add implementation for paper "A Multi-LLM Agent"

.dev_scripts/dockerci.sh

@@ -13,4 +13,4 @@ cp tests/samples/* "${CODE_INTERPRETER_WORK_DIR}/"
 ls  "${CODE_INTERPRETER_WORK_DIR}"
 
 # run ci
-pytest
+pytest tests

demo/alpha_umi/run_deploy.sh

@@ -0,0 +1,24 @@
+export PYTHONPATH=./
+
+export VLLM_USE_MODELSCOPE=True  
+python -m vllm.entrypoints.openai.api_server \
+ --model=iic/alpha-umi-planner-7b \
+ --revision=v1.0.0 --trust-remote-code \
+ --port 8090 \
+ --dtype float16 \
+ --gpu-memory-utilization 0.3 > planner.log &
+
+python -m vllm.entrypoints.openai.api_server \
+ --model=iic/alpha-umi-caller-7b \
+ --revision=v1.0.0 --trust-remote-code \
+ --port 8091 \
+ --dtype float16 \
+ --gpu-memory-utilization 0.3 > caller.log &
+
+python -m vllm.entrypoints.openai.api_server \
+ --model=iic/alpha-umi-summarizer-7b \
+ --revision=v1.0.0 --trust-remote-code \
+ --port 8092 \
+ --dtype float16 \
+ --gpu-memory-utilization 0.3 > summarizer.log &
+

demo/alpha_umi/run_test.sh

@@ -0,0 +1,5 @@
+export PYTHONPATH=./
+export RAPID_API_TOKEN="1010919056msh03dc548f7c5ff35p1e0988jsndc80beff3fa8"
+export MODELSCOPE_API_TOKEN="b9144b02-b94c-4c62-956d-a4c8228854e9"
+
+python demo/alpha_umi/test_alpha_umi.py

demo/alpha_umi/test_alpha_umi.py

@@ -0,0 +1,53 @@
+import os
+import time
+
+from modelscope_agent.agents.alpha_umi import AlphaUmi
+from openai import OpenAI
+
+llm_configs = {
+    'planner_llm_config': {
+        'model': 'iic/alpha-umi-planner-7b',
+        'model_server': 'openai',
+        'api_base': 'http://localhost:8090/v1',
+        'is_chat': False
+    },
+    'caller_llm_config': {
+        'model': 'iic/alpha-umi-caller-7b',
+        'model_server': 'openai',
+        'api_base': 'http://localhost:8091/v1',
+        'is_chat': False
+    },
+    'summarizer_llm_config': {
+        'model': 'iic/alpha-umi-summarizer-7b',
+        'model_server': 'openai',
+        'api_base': 'http://localhost:8092/v1',
+        'is_chat': False
+    },
+}
+
+
+def test_alpha_umi():
+    function_list = [
+        "get_data_fact_for_numbers", "get_math_fact_for_numbers",
+        "get_year_fact_for_numbers", "listquotes_for_current_exchange",
+        "exchange_for_current_exchange"
+    ]
+
+    bot = AlphaUmi(
+        function_list=function_list,
+        llm_planner=llm_configs['planner_llm_config'],
+        llm_caller=llm_configs['caller_llm_config'],
+        llm_summarizer=llm_configs['summarizer_llm_config'],
+    )
+
+    response = bot.run('how many CNY can I exchange for 1 US dollar? \
+        also, give me a special property about the number of CNY after exchange'
+                       )
+
+    for chunk in response:
+        print(chunk)
+
+
+if __name__ == '__main__':
+
+    test_alpha_umi()

