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QwenLM / Qwen-Agent

Agent framework and applications built upon Qwen>=2.0, featuring Function Calling, Code Interpreter, RAG, and Chrome extension.
https://pypi.org/project/qwen-agent/
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Error code: 400. Error message: The input messages exceed the maximum context length (5800 tokens) after keeping only the system message and the latest one user message (around 15153 tokens). To configure the context limit, please specifiy "max_input_tokens" in the model generate_cfg. Example: generate_cfg = {..., "max_input_tokens": 15200} #265

Open QuintinTao opened 4 months ago

QuintinTao commented 4 months ago

token 被这玩意撑爆了，有办法解决没？ {'role': 'user', 'content': 'Answer the following questions as best you can. You have access to the following tools:\n\ncode_interpreter: Call this tool to interact with the code_interpreter API. What is the code_interpreter API useful for? Python代码沙盒，可用于执行Python代码。 Parameters: [{"name": "code", "type": "string", "description": "待执行的代码", "required": true}] 此工具的输入应为Markdown代码块。\n\nUse the following format:\n\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to take, should be one of [code_interpreter]\nAction Input: the input to the action\nObservation: the result of the action\n... (this Thought/Action/Action Input/Observation can be repeated zero or more times)\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n\nBegin!\n\nQuestion: 用柱状图或者饼图分析{\'category\': \'城市类型\', \'continuous_variable\': \'平均消费能力\'}使用D:\\python\\qw\\Qwen-Agent\\examples\\resource\\restaurant_data.csv作为数据文件进行分析，使用中文生成柱状图,Final answer要少于30个字，尽可能简短,并简短告知分析结论\nThought: 我需要查看文件数据，应该使用代码解释器API\nAction: code_interpreter\nAction Input: \npy\nimport pandas as pd\ndf = pd.read_csv("D:\\\\python\\\\qw\\\\Qwen-Agent\\\\examples\\\\resource\\\\restaurant_data.csv")\ndf.head() \n\nObservation: execute_result:\n\n\n Name Location Cuisine Rating Seating Capacity \\\n0 Restaurant 0 Rural Japanese 4.0 38 \n1 Restaurant 1 Downtown Mexican 3.2 76 \n2 Restaurant 2 Rural Italian 4.7 48 \n3 Restaurant 3 Rural Italian 4.4 34 \n4 Restaurant 4 Downtown Japanese 4.9 88 \n\n Average Meal Price Marketing Budget Social Media Followers \\\n0 73.98 2224 23406 \n1 28.11 4416 42741 \n2 48.29 2796 37285 \n3 51.55 1167 15214 \n4 75.98 3639 40171 \n\n Chef Experience Years Number of Reviews Avg Review Length Ambience Score \\\n0 13 185 161.92490574327928 1.3 \n1 8 533 148.7597173739537 2.6 \n2 18 853 56.84918945954191 5.3 \n3 13 82 205.43326529316235 4.6 \n4 9 78 241.68158411313138 8.6 \n\n Service Quality Score Parking Availability Weekend Reservations \\\n0 7.0 Yes 13 \n1 3.4 Yes 48 \n2 6.7 No 27 \n3 2.8 Yes 9 \n4 2.1 No 37 \n\n Weekday Reservations Revenue \n0 4 638945.52 \n1 6 490207.83 \n2 14 541368.62 \n3 17 404556.8 \n4 26 1491046.35 \n\nThought: 数据集包含有关餐厅的各种信息，包括城市类型和平均消费能力，但我需要首先检查"城市类型"和"平均消费能力"这两列是否存在。