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Kohei Shoda shoda888 Tokyo Tech https://sho-d-blog.com Tokyo Tech student

k-jun/gopy-grpc 1

golang and python server connecting via grpc template

shoda888/local2lambda 1

Deploy local code to lambda

shoda888/AKRecorder 0

Recorder for Azure Kinect

shoda888/alexa2tello 0

Tello controlled by alexa through AWS

shoda888/awsrails 0

awsrails test

shoda888/cifa10test 0

deeplearning

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json定義を決めた

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Merge pull request #3 from TeamAiSeki/feature/20220503_add_matching Feature/20220503 add matching

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Merge pull request #3 from TeamAiSeki/feature/20220503_add_matching Feature/20220503 add matching

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Feature/20220503 add matching

やったこと

  • DB保存追加
  • ID取得←LineのIDを流用し数字のみ抽出
  • json質問・回答文更新

あとやること

  • IDを6桁まで減らす
  • ブロックされた時にerror走るところ直す
  • 質問時画像の刷新
  • 処理関数化←必要箇所あれば
+1828 -441

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Merge pull request #4 from TeamAiSeki/fix/20220503_add_matching Fix/20220503 add matching

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Fix/20220503 add matching
  • json再定義
  • 不要部分削除
+381 -481

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PR opened TeamAiSeki/deployLambdaDemo

Fix/20220503 add matching
  • json再定義
  • 不要部分削除
+381 -481

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pull request commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

ひとまず,コンフリクト解消

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init

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add major club work question

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Merge pull request #1 from TeamAiSeki/feature/QR Feature/qr

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Merge pull request #2 from TeamAiSeki/feature/college Feature/college

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refix README

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pull request commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

Conflictもしているので,適宜俺が修正しておく.

waretaflow

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Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

+"""後日、コード綺麗にします。ちょっと本業に想定の5倍くらい時間取られた""" import json import urllib.request import re import os+import re+import boto3+#各種機械学習モジュールのimport、使うなら+# import keras+# import numpy as np++dynamo_db = boto3.resource('dynamodb')+table= dynamo_db.Table('AIsekiya') +#User情報を引数に受け取り、診断結果を返す関数。オバソン記述予定。+def matching(user_id):+    #DBから相手先の情報を取得+    # partner_info = table.get_item(+    #     Key={+    #         'user_id': user_id+    #         }+    #     )+    +    #機械学習処理+    model_output = "96%"+    return model_output+  def lambda_handler(event, context):+    read_flag = True     url = "https://api.line.me/v2/bot/message/reply"     method = "POST"     headers = {-        'Authorization': 'Bearer ' + os.environ['CHANNEL_ACCESS_TOKEN'],+        'Authorization': 'Bearer ' + os.environ['DEV_CHANNEL_ACCESS_TOKEN'],         'Content-Type': 'application/json'     }     message_dist = json.loads(event["body"])-    -    print(message_dist["events"])-    ++    #UserIDを取得+    user_id = message_dist["events"][0]["source"]["userId"]+    #LineでのUser_IDは文字列を含むため、数値のみを抽出する。ちょっとこのままだと長すぎる。+    user_num = re.sub("\\D", "", user_id)+     # 友達登録時     if message_dist["events"][0]["type"] == "follow":-        json_open = open('json/Romance.json', 'r')+        json_open = open('json/Height.json', 'r')      elif message_dist["events"][0]["type"] == "postback":         postback = message_dist["events"][0]["postback"]["data"]          postback_action = postback.split("&")[0].split("=")[1]-        # DB保存用-        # postback_value = postback.split("&")[1].split("=")[1]-        if postback_action == "romance":-            json_open = open('json/Height.json', 'r')         if postback_action == "height":+            table.put_item(

DB処理は別Lambdaでやる予定

waretaflow

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Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

+"""後日、コード綺麗にします。ちょっと本業に想定の5倍くらい時間取られた""" import json import urllib.request import re import os+import re+import boto3+#各種機械学習モジュールのimport、使うなら+# import keras+# import numpy as np++dynamo_db = boto3.resource('dynamodb')+table= dynamo_db.Table('AIsekiya') +#User情報を引数に受け取り、診断結果を返す関数。オバソン記述予定。+def matching(user_id):+    #DBから相手先の情報を取得+    # partner_info = table.get_item(+    #     Key={+    #         'user_id': user_id+    #         }+    #     )+    +    #機械学習処理+    model_output = "96%"+    return model_output+  def lambda_handler(event, context):+    read_flag = True     url = "https://api.line.me/v2/bot/message/reply"     method = "POST"     headers = {-        'Authorization': 'Bearer ' + os.environ['CHANNEL_ACCESS_TOKEN'],+        'Authorization': 'Bearer ' + os.environ['DEV_CHANNEL_ACCESS_TOKEN'],         'Content-Type': 'application/json'     }     message_dist = json.loads(event["body"])-    -    print(message_dist["events"])-    ++    #UserIDを取得+    user_id = message_dist["events"][0]["source"]["userId"]+    #LineでのUser_IDは文字列を含むため、数値のみを抽出する。ちょっとこのままだと長すぎる。+    user_num = re.sub("\\D", "", user_id)

数値のみ抽出で,userの一意性が保たれるか

waretaflow

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Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

+"""後日、コード綺麗にします。ちょっと本業に想定の5倍くらい時間取られた""" import json import urllib.request import re import os+import re+import boto3+#各種機械学習モジュールのimport、使うなら+# import keras+# import numpy as np++dynamo_db = boto3.resource('dynamodb')+table= dynamo_db.Table('AIsekiya') +#User情報を引数に受け取り、診断結果を返す関数。オバソン記述予定。+def matching(user_id):

別のLambdaに移動予定

waretaflow

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Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

