Google-Format
Base-Path:
https://api.hyprlab.ioNon-Stream Path:
https://api.hyprlab.io/v1beta/models/[MODEL]:generateContent?key=[API-KEY]Stream Path:
https://api.hyprlab.io/v1beta/models/[MODEL]:streamGenerateContent?alt=sse&key=[API-KEY]Sample API Request
Basic Request:
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": [
{
"role": "user",
"parts": [{
"text": "Hello"
}]
},
{
"role": "model",
"parts": [{
"text": "Great to meet you. What would you like to know?"
}]
},
{
"role": "user",
"parts": [{
"text": "I have two dogs in my house. How many paws are in my house?"
}]
}
],
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}'= = =
Node.js:
= = =
const axios = require('axios');
const API_KEY = 'API_HERE'; // Replace with your API key
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContent() {
const payload = {
system_instruction: {
parts: {
text: "You are a helpful assistant."
}
},
contents: [
{
role: "user",
parts: [{
text: "Hello"
}]
},
{
role: "model",
parts: [{
text: "Great to meet you. What would you like to know?"
}]
},
{
role: "user",
parts: [{
text: "I have two dogs in my house. How many paws are in my house?"
}]
}
],
generationConfig: {
temperature: 0.7,
topP: 0.95,
topK: 0,
max_output_tokens: 8192,
response_mime_type: "text/plain"
},
safetySettings: [
{
category: "HARM_CATEGORY_HARASSMENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_HATE_SPEECH",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_SEXUALLY_EXPLICIT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_DANGEROUS_CONTENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_CIVIC_INTEGRITY",
threshold: "BLOCK_NONE"
}
]
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
// Handle the response
if (response.data.candidates && response.data.candidates.length > 0) {
console.log('Model Response:', response.data.candidates[0].content.parts[0].text);
} else {
console.log('No response generated');
}
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Call the function
generateContent()
.then(result => {
// Additional processing if needed
})
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
import requests
API_KEY = "API_HERE" # Replace with your API key
API_BASE = "api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content(conversation):
"""
Generate content using Gemini Model
Args:
conversation: List of message objects with role and text
"""
payload = {
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": conversation,
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
conversation = [
{
"role": "user",
"parts": [{
"text": "Hello"
}]
},
{
"role": "model",
"parts": [{
"text": "Great to meet you. What would you like to know?"
}]
},
{
"role": "user",
"parts": [{
"text": "I have two dogs in my house. How many paws are in my house?"
}]
}
]
response = generate_content(conversation)
if "candidates" in response:
print(response["candidates"][0]["content"]["parts"][0]["text"])Image Input:
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": {
"parts": [
{
"inline_data": {
"mime_type": "image/jpeg",
"data": "'$(base64 /path/to/image.jpg)'"
}
},
{
"text": "What do you see in this image?"
}
]
},
"generationConfig": {
"temperature": 0.7,
"topP": 0.9,
"topK": 40,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}'= = =
Node.js:
= = =
const axios = require('axios');
const fs = require('fs');
const API_KEY = 'API_HERE'; // Replace with your API key
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContentWithImage(imagePath) {
// Read and convert image to base64
const imageData = fs.readFileSync(imagePath);
const base64Image = imageData.toString('base64');
const payload = {
system_instruction: {
parts: {
text: "You are a helpful assistant."
}
},
contents: {
parts: [
{
inline_data: {
mime_type: "image/jpeg", // Adjust mime type based on your image
data: base64Image
}
},
{
text: "What do you see in this image?"
}
]
},
generationConfig: {
temperature: 0.7,
topP: 0.95,
topK: 0,
max_output_tokens: 8192,
response_mime_type: "text/plain"
},
safetySettings: [
{
category: "HARM_CATEGORY_HARASSMENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_HATE_SPEECH",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_SEXUALLY_EXPLICIT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_DANGEROUS_CONTENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_CIVIC_INTEGRITY",
threshold: "BLOCK_NONE"
}
]
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
// Handle the response
if (response.data.candidates && response.data.candidates.length > 0) {
console.log('Model Response:', response.data.candidates[0].content.parts[0].text);
} else {
console.log('No response generated');
}
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Example usage
generateContentWithImage('/path/to/image.jpg')
.then(result => {
// Handle result if needed
})
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
import base64
import requests
API_KEY = "API_HERE" # Replace with your API key
API_BASE = "https://api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content_with_image(image_path):
"""
Generate content using Gemini Model with image input
Args:
image_path: Path to the image file
"""
# Read and encode image to base64
with open(image_path, "rb") as image_file:
base64_image = base64.b64encode(image_file.read()).decode('utf-8')
payload = {
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": {
"parts": [
{
"inline_data": {
"mime_type": "image/jpeg", # Adjust mime type based on your image
"data": base64_image
}
},
{
"text": "What do you see in this image?"
