Source: https://ailoot.ai/models/zh-hant-tw/gemini-2-5-flash-thinking/ Canonical: https://ailoot.ai/models/zh-hant-tw/gemini-2-5-flash-thinking/ Language: zh-hant-tw # Gemini 2.5 Flash Thinking [Markdown](https://ailoot.ai/models/zh-hant-tw/gemini-2-5-flash-thinking/index.md) · [JSON](https://ailoot.ai/models/zh-hant-tw/gemini-2-5-flash-thinking/facts.json) ## [Gemini 2.5 Flash Thinking](https://ailoot.ai/models/zh-hant-tw/gemini-2-5-flash-thinking/) Gemini 2.5 Flash Thinking 是具名的文字與影像設定檔，列出的上下文容量為 1,048,576 token。請將書面問題與相關影像一起提供，以取得聚焦的文字回答。 - [**Ailoot · Anthropic Messages** `POST /v1/messages` `gemini-2.5-flash-thinking`](https://ailoot.ai/models/zh-hant-tw/gemini-2-5-flash-thinking/#method-0) - [**Ailoot · Gemini generateContent** `POST /v1beta/models/{model}:generateContent` `gemini-2.5-flash-thinking`](https://ailoot.ai/models/zh-hant-tw/gemini-2-5-flash-thinking/#method-1) 關於模型 此說明介紹模型的能力。Ailoot 可用的輸入、輸出與選項，依所選方法列於下方。 Gemini 2.5 Flash Thinking 是此處介紹的具名設定檔，接收文字與圖片，輸出文字。列出的上下文為 1,048,576 詞元，最大輸出為 65,536 詞元。 圖片問題請提供圖片，並說明要檢查什麼：可見文字、圖表、版面或特定細節。文件簡報則指定要比較的章節與答案形式。 指令應明確說明使用哪些證據，以及回應長度。Thinking 修飾詞是此設定檔名稱的一部分。 實用任務 ### 實用任務 英文技術範例 ``` Separate two contract obligations Compare these written clauses. C1: 'The supplier sends a dispatch notice within one business day of shipment.' C2: 'The buyer reports damaged goods within three calendar days of receipt.' Return who acts, the trigger and the time unit for each clause, followed by one sentence explaining why the deadlines cannot share a single start date. ``` #### 預期結果 ``` Two clause-linked obligation records and a short distinction between their triggers. ``` #### 檢查結果 ``` Preserve business days versus calendar days and shipment versus receipt. ``` **Ailoot · Anthropic Messages** `POST /v1/messages` `gemini-2.5-flash-thinking` [`gemini-2.5-flash-thinking`](https://ailoot.ai/models/zh-hant-tw/#m=gemini-2.5-flash-thinking&route=Core&caller=gemini-2.5-flash-thinking&fmt=messages) Google /`gemini-2.5-flash-thinking` ### 入門 Gemini 2.5 Flash Thinking 是具名的文字與影像設定檔，列出的上下文容量為 1,048,576 token。請將書面問題與相關影像一起提供，以取得聚焦的文字回答。 接受的輸入 文字 · 圖片 結果 文字 ### Ailoot 可用 · 輸入與方法 **Ailoot · Anthropic Messages** `POST /v1/messages` 輸入 `text`, `image` 輸出 `text` 上下文 1,048,576 tokens 輸出上限 65,536 tokens 輸出格式 json 或 SSE | 欄位 | 類型 | 要求 | 值與限制 | 預設值 | | --- | --- | --- | --- | --- | | 欄位`model` | 類型`string` | 要求必填 | 值與限制 gemini-2.5-flash-thinking | 預設值— | | 欄位`messages` | 類型`message[]` | 要求必填 | 值與限制 項目數下限: 1 | 預設值— | | 欄位`messages[].role` | 類型`string` | 要求必填 | 值與限制 user, assistant | 預設值— | | 欄位`messages[].content` | 類型`string\|content_block[]` | 要求必填 | 值與限制 | 預設值— | | 欄位`system` | 類型`string\|content_block[]` | 要求選填 | 值與限制 | 預設值— | | 欄位`max_tokens` | 類型`integer` | 要求必填 | 值與限制 最小值: 1 限制適用對象: 所選模型／卡片的確切上限 | 預設值— | | 欄位`stream` | 類型`boolean` | 要求選填 | 值與限制 | 預設值false | | 欄位`temperature` | 類型`number` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`top_p` | 類型`number` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`stop_sequences` | 類型`string[]` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`tools` | 類型`tool[]` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`tools[].name` | 類型`string` | 要求選填 | 值與限制 適用條件: 已提供工具 | 預設值— | | 欄位`tools[].description` | 類型`string` | 要求選填 | 值與限制 | 預設值— | | 欄位`tools[].input_schema` | 類型`JSON_schema` | 要求選填 | 值與限制 | 預設值— | | 欄位`tool_choice` | 類型`object` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`thinking.type` | 類型`string` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`thinking.budget_tokens` | 類型`integer` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`output_config.effort` | 類型`string` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`metadata` | 類型`object` | 要求選填 | 值與限制 | 預設值— | | 欄位`cache_control` | 類型`object` | 要求選填 | 值與限制 依模型而定 | 預設值— | 輸入素材組合 **文字** · UTF8 文字 `messages[].content 或 type=text 區塊` **文字 + 圖片** `{type:image,source:{type:base64,media_type,data}} 或 type=url 的來源` 方法參數與生命週期 | 參數 | 規格 | | --- | --- | | 參數`material_types` | 規格text, image | | 參數`required` | 規格model, messages, max\_tokens | | 參數`optional_controls` | 規格null | | 參數`content_type` | 規格application/json | | 參數`text_file_material` | 規格實際 UTF-8 內容以文字插入；檔案 ID／URLs 需要另有精確支援 | 生命週期： `exact retained published method` 方法結構與 ID 均為精確值；供應商能力與准入狀態分開。 ### 方案 #### Ailoot 方法費率 輸入 US$0.0003 */ 1K* 輸出 US$0.0025 */ 1K* 讀取快取 ≈US$0.00003 */ 1K* Ailoot 會在請求前預留估算金額。取得結果後，依實測用量結算最終費用。串流結算採用最終用量紀錄。[預留金額與結算的運作方式 →](https://ailoot.ai/docs/zh-hant-tw/billing/reserve/) ### 請求範例 #### Ailoot · Anthropic Messages 文字範例輸入，圖片Python SDKNode.js SDKPython 串流 ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}" export AILOOT_TEXT_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "gemini-2.5-flash-thinking", "max_tokens": 1024, "messages": []}') f=Path(os.environ["AILOOT_TEXT_FILE"]) if not f.is_file():raise SystemExit("Choose your actual UTF-8 source material") text=f.read_text(encoding="utf-8") if not text.strip():raise SystemExit("Source material must contain text") p["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\n\n"+text}] Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \ -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path print(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2)) PY_RESULT ``` ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}" export AILOOT_IMAGE_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "gemini-2.5-flash-thinking", "max_tokens": 1024, "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}') import base64 f=Path(os.environ["AILOOT_IMAGE_FILE"]) if not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image") raw=f.read_bytes() mime="image/png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "image/jpeg" if raw.startswith(b"\xff\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None if not mime:raise SystemExit("Use PNG JPEG or WebP") b64=base64.b64encode(raw).decode() p["messages"][0]["content"].append({"type":"image","source":{"type":"base64","media_type":mime,"data":b64}}) Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \ -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path print(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2)) PY_RESULT ``` ```python import anthropic import os if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client = anthropic.Anthropic(base_url="https://api.ailoot.ai", api_key=os.environ["AILOOT_API_KEY"], max_retries=0) msg = client.messages.create( model="gemini-2.5-flash-thinking", max_tokens=1024, messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}], ) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(msg.to_dict(mode="json")) ``` ```js import Anthropic from "@anthropic-ai/sdk"; if (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request"); const client = new Anthropic({ baseURL: "https://api.ailoot.ai", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 }); const msg = await client.messages.create({ model: "gemini-2.5-flash-thinking", max_tokens: 1024, messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }], }); import { writeFileSync } from "node:fs"; function saveResult(data, stem = "result") { writeFileSync(stem + ".json", JSON.stringify(data, null, 2)); console.log(JSON.stringify(data, null, 2)); const saveBlob = (encoded, suffix, label) => { const raw = Buffer.from(encoded, "base64"); const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix; const file = `${stem}-${label}.