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147 lines
6.0 KiB
Plaintext
147 lines
6.0 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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"## RAG OpenAI Assistants in AutoGen\n",
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"\n",
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"This notebook shows an example of the [`GPTAssistantAgent`](https://github.com/microsoft/autogen/blob/main/autogen/agentchat/contrib/gpt_assistant_agent.py#L16C43-L16C43) with retrieval augmented generation. `GPTAssistantAgent` is an experimental AutoGen agent class that leverages the [OpenAI Assistant API](https://platform.openai.com/docs/assistants/overview) for conversational capabilities, working with\n",
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"`UserProxyAgent` in AutoGen."
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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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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"assistant_id was None, creating a new assistant\n"
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]
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},
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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[33muser_proxy\u001b[0m (to assistant):\n",
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"\n",
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"What is the name of the class of agents I gave you?\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33massistant\u001b[0m (to user_proxy):\n",
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"\n",
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"The class of agents provided in the file is called `ConversableAgent`.\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33muser_proxy\u001b[0m (to assistant):\n",
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"\n",
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"What does it do?\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33massistant\u001b[0m (to user_proxy):\n",
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"\n",
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"The `ConversableAgent` class is designed as a generic conversable agent that can be configured to act either as an assistant or user proxy. When it receives a message, it automatically generates and sends a reply unless the message is a termination message. It features a method to initiate a chat with another agent and can have its auto-reply behavior adjusted by overriding the `generate_reply` method.\n",
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"\n",
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"Here are some specific functionalities and mechanisms included in the `ConversableAgent` class:\n",
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"\n",
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"- It can process received messages and decide whether or not a reply is necessary or requested.\n",
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"- It can reset consecutive auto-reply counters and clear chat history when starting a new conversation.\n",
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"- It allows initiating chats either synchronously or asynchronously with the ability to pass context information and control chattiness.\n",
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"- It has the ability to register reply functions with specific triggers and order them based on preference.\n",
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"- The class supports setting a maximum number of consecutive auto-replies, after which it can prompt for human input based on configured criteria (e.g., always, on termination, or never).\n",
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"- The auto-reply trigger mechanism can be finely controlled by associating reply functions with triggers such as instances of particular classes, specific strings, or custom callable conditions.\n",
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"\n",
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"This class provides an extensible framework for creating bots or agents that can interact in a chat-like context, with custom behavior that developers can tailor to specific applications.\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n",
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"\u001b[31m\n",
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">>>>>>>> USING AUTO REPLY...\u001b[0m\n",
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"\u001b[33muser_proxy\u001b[0m (to assistant):\n",
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"\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33massistant\u001b[0m (to user_proxy):\n",
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"\n",
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"It seems that your request was incomplete. Could you please provide more information or clarify your request?\n",
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"\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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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Permanently deleting assistant...\n"
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]
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}
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],
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"source": [
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"import logging\n",
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"import os\n",
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"\n",
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"from autogen import UserProxyAgent, config_list_from_json\n",
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"from autogen.agentchat.contrib.gpt_assistant_agent import GPTAssistantAgent\n",
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"\n",
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"logger = logging.getLogger(__name__)\n",
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"logger.setLevel(logging.WARNING)\n",
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"\n",
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"assistant_id = os.environ.get(\"ASSISTANT_ID\", None)\n",
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"\n",
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"config_list = config_list_from_json(\"OAI_CONFIG_LIST\")\n",
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"llm_config = {\n",
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" \"config_list\": config_list,\n",
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" \"assistant_id\": assistant_id,\n",
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" \"tools\": [{\"type\": \"retrieval\"}],\n",
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" \"file_ids\": [\"file-CmlT0YKLB3ZCdHmslF9FOv69\"]\n",
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" # add id of an existing file in your openai account\n",
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" # in this case I added the implementation of conversable_agent.py\n",
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"}\n",
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"\n",
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"gpt_assistant = GPTAssistantAgent(\n",
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" name=\"assistant\", instructions=\"You are adapt at question answering\", llm_config=llm_config\n",
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")\n",
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"\n",
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"user_proxy = UserProxyAgent(\n",
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" name=\"user_proxy\",\n",
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" code_execution_config=False,\n",
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" is_termination_msg=lambda msg: \"TERMINATE\" in msg[\"content\"],\n",
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" human_input_mode=\"ALWAYS\",\n",
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")\n",
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"user_proxy.initiate_chat(gpt_assistant, message=\"What is the name of the class of agents I gave you?\")\n",
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"\n",
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"gpt_assistant.delete_assistant()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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