תאימות ל-OpenAI

כדי לגשת למודלים של Gemini, צריך לעדכן שלוש שורות קוד ולהשתמש במפתח ה-API של Gemini וגם באמצעות ספריות OpenAI (Python ו-TypeScript או JavaScript) וגם דרך API ל-REST. אם אתם עדיין לא משתמשים בספריות של OpenAI, מומלץ להפעיל את Gemini API ישירות.

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-1.5-flash",
    n=1,
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {
            "role": "user",
            "content": "Explain to me how AI works"
        }
    ]
)

print(response.choices[0].message)

Node.js

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-1.5-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);

REST

curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer gemini_api_key" \
-d '{
    "model": "gemini-1.5-flash",
    "messages": [
        {"role": "user", "content": "Explain to me how AI works"}
    ]
    }'

סטרימינג

ה-Gemini API תומך בשידור תשובות.

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-1.5-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)

Node.js

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-1.5-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();

REST

curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer gemini_api_key" \
-d '{
    "model": "gemini-1.5-flash",
    "messages": [
        {"role": "user", "content": "Explain to me how AI works"}
    ],
    "stream": true
  }'

קריאה לפונקציה

קריאה לפונקציות מאפשרת לכם לקבל בקלות רבה יותר פלט של נתונים מובְנים ממודלים גנרטיביים, והיא נתמכת ב-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-1.5-flash",
  messages=messages,
  tools=tools,
  tool_choice="auto"
)

print(response)

Node.js

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-1.5-flash",
    messages: messages,
    tools: tools,
    tool_choice: "auto",
  });

  console.log(response);
}

main();

REST

curl "https://generativelanguage.googleapis.com/v1beta/openai/chat/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer gemini_api_key" \
-d '{
  "model": "gemini-1.5-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"
}'

הטמעות

הטמעות טקסט מודדות את הקשר בין מחרוזות טקסט, וניתן ליצור אותן באמצעות Gemini API.

Python

from openai import OpenAI

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

response = client.embeddings.create(
    input="Your text string goes here",
    model="text-embedding-004"
)

print(response.data[0].embedding)

Node.js

import OpenAI from "openai";

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

async function main() {
  const embedding = await openai.embeddings.create({
    model: "text-embedding-004",
    input: "Your text string goes here",
  });

  console.log(embedding);
}

main();

REST

curl "https://generativelanguage.googleapis.com/v1beta/openai/embeddings" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer gemini_api_key" \
-d '{
    "input": "Your text string goes here",
    "model": "text-embedding-004"
  }'

המגבלות הנוכחיות

התמיכה בספריות של OpenAI עדיין בגרסת בטא בזמן שאנחנו מרחיבים את תמיכת התכונות. הפונקציות הבאות מוגבלות:

העלאת תמונה באמצעות כתובת URL או Base64
פלט מובנה

אם יש לכם שאלות על פרמטרים נתמכים או על תכונות עתידיות, או אם נתקלתם בבעיות בתחילת השימוש ב-Gemini, תוכלו להצטרף לפורום למפתחים.