}
]
},
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
try:
response = generate_content_with_image("/path/to/image.jpg")
if "candidates" in response:
print(response["candidates"][0]["content"]["parts"][0]["text"])
except Exception as e:
print(f"An error occurred: {e}")Audio Input:
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": {
"parts": [
{
"inline_data": {
"mime_type": "audio/mpeg",
"data": "'$(base64 /path/to/audio.mp3)'"
}
},
{
"text": "What is being said in this audio?"
}
]
},
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}'= = =
Node.js:
= = =
const axios = require('axios');
const fs = require('fs');
const API_KEY = 'API_HERE'; // Replace with your API key
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContentWithAudio(audioPath) {
// Read and convert audio to base64
const audioData = fs.readFileSync(audioPath);
const base64Audio = audioData.toString('base64');
const payload = {
system_instruction: {
parts: {
text: "You are a helpful assistant."
}
},
contents: {
parts: [
{
inline_data: {
mime_type: "audio/mpeg", // Adjust mime type based on your audio format
data: base64Audio
}
},
{
text: "What is being said in this audio?"
}
]
},
generationConfig: {
temperature: 0.7,
topP: 0.95,
topK: 0,
max_output_tokens: 8192,
response_mime_type: "text/plain"
},
safetySettings: [
{
category: "HARM_CATEGORY_HARASSMENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_HATE_SPEECH",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_SEXUALLY_EXPLICIT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_DANGEROUS_CONTENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_CIVIC_INTEGRITY",
threshold: "BLOCK_NONE"
}
]
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
// Handle the response
if (response.data.candidates && response.data.candidates.length > 0) {
console.log('Model Response:', response.data.candidates[0].content.parts[0].text);
} else {
console.log('No response generated');
}
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Example usage
generateContentWithAudio('/path/to/audio.mp3')
.then(result => {
// Handle result if needed
})
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
import base64
import requests
API_KEY = "API_HERE" # Replace with your API key
API_BASE = "https://api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content_with_audio(audio_path):
"""
Generate content using Gemini Model with audio input
Args:
audio_path: Path to the audio file
"""
# Read and encode audio to base64
with open(audio_path, "rb") as audio_file:
base64_audio = base64.b64encode(audio_file.read()).decode('utf-8')
payload = {
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": {
"parts": [
{
"inline_data": {
"mime_type": "audio/mpeg", # Adjust mime type based on your audio format
"data": base64_audio
}
},
{
"text": "What is being said in this audio?"
}
]
},
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
try:
response = generate_content_with_audio("/path/to/audio.mp3")
if "candidates" in response:
print(response["candidates"][0]["content"]["parts"][0]["text"])
except Exception as e:
print(f"An error occurred: {e}")Video Input:
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": {
"parts": [
{
"inline_data": {
"mime_type": "video/mp4",
"data": "'$(base64 /path/to/video.mp4)'"
}
},
{
"text": "What is happening in this video?"
}
]
},
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}'= = =
Node.js:
= = =
const axios = require('axios');
const fs = require('fs');
const API_KEY = 'API_HERE';
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContentWithVideo(videoPath) {
// Read and convert video to base64
const videoData = fs.readFileSync(videoPath);
const base64Video = videoData.toString('base64');
const payload = {
system_instruction: {
parts: {
text: "You are a helpful assistant."
}
},
contents: {
parts: [
{
inline_data: {
mime_type: "video/mp4",
data: base64Video
}
},
{
text: "What is happening in this video?"
