From ca2e0b889e13a13e3d4c4c737fc5899c4919ff62 Mon Sep 17 00:00:00 2001 From: Shruti Patel Date: Sat, 21 Oct 2023 19:56:46 -0400 Subject: [PATCH] Update agentchat_MathChat.ipynb (#341) --- notebook/agentchat_MathChat.ipynb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/notebook/agentchat_MathChat.ipynb b/notebook/agentchat_MathChat.ipynb index 133db1d44af7..9dd90fb0635e 100644 --- a/notebook/agentchat_MathChat.ipynb +++ b/notebook/agentchat_MathChat.ipynb @@ -17,7 +17,7 @@ "\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. Please find documentation about this feature [here](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat).\n", "\n", - "MathChat is an experimental convesational framework for math problem solving. In this notebook, we demonstrate how to use MathChat to solve math problems. MathChat uses the `AssistantAgent` and `MathUserProxyAgent`, which is similar to the usage of `AssistantAgent` and `UserProxyAgent` in other notebooks (e.g., [Automated Task Solving with Code Generation, Execution & Debugging](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_auto_feedback_from_code_execution.ipynb)). Essentially, `MathUserProxyAgent` implements a different auto reply mechanism corresponding to the MathChat prompts. You can find more details in the paper [An Empirical Study on Challenging Math Problem Solving with GPT-4](https://arxiv.org/abs/2306.01337) or the [blogpost](https://microsoft.github.io/autogen/blog/2023/06/28/MathChat).\n", + "MathChat is an experimental conversational framework for math problem solving. In this notebook, we demonstrate how to use MathChat to solve math problems. MathChat uses the `AssistantAgent` and `MathUserProxyAgent`, which is similar to the usage of `AssistantAgent` and `UserProxyAgent` in other notebooks (e.g., [Automated Task Solving with Code Generation, Execution & Debugging](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_auto_feedback_from_code_execution.ipynb)). Essentially, `MathUserProxyAgent` implements a different auto reply mechanism corresponding to the MathChat prompts. You can find more details in the paper [An Empirical Study on Challenging Math Problem Solving with GPT-4](https://arxiv.org/abs/2306.01337) or the [blogpost](https://microsoft.github.io/autogen/blog/2023/06/28/MathChat).\n", "\n", "## Requirements\n", "\n", @@ -235,7 +235,7 @@ "------------------------------------\n", "### Using other prompts\n", "\n", - "MathChat allows different prompts that instruct assistant to solve the problem.\n", + "MathChat allows different prompts that instruct the assistant to solve the problem.\n", "\n", "Check out `MathUserProxyAgent.generate_init_message(problem, prompt_type='default', customized_prompt=None)`:\n", "- You may choose from `['default', 'python', 'two_tools']` for parameter `prompt_type`. We include two more prompts in the paper: \n", @@ -292,7 +292,7 @@ "metadata": {}, "outputs": [], "source": [ - "# The wolfram alpha appid is required for this example (the assistant may choose to query Wolfram Alpha).\n", + "# The wolfram alpha app id is required for this example (the assistant may choose to query Wolfram Alpha).\n", "import os\n", "if \"WOLFRAM_ALPHA_APPID\" not in os.environ:\n", " os.environ[\"WOLFRAM_ALPHA_APPID\"] = open(\"wolfram.txt\").read().strip()\n",