Përputhshmëria me OpenAI

Modelet Gemini janë të arritshme duke përdorur bibliotekat OpenAI (Python dhe TypeScript / Javascript) së bashku me REST API, duke përditësuar tre rreshta kodi dhe duke përdorur çelësin tuaj Gemini API . Nëse nuk i përdorni tashmë bibliotekat OpenAI, ju rekomandojmë që të telefononi direkt Gemini API .

Python 

from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

response = client.chat.completions.create(
    model="gemini-3.7-flash",
    messages=[
        {   "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user",
            "content": "Explain to me how AI works"
        }
    ]
)

print(response.choices[0].message)

JavaScript 

import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: "GEMINI_API_KEY",
    baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/"
});

const response = await openai.chat.completions.create({
    model: "gemini-3.7-flash",
    messages: [
        {   role: "system",
            content: "You are a helpful assistant." 
        },
        {
            role: "user",
            content: "Explain to me how AI works",
        },
    ],
});

console.log(response.choices[0].message);

PUSHTIM 

curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $GEMINI_API_KEY" \
  -d '{
    "model": "gemini-3.7-flash",
    "messages": [
      {
        "role": "user",
        "content": "Explain to me how AI works"
      }
    ]
  }'

Çfarë ndryshoi? Vetëm tre rreshta!

  • api_key="GEMINI_API_KEY" : Zëvendësoni " GEMINI_API_KEY " me çelësin tuaj aktual Gemini API, të cilin mund ta merrni në Google AI Studio .

  • base_url="https://generativelanguage.googleapis.com/v1beta/openai/" : Kjo i tregon bibliotekës OpenAI të dërgojë kërkesa te pika fundore e API-t Gemini në vend të URL-së së parazgjedhur.

  • model="gemini-3.7-flash" : Zgjidhni një model të pajtueshëm Gemini

Të menduarit

Modelet Gemini janë të trajnuara për të menduar përmes problemeve komplekse, duke çuar në një arsyetim të përmirësuar ndjeshëm. API-ja Gemini vjen me parametra të të menduarit të cilët i japin kontroll të imët mbi mënyrën se si do të mendojë modeli.

Modele të ndryshme Gemini kanë konfigurime të ndryshme arsyetimi, mund të shihni se si ato përputhen me përpjekjet e arsyetimit të OpenAI si më poshtë:

reasoning_effort (OpenAI) thinking_level (Gemini 3.1 Pro) thinking_level (Gemini 3.1 Flash-Lite) thinking_level (Binjakët 3 Flash) thinking_budget (Binjakët 2.5)
minimal low minimal minimal 1,024
low low low low 1,024
medium medium medium medium 8,192
high high high high 24,576

Nëse nuk specifikohet reasoning_effort , Gemini përdor nivelin ose buxhetin e parazgjedhur të modelit.

Nëse doni të çaktivizoni të menduarit, mund ta vendosni reasoning_effort në "none" për modelet 2.5. Arsyetimi nuk mund të çaktivizohet për modelet Gemini 2.5 Pro ose 3.

Python 

from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

response = client.chat.completions.create(
    model="gemini-3.7-flash",
    reasoning_effort="low",
    messages=[
        {   "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user",
            "content": "Explain to me how AI works"
        }
    ]
)

print(response.choices[0].message)

JavaScript 

import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: "GEMINI_API_KEY",
    baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/"
});

const response = await openai.chat.completions.create({
    model: "gemini-3.7-flash",
    reasoning_effort: "low",
    messages: [
        {   role: "system",
            content: "You are a helpful assistant." 
        },
        {
            role: "user",
            content: "Explain to me how AI works",
        },
    ],
});

console.log(response.choices[0].message);

PUSHTIM 

curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $GEMINI_API_KEY" \
  -d '{
    "model": "gemini-3.7-flash",
    "reasoning_effort": "low",
    "messages": [
      {
        "role": "user",
        "content": "Explain to me how AI works"
      }
    ]
  }'

Modelet e të menduarit Gemini prodhojnë gjithashtu përmbledhje mendimesh . Mund të përdorni fushën extra_body për të përfshirë fushat Gemini në kërkesën tuaj.