}
]
},
generationConfig: {
temperature: 0.7,
topP: 0.9,
topK: 40,
max_output_tokens: 8192,
response_mime_type: "text/plain"
},
safetySettings: [
{
category: "HARM_CATEGORY_HARASSMENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_HATE_SPEECH",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_SEXUALLY_EXPLICIT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_DANGEROUS_CONTENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_CIVIC_INTEGRITY",
threshold: "BLOCK_NONE"
}
]
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
if (response.data.candidates && response.data.candidates.length > 0) {
console.log('Model Response:', response.data.candidates[0].content.parts[0].text);
} else {
console.log('No response generated');
}
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Example usage
generateContentWithVideo('/path/to/video.mp4')
.then(result => {
// Handle result if needed
})
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
# PYTHON
import base64
import requests
API_KEY = "API_HERE"
API_BASE = "https://api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content_with_video(video_path):
"""
Generate content using Gemini Model with video input
Args:
video_path: Path to the video file
"""
# Read and encode video to base64
with open(video_path, "rb") as video_file:
base64_video = base64.b64encode(video_file.read()).decode('utf-8')
payload = {
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": {
"parts": [
{
"inline_data": {
"mime_type": "video/mp4",
"data": base64_video
}
},
{
"text": "What is happening in this video?"
}
]
},
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
try:
response = generate_content_with_video("/path/to/video.mp4")
if "candidates" in response:
print(response["candidates"][0]["content"]["parts"][0]["text"])
except Exception as e:
print(f"An error occurred: {e}")File input:
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": {
"parts": [
{
"inline_data": {
"mime_type": "application/pdf",
"data": "'$(base64 /path/to/document.pdf)'"
}
},
{
"text": "What is this document about?"
}
]
},
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}'= = =
Nodejs:
= = =
const axios = require('axios');
const fs = require('fs');
const API_KEY = 'API_HERE';
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContentWithPDF(pdfPath) {
// Read and convert PDF to base64
const pdfData = fs.readFileSync(pdfPath);
const base64PDF = pdfData.toString('base64');
const payload = {
system_instruction: {
parts: {
text: "You are a helpful assistant."
}
},
contents: {
parts: [
{
inline_data: {
mime_type: "application/pdf",
data: base64PDF
}
},
{
text: "What is this document about?"
}
]
},
generationConfig: {
temperature: 0.7,
topP: 0.95,
topK: 0,
max_output_tokens: 8192,
response_mime_type: "text/plain"
},
safetySettings: [
{
category: "HARM_CATEGORY_HARASSMENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_HATE_SPEECH",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_SEXUALLY_EXPLICIT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_DANGEROUS_CONTENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_CIVIC_INTEGRITY",
threshold: "BLOCK_NONE"
}
]
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
if (response.data.candidates && response.data.candidates.length > 0) {
console.log('Model Response:', response.data.candidates[0].content.parts[0].text);
} else {
console.log('No response generated');
}
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Example usage
generateContentWithPDF('/path/to/document.pdf')
.then(result => {
// Handle result if needed
})
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
import base64
import requests
API_KEY = "API_HERE"
API_BASE = "https://api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content_with_pdf(pdf_path):
"""
Generate content using Gemini Model with PDF input
Args:
pdf_path: Path to the PDF file
"""
# Read and encode PDF to base64
with open(pdf_path, "rb") as pdf_file:
base64_pdf = base64.b64encode(pdf_file.read()).decode('utf-8')
payload = {
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": {
"parts": [
{
"inline_data": {
"mime_type": "application/pdf",
"data": base64_pdf
}
},
{
"text": "What is this document about?"
}
]
},
"generationConfig": {
"temperature": 0.7,
"topP": 0.95,
"topK": 0,
"max_output_tokens": 8192,
"response_mime_type": "text/plain"
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
try:
response = generate_content_with_pdf("/path/to/document.pdf")
if "candidates" in response:
print(response["candidates"][0]["content"]["parts"][0]["text"])
except Exception as e:
print(f"An error occurred: {e}")Structured Output:
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": [{
"parts": [{
"text": "List 5 popular cookie recipes"
}]
}],
"generationConfig": {
"response_mime_type": "application/json",
"response_schema": {
"type": "ARRAY",
"items": {
"type": "OBJECT",
"properties": {
"recipe_name": {"type": "STRING"}
}
}
}
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}'= = =
Nodejs:
= = =
const axios = require('axios');
const API_KEY = 'API_HERE';
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContent() {
const payload = {
system_instruction: {
parts: {
text: "You are a helpful assistant."
