From 1247af9143ac2a363854a8e6e64297cd8c8ad6c1 Mon Sep 17 00:00:00 2001
From: Jianxin Ma <majx13fromthu@gmail.com>
Date: Thu, 10 Aug 2023 15:32:31 +0800
Subject: [PATCH] Add files via upload

---
 examples/langchain_tooluse.ipynb | 105 ++++++++++++++++++-------------
 1 file changed, 60 insertions(+), 45 deletions(-)

diff --git a/examples/langchain_tooluse.ipynb b/examples/langchain_tooluse.ipynb
index 0efc608..de91bce 100644
--- a/examples/langchain_tooluse.ipynb
+++ b/examples/langchain_tooluse.ipynb
@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "e21c6728",
    "metadata": {},
    "outputs": [],
@@ -65,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 2,
    "id": "07e49b98-9d6c-41f2-9b18-f043f2d13e1a",
    "metadata": {},
    "outputs": [],
@@ -124,7 +124,7 @@
     "        'parameters': [{\n",
     "            \"name\": \"query\",\n",
     "            \"type\": \"string\",\n",
-    "            \"description\": \"search query of Wolfram Alpha\",\n",
+    "            \"description\": \"the problem to solved by Wolfram Alpha\",\n",
     "            'required': True\n",
     "        }], \n",
     "        'tool_api': tool_wrapper_for_qwen(WolframAlpha)\n",
@@ -277,36 +277,55 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "The model is automatically converting to bf16 for faster inference. If you want to disable the automatic precision, please manually add bf16/fp16/fp32=True to \"AutoModelForCausalLM.from_pretrained\".\n",
-      "Try importing flash-attention for faster inference...\n",
-      "Warning: import flash_attn rotary fail, please install FlashAttention rotary to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/rotary\n",
-      "Warning: import flash_attn rms_norm fail, please install FlashAttention layer_norm to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/layer_norm\n",
-      "Warning: import flash_attn fail, please install FlashAttention to get higher efficiency https://github.com/Dao-AILab/flash-attention\n"
+      "A new version of the following files was downloaded from https://huggingface.co/Qwen/Qwen-7B-Chat:\n",
+      "- tokenization_qwen.py\n",
+      ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n",
+      "A new version of the following files was downloaded from https://huggingface.co/Qwen/Qwen-7B-Chat:\n",
+      "- configuration_qwen.py\n",
+      ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n",
+      "A new version of the following files was downloaded from https://huggingface.co/Qwen/Qwen-7B-Chat:\n",
+      "- qwen_generation_utils.py\n",
+      ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n",
+      "A new version of the following files was downloaded from https://huggingface.co/Qwen/Qwen-7B-Chat:\n",
+      "- modeling_qwen.py\n",
+      "- qwen_generation_utils.py\n",
+      ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ed76951f2662402c9932f0b27548a47b",
+       "model_id": "23435445dded44d6951aa6a7b771a963",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Loading checkpoint shards:   0%|          | 0/8 [00:00<?, ?it/s]"
+       "Downloading shards:   0%|          | 0/8 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "The model is automatically converting to bf16 for faster inference. If you want to disable the automatic precision, please manually add bf16/fp16/fp32=True to \"AutoModelForCausalLM.from_pretrained\".\n",
+      "Try importing flash-attention for faster inference...\n",
+      "Warning: import flash_attn rotary fail, please install FlashAttention rotary to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/rotary\n",
+      "Warning: import flash_attn rms_norm fail, please install FlashAttention layer_norm to get higher efficiency https://github.com/Dao-AILab/flash-attention/tree/main/csrc/layer_norm\n",
+      "Warning: import flash_attn fail, please install FlashAttention to get higher efficiency https://github.com/Dao-AILab/flash-attention\n"
+     ]
+    },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d448bf9d60dd42648e60918276c0729e",
+       "model_id": "728a1c13c2884291ade4cb4a1edfaaf2",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Downloading (…)neration_config.json:   0%|          | 0.00/194 [00:00<?, ?B/s]"
+       "Loading checkpoint shards:   0%|          | 0/8 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
@@ -491,7 +510,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 9,
    "id": "6dc38a34",
    "metadata": {
     "collapsed": false,
@@ -509,7 +528,7 @@
       "\n",
       "Search: Call this tool to interact with the google search API. What is the google search API useful for? useful for when you need to answer questions about current events. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"search query of google\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