Vini re se reasoning_effort dhe thinking_level / thinking_budget mbivendosen me njëra-tjetrën, kështu që ato nuk mund të përdoren në të njëjtën kohë.

Python 

from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

response = client.chat.completions.create(
    model="gemini-3.7-flash",
    messages=[{"role": "user", "content": "Explain to me how AI works"}],
    extra_body={
      'extra_body': {
        "google": {
          "thinking_config": {
            "thinking_level": "low",
            "include_thoughts": True
          }
        }
      }
    }
)

print(response.choices[0].message)

JavaScript 

import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: "GEMINI_API_KEY",
    baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/"
});

const response = await openai.chat.completions.create({
    model: "gemini-3.7-flash",
    messages: [{role: "user", content: "Explain to me how AI works",}],
    extra_body: {
      "google": {
        "thinking_config": {
          "thinking_level": "low",
          "include_thoughts": true
        }
      }
    }
});

console.log(response.choices[0].message);

PUSHTIM 

curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer GEMINI_API_KEY" \
  -d '{
      "model": "gemini-3.7-flash",
        "messages": [{"role": "user", "content": "Explain to me how AI works"}],
        "extra_body": {
          "google": {
            "thinking_config": {
              "thinking_level": "low",
              "include_thoughts": true
            }
          }
        }
      }'

Gemini 3 mbështet përputhshmërinë me OpenAI për nënshkrimet e mendimeve në API-të e përfundimit të bisedave. Mund ta gjeni shembullin e plotë në faqen e nënshkrimeve të mendimeve .

Transmetim

API-ja Gemini mbështet përgjigjet e transmetimit .

Python 

from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

response = client.chat.completions.create(
  model="gemini-3.7-flash",
  messages=[
    {
        "role": "system",
        "content": "You are a helpful assistant."
    },
    {   "role": "user",
        "content": "Hello!"
    }
  ],
  stream=True
)

for chunk in response:
    print(chunk.choices[0].delta)

JavaScript 

import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: "GEMINI_API_KEY",
    baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/"
});

async function main() {
  const completion = await openai.chat.completions.create({
    model: "gemini-3.7-flash",
    messages: [
      {
          "role": "system",
          "content": "You are a helpful assistant."
      },
      {
          "role": "user",
          "content": "Hello!"
      }
    ],
    stream: true,
  });

  for await (const chunk of completion) {
    console.log(chunk.choices[0].delta.content);
  }
}

main();

PUSHTIM 

curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer GEMINI_API_KEY" \
  -d '{
      "model": "gemini-3.7-flash",
      "messages": [
          {"role": "user", "content": "Explain to me how AI works"}
      ],
      "stream": true
    }'

Thirrja e funksionit

Thirrja e funksioneve e bën më të lehtë për ju marrjen e rezultateve të të dhënave të strukturuara nga modelet gjeneruese dhe mbështetet në Gemini API .

Python 

from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

tools = [
  {
    "type": "function",
    "function": {
      "name": "get_weather",
      "description": "Get the weather in a given location",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {
            "type": "string",
            "description": "The city and state, e.g. Chicago, IL",
          },
          "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
        },
        "required": ["location"],
      },
    }
  }
]

messages = [{"role": "user", "content": "What's the weather like in Chicago today?"}]
response = client.chat.completions.create(
  model="gemini-3.7-flash",
  messages=messages,
  tools=tools,
  tool_choice="auto"
)

print(response)

JavaScript 

import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: "GEMINI_API_KEY",
    baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/"
});

async function main() {
  const messages = [{"role": "user", "content": "What's the weather like in Chicago today?"}];
  const tools = [
      {
        "type": "function",
        "function": {
          "name": "get_weather",
          "description": "Get the weather in a given location",
          "parameters": {
            "type": "object",
            "properties": {
              "location": {
                "type": "string",
                "description": "The city and state, e.g. Chicago, IL",
              },
              "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
            },
            "required": ["location"],
          },
        }
      }
  ];

  const response = await openai.chat.completions.create({
    model: "gemini-3.7-flash",
    messages: messages,
    tools: tools,
    tool_choice: "auto",
  });

  console.log(response);
}

main();

PUSHTIM 

curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer GEMINI_API_KEY" \
-d '{
  "model": "gemini-3.7-flash",
  "messages": [
    {
      "role": "user",
      "content": "What'\''s the weather like in Chicago today?"
    }
  ],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get the current weather in a given location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state, e.g. Chicago, IL"
            },
            "unit": {
              "type": "string",
              "enum": ["celsius", "fahrenheit"]
            }
          },
          "required": ["location"]
        }
      }
    }
  ],
  "tool_choice": "auto"
}'

Kuptimi i imazhit

Modelet Gemini janë multimodale në thelb dhe ofrojnë performancën më të mirë në klasën e tyre në shumë detyra të zakonshme të shikimit .