\nAction: code_interpreter\nAction Input: \npy\n# 检查\'城市类型\'和\'平均消费能力\'列是否存在\nif \'Location\' in df.columns and \'Average Meal Price\' in df.columns:\n print("这两列都存在")\nelse:\n print("至少有一列不存在")\n\nObservation: stdout:\n\n\n这两列都存在\n\n\nThought: 数据集中有\'城市类型\'（Location）和\'平均消费能力\'（Average Meal Price）这两列，可以继续进行分析。\nAction: code_interpreter\nAction Input: \npy\nimport pandas as pd\nimport matplotlib.pyplot as plt\nplt.rcParams[\'font.sans-serif\'] = [\'SimHei\'] # 设置字体解决中文显示问题\nplt.rcParams[\'axes.unicode_minus\'] = False \n\n# 加载数据\ndf = pd.read_csv("D:\\\\python\\\\qw\\\\Qwen-Agent\\\\examples\\\\resource\\\\restaurant_data.csv")\n\n# 分析\'城市类型\'和\'平均消费能力\'，计算每个城市的平均消费\naverage_meal_prices = df.groupby(\'Location\')[\'Average Meal Price\'].mean().reset_index()\n\n# 创建柱状图\nplt.figure(figsize=(10,6))\nplt.bar(average_meal_prices[\'Location\'], average_meal_prices[\'Average Meal Price\'])\nplt.xlabel(\'城市类型\', fontsize=12)\nplt.ylabel(\'平均消费能力\', fontsize=12)\nplt.title(\'各类型城市平均消费能力\')\nplt.show()\n\nObservation: error:\n\n**\nTypeError: Could not convert string** 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8133.1838.0833.160.9626.3649.8473.9326.139.1563.2935.2763.166.1236.6839.4132.2965.8834.7261.1456.3147.4734.3142.7745.0445.9825.066.245.5849.5634.5737.9266.529.5242.8144.2562.4960.0634.0142.338.1640.3630.7961.2344.3129.5371.6439.0135.1350.8546.3656.7532.131.2571.9965.1137.5330.3428.8359.7125.8257.8656.0236.1665.333.0757.6540.9275.5570.2237.471.2439.5827.7853.3552.2449.2438.2532.3775.1428.9636.7359.9944.0255.3353.9334.5430.6541.4337.6427.3534.2245.1661.6635.8127.9359.0632.3938.0570.2355.5840.5555.0452.6831.5538.8226.2256.9730.1645.9330.8341.1236.9747.4633.0925.1140.0931.369.2425.0631.4767.9736.9561.8445.8661.0174.3664.0335.0265.963.4361.546.6439.0939.9932.8336.4266.3564.7831.5728.1547.4972.762.630.7140.037.3545.2856.2429.5846.4271.3648.8462.1736.536.8538.1535.769.3965.0737.9257.4362.1237.5146.1670.2448.1667.6635.6855.1525.7353.5564.868.8962.545.6130.3443.3629.0259.6129.2960.2759.2125.9965.9341.0240.8645.4867.0257.2962.6536.044.0758.9135.1340.8762.6968.1126.1667.7930.6647.2438.4934.1573.850.5346.0240.5747.3736.352.7675.7534.2968.1874.0133.1566.8830.6937.1554.8758.5630.2549.6845.8872.3933.4957.5251.0336.6329.7835.2632.2473.5942.3339.3130.7438.9862.5670.173.2736.6640.4638.8232.2640.2157.8845.8861.9230.5851.5625.1752.4631.3433.3369.1433.834.1447.6149.4952.6142.3139.8733.6755.1636.7146.042.6531.6739.8333.2361.0849.9234.162.037.9250.6654.9925.0826.3230.0838.7239.1938.2835.8627.0165.7134.5244.0136.5131.7235.6635.4770.0941.4839.2428.8346.1355.7152.0454.8465.9849.6338.8765.436.5336.474.4866.3161.3143.1765.7638.8740.2736.2842.8334.7427.0741.2645.5830.6660.5155.332.8565.4655.2727.5273.2845.2163.4861.3763.9650.7857.030.7734.7527.2465.9737.2850.635.5538