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--- tags: vtaiwan --- # 「SenseMaker意見綜整器」使用說明 * 官方說明文:https://jigsaw-code.github.io/sensemaking-tools/ * 開源程式庫:https://github.com/Jigsaw-Code/sensemaking-tools/ * 開源程式庫(實驗版):https://github.com/bestian/sensemaking-tools/ note:實驗版要切換至`new-feature-open-router`分支 ## SenseMaker是什麼?: * [SenseMaker意見綜整器](https://github.com/Jigsaw-Code/sensemaking-tools) 透過Google 的 AI 服務,可以用來分析大數據,產生有意義的結果,包含主要共同點和主要意見分岐等。 * 這是[一則23頁的報告實例(中譯版)](https://docs.google.com/document/d/14nBRvseptZd0XX1itfqaeHrEOaTrywoE2UcC9DMRJjk/edit?tab=t.0),主題是'Share your views on generative AI',包括:*356 條聲明和8,005 票* ## SenseMaker可以解決什麼問題?: * 審議民主常用的非同步意見徵集工具[Polis城邦](https://polis.tw/),當意見項目多,且有相似與重覆的意見時,大工要海量資料中,分析出有意義的結果並不容易。 * 此時,SenseMaker可以做報告的後製工作,將意見彙整成有意義的結果。 ## Sensemaking-Tools的需要什麼輸入資料(Input)?: * 具有特定欄位的CSV檔,可由polis report得到 ## Sensemaking-Tools可以輸入什麼結果(Output)?: 1. Markdown(推薦。這應該是最直觀有利閱讀的輸出) 2. HTML網頁 3. JSON Object 4. CSV檔 ## 如何安裝與執行Sensemaking-Tools?: 您需要: ### 1. 準備輸入資料 0. 先clone專案到近端電腦上 * 開發中的實驗版網址(推薦):https://github.com/bestian/sensemaking-tools --- * 穩定版網址: https://github.com/Jigsaw-Code/sensemaking-tools #### 對poliw.tw的報告 1. 進入Plois的報告頁report page,開啟開發者模式,找到用 GET /api/v3/comments 回來的 JSON 。 * 開發者模式選「網路」> 「全部」>「回應」 * 過濾器打上「/api/v3/comments」 * 重新載入頁面,會找到唯一一個JSON格式的資料,就是它 ![](https://g0v.hackmd.io/_uploads/S1rc6zjHeg.png) 2. 把它存進電腦,命名為polis_report.json 3. (把json轉換成格式正確的csv, 方法1) 用開源軟體 * 安裝[json-2-csv-cli套件](https://github.com/mrodrig/json-2-csv-cli) * json2csv polis_report.json -o comments_raw.csv * 執行[csv_converter.py](https://github.com/bestian/sensemaking-tools/blob/new-feature-multilang/polis_csv_fixer/csv_converter.py) * ```bash python3 ./polis_csv_fixer/csv_converter.py ./files/comments_raw.csv ./files/comments.csv ``` * 取得格式正確的comments.csv,可以餵給SenseMaker了! 3. (把json轉換成格式正確的csv, 方法2, 由chatGPT工作, 非開源) 請chatGPT幫忙把.json轉成.csv檔案,使用如下對話指令: ``` bash 請幫我把以下的JSON轉成.csv,欄位格式範例如下: comment-id,comment_text,votes,agrees,disagrees,passes,a-votes,a-agree-count,a-disagree-count,a-pass-count,b-votes,b-agree-count,b-disagree-count,b-pass-count 0,"this is a test.",1,1,0,0,0,0,0,0,1,1,0,0 ``` 4. 下載結果,命名為comments.csv,放入近端電腦上的正確目錄 --- #### 對pol.is的報告 1. 從報告頁導出comments有關的csv檔,改名為comments_raw.csv 2. 執行[csv_converter_new.py](https://github.com/bestian/sensemaking-tools/blob/new-feature-multilang/polis_csv_fixer/csv_converter_new.py) ```bash python3 ./polis_csv_fizer/csv_converter_new.py ./files/comments_raw.csv ``` * 再改名 comments_realdata_fixed.csv 為 comments.csv * 取得格式正確的comments.csv,可以餵給SenseMaker了! #### 報告存檔目錄位置 * 實驗版(推薦): sensemaking-tools/files這個目錄(請自行創建/files目錄) --- * 穩定版:sensemaking-tools這個目錄(即專案根目錄)。 --- ### 2 註冊AI模型後端服務帳戶 * 實驗版(推薦):請註冊一個[open router](https://openrouter.ai/)帳號,並取得API KEY 1. 需儲值(體驗的話,先存5美金 = 150台幣就夠用許多次了。) 2. 儲值後取得API KEY 3. 將.env.example檔,複製並更名為.env檔 4. 把.env中OPENROUTER_API_KEY欄位之值,改為你的API KEY --- * 穩定版:註冊一個綁定付費帳號的google cloud Project,並啟用[VertexAI](https://cloud.google.com/vertex-ai?hl=zh_tw) 1. 需購買模型:gemini-2.5-pro 2. https://cloud.google.com/ 3. https://cloud.google.com/vertex-ai?hl=zh_tw 4. 安裝GCloud CLI,可參考此[官方說明](https://cloud.google.com/sdk/docs/install)或此[chatGPT對話](https://chatgpt.com/share/686d9ede-7960-800b-a265-cc446f4b4edc) ### 3. 執行分析,並生成Markdown或網頁檔 * 實驗版(推薦): 1. 在終端機專案根目錄,執行: ```bash npx ts-node ./library/examples/tutorial.ts ``` 即可於終端機顯示出生成的意見彙整分析報告(Markdown格式)內容了! 2. 在根目錄,執行 ``` npx ts-node ./library/runner-cli/runner_openrouter.ts \ --outputBasename out \ --inputFile "./files/comments.csv" \ --additionalContext "Description of the conversation" ``` 即可於終端機顯示出生成的意見彙整分析報告(.md, .HTML, .JSON, .CSV)內容了! --- * 穩定版 1. 先登入google could CLI: ``` gcloud auth login ``` 2. 在專案根目錄,執行: ```gcloud config set project <your project id here>``` ```gcloud auth application-default login``` 3. 在專案根目錄,執行: ```npm install``` 4. 在專案根目錄,執行: ```npx ts-node ./library/runner-cli/runner.ts --outputBasename out --vertexProject "{Your_Project_ID}" --inputFile "comments.csv"``` 即可生成文字版的意見彙整報告(.md, .HTML, .JSON, .CSV)內容了!

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