Використовуйте нативний формат API Gemini через CometAPI для генерації тексту, multimodal input, thinking/reasoning, function calling, Google Search grounding, JSON mode та Streaming.
from google import genai
client = genai.Client(
api_key="<COMETAPI_KEY>",
http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"},
)
response = client.models.generate_content(
model="gemini-2.5-flash",
contents="Explain how AI works in a few words",
)
print(response.text){
"candidates": [
{
"content": {
"role": "<string>",
"parts": [
{
"text": "<string>",
"functionCall": {
"name": "<string>",
"args": {}
},
"inlineData": {
"mimeType": "<string>",
"data": "<string>"
},
"thought": true
}
]
},
"finishReason": "STOP",
"safetyRatings": [
{
"category": "<string>",
"probability": "<string>",
"blocked": true
}
],
"citationMetadata": {
"citationSources": [
{
"startIndex": 123,
"endIndex": 123,
"uri": "<string>",
"license": "<string>"
}
]
},
"tokenCount": 123,
"avgLogprobs": 123,
"groundingMetadata": {
"groundingChunks": [
{
"web": {
"uri": "<string>",
"title": "<string>"
}
}
],
"groundingSupports": [
{
"groundingChunkIndices": [
123
],
"confidenceScores": [
123
],
"segment": {
"startIndex": 123,
"endIndex": 123,
"text": "<string>"
}
}
],
"webSearchQueries": [
"<string>"
]
},
"index": 123
}
],
"promptFeedback": {
"blockReason": "SAFETY",
"safetyRatings": [
{
"category": "<string>",
"probability": "<string>",
"blocked": true
}
]
},
"usageMetadata": {
"promptTokenCount": 123,
"candidatesTokenCount": 123,
"totalTokenCount": 123,
"trafficType": "<string>",
"thoughtsTokenCount": 123,
"promptTokensDetails": [
{
"modality": "<string>",
"tokenCount": 123
}
],
"candidatesTokensDetails": [
{
"modality": "<string>",
"tokenCount": 123
}
]
},
"modelVersion": "<string>",
"createTime": "<string>",
"responseId": "<string>"
}| Налаштування | Значення Google за замовчуванням | CometAPI |
|---|---|---|
| Base URL | generativelanguage.googleapis.com | api.cometapi.com |
| API Key | $GEMINI_API_KEY | $COMETAPI_KEY |
x-goog-api-key, так і Authorization: Bearer.thinkingLevel для керування глибиною reasoning. Доступні рівні: MINIMAL, LOW, MEDIUM, HIGH.curl "https://api.cometapi.com/v1beta/models/gemini-3.1-pro-preview:generateContent" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $COMETAPI_KEY" \
-d '{
"contents": [{"parts": [{"text": "Explain quantum physics simply."}]}],
"generationConfig": {
"thinkingConfig": {"thinkingLevel": "LOW"}
}
}'
thinkingBudget для детального керування на рівні token:0 — вимкнути thinking-1 — динамічно (модель вирішує сама, за замовчуванням)> 0 — конкретний бюджет token (наприклад, 1024, 2048)curl "https://api.cometapi.com/v1beta/models/gemini-2.5-flash:generateContent" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $COMETAPI_KEY" \
-d '{
"contents": [{"parts": [{"text": "Solve this logic puzzle step by step."}]}],
"generationConfig": {
"thinkingConfig": {"thinkingBudget": 2048}
}
}'
thinkingLevel з моделями Gemini 2.5 (або thinkingBudget з моделями Gemini 3) може спричинити помилки. Використовуйте правильний параметр для вашої версії моделі.streamGenerateContent?alt=sse як оператор, щоб отримувати Server-Sent Events у процесі генерації контенту моделлю. Кожна SSE-подія містить рядок data: з JSON-об’єктом GenerateContentResponse.
curl "https://api.cometapi.com/v1beta/models/gemini-2.5-flash:streamGenerateContent?alt=sse" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $COMETAPI_KEY" \
--no-buffer \
-d '{
"contents": [{"parts": [{"text": "Write a short poem about the stars"}]}]
}'
systemInstruction:
curl "https://api.cometapi.com/v1beta/models/gemini-2.5-flash:generateContent" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $COMETAPI_KEY" \
-d '{
"contents": [{"parts": [{"text": "What is 2+2?"}]}],
"systemInstruction": {
"parts": [{"text": "You are a math tutor. Always show your work."}]
}
}'
responseMimeType. За потреби також можна вказати responseSchema для суворої валідації схеми:
curl "https://api.cometapi.com/v1beta/models/gemini-2.5-flash:generateContent" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $COMETAPI_KEY" \
-d '{
"contents": [{"parts": [{"text": "List 3 planets with their distances from the sun"}]}],
"generationConfig": {
"responseMimeType": "application/json"
}
}'
googleSearch:
curl "https://api.cometapi.com/v1beta/models/gemini-2.5-flash:generateContent" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $COMETAPI_KEY" \
-d '{
"contents": [{"parts": [{"text": "Who won the euro 2024?"}]}],
"tools": [{"google_search": {}}]
}'
groundingMetadata з URL-адресами джерел і оцінками впевненості.
