEAFRLYWGhQkJCtHv3brVo0ULR0dHq27ev0WMBqEM0lACAOxYeHi5PT0/t3r1b48ePV05ODmESsEMESgDAbTObzXrwwQc1btw4VVRU6KuvvtKaNWs48QawU/yXDwC4LampqQoMDNSZM2fUs2dPxcfHq1WrVkaPBcBANJQAgFv2j3/8Qz169FB2drZefvllHT58mDAJgIYSAPDzioqKFBoaqp07d6p58+aKjIzUgAEDjB4LgIWgoQQA/KSIiAh5eHho586dGjt2rHJzcwmTAK5DoAQA3JTZbNYjjzyi0aNHq6ysTF988YU2bNjAiTcAbsCfCgCAG6SlpSkwMFCnT59W9+7dFR8fL3d3d6PHAmChaCgBANd555131L17d2VlZemFF15QcnIyYRLAT6KhBABIkoqLizVixAht375dzZo1U2RkpAYOHGj0WACsAA0lAEDR0dFyd3fX9u3bNWrUKOXk5BAmAdwyAiUA2DGz2axf/epXGjFihEpLS7VkyRJt2rRJDRo0MHo0AFaEJW8AsFPp6ekKDAzUyZMn5ePjo/j4eHl6eho9FgArREMJAHZo8eLF8vHx0alTp/Tss8/q6NGjhEkAd4yGEgDsSHFxsUaNGqUtW7aoadOm2rhxo4YMGWL0WACsHA0lANiJmJgYubu7a8uWLRoxYoRyc3MJkwBqBIESAGyc2WzWb37zG4WGhurKlSv6z3/+o6ioKE68AVBjWPIGABuWmZmpgIAAZWRkyNvbWyaTSe3atTN6LAA2hoYSAGzU+++/ry5duigjI0O/+93vdOzYMcIkgFpBQwkANqakpESjR4+WyWSSm5ubwsPDNWzYMKPHAmDDaCgBwIbEx8fL3d1dJpNJwcHBysnJIUwCqHUESgCwEb/97W8VGBioy5cv68MPP1RMTIycnZ2NHguAHWDJGwCs3KlTpxQQEKD09HR17txZ8fHxat++vdFjAbAjNJQAYMU++ugjde7cWenp6Zo9e7aOHz9OmARQ52goAcAKlZaWasyYMYqJiVHjxo21YcMGBQQEGD0WADtFoAQAK7N161aNHTtWhYWFCggIUEREBN+VBGAolrwBwIrMmTNHw4cP16VLl/Svf/1LJpOJMAnAcDSUAGAFsrKy5O/vr+PHj8vLy0vx8fHq2LGj0WMBgCQaSgCweB9//LE6duyo48eP67HHHlN6ejphEoBFoaEEAAtVWlqqcePGafPmzXJ1dVVERIRCQkKMHgsAbkCgBAALtGPHDo0aNUoFBQUaNmyYIiMj5eLiYvRYAHBTLHkDgIV57rnnNGTIEBUVFen//b//py1bthAmAVg0GkoAsBDZ2dkKCAhQamqqOnToIJPJpM6dOxs9FgD8LBpKALAAn332mby8vJSamqpZs2bpxIkThEkAVoOGEgAMVFpaqvHjxysiIkIuLi7asGGDRo4cafRYAHBbCJQAYJDExESFhYUpPz9fQ4YM0ebNm/muJACrxJI3ABjgxRdf1KBBg1RYWKiFCxdq27ZthEkAVouGEgDqUG5urgICApSSkqJ27drJZDLJ29vb6LEAoFpoKAGgjnz55Zdq3769UlJS9MgjjygzM5MwCcAm0FACQC0rLy/XhAkTFB4eLhcXF61bt06jRo0yeiwAqDEESgCoRbt27VJYWJguXLigu+++W9HR0WrcuLHRYwFAjWLJGwBqyR/+8AfdfffdKigo0FtvvaUdO3YQJgHYJBpKAKhh586dU0BAgI4cOaI2bdrIZDLJx8fH6LEAoNbQUAJADfr666/Vrl07HTlyRA8++KBOnTpFmARg82goAaAGlJeXa8qUKVq7dq0aNWqkDRs2aOzYsUaPBQB1gkAJANW0b98+jRgxQufPn9cvfvELxcTEyM3NzeixAKDOsOQNANXwyiuvqH///rpw4YL+9re/adeuXYRJAHaHhhIA7kBeXp4CAwN18OBBeXh4KDY2Vj179jR6LAAwBA0lANymFStWqG3btjp48KDuv/9+ZWVlESYB2DUaSgC4RWazWVOnTtWqVavk7OysNWvWaPz48UaPBQCGI1ACwC04ePCggoODde7cOfXv31+xsbF8VxIA/oclbwD4GfPmzZOfn5/y8vL0l7/8Rbt37yZMAsA1aCgB4Efk5+crMDBQBw4ckLu7u2JiYtS7d2+jxwIAi0NDCQA3sWrVKnl6eurAgQOaOnWqzpw5Q5gEgB9BoASAa5jNZk2bNk2TJ0+WJK1cuVLffvutHB354xIAfgxL3gDwP4cOHVJISIhyc3N11113KS4uTs2aNTN6LACwePwvNwBI+utf/yo/Pz+dPXtW8+bN0759+wiTAHCLaCgB2LX8/HyFhIRo7969atWqlWJjY9WnTx+jxwIAq0JDCcBurV27Vm3atNHevXs1adIkZWdnEyYB4A4QKAHYHbPZrOnTp2vChAmqrKzUt99+q5UrV6pevXpGjwYAVoklbwB25ciRIwoJCVF2drZ8fX0VFxenFi1aGD0WAFg1GkoAduONN95Qnz59lJOToz/96U86cOAAYRIAagANJQCbV1hYqJCQEO3evVstW7bU5s2b1bdvX6PHAgCbQUMJwKaFh4fL09NTu3fv1vjx45WdnU2YBIAaRqAEYJPMZrMefPBBjRs3ThUVFVq2bJnWrFkjJycWZgCgpvEnKwCbc/ToUQUGBio7O1u9evWSyWRSq1atjB4LAGwWDSUAm/KPf/xDPXv2VE5Ojl5++WUdOnSIMAkAtYyGEoBNKCoqUkhIiBITE9W8eXNt3rxZ/fv3N3osALALNJQArN7GjRvl4eGhxMREjRs3Trm5uYRJAKhDBEoAVstsNuuRRx7R2LFjVVZWpi+//FLr16/nxBsAqGP8qQvAKqWlpSkgIEBZWVnq0aOHTCaT3N3djR4LAOwSDSUAq/PPf/5T3bp105kzZ/Tiiy/qyJEjhEkAMBANJQCrUVxcrNDQUH333Xdq1qyZIiMjNXDgQKPHAgC7R0MJwCpERUWpdevW+u677zR69Gjl5OQQJgHAQhAoAVg0s9msWbNmKSwsTGVlZVqyZIk2btyoBg0aGD0aAOB/WPIGYLHS09MVEBCgU6dOycfHR/Hx8fL09DR6LADAD9BQArBIixcvlo+Pj06fPq1nn31WR48eJUwCgIWioQRgUYqLixUWFqatW7eqadOmioiI0KBBg4weCwDwE2goAViMmJgYubu7a+vWrRo5cqRyc3MJkwBgBQiUAAxnNpv12GOPKTQ0VFeuXNEnn3yiyMhITrwBACvBkjcAQ2VkZCggIECZmZny9vZWfHy82rZta/RYAIDbQEMJwDDvvfeevL29lZmZqTlz5ujYsWOESQCwQjSUAOpcSUmJwsLClJCQIDc3N4WHh2vYsGFGjwUAuEM0lADqVHx8vFq3bq2EhASFhIQoJyeHMAkAVo5ACaDOzJ49W4GBgSopKdGHH36o6OhoOTs7Gz0WAKCaWPIGUOsyMzMVGBioEydOqEuXLjKZTGrfvr3RYwEAaggNJYBa9eGHH8rb21snTpzQb3/7W6WlpREmAcDG0FACqBUlJSUaM2aM4uLi1KRJE61fv14BAQFGjwUAqAUESgA1bsuWLRo7dqwuXryowMBAbdq0ie9KAoANY8kbQI363e9+J39/fxUXF+u9995TXFwcYRIAbBwNJYAakZWVJX9/fx0/flwdO3ZUfHy8vLy8jB4LAFAHaCgBVNvHH3+sjh076vjx43r88cd1/PhxwiQA2BEaSgB3rLS0VGPHjlV0dLRcXV0VFRWloKAgo8cCANQxAiWAO7J9+3aNHj1ahYWFGj58uCIiIuTi4mL0WAAAA7DkDeC2Pfvssxo2bJguXbqkxYsXKyEhgTAJAHaMhhLALTtz5owCAgJ07NgxdejQQQkJCerYsaPRYwEADEZDCeCWLFmyRB07dtSxY8f06KOP6sSJE4RJAIAkGkoAP6O0tFTjx49XRESEXF1dtXHjRoWGhho9FgDAghAoAfyonTt3KiwsTAUFBRoyZIg2b97MdyUBADdgyRvATb344osaPHiwioqKtHDhQm3bto0wCQC4KRpKANfJyclRQECAjh49qnbt2slkMsnb29vosQAAFoyGEkCVL7/8Uh06dNDRo0f1yCOPKDMzkzAJAPhZNJQAVF5ervHjx2vjxo1ycXHRunXrNGrUKKPHAgBYCQIlYOd27dqlsLAwXbhwQXfffbeio6PVuHFjo8cCAFgRlrwBO/aHP/xBd999twoKCvTWW29px44dhEkAwG2joQTsUG5urgIDA5WcnKw2bdrIZDLJx8fH6LEAAFaKhhKwM19//bU6dOig5ORkPfjggzp16hRhEgBQLTSUgJ0oLy/XpEmTtH79ejVq1EgbNmzQ2LFjjR4LAGADCJSAHdi3b59CQ0OVl5enAQMGKDo6Wm5ubkaPBQCwESx5Azbuj3/8o/r376/8/Hz97W9/U2JiImESAFCjaCgBG3Xu3DkFBQXp0KFD8vT0VFxcnLp37270WAAAG0RDCdigb775Ru3atdOhQ4c0ffp0nT59mjAJAKg1NJSADSkvL9fUqVO1Zs0aOTs7a82aNRo/frzRYwEAbByBErARBw4cUEhIiM6fP6/+/fsrNjaW70oCAOoES96ADZg3b5769u2rCxcu6K9//at2795NmAQA1BkaSsCK5eXlKSgoSElJSXJ3d1dMTIx69+5t9FgAADtDQwlYqf/+979q27atkpKSNG3aNJ05c4YwCQAwBIESsDJms1lTpkzR1KlTJUkrV67UN998I0dH/nMGABiDJW/Aihw8eFAhISE6e/as7rrrLsXFxalZs2ZGjwUAsHNUGoCV+POf/yw/Pz+dO3dO8+fP1759+wiTAACLQEMJWLj8/HwFBwdr3759at26tWJiYtSnTx+jxwIAoAoNJWDB1qxZozZt2mjfvn2aPHmysrOzCZMAAItDoAQskNls1i9/+UtNnDhRlZWV+vbbb/Xf//6XE28AABaJJW/Awhw5ckRBQUHKzc2Vr6+v4uLi1KJFC6PHAgDgR1F3ABbkb