Google Cloud Platform

import google.generativeai as genai

genai.configure(api_key="AIza...")

# ── Gemini 2.0 Flash (تېز ۋە ئارزان) ────────────────────
model = genai.GenerativeModel("gemini-2.0-flash")

response = model.generate_content("ئۇيغۇر تىلى ھەققىدە قىسقا چۈشەندۈر")
print(response.text)

# ── كۆپ مەرتىبىلىك سۆھبەت ────────────────────────────────
chat = model.start_chat(history=[])
r1 = chat.send_message("مېنىڭ ئىسمىم ئىدراك")
r2 = chat.send_message("مېنىڭ ئىسمىم نېمە؟")
print(r2.text)  # → "سىزنىڭ ئىسمىڭىز ئىدراك."

# ── رەسىم + تېكىست ───────────────────────────────────────
import PIL.Image
img   = PIL.Image.open("photo.jpg")
resp  = model.generate_content([img, "بۇ رەسىمدە نېمە بار؟"])

# ── Vertex AI ئارقىلىق (Production) ─────────────────────
import vertexai
from vertexai.generative_models import GenerativeModel

vertexai.init(project="my-project", location="us-central1")
model = GenerativeModel("gemini-2.0-flash-001")
resp  = model.generate_content("RAG دېگەن نېمە؟")

# ── LangChain بىلەن ──────────────────────────────────────
from langchain_google_genai import ChatGoogleGenerativeAI

llm = ChatGoogleGenerativeAI(
    model       = "gemini-2.0-flash",
    temperature = 0.7,
    google_api_key = "AIza..."
)
result = llm.invoke("ئۇيغۇرچە شىئىر يازغىن")

-- ── ئاساسلىق سوئال ────────────────────────────────────
SELECT
    country,
    COUNT(*) AS user_count,
    AVG(session_duration) AS avg_duration
FROM `my-project.analytics.sessions`
WHERE DATE(created_at) = CURRENT_DATE()
GROUP BY country
ORDER BY user_count DESC
LIMIT 10;

-- ── BigQuery ML: Linear Regression ───────────────────
CREATE OR REPLACE MODEL `my-project.models.price_model`
OPTIONS (model_type='linear_reg', input_label_cols=['price']) AS
SELECT area, rooms, location, price
FROM `my-project.data.houses`;

-- ── Gemini بىلەن BigQuery ─────────────────────────────
SELECT
    review_text,
    ml.generate_text(
        MODEL `my-project.models.gemini`,
        STRUCT(
            CONCAT('تويغۇنى بەلگىلە: ', review_text) AS prompt,
            100 AS max_output_tokens
        )
    ) AS sentiment
FROM `my-project.data.reviews`
LIMIT 10;