文生图 · nano-banana-2
用文本提示词直接生成图片，使用 Google Gemini 兼容接口，响应中以 base64 形式返回 PNG。
</>
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接口信息
POST /v1beta/models/nano-banana-2:generateContent
API 地址
https://aitkapi.com/v1beta/models/nano-banana-2:generateContent?key=YOUR_API_KEY
请求方式
POST
响应方式
同步返回 JSON（图片 base64 在 candidates[0].content.parts[].inlineData.data）
⚡
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调用示例
# 文生图：nano-banana-2（Gemini 原生协议，参数包在 generationConfig.imageConfig）
curl -X POST "https://aitkapi.com/v1beta/models/nano-banana-2:generateContent?key=YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [{ "text": "一只可爱的猫咪在草地上玩耍" }]
}],
"generationConfig": {
"imageConfig": { "aspectRatio": "1:1", "imageSize": "1K" }
}
}' -o response.json
import base64, requests
api_key = "YOUR_API_KEY"
url = f"https://aitkapi.com/v1beta/models/nano-banana-2:generateContent?key={api_key}"
payload = {
"contents": [{
"parts": [{"text": "一只可爱的猫咪在草地上玩耍"}]
}],
"generationConfig": {
"imageConfig": {"aspectRatio": "1:1", "imageSize": "1K"}
},
}
resp = requests.post(url, json=payload, timeout=300).json()
for i, part in enumerate(resp["candidates"][0]["content"]["parts"]):
if "inlineData" in part:
open(f"out_{i}.png", "wb").write(base64.b64decode(part["inlineData"]["data"]))
import fs from "node:fs";
const apiKey = "YOUR_API_KEY";
const url = `https://aitkapi.com/v1beta/models/nano-banana-2:generateContent?key=${apiKey}`;
const res = await fetch(url, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
contents: [{ parts: [{ text: "一只可爱的猫咪在草地上玩耍" }] }],
generationConfig: {
imageConfig: { aspectRatio: "1:1", imageSize: "1K" },
},
}),
});
const data = await res.json();
data.candidates[0].content.parts.forEach((p, i) => {
if (p.inlineData) fs.writeFileSync(`out_${i}.png`, Buffer.from(p.inlineData.data, "base64"));
});
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参数说明
文生图 · nano-banana-pro
高质量版本，支持 1K / 2K / 4K，分辨率越高生成时间越长。
</>
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接口信息
POST /v1beta/models/nano-banana-pro:generateContent
API 地址
https://aitkapi.com/v1beta/models/nano-banana-pro:generateContent?key=YOUR_API_KEY
请求方式
POST
响应方式
同步返回 JSON（图片 base64 在 candidates[0].content.parts[].inlineData.data）
⚡
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调用示例
# 文生图：nano-banana-pro（Gemini 原生协议；imageSize 支持 1K/2K/4K）
curl -X POST "https://aitkapi.com/v1beta/models/nano-banana-pro:generateContent?key=YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [{ "text": "一只猫咪在电竞椅上舔毛" }]
}],
"generationConfig": {
"imageConfig": { "aspectRatio": "1:1", "imageSize": "2K" }
}
}' -o response.json
import base64, requests
api_key = "YOUR_API_KEY"
url = f"https://aitkapi.com/v1beta/models/nano-banana-pro:generateContent?key={api_key}"
payload = {
"contents": [{
"parts": [{"text": "一只猫咪在电竞椅上舔毛"}]
}],
"generationConfig": {
"imageConfig": {"aspectRatio": "1:1", "imageSize": "2K"}
},
}
resp = requests.post(url, json=payload, timeout=300).json()
for i, part in enumerate(resp["candidates"][0]["content"]["parts"]):
if "inlineData" in part:
open(f"cat_{i}.png", "wb").write(base64.b64decode(part["inlineData"]["data"]))
import fs from "node:fs";
const apiKey = "YOUR_API_KEY";
const url = `https://aitkapi.com/v1beta/models/nano-banana-pro:generateContent?key=${apiKey}`;
const res = await fetch(url, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
contents: [{ parts: [{ text: "一只猫咪在电竞椅上舔毛" }] }],
generationConfig: {
imageConfig: { aspectRatio: "1:1", imageSize: "2K" },
},
}),
});
const data = await res.json();
data.candidates[0].content.parts.forEach((p, i) => {
if (p.inlineData) fs.writeFileSync(`cat_${i}.png`, Buffer.from(p.inlineData.data, "base64"));
});
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参数说明
文生图 · gpt-image-2-vip
OpenAI Images 兼容接口，支持 1K / 2K / 4K，同步返回图片 URL。
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接口信息
POST /v1/images/generations
API 地址
https://aitkapi.com/v1/images/generations
请求方式
POST
响应方式