.4846.2259.5731.7639.1654.538.8336.9927.3538.3975.0132.9373.0140.0572.773.0339.2862.9858.3343.233.7856.830.4950.9375.4141.7339.5334.0236.934.6426.4436.8529.4440.8456.5265.6465.2636.0857.9651.5740.1155.2566.0734.3675.3149.4632.5545.2446.5271.0933.5630.8756.3635.1325.1743.7645.2537.5936.7330.2965.9371.2347.4346.3653.2746.8855.0230.9443.9663.7335.0958.9837.3967.3525.1131.8936.060.9471.447.2138.2559.7140.666.5974.4355.153.1148.8234.0464.438.1845.0839.5946.8830.2835.0933.6774.2255.7569.2851.4375.9361.056.5340.6564.6458.7470.9731.0832.5765.2740.3865.7760.2436.3745.9738.9752.5129.4751.7137.4154.0764.4741.6451.5337.4325.3131.437.8474.0627.1739.444.3433.8331.1137.9554.8828.6269.1631.2345.8764.6731.0966.9930.8228.0460.3261.2439.4639.1240.7461.2135.9235.8747.729.641.4933.6938.8852.2535.3333.4629.1428.6226.5356.4255.2531.1149.8572.771.754.8228.7169.4961.848.5240.933.745.2829.4269.0631.1843.4147.1863.1335.4335.9451.973.8855.5534.5660.6661.7975.4850.7250.9665.3435.4732.344.3652.1232.4855.8535.6627.8134.2626.3946.9728.7438.9439.3167.1152.6852.7237.833.449.0435.3964.9758.9754.5254.961.4566.1674.1632.9373.8740.7333.4271.2740.739.8464.6233.148.3350.4736.4863.637.566.7430.748.5845.525.8451.454.8641.1155.2436.8168.9927.8358.1158.639.6574.162.7130.4847.3965.6242.456.8351.7743.5664.0431.5970.4360.7435.0527.061.7840.9531.2370.9452.4769.4935.4141.3434.2462.1355.8344.8862.3838.2953.6240.8843.7141.8247.8964.7829.5951.5345.6838.6633.6357.1443.1672.7565.7475.3939.1530.9938.3572.4662.8375.4134.9948.6563.7437.2140.4140.1627.955.8459.2530.7428.4229.9447.0528.739.2542.8475.8631.8153.057.034.0165.5326.6629.3955.5234.3645.4347.3455.9974.6573.7838.6838.5363.3350.953.8267.5857.0566.0265.065.3939.4733.4668.3444.6762.7631.5328.1141.2329.2155.5172.7438.0239.1858.656.6445.3235.4259.4440.3948.6432.9375.7154.4263.7427.0538.9928.349.4856.8327.1729.6241.9240.626.8531.7860.441.1631.541.360.3743.0439.8356.8335.3147.5135.8445.651.4758.0839.6935.0128.2466.3958.2661.5734.2435.0632.6330.343.0973.5866.5944.127.3936.3231.0532.6369.2742.0774.2375.0629.4264.0657.7549.3745.230.3945.8536.4147.9233.3139.2652.1831.3158.5362.1364.3334.6845.8759.6631.5866.1260.1259.8938.7846.87\' to numeric\n\n\nThe above exception was the direct cause of the following exception:\n\nTypeError: agg function failed [how->mean,dtype->object]\n\n\nThought: '}

QuintinTao commented 4 months ago

ReActChat

QuintinTao commented 4 months ago

打了一下token 的内容，看了一下应该是数据里面有点问题，导致执行python 代码报错了，给爆掉了。修改 一下数据，再执行没问题了。

zhangwt commented 3 months ago

请问 Qwen-Agent 有提供直接设置max_input_tokens的配置选项么?

JianxinMa commented 3 months ago

请问 Qwen-Agent 有提供直接设置max_input_tokens的配置选项么?

@zhangwt 这样配置：

llm_cfg = {
    'model': 'Qwen2-7B-Chat',
    'model_server': 'http://localhost:8000/v1', 
    'api_key': 'EMPTY',
    'generate_cfg': {
        "max_input_tokens": 28000  # 这里
    }
}

bot = Assistant(llm=llm_cfg,