3/7m/r06aOzZ8/qlVde0YEDBwiTAACLR0MJWIDCwkIFBwdrz549atmypWJiYuTn52f0WAAA3BIaSsBg69atk4eHh/bs2aMJEyYoOzubMAkAsCoESsAgZrNZDzzwgMaPHy+z2axly5Zp9erVcnJi4QAAYF34mwswQEpKioKCgpSdna1evXrJZDKpVatWRo8FAMAdoaEE6tjf//539erVSzk5OfrDH/6gQ4cOESYBAFaNhhKoI0VFRQoJCVFiYqJatGihqKgo9e/f3+ixAACoNhpKoA5s3LhR7u7uSkxM1Lhx45STk0OYBADYDAIlUIvMZrMefvhhjR07VhUVFfryyy+1fv16TrwBANgU/lYDaklqaqoCAwN15swZ9ejRQyaTSe7u7kaPBQBAjaOhBGrB22+/rR49eig7O1svvfSSjhw5QpgEANgsGkqgBhUVFWnEiBHasWOHmjVrpqioKA0YMMDosQAAqFU0lEANiYyMlIeHh3bs2KHRo0crJyeHMAkAsAsESqCazGazZs2apVGjRqmsrEyfffaZNm7cqAYNGhg9GgAAdYIlb6Aa0tPT5e/vr9OnT8vHx0fx8fHy9PQ0eiwAAOoUDSVwhxYtWiQfHx9lZWXpueee09GjRwmTAAC7REMJ3Kbi4mKNHDlS27ZtU9OmTRUREaFBgwYZPRYAAIahoQRuQ3R0tNzd3bVt2zaNHDlSubm5hEkAgN0jUAK3wGw267HHHtOIESN05coVffLJJ4qMjOTEGwAAxJI38LMyMjLk7++vkydPqmvXrjKZTGrbtq3RYwEAYDFoKIGf8O6778rb21snT57UnDlzlJqaSpgEAOAHaCiBm7h8+bLCwsK0ZcsWubm5KTw8XMOGDTN6LAAALBINJfADcXFxcnd315YtWxQaGqqzZ88SJgEA+AkESuAas2fPVnBwsEpKSvTvf/9bmzdv5sQbAAB+BkvegKTMzEwFBAQoIyNDXbp0kclkUvv27Y0eCwAAq0BDCbv3wQcfyNvbWxkZGXrqqaeUlpZGmAQA4DbQUMJulZSUaPTo0TKZTGrSpInCw8M1fPhwo8cCAMDq0FDCLm3ZskXu7u4ymUwKCgpSbm4uYRIAgDtEoITdefLJJ+Xv76/i4mK99957io2NlbOzs9FjAQBgtVjyht04deqUAgIClJ6ero4dOyo+Pl5eXl5GjwUAgNWjoYRd+Pe//63OnTsrPT1dTzzxhE6cOEGYBACghtBQwqaVlpZqzJgxiomJUePGjbVu3ToFBQUZPRYAADaFQAmbtW3bNo0ZM0aFhYXy9/fXpk2b5OLiYvRYAADYHJa8YZOefvppDRs2TJcuXdLixYsVHx9PmAQAoJbQUMKmZGVlKSAgQGlpaerQoYMSEhLUsWNHo8cCAMCm0VDCZnz66afq2LGj0tLS9Otf/1onTpwgTAIAUAdoKGH1SktLdc899ygqKkqurq7atGmTQkNDjR4LAAC7QaCEVduxY4dGjRqlgoICDR06VFFRUXxXEgCAOsaSN6zW888/ryFDhqioqEjvvPOOtm7dSpgEAMAANJSwOtnZ2QoMDNTRo0fVrl07mUwmeXt7Gz0WAAB2i4YSVuXzzz+Xl5eXjh49qpkzZyozM5MwCQCAwWgoYRXKy8t17733Vl2cfMOGDRo5cqTRYwEAABEoYQUSExMVFham/Px8DRo0SJs3b1bjxo2NHgsAAPwPS96waL///e81aNAgFRYW6u2339Z3331HmAQAwMLQUMIi5ebmKjAwUMnJyWrTpo1MJpN8fHyMHgsAANwEDSUszldffaUOHTooOTlZDz30kE6dOkWYBADAgtFQwmKUl5dr4sSJ2rBhgxo1aqTw8HCNGTPG6LEAAMDPIFDCIuzZs0cjR45UXl6eBgwYoOjoaLm5uRk9FgAAuAUsecNwf/zjHzVgwADl5+frzTffVGJiImESAAArQkMJw5w7d06BgYE6fPiwPD09FRcXp+7duxs9FgAAuE00lDDE8uXL1a5dOx0+fFjTp0/X6dOnCZMAAFgpGkrUqfLyck2ZMkVr166Vs7Oz1q1bp3vuucfosQAAQDUQKFFn9u/fr9DQUJ0/f179+/dXbGws35UEAMAGsOSNOvHqq6+qX79+unDhghYsWKDdu3cTJgEAsBE0lKhVeXl5CgoKUlJSktzd3RUXF6eePXsaPRYAAKhBNJSoNf/973/Vtm1bJSUladq0aTpz5gxhEgAAG0RDiRpnNps1depUrVq1Ss7Ozlq9erUmTJhg9FgAAKCWEChRow4ePKjg4GCdO3dOffv2VWxsrJo1a2b0WAAAoBax5I0aM3/+fPn5+en8+fOaP3++9u7dS5gEAMAO0FCi2vLz8xUUFKT9+/erdevWiomJUZ8+fYweCwAA1BEaSlTLqlWr1KZNG+3fv19TpkxRdnY2YRIAADtDoMQdMZvNmjZtmiZPnqzKykqtWLFCK1askKMj/0oBAGBvWPLGbTt8+LCCg4OVm5srX19fxcXFqUWLFkaPBQAADEKdhNvy+uuvy9fXV2fPntUrr7yiAwcOECYBALBzNJS4JYWFhQoKCtLevXvVsmVLxcTEyM/Pz+ixAACABaChxM9au3atPDw8tHfvXk2cOFHZ2dmESQAAUIVAiR9lNps1ffp0TZgwQWazWcuXL9eqVavk5ESxDQAA/g/JADeVkpKioKAgZWdnq3fv3oqLi1OrVq2MHgsAAFggGkrc4M0331SvXr2Uk5OjuXPn6uDBg4RJAADwo2goUaWwsFAhISHavXu3WrRooaioKPXv39/osQAAgIWjoYQkKTw8XJ6entq9e7fuuece5eTkECYBAMAtIVDaObPZrBkzZmjcuHGqqKjQV199pXXr1nHiDQAAuGWkBjuWmpqqwMBAnTlzRj169JDJZJK7u7vRYwEAACtDQ2mn3nrrLfXo0UPZ2dl66aWXdOTIEcIkAAC4IzSUdqaoqEihoaHauXOnmjdvrsjISA0YMMDosQAAgBWjobQjERER8vDw0M6dOzVmzBjl5uYSJgEAQLXZTaCsrKw0egTDmM1mPfLIIxo9erTKysr0xRdfKDw8nBNvAABAjbCLQHnw4EE1aNBADz30kI4ePWr0OHXq+PHj8vLy0ueff65u3bopMzNTM2bMMHosAABgQ+wiUGZnZ6u8vFxfffWVevToYTfB8p133lG3bt2UlZWlF154QSkpKfL09DR6LAAAYGMcKu1gLXjz5s0aOXJk1e/r1asns9mswMBALVq0SEVFRbp48aJcXV3Vp08fNWvWzLhha0BxcbFGjBih7du3q2nTpoqIiNCgQYOMHgsAANgou/gSXWlp6XW/r6iokCTFxcXp0Ucf1eHDh1VcXFz1eq9evTRkyBAFBwdr2rRpatCgQZ3OWx3R0dGaMGGCLl26pLCwMK1bt86q5gcAANbHppe8y8vL9Z///EePPPLIDa+1bt1ab775puLj45Wdna3MzEwdOHBAS5Yskb+/vxITEzVjxgx5e3vrX//6l0pKSgz4BLfObDbr0Ucf1YgRI1RaWqolS5YoIiKCMAkAAGqdzS55p6SkaNKkSTpy5IiCgoIUFxcnSWrTpo1ee+01zZw5Uw0bNvzJfRw+fFgLFizQ119/LU9PT3355ZcKDg6ug+lvz4kTJ+Tv769Tp06pa9euMplMatu2rdFjAQAAO2GTDeXWrVs1dOhQSdKePXv0xRdfaPjw4frggw+Unp6uxx9//GfDpHR16fvLL79UcnKyevbsqZEjR+pf//qXRV2CaPHixeratatOnTqlZ555RqmpqYRJAABQp2yuoYyIiNCECRM0aNAgrV69Ws2bN6+R/ZaXl+vFF1/UO++8o9/97ndatGiRHBwcamTfd6K4uFhhYWHaunWr3NzcFB4ermHDhhk2DwAAsF82FShPnjypvn37atCgQVq1atUttZC364MPPtDs2bO1ePFiPfXUUzW+/1sRGxure++9V5cuXVJoaKjCw8P5riQAADCMzQTK8vJyhYSEKD09Xfv27VPLli1r7VjPPvus3n33XcXExMjf37/WjvNDZrNZs2fP1kcffSQnJye9//77+vWvf11nxwcAALgZmwmUCxcu1AsvvKC4uLhaD3llZWUaOXKkUlJSlJqaqsaNG9fq8SQpIyNDAQEByszMVJcuXWQymdS+fftaPy4AAMDPsYmTckpKSvT3v/9dM2fOrJPGsH79+vrss890/vx5LVq0qNaP995778nb21uZmZl66qmnlJaWRpgEAAAWwyYayg8++EBPPvmkkpOT5ePjU2fHnTNnjj7//HOlp6fX2Mk/1yopKdGoUaMUHx+vJk2aKDw8XMOHD6/x4wAAAFSH1TeUlZWVevvttzV16tQ6DZOSNHfuXJWVlWnx4sU1vu/4+Hi5u7srPj5eQUFBys3NJUwCAACLZPWBMjk5WceOHdPMmTPr/Nienp6aMmWKvvnmmxrd75NPPqnAwEBdvnxZH3zwgWJjY+Xs7FyjxwAAAKgpVn8v740bN8rZ2VlBQUGGHH/SpEn64osvdPToUXXr1q1a+zp58qQCAgJ04sQJderUSSaTSV5eXjU0KQAAQO2w+oZy06ZNCgwMVKNGjQw5/qhRo9SoUSOtWrWqWvv56KOP1KVLF504cUJPPPGE0tPTCZMAAMAqWH1DuXfvXs2ZM8ew47u4uGjYsGHasWPHHb3/ypUrGjNmjGJjY9W4cWOtW7fOsLYVAADgTlh1Q1lUVKRz586pS5cuhs7RvXt3paSk3Pb7tm7dKnd3d8XGxiogIEBnz54lTAIAAKtj1YEyIyNDktSpUydD5+jevbuOHTumioqKW37PnDlzNHz4cF26dEn/+te/ZDKZOPEGAABYJate8j516pQkGX6R765du6q0tFSnT5/+2e89ZmVlKSAgQGlpafLy8lJ8fLw6duxYR5MCAADUPKtuKL/n4OBg6PG/bxbLy8t/crtPPvlEHTt2VFpamh577DGlp6cTJgEAgNWz6oayQYMGkq7eW9uSlZaWaty4cdq8ebNcXV21adMmhYaGGj0WAABAjbDqQFm/fn1Jlh0ov/vuO40ePVoFBQUaNmyYIiMj5eLiYvRYAAAANcaql7xbtmwpScrJyTF0jvPnz0uS3Nzcrnv+2Wef1dChQ1VUVKR33nlHW7ZsIUwCAACbY9UNZdeuXeXk5KRDhw4pMDDQsDlSUlLUokULtWrVSpKUnZ2tgIAApaamqn379oqPj1fnzp0Nmw8AAKA2WXVDWb9+fXXr1k2HDh0ydI6UlJSq2y5+9tln8vLyUmpqqmbNmqWMjAzCJAAAsGlWHSglydfXV3v27Knz46anp2vs2LE6fvy4kpKS1LVrV40ePVozZ85U/fr1FRkZqU8++USOjlb/IwYAAPhJDpWVlZVGD1Edn332mWbNmqVTp06pbdu2t/3+S1fKdeL8JZWWm9XAyVGdWrrKteHPfxPg/vvv1/Lly+Xr66ukpCS5uLiouLhYgwcPVlRUlBo3bnwnHwcAAMDqWH2gvHDhgjw8PPTPf/5TTz311C29JzXnopbuyFRsSq4y84p17Q/AQZJXCxcFd3fXg4O85OPR5Ib379u3T/369bvuOUdHR/3jH//Qc889V41PAwAAYH2sPlBK0tixY1VQUKCtW7f+5HYn84o1d1WSEo6dUz1HB1WYf/yjf/+6f9dWWjDJVx1a/N/Z2aNHj9bmzZuvu9Xi0qVL9cADD1T/wwAAAFgZmwiUq1ev1qRJkxQdHa2QkJCbbrMsMVOvrT2kcnPlTwbJH6rn6CAnRwfNH99b9w/0UkJCggICAq7bxsHBQZ6enjp06JCaN29erc8CAABgbWwiUFZWVmrw4MGSrl5I/Ie3Ynw3NlVvRR6t9nGeG+Gj16YOUn5+/k1fj4mJUXBwcLWPAwAAYE1s4hRkBwcH/e1vf9POnTv1zTffXPfassTMGgmTkvTPzakq9xooJycn9ejRQ5L0+OOPKyoqSqdPnyZMAgAAu2RxgfKJJ56Qg4ND1a833njjlt4XEhKiqVOn6je/+Y2Sk5MlXf3O5Gtra/AalZWV8rznaZl2HVROTo7Gjh2rxx9/XFu2bNFHH32kuLi4m76tsLBQv//97+Xt7a2GDRvKw8NDM2bMUFpaWs3NBgAAYBCLWvIuKytTmzZtqm5lKEl33XWX9u3bd0vvv3jxogYNGiSz2awdO3boqRXJ2nb8/G19Z/Ln1HOUHHJSVRm7WLt27dKaNWs0a9YsSdJrr72mefPmXbd9YWGh/P39deDAgRv21bx5c5lMJvn6+tbYfAAAAHXNohrKqKio68KkJO3fv7+qcfw5TZo00erVq5Wdna0RUx5SwrFzNRomJanCLJW39tHiz769pRNw5s2bVxUmAwICtHr1aj3++OOSrl7y6NFHH63R+QAAAOqaRTWUDz/8sL744gtJVy8cvmzZMkk3b/5WrFihefPm6dixY+ratateffVVHT58WPPnz5ckNesbJrewJ+XgWE+SVJqbroLt3+pKZpIqLl9UPRc3NeoyQE2HPyAnt1ZV+81PWKqCrV9LklqOfVrmK8W6uHu9yi+eVf0W7dU89DG5dr5LDw/upCVzxikjI+Omn+W1117T3Llz5eHhofz8fDk4OOj06dNq06aNKisr1atXr6qgvGvXLv3iF7+ouR8kAABAHbKYhrKkpESrV6+WJLVu3VrvvPOOnJyu3rHm+2D5vZUrV+qXv/ylDh06pCtXrujQoUO67777qt4vSa26+lWFyctpu3Tms+dUfCReFZcuSOZyVRTlqehApLI/e1Zl+dk3nalg23JdiP63yvPPSBXlKjt7QmdX/lVll4sUezT3Zz/TwYMHq84I79Spk9q0aSPp6klEQ4YMqdouISHhln5GAAAAlshiAuX69et18eJFSdLEiRPl4eGhoKAgSVJKSor27t0rSaqoqNAzzzyj74vVadOmacOGDZozZ472799ftb8LxeWSJHNZic5tWChVlEmO9dQs4GG53/cXuQ2acnV/ly4oL/L9m85Unp8tt8FT1XrKK6rv3lmSVFl6WcWH4pR5vlhffLVMc+fOrdp+1qxZSkhIUEJCgn71q1/pxIkTVa95eHhct293d/eqx+np6bf98wIAALAUFhMor20hp06det0/r3199+7dOnnypCTJ09NTS5cu1dixY7Vo0aKqa1FeqyR9r8zFBZIk50591bBDbzk4NVCjrnerXtOrIa/k+B5V/G+bazXyGazmQTPl4jNITYdMq3q+7MIZVUpq0amnfHx8qp738vLS8OHDNXz4cHl5eenSpUtVrzVo0OC6fV/7+2u3AwAAsDYWESgvXryoDRs2SJJatGhRdbebyZMnq169q8vWy5cvV2VlpY4fP171vv79+6t+/fpVv792Gfl7ZXmnqx6XHN+tnKW/r/pVUZDzv1cqVXb+1A3vde7Qp+qxYyO3qsfmK1cDYGm5+Sc/l6ura9XjK1euXPdaaWnpTbcDAACwNk5GDyBdvXViSUmJJCkvL++6kPi9jIwMbd++/brnfnhHnOqoLCu54TlH58bXHOua7P2/5fYGTj+dxzt16lT1OCcn57rXsrP/73ubnTt3vp1RAQAALIpFBMqvv/76lrZbtmyZHnrooarf7927VxUVFVUt5g8DpyTVb9Gu6rFrn1C1uufZG7Yxl5XIsb7zbc3sIKlTS1ftdvy/UGk2X99Y9unTR02bNlVBQYEyMjJ0+vRptWvXTpWVlfruu++qtvP397+tYwMAAFgSwwPl+fPnFRUVJenqdSQXLFhw3eulpaV6/vnnJUnffvutFi5cqA4dOujkyZPKysrSww8/rAcffFARERHXhbSWjRvoiiTnTv3k6NJU5uICXToYI8dGjdWoUz9VVppVXpCjK6eOqCw3XW0fu/mJOT/Gq6WLXBs6XXctyk2bNikgIEDOzs7y9fVV06ZN9atf/UoLFy5UZWWlpk+frhdeeEEbNmxQSkqKJGnAgAFcMggAAFg1w69D+eGHH+qJJ56QJE2ZMkUrVqy4YZt+/fpV3S1n8+bNKigo0NSpU/XD0X19fZWUlCRJmjDnr0pq3E8V5kpdTktU7soFV8/0vol6bu5q/9tPJP3wOpTPqLHfCElSScYB5Xx99Yzuxr6hev6vizRvfG+dO3dO7du3v+E7krGxsQoKCvrJO+U0a9ZM8fHx3CkHAABYNcNPyrl2uXv8+PE33ebee++terxs2TJNnjxZ33zzjXr16qUGDRqoZ8+e+uqrrxQaGlq1XXDv9lV3yWnkPVBtZi6Ua+9g1WvSSnJ0kmMjN9V376ImAyeq9aSXb2vmykppxmAvSVKrVq20evVq9evXT40aNbphWzc3NyUkJOjFF19U586d1aBBA7m7u+uBBx5QYmIiYRIAAFg9wxvKO1FZWXnTE3IGDx6sHTt2SJL27Nmjf+4prYV7eTtoaJeW+uLRQTW2TwAAAGtmeEN5JxISEjR9+nRFREQoIyND+/fv15NPPlkVJrt376677rpLCyb5ysmx5s4ElyQnRwctmESrCAAA8D2rbCjj4uIUHBx809eaNGmiyMjIqoucL0vM1Msrk2rs2G9O9tV9A71qbH8AAADWziobyi5dumjGjBny9vaWi4uLGjZsqK5du2r27Nnav3//dXfMuX+gl14I61Yjx30xrDthEgAA4AessqG8E8sSM/Xa2kMqN1fe1ncq6zk6yMnRQX8e35swCQAAcBN2Eygl6WReseauSlLCsXOq5+jwk8Hy+9f9u7bSgkm+6tDCpQ4nBQAAsB52FSi/l5pzUUt3ZCr2aK4yzxfr2h+Ag65etDy4m7tmDPZSV/cmRo0JAABgFewyUF7r0pVynTh/SaXlZjVwclSnlq5ybWj4DYQAAACsht0HSgAAAFSPVZ7lDQAAAMtBoAQAAEC1ECgBAABQLQRKAAAAVAuBEgAAANVCoAQAAEC1ECgBAABQLQRKAAAAVAuBEgAAANVCoAQAAEC1ECgBAABQLQRKAAAAVAuBEgAAANVCoAQAAEC1ECgBAABQLQRKAAAAVAuBEgAAANVCoAQAAEC1ECgBAABQLQRKAAAAVAuBEgAAANVCoAQAAEC1ECgBAABQLQRKAAAAVAuBEgAAANVCoAQAAEC1ECgBAABQLQRKAAAAVAuBEgAAANVCoAQAAEC1ECgBAABQLQRKAAAAVAuBEgAAANVCoAQAAEC1ECgBAABQLQRKAAAAVMv/BxQ6vA4HzihGAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "agents = [ConversableAgent(name=f\"Agent{i}\", llm_config=False) for i in range(2)]\n", + "allowed_speaker_transitions_dict = {\n", + " agents[0]: [agents[0], agents[1]],\n", + " agents[1]: [agents[0], agents[1]],\n", + "}\n", + "\n", + "visualize_speaker_transitions_dict(allowed_speaker_transitions_dict, agents)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Demonstration" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`GroupChat` now takes in two optional arguments.\n", + "- allowed_or_disallowed_speaker_transitions: The keys are source agents, and the values are agents that the key agent can/can't transit to, depending on speaker_transitions_type. Default is None, which means all agents can transit to all other agents.