demo/demo_alpha_umi.ipynb

@@ -0,0 +1,254 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "45d56c67-7439-4264-912a-c0b4895cac63",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-09-04T14:17:41.716630Z",
+     "iopub.status.busy": "2023-09-04T14:17:41.716258Z",
+     "iopub.status.idle": "2023-09-04T14:17:42.097933Z",
+     "shell.execute_reply": "2023-09-04T14:17:42.097255Z",
+     "shell.execute_reply.started": "2023-09-04T14:17:41.716610Z"
+    }
+   },
+   "source": [
+    "### clone代码"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3851d799-7162-4e73-acab-3c13cb1e43bd",
+   "metadata": {
+    "ExecutionIndicator": {
+     "show": true
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!git clone https://github.com/modelscope/modelscope-agent.git"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f71e64d0-f967-4244-98ba-4e5bc4530883",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-09-04T14:17:41.716630Z",
+     "iopub.status.busy": "2023-09-04T14:17:41.716258Z",
+     "iopub.status.idle": "2023-09-04T14:17:42.097933Z",
+     "shell.execute_reply": "2023-09-04T14:17:42.097255Z",
+     "shell.execute_reply.started": "2023-09-04T14:17:41.716610Z"
+    }
+   },
+   "source": [
+    "### 安装特定依赖"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "489900d6-cc33-4ada-b2be-7e3a139cf6ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! cd modelscope-agent && pip install -r requirements.txt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9e9f3150",
+   "metadata": {},
+   "source": [
+    "### 本地配置"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a027a6e8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.chdir('modelscope-agent/demo')\n",
+    "\n",
+    "import sys\n",
+    "sys.path.append('../')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8f35e3f7",
+   "metadata": {},
+   "source": [
+    "### 部署模型"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ad038344",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "os.system(\"export VLLM_USE_MODELSCOPE=True\")\n",
+    "os.system(\"python -m vllm.entrypoints.openai.api_server \\\n",
+    " --model=iic/alpha-umi-planner-7b \\\n",
+    " --revision=v1.0.0 --trust-remote-code \\\n",
+    " --port 8090 \\\n",
+    " --dtype float16 \\\n",
+    " --gpu-memory-utilization 0.3 > planner.log &\")\n",
+    "\n",
+    "os.system(\"python -m vllm.entrypoints.openai.api_server \\\n",
+    " --model=iic/alpha-umi-caller-7b \\\n",
+    " --revision=v1.0.0 --trust-remote-code \\\n",
+    " --port 8091 \\\n",
+    " --dtype float16 \\\n",
+    " --gpu-memory-utilization 0.3 > caller.log &\")\n",
+    "\n",
+    "os.system(\"python -m vllm.entrypoints.openai.api_server \\\n",
+    " --model=iic/alpha-umi-summarizer-7b \\\n",
+    " --revision=v1.0.0 --trust-remote-code \\\n",
+    " --port 8092 \\\n",
+    " --dtype float16 \\\n",
+    " --gpu-memory-utilization 0.3 > summarizer.log &\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3de23896",
+   "metadata": {},
+   "source": [
+    "### API_KEY管理"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "65e5dcc8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "print('请输入DASHSCOPE_API_KEY')\n",
+    "os.environ['DASHSCOPE_API_KEY'] = input()\n",
+    "print('请输入ModelScope Token')\n",
+    "os.environ['MODELSCOPE_API_TOKEN'] = input()\n",
+    "print('请输入RapidAPI Token')\n",
+    "os.environ['RAPID_API_TOKEN'] = input()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8c8defa3",
+   "metadata": {},
+   "source": [
+    "### 构建agent"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "01e90564",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from modelscope_agent.agents.alpha_umi import AlphaUmi\n",
+    "\n",
+    "\n",
+    "llm_configs = {\n",
+    "    'planner_llm_config': {\n",
+    "        'model': 'iic/alpha-umi-planner-7b',\n",
+    "        'model_server': 'openai',\n",
+    "        'api_base': 'http://localhost:8090/v1',\n",
+    "        'is_chat': False\n",
+    "    },\n",
+    "    'caller_llm_config': {\n",
+    "        'model': 'iic/alpha-umi-caller-7b',\n",
+    "        'model_server': 'openai',\n",
+    "        'api_base': 'http://localhost:8091/v1',\n",
+    "        'is_chat': False\n",
+    "    },\n",
+    "    'summarizer_llm_config': {\n",
+    "        'model': 'iic/alpha-umi-summarizer-7b',\n",
+    "        'model_server': 'openai',\n",
+    "        'api_base': 'http://localhost:8092/v1',\n",
+    "        'is_chat': False\n",
+    "    },\n",
+    "}\n",
+    "\n",
+    "\n",
+    "\n",
+    "function_list = [\"get_data_fact_for_numbers\", \"get_math_fact_for_numbers\", \"get_year_fact_for_numbers\",\n",
+    "                    \"listquotes_for_current_exchange\",\n",
+    "                    \"exchange_for_current_exchange\"]\n",
+    "\n",
+    "\n",
+    "bot = AlphaUmi(\n",
+    "        function_list=function_list,\n",
+    "        llm_planner=llm_configs['planner_llm_config'],\n",
+    "        llm_caller=llm_configs['caller_llm_config'],\n",
+    "        llm_summarizer=llm_configs['summarizer_llm_config'],\n",
+    "    )\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "064ad74e",
+   "metadata": {},
+   "source": [
+    "### 执行agent"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fdd379ab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "response = bot.run('how many CNY can I exchange for 3.5 US dollar? \\\n",
+    "                   also, give me a special property about the number of CNY after exchange')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "85434381",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "text = ''\n",
+    "for chunk in response:\n",
+    "    text += chunk\n",
+    "print(text)"
+   ]
+  }
+ ],
+ "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": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}