${ext}`; writeFileSync(file, raw); console.log("Saved", file); }; for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block)); for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {})); for (const [i, item] of (data.output || []).entries()) { console.log("Output", i, JSON.stringify(item)); if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`); } for (const [ci, candidate] of (data.candidates || []).entries()) { for (const [pi, part] of (candidate.content?.parts || []).entries()) { console.log("Candidate/part", ci, pi, JSON.stringify(part)); const blob = part.inlineData || part.inline_data; if (blob?.data) { const mime = blob.mimeType || blob.mime_type; const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin"; saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`); } } } } saveResult(msg); ``` ```python import anthropic,os from pathlib import Path if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client=anthropic.Anthropic(base_url="https://api.ailoot.ai",api_key=os.environ["AILOOT_API_KEY"],max_retries=0) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) with client.messages.stream(model='gemini-2.5-flash-thinking',max_tokens=1024,messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream: with Path("stream-events.jsonl").open("w",encoding="utf-8") as log: for event in stream: payload=event.to_dict(mode="json") log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush() print(json.dumps(payload,ensure_ascii=False)) final=stream.get_final_message() save_result(final.to_dict(mode="json"),"stream-result") ``` ### 接收並儲存結果 #### Ailoot · Anthropic Messages json 或 SSE ##### 保留所有已完成的結果 請保留所有完整傳回的回應、檔案與內容區塊。 保留所有內容區塊、思考簽章與實際工具使用 ID。組合所有 SSE 區塊增量；第一個文字區塊不是完整輸出。 ##### 需要檢查原始回應時 保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。 回應欄位 | 欄位 | 類型 | | --- | --- | | 欄位`id` | 類型string | | 欄位`model` | 類型string | | 欄位`content[]` | 類型text\|thinking\|tool\_use\|other content block | | 欄位`stop_reason` | 類型string\|null | | 欄位`usage` | 類型object | 錯誤與後續步驟 | 回應 | 條件 | 下一步 | | --- | --- | --- | | 回應400 · `invalid_request_error` | 條件必要欄位、素材表示方式或參數值無效 | 下一步提出新的建立請求前，先修正指定欄位。 | ### 別名 #### 模型別名 **Ailoot** [`gemini-2.5-flash-thinking`](https://ailoot.ai/models/zh-hant-tw/#m=gemini-2.5-flash-thinking&route=Core&caller=gemini-2.5-flash-thinking&fmt=messages) #### 方法路徑別名 請使用上方列出的 API 方法路徑。 #### 相關呼叫用 ID [`gemini-2.5-flash-thinking`](https://ailoot.ai/models/zh-hant-tw/#m=gemini-2.5-flash-thinking&route=Core&caller=gemini-2.5-flash-thinking&fmt=messages) **Ailoot · Gemini generateContent** `POST /v1beta/models/{model}:generateContent` `gemini-2.5-flash-thinking` [`gemini-2.5-flash-thinking`](https://ailoot.ai/models/zh-hant-tw/#m=gemini-2.5-flash-thinking&route=Core&caller=gemini-2.5-flash-thinking&fmt=gemini) Google /`gemini-2.5-flash-thinking` ### 入門 Gemini 2.5 Flash Thinking 是具名的文字與影像設定檔，列出的上下文容量為 1,048,576 token。請將書面問題與相關影像一起提供，以取得聚焦的文字回答。 接受的輸入 文字 · 圖片 結果 文字 ### Ailoot 可用 · 輸入與方法 **Ailoot · Gemini generateContent** `POST /v1beta/models/{model}:generateContent` 輸入 `text`, `image` 輸出 `text` 上下文 1,048,576 tokens 輸出上限 65,536 tokens 輸出格式 json 或支援的串流 | 欄位 | 類型 | 要求 | 值與限制 | 預設值 | | --- | --- | --- | --- | --- | | 欄位`path.model` | 類型`string` | 要求必填 | 值與限制 gemini-2.5-flash-thinking | 預設值— | | 欄位`contents` | 類型`content[]` | 要求必填 | 值與限制 項目數下限: 1 | 預設值— | | 欄位`contents[].role` | 類型`string` | 要求選填 | 值與限制 user, model | 預設值— | | 欄位`contents[].parts` | 類型`part[]` | 要求必填 | 值與限制 | 預設值— | | 欄位`systemInstruction` | 類型`content` | 要求選填 | 值與限制 | 預設值— | | 欄位`generationConfig.maxOutputTokens` | 類型`integer` | 要求選填 | 值與限制 最小值: 1 依模型而定 | 預設值— | | 欄位`generationConfig.temperature` | 類型`number` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`generationConfig.topP` | 類型`number` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`generationConfig.topK` | 類型`integer` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`generationConfig.stopSequences` | 類型`string[]` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`generationConfig.thinkingConfig.includeThoughts` | 類型`boolean` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`generationConfig.thinkingConfig.thinkingBudget` | 類型`integer` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`tools[].functionDeclarations` | 類型`function_declaration[]` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`toolConfig.functionCallingConfig.mode` | 類型`string` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`safetySettings` | 類型`object[]` | 要求選填 | 值與限制 依模型而定 | 預設值— | | 欄位`sessionId` | 類型`string` | 要求選填 | 值與限制 | 預設值— | 輸入素材組合 **文字** · UTF8 文字 `contents[].parts[].text` **文字 + 圖片** `parts[].inlineData={mimeType,data}` 方法參數與生命週期 | 參數 | 規格 | | --- | --- | | 參數`material_types` | 規格text, image | | 參數`required` | 規格contents | | 參數`optional_controls` | 規格null | | 參數`content_type` | 規格application/json | | 參數`text_file_material` | 規格實際 UTF-8 內容以文字插入；檔案 ID／URLs 需要另有精確支援 | 生命週期： `exact retained published method` 方法結構與 ID 均為精確值；供應商能力與准入狀態分開。 ### 方案 #### Ailoot 方法費率 輸入 US$0.0003 */ 1K* 輸出 US$0.0025 */ 1K* 讀取快取 ≈US$0.00003 */ 1K* Ailoot 會在請求前預留估算金額。取得結果後，依實測用量結算最終費用。串流結算採用最終用量紀錄。[預留金額與結算的運作方式 →](https://ailoot.ai/docs/zh-hant-tw/billing/reserve/) ### 請求範例 #### Ailoot · Gemini generateContent 文字範例輸入，圖片Python SDKNode.js SDKPython 串流 ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}" export AILOOT_TEXT_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"contents": []}') f=Path(os.environ["AILOOT_TEXT_FILE"]) if not f.is_file():raise SystemExit("Choose your actual UTF-8 source material") text=f.read_text(encoding="utf-8") if not text.strip():raise SystemExit("Source material must contain text") p["contents"]=[{"role":"user","parts":[{"text":"Summarize this material and quote supporting source passages.\n\n"+text}]}] Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1beta/models/gemini-2.5-flash-thinking:generateContent \ -H "x-goog-api-key: $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(json.loads(Path("result.json").read_text(encoding="utf-8"))) PY_RESULT ``` ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}" export AILOOT_IMAGE_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"contents": [{"role": "user", "parts": [{"text": "Read labels and numbers in this image; flag unreadable text."}]}]}') import base64 f=Path(os.environ["AILOOT_IMAGE_FILE"]) if not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image") raw=f.read_bytes() mime="image/png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "image/jpeg" if raw.startswith(b"\xff\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None if not mime:raise SystemExit("Use PNG JPEG or WebP") b64=base64.b64encode(raw).decode() p["contents"][0]["parts"].append({"inlineData":{"mimeType":mime,"data":b64}}) Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1beta/models/gemini-2.5-flash-thinking:generateContent \ -H "x-goog-api-key: $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(json.loads(Path("result.json").read_text(encoding="utf-8"))) PY_RESULT ``` ```python from google import genai from google.genai import types import os if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client = genai.Client( api_key=os.environ["AILOOT_API_KEY"], http_options=types.HttpOptions(base_url="https://api.ailoot.ai"), ) resp = client.models.generate_content(model="gemini-2.5-flash-thinking", contents="Explain the difference between an observation and a hypothesis in three sentences.") import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(resp.to_json_dict()) ``` ```js import { GoogleGenAI } from "@google/genai"; if (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request"); const ai = new GoogleGenAI({ apiKey: process.env.AILOOT_API_KEY, httpOptions: { baseUrl: "https://api.ailoot.ai" } }); const resp = await ai.models.generateContent({ model: "gemini-2.5-flash-thinking", contents: "Explain the difference between an observation and a hypothesis in three sentences." }); import { writeFileSync } from "node:fs"; function saveResult(data, stem = "result") { writeFileSync(stem + ".json", JSON.stringify(data, null, 2)); console.log(JSON.stringify(data, null, 2)); const saveBlob = (encoded, suffix, label) => { const raw = Buffer.from(encoded, "base64"); const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix; const file = `${stem}-${label}.