}
},
contents: [{
parts: [{
text: "List 5 popular cookie recipes"
}]
}],
generationConfig: {
response_mime_type: "application/json",
response_schema: {
type: "ARRAY",
items: {
type: "OBJECT",
properties: {
recipe_name: {"type": "STRING"}
}
}
}
},
safetySettings: [
{
category: "HARM_CATEGORY_HARASSMENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_HATE_SPEECH",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_SEXUALLY_EXPLICIT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_DANGEROUS_CONTENT",
threshold: "BLOCK_NONE"
},
{
category: "HARM_CATEGORY_CIVIC_INTEGRITY",
threshold: "BLOCK_NONE"
}
]
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
if (response.data.candidates && response.data.candidates.length > 0) {
console.log('Model Response:', response.data.candidates[0].content.parts[0].text);
} else {
console.log('No response generated');
}
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Example usage
generateContent()
.then(result => {
// Handle result if needed
})
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
import requests
API_KEY = "API_HERE"
API_BASE = "https://api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content():
payload = {
"system_instruction": {
"parts": {
"text": "You are a helpful assistant."
}
},
"contents": [{
"parts": [{
"text": "List 5 popular cookie recipes"
}]
}],
"generationConfig": {
"response_mime_type": "application/json",
"response_schema": {
"type": "ARRAY",
"items": {
"type": "OBJECT",
"properties": {
"recipe_name": {"type": "STRING"}
}
}
}
},
"safetySettings": [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_NONE"
},
{
"category": "HARM_CATEGORY_CIVIC_INTEGRITY",
"threshold": "BLOCK_NONE"
}
]
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
try:
response = generate_content()
if "candidates" in response:
print(response["candidates"][0]["content"]["parts"][0]["text"])
except Exception as e:
print(f"An error occurred: {e}")Function Calling:
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"system_instruction": {
"parts": {
"text": "You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks."
}
},
"tools": [
{
"function_declarations": [
{
"name": "enable_lights",
"description": "Turn on the lighting system.",
"parameters": { "type": "object" }
},
{
"name": "set_light_color",
"description": "Set the light color. Lights must be enabled for this to work.",
"parameters": {
"type": "object",
"properties": {
"rgb_hex": {
"type": "string",
"description": "The light color as a 6-digit hex string, e.g. ff0000 for red."
}
},
"required": ["rgb_hex"]
}
},
{
"name": "stop_lights",
"description": "Turn off the lighting system.",
"parameters": { "type": "object" }
}
]
}
],
"tool_config": {
"function_calling_config": {"mode": "none"}
},
"contents": {
"role": "user",
"parts": {
"text": "What can you do?"
}
}
}'= = =
Node.js
= = =
const axios = require('axios');
const API_KEY = 'API_HERE';
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContent() {
const payload = {
system_instruction: {
parts: {
text: "You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks."
}
},
tools: [
{
function_declarations: [
{
name: "enable_lights",
description: "Turn on the lighting system.",
parameters: { type: "object" }
},
{
name: "set_light_color",
description: "Set the light color. Lights must be enabled for this to work.",
parameters: {
type: "object",
properties: {
rgb_hex: {
type: "string",
description: "The light color as a 6-digit hex string, e.g. ff0000 for red."
}
},
required: ["rgb_hex"]
}
},
{
name: "stop_lights",
description: "Turn off the lighting system.",
parameters: { type: "object" }
}
]
}
],
tool_config: {
function_calling_config: {mode: "none"}
},
contents: {
role: "user",
parts: {
text: "What can you do?"
}
}
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Example usage
generateContent()
.then(result => {
if (result.candidates) {
console.log(result.candidates[0].content.parts[0].text);
}
})
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
import requests
API_KEY = "API_HERE"
API_BASE = "https://api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content():
payload = {
"system_instruction": {
"parts": {
"text": "You are a helpful lighting system bot. You can turn lights on and off, and you can set the color. Do not perform any other tasks."
}
},
"tools": [
{
"function_declarations": [
{
"name": "enable_lights",
"description": "Turn on the lighting system.",
"parameters": { "type": "object" }
},
{
"name": "set_light_color",
"description": "Set the light color. Lights must be enabled for this to work.",
"parameters": {
"type": "object",
"properties": {
"rgb_hex": {
"type": "string",
"description": "The light color as a 6-digit hex string, e.g. ff0000 for red."
}
},
"required": ["rgb_hex"]
}
},
{
"name": "stop_lights",
"description": "Turn off the lighting system.",
"parameters": { "type": "object" }
}
]
}
],
"tool_config": {
"function_calling_config": {"mode": "none"}
},
"contents": {
"role": "user",
"parts": {
"text": "What can you do?"
}
}
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
try:
response = generate_content()
if "candidates" in response:
print(response["candidates"][0]["content"]["parts"][0]["text"])
except Exception as e:
print(f"An error occurred: {e}")Code Execution:
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"tools": [{"code_execution": {}}],
"contents": [
{
"role": "user",
"parts": [{
"text": "Can you print \"Hello world!\"?"