\n", + "- speaker_transitions_type: whether the speaker_transitions_type is a dictionary containing lists of allowed agents or disallowed agents. \"allowed\" means the `allowed_or_disallowed_speaker_transitions` is a dictionary containing lists of allowed agents." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Team Operations\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Create an empty directed graph\n", + "agents = []\n", + "speaker_transitions_dict = {}\n", + "secret_values = {}\n", + "\n", + "# Outer loop for prefixes 'A', 'B', 'C'\n", + "for prefix in [\"A\", \"B\", \"C\"]:\n", + " # Add 3 nodes with each prefix to the graph using a for loop\n", + " for i in range(3):\n", + " node_id = f\"{prefix}{i}\"\n", + " secret_value = random.randint(1, 5) # Generate a random secret value\n", + " secret_values[node_id] = secret_value\n", + "\n", + " # Create an AssistantAgent for each node (assuming AssistantAgent is a defined class)\n", + " agents.append(\n", + " AssistantAgent(\n", + " name=node_id,\n", + " system_message=f\"\"\"Your name is {node_id}.\n", + " Do not respond as the speaker named in the NEXT tag if your name is not in the NEXT tag. Instead, suggest a relevant team leader to handle the mis-tag, with the NEXT: tag.\n", + "\n", + " You have {secret_value} chocolates.\n", + "\n", + " The list of players are [A0, A1, A2, B0, B1, B2, C0, C1, C2].\n", + "\n", + " Your first character of your name is your team, and your second character denotes that you are a team leader if it is 0.\n", + " CONSTRAINTS: Team members can only talk within the team, whilst team leader can talk to team leaders of other teams but not team members of other teams.\n", + "\n", + " You can use NEXT: to suggest the next speaker. You have to respect the CONSTRAINTS, and can only suggest one player from the list of players, i.e., do not suggest A3 because A3 is not from the list of players.\n", + " Team leaders must make sure that they know the sum of the individual chocolate count of all three players in their own team, i.e., A0 is responsible for team A only.\n", + "\n", + " Keep track of the player's tally using a JSON format so that others can check the total tally. Use\n", + " A0:?, A1:?, A2:?,\n", + " B0:?, B1:?, B2:?,\n", + " C0:?, C1:?, C2:?\n", + "\n", + " If you are the team leader, you should aggregate your team's total chocolate count to cooperate.\n", + " Once the team leader know their team's tally, they can suggest another team leader for them to find their team tally, because we need all three team tallys to succeed.\n", + " Use NEXT: to suggest the next speaker, e.g., NEXT: A0.\n", + "\n", + " Once we have the total tally from all nine players, sum up all three teams' tally, then terminate the discussion using TERMINATE.\n", + "\n", + " \"\"\",\n", + " llm_config=config_list_gpt4,\n", + " )\n", + " )\n", + " speaker_transitions_dict[agents[-1]] = []\n", + "\n", + " # Add edges between nodes with the same prefix using a nested for loop\n", + " for source_node in range(3):\n", + " source_id = f\"{prefix}{source_node}\"\n", + " for target_node in range(3):\n", + " target_id = f\"{prefix}{target_node}\"\n", + " if source_node != target_node: # To avoid self-loops\n", + " speaker_transitions_dict[get_agent_of_name(agents, source_id)].append(\n", + " get_agent_of_name(agents, name=target_id)\n", + " )\n", + "\n", + "\n", + "# Adding edges between teams\n", + "speaker_transitions_dict[get_agent_of_name(agents, \"A0\")].append(get_agent_of_name(agents, name=\"B0\"))\n", + "speaker_transitions_dict[get_agent_of_name(agents, \"A0\")].append(get_agent_of_name(agents, name=\"C0\"))\n", + "speaker_transitions_dict[get_agent_of_name(agents, \"B0\")].append(get_agent_of_name(agents, name=\"A0\"))\n", + "speaker_transitions_dict[get_agent_of_name(agents, \"B0\")].append(get_agent_of_name(agents, name=\"C0\"))\n", + "speaker_transitions_dict[get_agent_of_name(agents, \"C0\")].append(get_agent_of_name(agents, name=\"A0\"))\n", + "speaker_transitions_dict[get_agent_of_name(agents, \"C0\")].append(get_agent_of_name(agents, name=\"B0\"))\n", + "\n", + "\n", + "# Visualization only\n", + "graph = nx.DiGraph()\n", + "\n", + "# Add nodes\n", + "graph.add_nodes_from([agent.name for agent in agents])\n", + "\n", + "# Add edges\n", + "for key, value in speaker_transitions_dict.items():\n", + " for agent in value:\n", + " graph.add_edge(key.name, agent.name)\n", + "\n", + "# Visualize\n", + "# Draw the graph with secret values annotated\n", + "plt.figure(figsize=(12, 10))\n", + "pos = nx.spring_layout(graph) # positions for all nodes\n", + "\n", + "# Draw nodes with their colors\n", + "nx.draw(graph, pos, with_labels=True, font_weight=\"bold\")\n", + "\n", + "# Annotate secret values\n", + "for node, (x, y) in pos.items():\n", + " secret_value = secret_values[node]\n", + " plt.text(x, y + 0.1, s=f\"Secret: {secret_value}\", horizontalalignment=\"center\")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# Termination message detection\n", + "\n", + "\n", + "def is_termination_msg(content) -> bool:\n", + " have_content = content.get(\"content\", None) is not None\n", + " if have_content and \"TERMINATE\" in content[\"content\"]:\n", + " return True\n", + " return False\n", + "\n", + "\n", + "# Terminates the conversation when TERMINATE is detected.