+{+    "type": "flex",+    "altText": "最も時間をかけたアルバイトや仕事を教えてください",+	"quickReply": {+		"items": [+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "飲食(居酒屋、フード)",+					"displayText": "飲食(居酒屋、フード)",+					"data": "action=job&job=飲食(居酒屋、フード)"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "販売(コンビニ、アパレル)",+					"displayText": "販売(コンビニ、アパレル)",+					"data": "action=job&job=2販売(コンビニ、アパレル)"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "接客(カラオケ、ネカフェ)",+					"displayText": "接客(カラオケ、ネカフェ)",+					"data": "action=job&job=接客(カラオケ、ネカフェ)"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "教育(塾、家庭教師)",+					"displayText": "教育(塾、家庭教師)",+					"data": "action=job&job=教育(塾、家庭教師)"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "サービス(ホテル、コールセンター)",+					"displayText": "サービス(ホテル、コールセンター)",+					"data": "action=job&job=サービス(ホテル、コールセンター)"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "35~39",+					"displayText": "35~39",+					"data": "action=age&age=35-39"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "40以上",+					"displayText": "40以上",+					"data": "action=age&age=40-00"+        }+      }+    ]+	},+    "contents": {+      "type": "bubble",+      "hero": {+        "type": "image",+        "url": "https://aisekiimagebucket.s3-ap-northeast-1.amazonaws.com/youth-640094_640.jpg",+        "size": "full",+        "aspectRatio": "20:13",+        "aspectMode": "cover"+      },+      "body": {+        "type": "box",+        "layout": "vertical",+        "contents": [+          {+            "type": "text",+            "text": "最も時間をかけたアルバイトや仕事を教えてください",+            "size": "lg",+            "weight": "regular"

"wrap": true

waretaflow

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Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

+{+    "type": "flex",+    "altText": "最も時間をかけてサークル・クラブ活動は何ですか?",+	"quickReply": {+		"items": [+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "体育会(部活)",+					"displayText": "体育会(部活)",+					"data": "action=club&club=体育会(部活)"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "スポーツ・アウトドア・レクリエーション",+					"displayText": "スポーツ・アウトドア・レクリエーション",+					"data": "action=club&club=スポーツ・アウトドア・レクリエーション"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "音楽・芸術・演劇",+					"displayText": "音楽・芸術・演劇",+					"data": "action=club&club=音楽・芸術・演劇"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "人文・社会・教養・語学・ボランティア",+					"displayText": "人文・社会・教養・語学・ボランティア",+					"data": "action=club&club=人文・社会・教養・語学・ボランティア"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "文化系同好会",+					"displayText": "文化系同好会",+					"data": "action=club&club=文化系同好会"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "理科系(ロボット、サイエンス)",+					"displayText": "理科系(ロボット、サイエンス)",+					"data": "action=club&club=理科系(ロボット、サイエンス)"+        }+      },+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "所属していない",+					"displayText": "所属していない",+					"data": "action=club&club=所属していない"+        }+      }+    ]+	},+    "contents": {+      "type": "bubble",+      "hero": {+        "type": "image",+        "url": "https://aisekiimagebucket.s3-ap-northeast-1.amazonaws.com/youth-640094_640.jpg",+        "size": "full",+        "aspectRatio": "20:13",+        "aspectMode": "cover"+      },+      "body": {+        "type": "box",+        "layout": "vertical",+        "contents": [+          {+            "type": "text",+            "text": "最も時間をかけてサークル・クラブ活動は何ですか?",+            "size": "lg",+            "weight": "regular"

"wrap": true が無いと質問が最後まで見えない.

waretaflow

comment created time in 3 months

Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

         "type": "action",         "action": { 					"type": "postback",-					"label": "18",-					"displayText": "18",-					"data": "action=age&age=18"+					"label": "18~20",+					"displayText": "18~20",+					"data": "action=age&age=18-20"

大学生世代は刻んだ方が良いかも

waretaflow

comment created time in 3 months

Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

 echo "DEPLOY START!!" funcname="aisekiyaFunc"  docker run --rm -v "$PWD":/var/task shoda888/local2pylambda:latest-aws lambda update-function-code --function-name ${funcname} --zip-file fileb://deploy_package.zip --profile aisekiya-user+aws lambda update-function-code --function-name ${funcname} --zip-file fileb://deploy_package.zip

ローカル環境でawsユーザーを分けてた場合,これだとdefaultUserとしてデプロイされてしまうので, --profile sisekiya-user で運用したい

waretaflow

comment created time in 3 months

Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

+{+    "type": "flex",+    "altText": "煙草は吸いますか?",+	"quickReply": {+		"items": [+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "吸わない",+					"displayText": "吸わない",+					"data": "action=smoke&smoke=吸わない"

データの形式

waretaflow

comment created time in 3 months

Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

+{+    "type": "flex",+    "altText": "最も時間をかけたアルバイトや仕事を教えてください",+	"quickReply": {+		"items": [+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "飲食(居酒屋、フード)",+					"displayText": "飲食(居酒屋、フード)",+					"data": "action=job&job=飲食(居酒屋、フード)"

dataの形式

waretaflow

comment created time in 3 months

Pull request review commentTeamAiSeki/deployLambdaDemo

Feature/20220503 add matching

+{+    "type": "flex",+    "altText": "おしゃれは好きですか?",+	"quickReply": {+		"items": [+      {+        "type": "action",+        "action": {+					"type": "postback",+					"label": "こだわる",+					"displayText": "こだわる",+					"data": "action=fashion&fashion=こだわる"

dataの形式が日本語が危うい

waretaflow

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create barnchTeamAiSeki/deployLambdaDemo

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push eventshoda888/local2lambda

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reUpdate README.md

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fix README.md

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