Python 

import base64
from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

# Function to encode the image
def encode_image(image_path):
  with open(image_path, "rb") as image_file:
    return base64.b64encode(image_file.read()).decode('utf-8')

# Getting the base64 string
base64_image = encode_image("Path/to/agi/image.jpeg")

response = client.chat.completions.create(
  model="gemini-3.7-flash",
  messages=[
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What is in this image?",
        },
        {
          "type": "image_url",
          "image_url": {
            "url":  f"data:image/jpeg;base64,{base64_image}"
          },
        },
      ],
    }
  ],
)

print(response.choices[0])

JavaScript 

import OpenAI from "openai";
import fs from 'fs/promises';

const openai = new OpenAI({
  apiKey: "GEMINI_API_KEY",
  baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/"
});

async function encodeImage(imagePath) {
  try {
    const imageBuffer = await fs.readFile(imagePath);
    return imageBuffer.toString('base64');
  } catch (error) {
    console.error("Error encoding image:", error);
    return null;
  }
}

async function main() {
  const imagePath = "Path/to/agi/image.jpeg";
  const base64Image = await encodeImage(imagePath);

  const messages = [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What is in this image?",
        },
        {
          "type": "image_url",
          "image_url": {
            "url": `data:image/jpeg;base64,${base64Image}`
          },
        },
      ],
    }
  ];

  try {
    const response = await openai.chat.completions.create({
      model: "gemini-3.7-flash",
      messages: messages,
    });

    console.log(response.choices[0]);
  } catch (error) {
    console.error("Error calling Gemini API:", error);
  }
}

main();

PUSHTIM 

bash -c '
  base64_image=$(base64 -i "Path/to/agi/image.jpeg");
  curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer GEMINI_API_KEY" \
    -d "{
      \"model\": \"gemini-3.7-flash\",
      \"messages\": [
        {
          \"role\": \"user\",
          \"content\": [
            { \"type\": \"text\", \"text\": \"What is in this image?\" },
            {
              \"type\": \"image_url\",
              \"image_url\": { \"url\": \"data:image/jpeg;base64,${base64_image}\" }
            }
          ]
        }
      ]
    }"
'

Gjeneroni një imazh

Gjeneroni një imazh duke përdorur gemini-2.5-flash-image ose gemini-3-pro-image-preview . Parametrat e mbështetur përfshijnë prompt , model , n , size dhe response_format . Çdo parametër tjetër që nuk është renditur këtu ose në seksionin extra_body do të injorohet në heshtje nga shtresa e përputhshmërisë.

Python 

import base64
from openai import OpenAI
from PIL import Image
from io import BytesIO

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
)

response = client.images.generate(
    model="gemini-2.5-flash-image",
    prompt="a portrait of a sheepadoodle wearing a cape",
    response_format='b64_json',
    n=1,
)

for image_data in response.data:
  image = Image.open(BytesIO(base64.b64decode(image_data.b64_json)))
  image.show()

JavaScript 

import OpenAI from "openai";

const openai = new OpenAI({
  apiKey: "GEMINI_API_KEY",
  baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/",
});

async function main() {
  const image = await openai.images.generate(
    {
      model: "gemini-2.5-flash-image",
      prompt: "a portrait of a sheepadoodle wearing a cape",
      response_format: "b64_json",
      n: 1,
    }
  );

  console.log(image.data);
}

main();

PUSHTIM 

curl "https://generativelanguage.googleapis.com/v1beta/openai/images/generations" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer GEMINI_API_KEY" \
  -d '{
        "model": "gemini-2.5-flash-image",
        "prompt": "a portrait of a sheepadoodle wearing a cape",
        "response_format": "b64_json",
        "n": 1,
      }'

Gjenero një video

Gjeneroni një video duke përdorur veo-3.1-generate-preview nëpërmjet pikës fundore /v1/videos të pajtueshme me Sora. Parametrat e nivelit të lartë të mbështetur janë prompt dhe model . Parametrat shtesë si duration_seconds , image dhe aspect_ratio duhet të kalohen me extra_body . Shihni seksionin extra_body për të gjithë parametrat e disponueshëm.