\n", + "user_proxy = autogen.UserProxyAgent(\n", + " name=\"User_proxy\",\n", + " system_message=\"Terminator admin.\",\n", + " code_execution_config=False,\n", + " is_termination_msg=is_termination_msg,\n", + " human_input_mode=\"NEVER\",\n", + ")\n", + "\n", + "agents.append(user_proxy)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:root:Warning: There are isolated agent nodes, there are not incoming nor outgoing edges. Isolated agents: ['User_proxy']\n", + "WARNING:root:Warning: The set of agents in allowed_speaker_transitions do not match agents. Offending agents: ['User_proxy']\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mA0\u001b[0m (to chat_manager):\n", + "\n", + "\n", + " There are 9 players in this game, split equally into Teams A, B, C. Therefore each team has 3 players, including the team leader.\n", + " The task is to find out the sum of chocolate count from all nine players. I will now start with my team.\n", + " NEXT: A1\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mA1\u001b[0m (to chat_manager):\n", + "\n", + "As A1, I have 2 chocolates. \n", + "\n", + "A0:?, A1:2, A2:?, \n", + "B0:?, B1:?, B2:?, \n", + "C0:?, C1:?, C2:?\n", + "\n", + "NEXT: A2\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mA2\u001b[0m (to chat_manager):\n", + "\n", + "As A2, I have 2 chocolates.\n", + "\n", + "A0:?, A1:2, A2:2, \n", + "B0:?, B1:?, B2:?, \n", + "C0:?, C1:?, C2:?\n", + "\n", + "NEXT: A0\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mA0\u001b[0m (to chat_manager):\n", + "\n", + "As A0, I have 1 chocolate. So, the total chocolate count for team A is 5.\n", + "\n", + "A0:1, A1:2, A2:2, \n", + "B0:?, B1:?, B2:?, \n", + "C0:?, C1:?, C2:?\n", + "\n", + "Now, I suggest the next team leader to find out their team's tally.\n", + "NEXT: B0\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mB0\u001b[0m (to chat_manager):\n", + "\n", + "As B0, I have 3 chocolates. Now, I will ask my team members about their count.\n", + "\n", + "B0:3, B1:?, B2:?, \n", + "A0:1, A1:2, A2:2, \n", + "C0:?, C1:?, C2:?\n", + "\n", + "NEXT: B1\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mB1\u001b[0m (to chat_manager):\n", + "\n", + "As B1, I have 1 chocolate.\n", + "\n", + "B0:3, B1:1, B2:?, \n", + "A0:1, A1:2, A2:2, \n", + "C0:?, C1:?, C2:?\n", + "\n", + "NEXT: B2\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mB2\u001b[0m (to chat_manager):\n", + "\n", + "As B2, I have 2 chocolates. So, the total chocolate count for team B is 6.\n", + "\n", + "B0:3, B1:1, B2:2, \n", + "A0:1, A1:2, A2:2, \n", + "C0:?, C1:?, C2:?\n", + "\n", + "Now, I suggest the next team leader to find out their team's tally.\n", + "NEXT: C0\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mB0\u001b[0m (to chat_manager):\n", + "\n", + "As C0, I have 4 chocolates. Now, I will ask my team members about their count.\n", + "\n", + "C0:4, C1:?, C2:?, \n", + "B0:3, B1:1, B2:2, \n", + "A0:1, A1:2, A2:2, \n", + "\n", + "NEXT: C1\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mC0\u001b[0m (to chat_manager):\n", + "\n", + "As C1, I have 2 chocolates.\n", + "\n", + "C0:4, C1:2, C2:?, \n", + "B0:3, B1:1, B2:2, \n", + "A0:1, A1:2, A2:2, \n", + "\n", + "NEXT: C2\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mC2\u001b[0m (to chat_manager):\n", + "\n", + "As C2, I have 1 chocolate. So, the total chocolate count for team C is 7.\n", + "\n", + "C0:4, C1:2, C2:1, \n", + "B0:3, B1:1, B2:2, \n", + "A0:1, A1:2, A2:2, \n", + "\n", + "Now, we have the total tally from all nine players. The sum of all three teams' tally is 18. \n", + "\n", + "TERMINATE.\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + }, + { + "data": { + "text/plain": [ + "ChatResult(chat_history=[{'content': '\\n There are 9 players in this game, split equally into Teams A, B, C. Therefore each team has 3 players, including the team leader.\\n The task is to find out the sum of chocolate count from all nine players. I will now start with my team.\\n NEXT: A1', 'role': 'assistant'}, {'content': 'As A1, I have 2 chocolates. \\n\\nA0:?, A1:2, A2:?, \\nB0:?, B1:?, B2:?, \\nC0:?, C1:?, C2:?\\n\\nNEXT: A2', 'name': 'A1', 'role': 'user'}, {'content': 'As A2, I have 2 chocolates.\\n\\nA0:?, A1:2, A2:2, \\nB0:?, B1:?, B2:?, \\nC0:?, C1:?, C2:?\\n\\nNEXT: A0', 'name': 'A2', 'role': 'user'}, {'content': \"As A0, I have 1 chocolate. So, the total chocolate count for team A is 5.\\n\\nA0:1, A1:2, A2:2, \\nB0:?, B1:?, B2:?, \\nC0:?, C1:?, C2:?\\n\\nNow, I suggest the next team leader to find out their team's tally.\\nNEXT: B0\", 'role': 'assistant'}, {'content': 'As B0, I have 3 chocolates. Now, I will ask my team members about their count.\\n\\nB0:3, B1:?, B2:?, \\nA0:1, A1:2, A2:2, \\nC0:?, C1:?, C2:?\\n\\nNEXT: B1', 'name': 'B0', 'role': 'user'}, {'content': 'As B1, I have 1 chocolate.