${ext}`; writeFileSync(file, raw); console.log("Saved", file); }; for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block)); for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {})); for (const [i, item] of (data.output || []).entries()) { console.log("Output", i, JSON.stringify(item)); if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`); } for (const [ci, candidate] of (data.candidates || []).entries()) { for (const [pi, part] of (candidate.content?.parts || []).entries()) { console.log("Candidate/part", ci, pi, JSON.stringify(part)); const blob = part.inlineData || part.inline_data; if (blob?.data) { const mime = blob.mimeType || blob.mime_type; const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin"; saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`); } } } } saveResult(resp); ``` ```python from google import genai from google.genai import types import os from pathlib import Path if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client=genai.Client(api_key=os.environ["AILOOT_API_KEY"],http_options=types.HttpOptions(base_url="https://api.ailoot.ai")) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) count=0 with Path("stream-events.jsonl").open("w",encoding="utf-8") as log: for chunk in client.models.generate_content_stream(model='gemini-2.5-flash-thinking',contents="Explain observations and hypotheses in three sentences."): payload=chunk.to_json_dict() log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush() save_result(payload,"stream-chunk-"+str(count)) count+=1 ``` ### 接收並儲存結果 #### Ailoot · Gemini generateContent json 或支援的串流 ##### 保留所有已完成的結果 請保留所有完整傳回的回應、檔案與內容區塊。 保留所有候選項與部分，包括函式呼叫、思考簽章與用量；依序組合串流片段。 ##### 需要檢查原始回應時 保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。 回應欄位 | 欄位 | 類型 | | --- | --- | | 欄位`responseId` | 類型string | | 欄位`modelVersion` | 類型string | | 欄位`candidates[].content.parts[]` | 類型text\|inlineData\|functionCall\|other part | | 欄位`candidates[].finishReason` | 類型string | | 欄位`usageMetadata` | 類型object | 錯誤與後續步驟 | 回應 | 條件 | 下一步 | | --- | --- | --- | | 回應400 · `invalid_request_error` | 條件必要欄位、素材表示方式或參數值無效 | 下一步提出新的建立請求前，先修正指定欄位。 | ### 別名 #### 模型別名 **Ailoot** [`gemini-2.5-flash-thinking`](https://ailoot.ai/models/zh-hant-tw/#m=gemini-2.5-flash-thinking&route=Core&caller=gemini-2.5-flash-thinking&fmt=gemini) #### 方法路徑別名 請使用上方列出的 API 方法路徑。 #### 相關呼叫用 ID [`gemini-2.5-flash-thinking`](https://ailoot.ai/models/zh-hant-tw/#m=gemini-2.5-flash-thinking&route=Core&caller=gemini-2.5-flash-thinking&fmt=gemini) FAQ · Gemini 2.5 Flash Thinking 可以使用哪些輸入與結果？ `POST /v1/messages` · `gemini-2.5-flash-thinking`: `text`, `image` → `text` `POST /v1beta/models/{model}:generateContent` · `gemini-2.5-flash-thinking`: `text`, `image` → `text` 請求使用哪些欄位？ `POST /v1/messages` · `gemini-2.5-flash-thinking`: `model`, `messages`, `system`, `max_tokens`, `stream`, `metadata` `POST /v1beta/models/{model}:generateContent` · `gemini-2.5-flash-thinking`: `contents`, `systemInstruction`, `sessionId` 適用哪些限制？ `POST /v1/messages` · `gemini-2.5-flash-thinking`: `ctx`: `1048576`; `max_out`: `65536`; `messages.min_items`: `1`; `max_tokens.minimum`: `1` `POST /v1beta/models/{model}:generateContent` · `gemini-2.5-flash-thinking`: `ctx`: `1048576`; `max_out`: `65536`; `contents.min_items`: `1` 將 Ailoot 串接 Claude Code、OpenCode、Hermes 或自己的應用程式。 ## 公司及其專案組合 公司及其專案組合：數百萬客戶，每月銷售額達數十億。 ## 優惠購買 token。 訂閱優惠適合持續工作，折扣碼購買 token 最高可折 50%。 訂閱 為定期請求選擇優惠方案。 最高 50% 折扣碼 購買時輸入代碼，價格依活動重算。 歷史中的費用 每次請求保存模型、token 與金額。 [選擇訂閱](https://ailoot.ai/docs/zh-hant-tw/billing/subscriptions/) · [查看模型價格](https://ailoot.ai/models/zh-hant-tw/) ## 將 API 加入 你銷售的產品。 依 Ailoot 正式服務條款與授權合約串接 SaaS、應用程式與機器人；轉售請申請經銷授權。 商用應用程式 在付費功能加入文字、圖片、影片與聲音生成。 經銷授權 提供專案說明與存取方式，要求書面使用和轉售條件。 網站文件 串接前可閱讀正式服務條款、授權合約與資料處理政策。 [申請經銷授權](mailto:support@ailoot.ai) · [正式服務條款與授權合約](https://ailoot.ai/legal/offer?lang=zh-hant-tw) ## Ailoot · 公司及其專案組合 Ailoot以累積的營運經驗、廣大的客戶群、穩定的服務及持續的KPI管理為基礎。 公司及其專案組合：數百萬客戶，每月銷售額達數十億。 Ailoot將這些營運經驗用於API存取，讓客戶的產品、代理、應用程式及自動化流程使用AI功能。