-      "Math: Call this tool to interact with the Wolfram Alpha API. What is the Wolfram Alpha API useful for? Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"search query of Wolfram Alpha\", \"required\": true}] Format the arguments as a JSON object.\n",
+      "Math: Call this tool to interact with the Wolfram Alpha API. What is the Wolfram Alpha API useful for? Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"the problem to solved by Wolfram Alpha\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
       "Arxiv: Call this tool to interact with the arxiv API. What is the arxiv API useful for? A wrapper around Arxiv.org Useful for when you need to answer questions about Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance, Statistics, Electrical Engineering, and Economics from scientific articles on arxiv.org. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"the document id of arxiv to search\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
@@ -529,18 +548,18 @@
       "Begin!\n",
       "\n",
       "Question: 加拿大2022年的人口数量有多少？\n",
-      "\u001b[32mThought: 我应该使用搜索工具帮助我完成任务。search api能完成搜索的任务。\n",
+      "\u001B[32mThought: 我应该使用搜索工具帮助我完成任务。search api能完成搜索的任务。\n",
       "Action: Search\n",
       "Action Input: {\"query\": \"加拿大 2022年人口数量\"}\n",
-      "Observation:\u001b[0m\u001b[34m 中新社多伦多3月22日电(记者余瑞冬)加拿大统计局3月22日公布的人口统计数据显示，截至今年1月1日，该国估算总人口约为3956.62万人，且2022年的人口增长数创纪录地突破100万人。 加统计局估算，该国人口在2022年增长105.011万人，年增长2.7%，创1957年以来最大增幅。\u001b[0m\n",
-      "\u001b[32mThought: I now know the final answer.\n",
-      "Final Answer: 加拿大2022年的人口数量约为3956.62万人。\u001b[0m\n",
+      "Observation:\u001B[0m\u001B[34m 中新社多伦多3月22日电(记者余瑞冬)加拿大统计局3月22日公布的人口统计数据显示，截至今年1月1日，该国估算总人口约为3956.62万人，且2022年的人口增长数创纪录地突破100万人。 加统计局估算，该国人口在2022年增长105.011万人，年增长2.7%，创1957年以来最大增幅。\u001B[0m\n",
+      "\u001B[32mThought: I now know the final answer.\n",
+      "Final Answer: 加拿大2022年的人口数量约为3956.62万人。\u001B[0m\n",
       "==========\n",
       "Answer the following questions as best you can. You have access to the following tools:\n",
       "\n",
       "Search: Call this tool to interact with the google search API. What is the google search API useful for? useful for when you need to answer questions about current events. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"search query of google\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
-      "Math: Call this tool to interact with the Wolfram Alpha API. What is the Wolfram Alpha API useful for? Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"search query of Wolfram Alpha\", \"required\": true}] Format the arguments as a JSON object.\n",
+      "Math: Call this tool to interact with the Wolfram Alpha API. What is the Wolfram Alpha API useful for? Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"the problem to solved by Wolfram Alpha\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
       "Arxiv: Call this tool to interact with the arxiv API. What is the arxiv API useful for? A wrapper around Arxiv.org Useful for when you need to answer questions about Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance, Statistics, Electrical Engineering, and Economics from scientific articles on arxiv.org. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"the document id of arxiv to search\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
@@ -560,26 +579,19 @@
       "Begin!\n",
       "\n",
       "Question: 求解方程 2x+5 = -3x + 7\n",
-      "\u001b[32mThought: 提供的工具对回答该问题帮助较小，我将不使用工具直接作答。\n",
-      "Final Answer: 为了解这个方程，我们需要对方程进行变换，以便找到x的值。首先，我们可以将方程中的2x移到右边，得到：\n",
-      "\n",
-      "2x - 3x = 7 - 5\n",
-      "\n",
-      "然后，我们可以简化这个方程，得到：\n",
-      "\n",
-      "-1x = 2\n",
-      "\n",
-      "接下来，我们将方程两边除以-1，以求得x的值：\n",
-      "\n",
-      "x = -2\n",
-      "\n",
-      "所以，方程2x + 5 = -3x + 7的解为x = -2。\u001b[0m\n",
+      "\u001B[32mThought: 我应该使用数学工具帮助我完成任务。Wolfram Alpha API应该能完成这项任务。\n",
+      "Action: Math\n",
+      "Action Input: {\"query\": \"2x+5 = -3x + 7\"}\n",
+      "Observation:\u001B[0m\u001B[34m Assumption: 2 x + 5 = -3 x + 7 \n",
+      "Answer: x = 2/5\u001B[0m\n",
+      "\u001B[32mThought: I now know the final answer.\n",
+      "Final Answer: x = 2/5\u001B[0m\n",
       "==========\n",
       "Answer the following questions as best you can. You have access to the following tools:\n",
       "\n",
       "Search: Call this tool to interact with the google search API. What is the google search API useful for? useful for when you need to answer questions about current events. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"search query of google\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
-      "Math: Call this tool to interact with the Wolfram Alpha API. What is the Wolfram Alpha API useful for? Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"search query of Wolfram Alpha\", \"required\": true}] Format the arguments as a JSON object.\n",