\\n\\nB0:3, B1:1, B2:?, \\nA0:1, A1:2, A2:2, \\nC0:?, C1:?, C2:?\\n\\nNEXT: B2', 'name': 'B1', 'role': 'user'}, {'content': \"As B2, I have 2 chocolates. So, the total chocolate count for team B is 6.\\n\\nB0:3, B1:1, B2:2, \\nA0:1, A1:2, A2:2, \\nC0:?, C1:?, C2:?\\n\\nNow, I suggest the next team leader to find out their team's tally.\\nNEXT: C0\", 'name': 'B2', 'role': 'user'}, {'content': 'As C0, I have 4 chocolates. Now, I will ask my team members about their count.\\n\\nC0:4, C1:?, C2:?, \\nB0:3, B1:1, B2:2, \\nA0:1, A1:2, A2:2, \\n\\nNEXT: C1', 'name': 'B0', 'role': 'user'}, {'content': 'As C1, I have 2 chocolates.\\n\\nC0:4, C1:2, C2:?, \\nB0:3, B1:1, B2:2, \\nA0:1, A1:2, A2:2, \\n\\nNEXT: C2', 'name': 'C0', 'role': 'user'}, {'content': \"As C2, I have 1 chocolate. So, the total chocolate count for team C is 7.\\n\\nC0:4, C1:2, C2:1, \\nB0:3, B1:1, B2:2, \\nA0:1, A1:2, A2:2, \\n\\nNow, we have the total tally from all nine players. The sum of all three teams' tally is 18. \\n\\nTERMINATE.\", 'name': 'C2', 'role': 'user'}], summary=\"As C2, I have 1 chocolate. So, the total chocolate count for team C is 7.\\n\\nC0:4, C1:2, C2:1, \\nB0:3, B1:1, B2:2, \\nA0:1, A1:2, A2:2, \\n\\nNow, we have the total tally from all nine players. The sum of all three teams' tally is 18. \\n\\n.\", cost=({'total_cost': 0.48207, 'gpt-4-0613': {'cost': 0.48207, 'prompt_tokens': 15865, 'completion_tokens': 102, 'total_tokens': 15967}}, {'total_cost': 0.48207, 'gpt-4-0613': {'cost': 0.48207, 'prompt_tokens': 15865, 'completion_tokens': 102, 'total_tokens': 15967}}), human_input=[])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "group_chat = GroupChat(\n", + " agents=agents,\n", + " messages=[],\n", + " max_round=20,\n", + " allowed_or_disallowed_speaker_transitions=speaker_transitions_dict,\n", + " speaker_transitions_type=\"allowed\",\n", + ")\n", + "\n", + "\n", + "# Create the manager\n", + "manager = autogen.GroupChatManager(\n", + " groupchat=group_chat,\n", + " llm_config=config_list_gpt4,\n", + " code_execution_config=False,\n", + " is_termination_msg=is_termination_msg,\n", + ")\n", + "\n", + "\n", + "# Initiates the chat with Alice\n", + "agents[0].initiate_chat(\n", + " manager,\n", + " message=\"\"\"\n", + " There are 9 players in this game, split equally into Teams A, B, C. Therefore each team has 3 players, including the team leader.\n", + " The task is to find out the sum of chocolate count from all nine players. I will now start with my team.\n", + " NEXT: A1\"\"\",\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/test/test_notebook.py b/test/test_notebook.py index b879cfe9e37a..2fd6c8a65097 100644 --- a/test/test_notebook.py +++ b/test/test_notebook.py @@ -101,21 +101,12 @@ def _test_oai_chatgpt_gpt4(save=False): run_notebook("oai_chatgpt_gpt4.ipynb", save=save) -@pytest.mark.skipif( - skip or not sys.version.startswith("3.11"), - reason="do not run if openai is not installed or py!=3.11", -) -def _test_hierarchy_flow_using_select_speaker(save=False): - # TODO: recover this test after rewriting after the new group chat api - run_notebook("agentchat_hierarchy_flow_using_select_speaker.ipynb", save=save) - - @pytest.mark.skipif( skip or not sys.version.startswith("3.12"), reason="do not run if openai is not installed or py!=3.12", ) -def test_graph_modelling_language_using_select_speaker(save=False): - run_notebook("agentchat_graph_modelling_language_using_select_speaker.ipynb", save=save) +def test_agentchat_groupchat_finite_state_machine(save=False): + run_notebook("agentchat_groupchat_finite_state_machine.ipynb", save=save) @pytest.mark.skipif( diff --git a/website/blog/2024-02-11-FSM-GroupChat/img/FSM_logic.png b/website/blog/2024-02-11-FSM-GroupChat/img/FSM_logic.png new file mode 100644 index 0000000000000000000000000000000000000000..66abd3c677baa94481c78b94242edc7d8071eee5 GIT binary patch literal 28311 zcmc$`by$>d+b%kYfQo>MN=YaUN{2KSEhya}DGVjuY13T-N=kRffJn#45JQLLP$Muj z!>oJ!t#^IzUf)`4?_=-pIJWz$r;ju}ziiHs`D%^^9q!XwS!LybOxc!g*rNIE=&wHz1T+~#+Mj+R&-=xO>jeZnF 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z5Z~OL@qA)7CS=vgJsEA#Xgjp!LzoiCAT~gs+Bihu1`akI1U&WyV+4XnRC?1@vs-Z^ zoLHIIAkAhq#7D&YXXNfH^!FDoqFRsP3Paj$Mi}HTcr@5gND>(>oe^`pFZR#;0SG9F zbys-3G^U2{m!8>XY*`a;*gxUBdHs|_ROu*?xynv8D5XPtjn<-XoCnoX(o61mS9GEp zkU-Pk9n@pV%`Mb>A#5WXUd{35*n3${Yt#!z)wc`Lc+y;Q;RmxO!K1WMv`OiSwKRq& zx!(KUYF6#VLTz%|l`%g%wAcRtwyBbo2{_|k56JXKnNtPPBV2E!=y41oo2U8nixh$C z0|)uAK-Oh;P*QrDaoJAnPEyw-06r-|J7otUfSc2&pUlLnwrV*ZUmQRJ7o!nLX;BDh z;mnhG#nJ^MDK%-y(q-I{aR}cFC|Q?Z^;O4`jDicxI*m-HsUA9r zE`wZx^B=xx{}&(o|MXQ-7EXG+&%Dj@ZDj~ciZ`hVZcH^>*QyAcw}MaL)q#w5Ln$iw z@g{!mmIbrg=gFinite State Machine (FSM) Group Chat allows the user to constrain agent transitions.