同步返回 JSON（OpenAI Images 兼容，data[].url 为图片地址）
请求头 Headers
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
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调用示例
# 文生图：gpt-image-2-vip · 2K 猫咪舔毛
curl -X POST "https://aitkapi.com/v1/images/generations" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-image-2-vip",
"prompt": "A cute cat licking its fur, photorealistic, 2K",
"size": "2048x2048",
"n": 1
}'
import requests
url = "https://aitkapi.com/v1/images/generations"
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
}
payload = {
"model": "gpt-image-2-vip",
"prompt": "A cute cat licking its fur, photorealistic, 2K",
"size": "2048x2048",
"n": 1,
}
data = requests.post(url, headers=headers, json=payload, timeout=300).json()
print(data["data"][0]["url"])
const res = await fetch("https://aitkapi.com/v1/images/generations", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "gpt-image-2-vip",
prompt: "A cute cat licking its fur, photorealistic, 2K",
size: "2048x2048",
n: 1,
}),
});
const data = await res.json();
console.log(data.data[0].url);
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参数说明
文生图 · gpt-image-2-all
OpenAI Images 兼容接口，通用版本，仅支持 1K 分辨率。
</>
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接口信息
POST /v1/images/generations
API 地址
https://aitkapi.com/v1/images/generations
请求方式
POST
响应方式
同步返回 JSON（OpenAI Images 兼容，data[].url 为图片地址）
请求头 Headers
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
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调用示例
# 文生图：gpt-image-2-all
curl -X POST "https://aitkapi.com/v1/images/generations" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-image-2-all",
"prompt": "A cute cat licking its fur, photorealistic",
"size": "1024x1024",
"n": 1
}'
import requests
url = "https://aitkapi.com/v1/images/generations"
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
}
payload = {
"model": "gpt-image-2-all",
"prompt": "A cute cat licking its fur, photorealistic",
"size": "1024x1024",
"n": 1,
}
data = requests.post(url, headers=headers, json=payload, timeout=300).json()
print(data["data"][0]["url"])
const res = await fetch("https://aitkapi.com/v1/images/generations", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "gpt-image-2-all",
prompt: "A cute cat licking its fur, photorealistic",
size: "1024x1024",
n: 1,
}),
});
const data = await res.json();
console.log(data.data[0].url);
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参数说明
图生图 · nano-banana-2
在
contents[].parts 里同时塞入文本与参考图（inline_data base64），按提示词改写。
</>
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接口信息
POST /v1beta/models/nano-banana-2:generateContentAPI 地址
https://aitkapi.com/v1beta/models/nano-banana-2:generateContent?key=YOUR_API_KEY
说明
在
contents[].parts 中加入一个 inline_data（参考图的 base64）即视为图生图
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调用示例
# 图生图：nano-banana-2，参考图以 base64 inline_data 上传
# 先把本地图片转为 base64：B64=$(base64 -i ./ref_cat.png)
curl -X POST "https://aitkapi.com/v1beta/models/nano-banana-2:generateContent?key=YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d "{
\"contents\": [{
\"parts\": [
{ \"text\": \"把图中的猫改成在睡觉\" },
{ \"inline_data\": { \"mime_type\": \"image/png\", \"data\": \"$B64\" } }
]
}],
\"generationConfig\": { \"imageConfig\": { \"imageSize\": \"1K\" } }
}" -o response.json
import base64, requests
api_key = "YOUR_API_KEY"
url = f"https://aitkapi.com/v1beta/models/nano-banana-2:generateContent?key={api_key}"
with open("./ref_cat.png", "rb") as f:
img_b64 = base64.b64encode(f.read()).decode()
payload = {
"contents": [{
"parts": [
{"text": "把图中的猫改成在睡觉"},
{"inline_data": {"mime_type": "image/png", "data": img_b64}},
]
}],
"generationConfig": {"imageConfig": {"imageSize": "1K"}},
}
resp = requests.post(url, json=payload, timeout=300).json()
print(resp)
import fs from "node:fs";
const apiKey = "YOUR_API_KEY";
const imgB64 = fs.readFileSync("./ref_cat.png").toString("base64");