+      "Math: Call this tool to interact with the Wolfram Alpha API. What is the Wolfram Alpha API useful for? Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"the problem to solved by Wolfram Alpha\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
       "Arxiv: Call this tool to interact with the arxiv API. What is the arxiv API useful for? A wrapper around Arxiv.org Useful for when you need to answer questions about Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance, Statistics, Electrical Engineering, and Economics from scientific articles on arxiv.org. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"the document id of arxiv to search\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
@@ -599,10 +611,10 @@
       "Begin!\n",
       "\n",
       "Question: 编号是1605.08386的论文讲了些什么？\n",
-      "\u001b[32mThought: 我需要使用Arxiv API来搜索论文\n",
+      "\u001B[32mThought: 我需要使用Arxiv API来搜索这篇论文。\n",
       "Action: Arxiv\n",
       "Action Input: {\"query\": \"1605.08386\"}\n",
-      "Observation:\u001b[0m\u001b[34m Published: 2016-05-26\n",
+      "Observation:\u001B[0m\u001B[34m Published: 2016-05-26\n",
       "Title: Heat-bath random walks with Markov bases\n",
       "Authors: Caprice Stanley, Tobias Windisch\n",
       "Summary: Graphs on lattice points are studied whose edges come from a finite set of\n",
@@ -611,14 +623,15 @@
       "then study the mixing behaviour of heat-bath random walks on these graphs. We\n",
       "also state explicit conditions on the set of moves so that the heat-bath random\n",
       "walk, a generalization of the Glauber dynamics, is an expander in fixed\n",
-      "dimension.\u001b[0m\n",
-      "\u001b[32mThought: I now know the final answer.\n",
-      "Final Answer: 论文编号为1605.08386的论文主要研究了热浴随机行走的性质。论文中，作者通过考虑有限个允许的任意长度的移动，研究了在有限矩阵的纤维上的图的直径的上界。此外，作者还研究了热浴随机行走的混合行为，并给出了在固定维度下，热浴随机行走是一种扩张的条件。\u001b[0m\n",
+      "dimension.\u001B[0m\n",
+      "\u001B[32mThought: I now know the final answer.\n",
+      "Final Answer: 这篇论文的题目是《热浴随机游走的马尔可夫基》，作者是Caprice Stanley和Tobias Windisch。摘要中提到，该论文研究了在有限的允许移动集合中，由任意长度的边构成的图的边。我们证明了这些图在固定整数矩阵纤维上的直径可以被一个常数所限制。然后，我们研究了热浴随机游走在这类图上的混合行为。我们还给出了一个明确的条件，使得热浴随机游走（一个Glauber动力学的推广）在固定维度下是一个扩张。\u001B[0m\n",
+      "==========\n",
       "Answer the following questions as best you can. You have access to the following tools:\n",
       "\n",
       "Search: Call this tool to interact with the google search API. What is the google search API useful for? useful for when you need to answer questions about current events. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"search query of google\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
-      "Math: Call this tool to interact with the Wolfram Alpha API. What is the Wolfram Alpha API useful for? Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"search query of Wolfram Alpha\", \"required\": true}] Format the arguments as a JSON object.\n",
+      "Math: Call this tool to interact with the Wolfram Alpha API. What is the Wolfram Alpha API useful for? Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"the problem to solved by Wolfram Alpha\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
       "Arxiv: Call this tool to interact with the arxiv API. What is the arxiv API useful for? A wrapper around Arxiv.org Useful for when you need to answer questions about Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance, Statistics, Electrical Engineering, and Economics from scientific articles on arxiv.org. Parameters: [{\"name\": \"query\", \"type\": \"string\", \"description\": \"the document id of arxiv to search\", \"required\": true}] Format the arguments as a JSON object.\n",
       "\n",
@@ -638,16 +651,17 @@
       "Begin!\n",
       "\n",
       "Question: 使用python对下面的列表进行排序： [2, 4135, 523, 2, 3]\n",
-      "\u001b[32mThought: 我应该使用python API来执行python命令。\n",
+      "\u001B[32mThought: 我应该使用python API来执行python命令。\n",
       "Action: python\n",
       "Action Input: {\"query\": \"sorted([2, 4135, 523, 2, 3])\"}\n",
-      "Observation:\u001b[0m\u001b[34m [2, 2, 3, 523, 4135]\u001b[0m\n",
-      "\u001b[32mThought: I now know the final answer.\n",
-      "Final Answer: 使用python对给定的列表进行排序，结果为 [2, 2, 3, 523, 4135]。\u001b[0m\n"
+      "Observation:\u001B[0m\u001B[34m [2, 2, 3, 523, 4135]\u001B[0m\n",
+      "\u001B[32mThought: I now know the final answer.\n",
+      "Final Answer: 使用python对给定的列表进行排序，结果为 [2, 2, 3, 523, 4135]。\u001B[0m\n"
      ]
     }
    ],
    "source": [
+    "# 请尽可能控制备选工具数量\n",
     "query = \"加拿大2022年的人口数量有多少？\" # 所提问题\n",
     "choose_tools = TOOLS # 选择备选工具\n",
     "print(\"=\" * 10)\n",
@@ -665,6 +679,7 @@
     "\n",
     "query =\"使用python对下面的列表进行排序： [2, 4135, 523, 2, 3]\"\n",
     "choose_tools = TOOLS # 选择备选工具\n",
+    "print(\"=\" * 10)\n",
     "main(query, choose_tools)"
    ]
   }
@@ -685,7 +700,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.9.16"
   }
  },
  "nbformat": 4,