+ + +## TL;DR +Recently, FSM Group Chat is released that allows the user to input a transition graph to constrain agent transitions. This is useful as the number of agents increases because the number of transition pairs (N choose 2 combinations) increases exponentially increasing the risk of sub-optimal transitions, which leads to wastage of tokens and/or poor outcomes. + +## Possible use-cases for transition graph +1. One-pass workflow, i.e., we want each agent to only have one pass at the problem, Agent A -> B -> C. +2. Decision tree flow, like a decision tree, we start with a root node (agent), and flow down the decision tree with agents being nodes. For example, if the query is a SQL query, hand over to the SQL agent, else if the query is a RAG query, hand over to the RAG agent. +3. Sequential Team Ops. Suppose we have a team of 3 developer agents, each responsible for a different GitHub repo. We also have a team of business analyst that discuss and debate the overall goal of the user. We could have the manager agent of the developer team speak to the manager agent of the business analysis team. That way, the discussions are more focused team-wise, and better outcomes can be expected. + +Note that we are not enforcing a directed acyclic graph; the user can specify the graph to be acyclic, but cyclic workflows can also be useful to iteratively work on a problem, and layering additional analysis onto the solution. + + +## Usage Guide +We have added two parameters `allowed_or_disallowed_speaker_transitions` and `speaker_transitions_type`. +- `allowed_or_disallowed_speaker_transitions`: is a dictionary with the type expectation of `{Agent: [Agent]}`. The key refers to the source agent, while the value(s) in the list refers to the target agent(s). If none, a fully connection graph is assumed. +- `speaker_transitions_type`: is a string with the type expectation of string, and specifically, one of ["allowed", "disallowed"]. We wanted the user to be able to supply a dictionary of allowed or disallowed transitions to improve the ease of use. In the code base, we would invert the disallowed transition into a allowed transition dictionary `allowed_speaker_transitions_dict`. + + +### Application of the FSM Feature + +A quick demonstration of how to initiate a FSM-based `GroupChat` in the `AutoGen` framework. In this demonstration, if we consider each agent as a state, and each agent speaks according to certain conditions. For example, User always initiates the task first, followed by Planner creating a plan. Then Engineer and Executor work alternately, with Critic intervening when necessary, and after Critic, only Planner should revise additional plans. Each state can only exist at a time, and there are transition conditions between states. Therefore, GroupChat can be well abstracted as a Finite-State Machine (FSM). + +![visualization](img/FSM_logic.png) + + +### Usage + +0. Pre-requisites +```bash +pip install autogen[graph] +``` + +1. Import dependencies + + ```python + from autogen.agentchat import GroupChat, AssistantAgent, UserProxyAgent, GroupChatManager + from autogen.oai.openai_utils import config_list_from_dotenv + ``` +2. Configure LLM parameters + + ```python + # Please feel free to change it as you wish + config_list = config_list_from_dotenv( + dotenv_file_path='.env', + model_api_key_map={'gpt-4-1106-preview':'OPENAI_API_KEY'}, + filter_dict={ + "model": { + "gpt-4-1106-preview" + } + } + ) + + gpt_config = { + "cache_seed": None, + "temperature": 0, + "config_list": config_list, + "timeout": 100, + } + ``` + +3. Define the task + + ```python + # describe the task + task = """Add 1 to the number output by the previous role. If the previous number is 20, output "TERMINATE".""" + ``` + +4. Define agents + + ```python + # agents configuration + engineer = AssistantAgent( + name="Engineer", + llm_config=gpt_config, + system_message=task, + description="""I am **ONLY** allowed to speak **immediately** after `Planner`, `Critic` and `Executor`. + If the last number mentioned by `Critic` is not a multiple of 5, the next speaker must be `Engineer`. + """ + ) + + planner = AssistantAgent( + name="Planner", + system_message=task, + llm_config=gpt_config, + description="""I am **ONLY** allowed to speak **immediately** after `User` or `Critic`. + If the last number mentioned by `Critic` is a multiple of 5, the next speaker must be `Planner`. + """ + ) + + executor = AssistantAgent( + name="Executor", + system_message=task, + is_termination_msg=lambda x: x.get("content", "") and x.get("content", "").rstrip().endswith("FINISH"), + llm_config=gpt_config, + description="""I am **ONLY** allowed to speak **immediately** after `Engineer`. + If the last number mentioned by `Engineer` is a multiple of 3, the next speaker can only be `Executor`. + """ + ) + + critic = AssistantAgent( + name="Critic", + system_message=task, + llm_config=gpt_config, + description="""I am **ONLY** allowed to speak **immediately** after `Engineer`. + If the last number mentioned by `Engineer` is not a multiple of 3, the next speaker can only be `Critic`. + """ + ) + + user_proxy = UserProxyAgent( + name="User", + system_message=task, + code_execution_config=False, + human_input_mode="NEVER", + llm_config=False, + description=""" + Never select me as a speaker. + """ + ) + ``` + + 1. Here, I have configured the `system_messages` as "task" because every agent should know what it needs to do. In this example, each agent has the same task, which is to count in sequence. + 2. **The most important point is the `description` parameter, where I have used natural language to describe the transition conditions of the FSM. Because the manager knows which agents are available next based on the constraints of the graph, I describe in the `description` field of each candidate agent when it can speak, effectively describing the transition conditions in the FSM.