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 {
        "id": "Step 2: I'm organizing a team-building event for my company and I want to start it off with some lighthearted jokes. Can you fetch jokes from the Jokester API and categorize them as 'team-building' and 'fun'? Also, it would be great if you could provide me with some motivational quotes from the mydailyinspiration API to inspire my team.",
        "conversations": [
            {
                "from": "system",
                "value": "You are AutoGPT, you can use many tools(functions) to do the following task.\nFirst I will give you the task description, and your task start.\nAt each step, you need to give your thought to analyze the status now and what to do next, with a function call to actually excute your step. Your output should follow this format:\nThought:\nAction\nAction Input:\n\nAfter the call, you will get the call result, and you are now in a new state.\nThen you will analyze your status now, then decide what to do next...\nAfter many (Thought-call) pairs, you finally perform 

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{"qst": "What will be the average temperature in New York City after one week?", "actions": ["Thought: I need to get the temperature of New York City for the next week, so I should call forecast_weather(New York City, 7).", "Information: OK.", "Action: forecast_weather(New York City, 7)", "Information: {over all weather: Sunny; max temperature: 12.7(C), 54.9(F); min temperature: -0.1(C), 31.8(F); average temperature: 6.8(C), 44.2(F); max wind speed: 20.9(kph), 13.0(mph); total precipitation: 0.0(mm), 0.0(inch); will rain today: 0, chance of rain: 0; total snow: 0.0(cm); will snow today: 0, chance of snow: 0; average visibility: 10.0(km), 6.0(miles); average humidity: 52.0; UV index: 3.0; sunrise time: 06:45 AM, sunset time: 07:18 PM; moonrise time: 11:50 AM, moonset time: 03:04 AM; }", "Thought: I have the average temperature information for the next week in New York City, I can give the final answer.", "Information: OK.", "Answer: the average temperature in New York City after one week is 6.8(C), 44.2(F)."]}

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{
        "api_list": [
            {
                "category_name": "Logistics",
                "tool_name": "SQUAKE",
                "api_name": "Checkhealth",
                "api_description": " ",
                "required_parameters": [],
                "optional_parameters": [],
                "method": "GET"

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5e-08 2e-07
small step: 0.0005  big step: 0.0020
Epoch 1 Batch 50 Loss 8.9662 Accuracy 0.0001 small step: 0.0005  big step: 0.0020
tf.Tensor(8.976346, shape=(), dtype=float32) tf.Tensor(8.956141, shape=(), dtype=float32)
setting to big step
Epoch 1 Batch 100 Loss 8.9406 Accuracy 0.0004 small step: 0.0010  big step: 0.0040
tf.Tensor(8.927561, shape=(), dtype=float32) tf.Tensor(8.901532, shape=(), dtype=float32)
setting to big step
Epoch 1 Batch 150 Loss 8.9037 Accuracy 0.0067 small step: 0.0020  big step: 0.0080
tf.Tensor(8.851914, shape=(), dtype=float32) tf.Tensor(8.806074, shape=(), dtype=float32)

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{
  "_index": "deals-1499727747450",
  "_type": "deals",
  "_id": "34147415-f1b4-4460-b943-9c3eb13d1815",
  "_score": 14.633316,
  "_source": {
    "parentId": null,
    "legacyId": 18104569,
    "permalink": "pg-institute-of-skin-and-body",
    "status": "launched",

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{
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{
  "query": {
    "filtered": {
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          "should": [
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              "bool": {
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                  {

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{
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  "timeout": 1000,
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{
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  "timeout": 1000,
  "query": {
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{
  "from": 0,
  "size": 600,
  "timeout": 1000,
  "query": {
    "filtered": {
      "query": {
        "bool": {
          "must": {
            "dis_max": {