const res = await fetch(`https://aitkapi.com/v1beta/models/nano-banana-2:generateContent?key=${apiKey}`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
contents: [{
parts: [
{ text: "把图中的猫改成在睡觉" },
{ inline_data: { mime_type: "image/png", data: imgB64 } },
],
}],
generationConfig: { imageConfig: { imageSize: "1K" } },
}),
});
console.log(await res.json());
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参数说明
图生图 · nano-banana-pro
高质量图生图，在
contents[].parts 中放入文本与一张或多张参考图（inline_data base64）。
</>
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接口信息
POST /v1beta/models/nano-banana-pro:generateContentAPI 地址
https://aitkapi.com/v1beta/models/nano-banana-pro:generateContent?key=YOUR_API_KEY
说明
在
contents[].parts 中加入一个或多个 inline_data（参考图的 base64）即视为图生图
⚡
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调用示例
# 图生图：nano-banana-pro，参考图以 base64 inline_data 上传
# 先把本地图片转为 base64：B64=$(base64 -i ./ref_cat.png)
curl -X POST "https://aitkapi.com/v1beta/models/nano-banana-pro:generateContent?key=YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d "{
\"contents\": [{
\"parts\": [
{ \"text\": \"保持构图，把猫换成柴犬\" },
{ \"inline_data\": { \"mime_type\": \"image/png\", \"data\": \"$B64\" } }
]
}],
\"generationConfig\": { \"imageConfig\": { \"imageSize\": \"2K\" } }
}" -o response.json
import base64, requests
api_key = "YOUR_API_KEY"
url = f"https://aitkapi.com/v1beta/models/nano-banana-pro:generateContent?key={api_key}"
with open("./ref_cat.png", "rb") as f:
img_b64 = base64.b64encode(f.read()).decode()
payload = {
"contents": [{
"parts": [
{"text": "保持构图，把猫换成柴犬"},
{"inline_data": {"mime_type": "image/png", "data": img_b64}},
]
}],
"generationConfig": {"imageConfig": {"imageSize": "2K"}},
}
resp = requests.post(url, json=payload, timeout=300).json()
print(resp)
import fs from "node:fs";
const apiKey = "YOUR_API_KEY";
const imgB64 = fs.readFileSync("./ref_cat.png").toString("base64");
const res = await fetch(`https://aitkapi.com/v1beta/models/nano-banana-pro:generateContent?key=${apiKey}`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
contents: [{
parts: [
{ text: "保持构图，把猫换成柴犬" },
{ inline_data: { mime_type: "image/png", data: imgB64 } },
],
}],
generationConfig: { imageConfig: { imageSize: "2K" } },
}),
});
console.log(await res.json());
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参数说明
图生图 · gpt-image-2-vip
基于参考图生成新图，OpenAI Images Edits 兼容，支持 1K / 2K / 4K。
</>
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接口信息
POST /v1/images/edits
API 地址
https://aitkapi.com/v1/images/edits
请求方式
POST
响应方式
同步返回 JSON（data[].url 为图片地址）
请求头 Headers
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "multipart/form-data"
}
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调用示例
# 图生图：gpt-image-2-vip · 2K
curl -X POST "https://aitkapi.com/v1/images/edits" \
-H "Authorization: Bearer YOUR_API_KEY" \
-F "model=gpt-image-2-vip" \
-F "image=@./ref_cat.png" \
-F "prompt=Same cat now sleeping peacefully, photorealistic" \
-F "size=2048x2048" \
-F "n=1"
import requests
url = "https://aitkapi.com/v1/images/edits"
headers = { "Authorization": "Bearer YOUR_API_KEY" }
files = { "image": open("./ref_cat.png", "rb") }
data = {
"model": "gpt-image-2-vip",
"prompt": "Same cat now sleeping peacefully, photorealistic",
"size": "2048x2048",
"n": 1,
}
result = requests.post(url, headers=headers, files=files, data=data, timeout=300).json()
print(result["data"][0]["url"])
import fs from "node:fs";
const form = new FormData();
form.append("model", "gpt-image-2-vip");
form.append("prompt", "Same cat now sleeping peacefully");
form.append("size", "2048x2048");
form.append("n", "1");
form.append("image", new Blob([fs.readFileSync("./ref_cat.png")]), "ref_cat.png");
const res = await fetch("https://aitkapi.com/v1/images/edits", {
method: "POST",
headers: { "Authorization": "Bearer YOUR_API_KEY" },
body: form,
});
const data = await res.json();
console.log(data.data[0].url);
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参数说明
图生图 · gpt-image-2-all
基于参考图生成新图，OpenAI Images Edits 兼容，仅支持 1K 分辨率。