** + +5. Define the graph + + ```python + graph_dict = {} + graph_dict[user_proxy] = [planner] + graph_dict[planner] = [engineer] + graph_dict[engineer] = [critic, executor] + graph_dict[critic] = [engineer, planner] + graph_dict[executor] = [engineer] + ``` + + 1. **The graph here and the transition conditions mentioned above together form a complete FSM. Both are essential and cannot be missing.** + 2. You can visualize it as you wish, which is shown as follows + + ![visualization](img/FSM_of_multi-agents.png) + +6. Define a `GroupChat` and a `GroupChatManager` + + ```python + agents = [user_proxy, engineer, planner, executor, critic] + + # create the groupchat + group_chat = GroupChat(agents=agents, messages=[], max_round=25, allowed_or_disallowed_speaker_transitions=graph_dict, allow_repeat_speaker=None, speaker_transitions_type="allowed") + + # create the manager + manager = GroupChatManager( + groupchat=group_chat, + llm_config=gpt_config, + is_termination_msg=lambda x: x.get("content", "") and x.get("content", "").rstrip().endswith("TERMINATE"), + code_execution_config=False, + ) + ``` + +7. Initiate the chat + + ```python + # initiate the task + user_proxy.initiate_chat( + manager, + message="1", + clear_history=True + ) + ``` + +8. You may get the following output(I deleted the ignorable warning): + + ``` + User (to chat_manager): + + 1 + + -------------------------------------------------------------------------------- + Planner (to chat_manager): + + 2 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 3 + + -------------------------------------------------------------------------------- + Executor (to chat_manager): + + 4 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 5 + + -------------------------------------------------------------------------------- + Critic (to chat_manager): + + 6 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 7 + + -------------------------------------------------------------------------------- + Critic (to chat_manager): + + 8 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 9 + + -------------------------------------------------------------------------------- + Executor (to chat_manager): + + 10 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 11 + + -------------------------------------------------------------------------------- + Critic (to chat_manager): + + 12 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 13 + + -------------------------------------------------------------------------------- + Critic (to chat_manager): + + 14 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 15 + + -------------------------------------------------------------------------------- + Executor (to chat_manager): + + 16 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 17 + + -------------------------------------------------------------------------------- + Critic (to chat_manager): + + 18 + + -------------------------------------------------------------------------------- + Engineer (to chat_manager): + + 19 + + -------------------------------------------------------------------------------- + Critic (to chat_manager): + + 20 + + -------------------------------------------------------------------------------- + Planner (to chat_manager): + + TERMINATE + ``` + +## Notebook examples +More examples can be found in the [notebook](https://microsoft.github.io/autogen/docs/notebooks/agentchat_groupchat_finite_state_machine/). The notebook includes more examples of possible transition paths such as (1) hub and spoke, (2) sequential team operations, and (3) think aloud and debate. It also uses the function `visualize_speaker_transitions_dict` from `autogen.graph_utils` to visualize the various graphs. diff --git a/website/blog/authors.yml b/website/blog/authors.yml index 7085702dfca9..7f6c2cbdb534 100644 --- a/website/blog/authors.yml +++ b/website/blog/authors.yml @@ -104,4 +104,16 @@ olgavrou: name: Olga Vrousgou title: Senior Software Engineer at Microsoft Research url: https://github.com/olgavrou/ - image_url: https://github.com/olgavrou.png + image_url: https://github.com/olgavrou.png + +joshkyh: + name: Joshua Kim + title: AI Freelancer at SpectData + url: https://github.com/joshkyh/ + image_url: https://github.com/joshkyh.png + +freedeaths: + name: Yishen Sun + title: Data Scientist at PingCAP LAB + url: https://github.com/freedeaths/ + image_url: https://github.com/freedeaths.png