{
"candidates": [
{
"content": {
"role": "model",
"parts": [{"text": "Hello"}]
},
"finishReason": "STOP",
"avgLogprobs": -0.0023
}
],
"usageMetadata": {
"promptTokenCount": 5,
"candidatesTokenCount": 1,
"totalTokenCount": 30,
"trafficType": "ON_DEMAND",
"thoughtsTokenCount": 24,
"promptTokensDetails": [{"modality": "TEXT", "tokenCount": 5}],
"candidatesTokensDetails": [{"modality": "TEXT", "tokenCount": 1}]
},
"modelVersion": "gemini-2.5-flash",
"createTime": "2026-03-25T04:21:43.756483Z",
"responseId": "CeynaY3LDtvG4_UP0qaCuQY"
}
thoughtsTokenCount у usageMetadata показує, скільки токенів модель витратила на внутрішнє міркування, навіть якщо результат мислення не включено до відповіді.| Функція | Gemini Native (/v1beta/models/...) | OpenAI-Compatible (/v1/chat/completions) |
|---|---|---|
| Керування thinking | thinkingConfig with thinkingLevel / thinkingBudget | Недоступно |
| Google Search grounding | tools: [\{"google_search": \{\}\}] | Недоступно |
| Google Maps grounding | tools: [\{"googleMaps": \{\}\}] | Недоступно |
| Модальність генерації зображень | responseModalities: ["IMAGE"] | Недоступно |
| Заголовок автентифікації | x-goog-api-key or Bearer | Лише Bearer |
| Формат відповіді | Gemini native (candidates, parts) | Формат OpenAI (choices, message) |
Your CometAPI key passed via the x-goog-api-key header. Bearer token authentication (Authorization: Bearer <key>) is also supported.
The Gemini model ID to use. See the Models page for current Gemini model IDs.
"gemini-2.5-flash"
The operation to perform. Use generateContent for synchronous responses, or streamGenerateContent?alt=sse for Server-Sent Events streaming.
generateContent, streamGenerateContent?alt=sse "generateContent"
The conversation history and current input. For single-turn queries, provide a single item. For multi-turn conversations, include all previous turns.
Show child attributes
System instructions that guide the model's behavior across the entire conversation. Text only.
Show child attributes
Tools the model may use to generate responses. Supports function declarations, Google Search, Google Maps, and code execution.
Show child attributes
Configuration for tool usage, such as function calling mode.
Show child attributes
Safety filter settings. Override default thresholds for specific harm categories.
Show child attributes
Configuration for model generation behavior including temperature, output length, and response format.
Show child attributes
The name of cached content to use as context. Format: cachedContents/{id}. See the Gemini context caching documentation for details.
Successful response. For streaming requests, the response is a stream of SSE events, each containing a GenerateContentResponse JSON object prefixed with data:.
The generated response candidates.
Show child attributes
Feedback on the prompt, including safety blocking information.
Show child attributes
Token usage statistics for the request.
Show child attributes
The model version that generated this response.
The timestamp when this response was created (ISO 8601 format).
Unique identifier for this response.
from google import genai
client = genai.Client(
api_key="<COMETAPI_KEY>",
http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"},
)
response = client.models.generate_content(
model="gemini-2.5-flash",
contents="Explain how AI works in a few words",
)
print(response.text){
"candidates": [
{
"content": {
"role": "<string>",
"parts": [
{
"text": "<string>",
"functionCall": {
"name": "<string>",
"args": {}
},
"inlineData": {
"mimeType": "<string>",
"data": "<string>"
},
"thought": true
}
]
},
"finishReason": "STOP",
"safetyRatings": [
{
"category": "<string>",
"probability": "<string>",
"blocked": true
}
],
"citationMetadata": {
"citationSources": [
{
"startIndex": 123,
"endIndex": 123,
"uri": "<string>",
"license": "<string>"
}
]
},
"tokenCount": 123,
"avgLogprobs": 123,
"groundingMetadata": {
"groundingChunks": [
{
"web": {
"uri": "<string>",
"title": "<string>"
}
}
],
"groundingSupports": [
{
"groundingChunkIndices": [
123
],
"confidenceScores": [
123
],
"segment": {
"startIndex": 123,
"endIndex": 123,
"text": "<string>"
}
}
],
"webSearchQueries": [
"<string>"
]
},
"index": 123
}
],
"promptFeedback": {
"blockReason": "SAFETY",
"safetyRatings": [
{
"category": "<string>",
"probability": "<string>",
"blocked": true
}
]
},
"usageMetadata": {
"promptTokenCount": 123,
"candidatesTokenCount": 123,
"totalTokenCount": 123,
"trafficType": "<string>",
"thoughtsTokenCount": 123,
"promptTokensDetails": [
{
"modality": "<string>",
"tokenCount": 123
}
],
"candidatesTokensDetails": [
{
"modality": "<string>",
"tokenCount": 123
}
]
},
"modelVersion": "<string>",
"createTime": "<string>",
"responseId": "<string>"
}