Gjenerimi i videos është një operacion afatgjatë që kthen një ID operacioni që mund ta anketoni për përfundim.

Python 

from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

# Returns a Long Running Operation (status: processing)
response = client.videos.create(
    model="veo-3.1-generate-preview",
    prompt="A cinematic drone shot of a waterfall",
)

print(f"Operation ID: {response.id}")
print(f"Status: {response.status}")

JavaScript 

import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: "GEMINI_API_KEY",
    baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/"
});

async function main() {
    // Returns a Long Running Operation (status: processing)
    const response = await openai.videos.create({
        model: "veo-3.1-generate-preview",
        prompt: "A cinematic drone shot of a waterfall",
    });

    console.log(`Operation ID: ${response.id}`);
    console.log(`Status: ${response.status}`);
}

main();

PUSHTIM 

curl "https://generativelanguage.googleapis.com/v1beta/openai/videos" \
  -H "Authorization: Bearer $GEMINI_API_KEY" \
  -F "model=veo-3.1-generate-preview" \
  -F "prompt=A cinematic drone shot of a waterfall"

Kontrolloni statusin e videos

Gjenerimi i videos është asinkron. Përdorni GET /v1/videos/{id} për të anketuar statusin dhe për të marrë URL-në përfundimtare të videos kur të përfundojë:

Python 

import time
from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

# Poll until video is ready
video_id = response.id  # From the create call
while True:
    video = client.videos.retrieve(video_id)
    if video.status == "completed":
        print(f"Video URL: {video.url}")
        break
    elif video.status == "failed":
        print(f"Generation failed: {video.error}")
        break
    print(f"Status: {video.status}. Waiting...")
    time.sleep(10)

JavaScript 

import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: "GEMINI_API_KEY",
    baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/"
});

async function main() {
    // Poll until video is ready
    const videoId = response.id;  // From the create call
    while (true) {
        const video = await openai.videos.retrieve(videoId);
        if (video.status === "completed") {
            console.log(`Video URL: ${video.url}`);
            break;
        } else if (video.status === "failed") {
            console.log(`Generation failed: ${video.error}`);
            break;
        }
        console.log(`Status: ${video.status}. Waiting...`);
        await new Promise(resolve => setTimeout(resolve, 10000));
    }
}

main();

PUSHTIM 

curl "https://generativelanguage.googleapis.com/v1beta/openai/videos/VIDEO_ID" \
  -H "Authorization: Bearer $GEMINI_API_KEY"

Kuptimi i audios

Analizoni hyrjen audio:

Python 

import base64
from openai import OpenAI

client = OpenAI(
    api_key="GEMINI_API_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

with open("/path/to/your/audio/file.wav", "rb") as audio_file:
  base64_audio = base64.b64encode(audio_file.read()).decode('utf-8')

response = client.chat.completions.create(
    model="gemini-3.7-flash",
    messages=[
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "Transcribe this audio",
        },
        {
              "type": "input_audio",
              "input_audio": {
                "data": base64_audio,
                "format": "wav"
          }
        }
      ],
    }
  ],
)

print(response.choices[0].message.content)

JavaScript 

import fs from "fs";
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "GEMINI_API_KEY",
  baseURL: "https://generativelanguage.googleapis.com/v1beta/openai/",
});

const audioFile = fs.readFileSync("/path/to/your/audio/file.wav");
const base64Audio = Buffer.from(audioFile).toString("base64");

async function main() {
  const response = await client.chat.completions.create({
    model: "gemini-3.7-flash",
    messages: [
      {
        role: "user",
        content: [
          {
            type: "text",
            text: "Transcribe this audio",
          },
          {
            type: "input_audio",
            input_audio: {
              data: base64Audio,
              format: "wav",
            },
          },
        ],
      },