</>
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接口信息
POST /v1/images/edits
API 地址
https://aitkapi.com/v1/images/edits
请求方式
POST
响应方式
同步返回 JSON（data[].url 为图片地址）
请求头 Headers
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "multipart/form-data"
}
⚡
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调用示例
# 图生图：把参考图里的猫改成在睡觉
curl -X POST "https://aitkapi.com/v1/images/edits" \
-H "Authorization: Bearer YOUR_API_KEY" \
-F "model=gpt-image-2-all" \
-F "image=@./ref_cat.png" \
-F "prompt=Same cat now sleeping peacefully, curled up, eyes closed" \
-F "size=1024x1024" \
-F "n=1"
import requests
url = "https://aitkapi.com/v1/images/edits"
headers = { "Authorization": "Bearer YOUR_API_KEY" }
files = { "image": open("./ref_cat.png", "rb") }
data = {
"model": "gpt-image-2-all",
"prompt": "Same cat now sleeping peacefully, curled up, eyes closed",
"size": "1024x1024",
"n": 1,
}
result = requests.post(url, headers=headers, files=files, data=data, timeout=300).json()
print(result["data"][0]["url"])
import fs from "node:fs";
const form = new FormData();
form.append("model", "gpt-image-2-all");
form.append("prompt", "Same cat now sleeping peacefully");
form.append("size", "1024x1024");
form.append("n", "1");
form.append("image", new Blob([fs.readFileSync("./ref_cat.png")]), "ref_cat.png");
const res = await fetch("https://aitkapi.com/v1/images/edits", {
method: "POST",
headers: { "Authorization": "Bearer YOUR_API_KEY" },
body: form,
});
const data = await res.json();
console.log(data.data[0].url);
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参数说明
文生视频 · seedance-2-0
用文本提示词生成短视频。任务异步处理，提交后轮询任务状态，完成后通过代理链接下载 MP4。
</>
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接口信息
POST /v1/video/generations提交任务
POST https://aitkapi.com/v1/video/generations
查询任务
GET https://aitkapi.com/v1/video/generations/{task_id}
下载视频（任务完成后）
GET https://aitkapi.com/v1/videos/{task_id}/content
请求头
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
响应方式
异步：提交返回 task_id → 轮询状态（queued / IN_PROGRESS / SUCCESS / FAILED）→ SUCCESS 后用代理链接下载 MP4（请求需带 Authorization）
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调用示例
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参数说明
图生视频 · seedance-2-0
在文生视频基础上传入首帧图片（URL 或 base64），让画面"动起来"。其他流程与文生视频一致。
</>
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接口信息
POST /v1/video/generations提交任务
POST https://aitkapi.com/v1/video/generations
查询任务
GET https://aitkapi.com/v1/video/generations/{task_id}
下载视频
GET https://aitkapi.com/v1/videos/{task_id}/content
请求头
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
响应方式
异步：与文生视频流程一致，提交时多传 image 字段（URL 或 data URI base64）
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调用示例
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参数说明
文生视频 · seedance-2-0-fast
seedance-2-0 的快速版本，生成更快。接口与字段完全一致，仅
model 改为 seedance-2-0-fast。
</>
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接口信息
POST /v1/video/generations提交任务
POST https://aitkapi.com/v1/video/generations
查询任务
GET https://aitkapi.com/v1/video/generations/{task_id}
下载视频（任务完成后）
GET https://aitkapi.com/v1/videos/{task_id}/content
请求头
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
响应方式
异步：提交返回 task_id → 轮询状态（queued / IN_PROGRESS / SUCCESS / FAILED）→ SUCCESS 后用代理链接下载 MP4（请求需带 Authorization）
⚡
⌃
调用示例
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⌃
参数说明
图生视频 · seedance-2-0-fast
seedance-2-0-fast 的图生视频版本。在文生视频基础上传入首帧图片（URL 或 base64），其他流程一致。
</>
⌃
接口信息
POST /v1/video/generations提交任务
POST https://aitkapi.com/v1/video/generations
查询任务
GET https://aitkapi.com/v1/video/generations/{task_id}
下载视频
GET https://aitkapi.com/v1/videos/{task_id}/content
请求头
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
响应方式
异步：与文生视频流程一致，提交时多传 image 字段（URL 或 data URI base64）
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调用示例
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⌃
参数说明
文字生成 · gemini-3.5-flash
OpenAI Chat Completions 兼容接口，用于多轮对话与文本生成。
</>
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接口信息
POST /v1/chat/completionsAPI 地址
https://aitkapi.com/v1/chat/completions
请求方式
POST
请求头
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
⚡
⌃
调用示例
curl -X POST "https://aitkapi.com/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-3.5-flash",
"messages": [{"role":"user","content":"用一句话介绍你自己"}]
}'
import requests
resp = requests.post(
"https://aitkapi.com/v1/chat/completions",
headers={"Authorization": "Bearer YOUR_API_KEY"},
json={
"model": "gemini-3.5-flash",
"messages": [{"role": "user", "content": "用一句话介绍你自己"}],
},
timeout=60,
).json()
print(resp["choices"][0]["message"]["content"])
const res = await fetch("https://aitkapi.com/v1/chat/completions", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "gemini-3.5-flash",
messages: [{ role: "user", content: "用一句话介绍你自己" }],
}),
});
const data = await res.json();
console.log(data.choices[0].message.content);
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参数说明
文字生成 · claude
Anthropic Claude 系列模型，支持 Anthropic 原生 Messages 协议，也兼容 OpenAI Chat Completions。仅需要替换
model 字段即可在不同版本之间切换。
</>
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接口信息（Anthropic 原生）
POST /v1/messagesAPI 地址
https://aitkapi.com/v1/messages
请求方式
POST
请求头
{
"x-api-key": "YOUR_API_KEY",
"anthropic-version": "2023-06-01",
"Content-Type": "application/json"
}
提示：也可以通过
POST /v1/chat/completions（Authorization: Bearer YOUR_API_KEY）以 OpenAI 兼容格式调用，下面调用示例提供了两套写法。
⚡
⌃
调用示例（Anthropic 原生）
curl -X POST "https://aitkapi.com/v1/messages" \
-H "x-api-key: YOUR_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-H "Content-Type: application/json" \
-d '{
"model": "claude-opus-4-8",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "用一句话介绍你自己"}
]
}'
import anthropic
client = anthropic.Anthropic(
api_key="YOUR_API_KEY",
base_url="https://aitkapi.com",
)
msg = client.messages.create(
model="claude-opus-4-8",
max_tokens=1024,
messages=[{"role": "user", "content": "用一句话介绍你自己"}],
)
print(msg.content[0].text)
import Anthropic from "@anthropic-ai/sdk";
const client = new Anthropic({
apiKey: "YOUR_API_KEY",
baseURL: "https://aitkapi.com",
});
const msg = await client.messages.create({
model: "claude-opus-4-8",
max_tokens: 1024,
messages: [{ role: "user", content: "用一句话介绍你自己" }],
});
console.log(msg.content[0].text);
⚡
⌃
调用示例（OpenAI 兼容）
/v1/chat/completionscurl -X POST "https://aitkapi.com/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "claude-opus-4-8",
"messages": [{"role":"user","content":"用一句话介绍你自己"}]
}'
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://aitkapi.com/v1",
)
resp = client.chat.completions.create(
model="claude-opus-4-8",
messages=[{"role": "user", "content": "用一句话介绍你自己"}],
)
print(resp.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
apiKey: "YOUR_API_KEY",
baseURL: "https://aitkapi.com/v1",
});
const resp = await client.chat.completions.create({
model: "claude-opus-4-8",
messages: [{ role: "user", content: "用一句话介绍你自己" }],
});
console.log(resp.choices[0].message.content);
≡
⌃
参数说明
文字生成 · gpt-5.5
OpenAI Chat Completions 兼容接口，最新一代 GPT 模型，适合多轮对话、长上下文与代码任务。
</>
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接口信息
POST /v1/chat/completionsAPI 地址
https://aitkapi.com/v1/chat/completions
请求方式
POST
请求头
{
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
⚡
⌃
调用示例
curl -X POST "https://aitkapi.com/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.5",
"messages": [{"role":"user","content":"用一句话介绍你自己"}]
}'
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://aitkapi.com/v1",
)
resp = client.chat.completions.create(
model="gpt-5.5",
messages=[{"role": "user", "content": "用一句话介绍你自己"}],
)
print(resp.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
apiKey: "YOUR_API_KEY",
baseURL: "https://aitkapi.com/v1",
});
const resp = await client.chat.completions.create({
model: "gpt-5.5",
messages: [{ role: "user", content: "用一句话介绍你自己" }],
});
console.log(resp.choices[0].message.content);
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