}]
},
{
"role": "model",
"parts": [
{
"text": ""
},
{
"executable_code": {
"language": "PYTHON",
"code": "\nprint(\"hello world!\")\n"
}
},
{
"code_execution_result": {
"outcome": "OUTCOME_OK",
"output": "hello world!\n"
}
},
{
"text": "I have printed \"hello world!\" using the provided python code block. \n"
}
]
},
{
"role": "user",
"parts": [{
"text": "What is the sum of the first 50 prime numbers? Generate and run code for the calculation, and make sure you get all 50."
}]
}
]
}'= = =
Node.js:
= = =
const axios = require('axios');
const API_KEY = 'API_HERE';
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContent() {
const payload = {
tools: [{code_execution: {}}],
contents: [
{
role: "user",
parts: [{
text: "Can you print \"Hello world!\"?"
}]
},
{
role: "model",
parts: [
{
text: ""
},
{
executable_code: {
language: "PYTHON",
code: "\nprint(\"hello world!\")\n"
}
},
{
code_execution_result: {
outcome: "OUTCOME_OK",
output: "hello world!\n"
}
},
{
text: "I have printed \"hello world!\" using the provided python code block. \n"
}
]
},
{
role: "user",
parts: [{
text: "What is the sum of the first 50 prime numbers? Generate and run code for the calculation, and make sure you get all 50."
}]
}
]
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Example usage
generateContent()
.then(result => {
if (result.candidates) {
console.log(result.candidates[0].content.parts[0].text);
}
})
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
import requests
API_KEY = "API_HERE"
API_BASE = "https://api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content():
payload = {
"tools": [{"code_execution": {}}],
"contents": [
{
"role": "user",
"parts": [{
"text": "Can you print \"Hello world!\"?"
}]
},
{
"role": "model",
"parts": [
{
"text": ""
},
{
"executable_code": {
"language": "PYTHON",
"code": "\nprint(\"hello world!\")\n"
}
},
{
"code_execution_result": {
"outcome": "OUTCOME_OK",
"output": "hello world!\n"
}
},
{
"text": "I have printed \"hello world!\" using the provided python code block. \n"
}
]
},
{
"role": "user",
"parts": [{
"text": "What is the sum of the first 50 prime numbers? Generate and run code for the calculation, and make sure you get all 50."
}]
}
]
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
try:
response = generate_content()
if "candidates" in response:
print(response["candidates"][0]["content"]["parts"][0]["text"])
except Exception as e:
print(f"An error occurred: {e}")Grounding (Google Search Retrieval)
= = =
Curl:
= = =
curl -X POST "https://api.hyprlab.io/v1beta/models/gemini-1.5-flash-002:generateContent?key=API_HERE" \
-H "Content-Type: application/json" \
-d '{
"contents": [{
"parts": [{
"text": "What is the current Google stock price?"
}]
}],
"tools": [{
"google_search_retrieval": {
"dynamic_retrieval_config": {
"mode": "MODE_DYNAMIC",
"dynamic_threshold": 0.6
}
}
}]
}'= = =
Node.js:
= = =
const axios = require('axios');
const API_KEY = 'API_HERE';
const API_BASE = 'https://api.hyprlab.io';
const MODEL = 'gemini-1.5-flash-002';
async function generateContent() {
const payload = {
contents: [{
parts: [{
text: "What is the current Google stock price?"
}]
}],
tools: [{
google_search_retrieval: {
dynamic_retrieval_config: {
mode: "MODE_DYNAMIC",
dynamic_threshold: 0.6
}
}
}]
};
try {
const response = await axios({
method: 'post',
url: `${API_BASE}/v1beta/models/${MODEL}:generateContent?key=${API_KEY}`,
headers: {
'Content-Type': 'application/json'
},
data: payload
});
console.log('Full Response:', JSON.stringify(response.data, null, 2));
return response.data;
} catch (error) {
console.error('Error:', error.response ? error.response.data : error.message);
throw error;
}
}
// Example usage
generateContent()
.catch(error => {
console.error('Failed to generate content:', error);
});= = =
Python:
= = =
import requests
import json
API_KEY = "API_HERE"
API_BASE = "https://api.hyprlab.io"
MODEL = "gemini-1.5-flash-002"
def generate_content():
payload = {
"contents": [{
"parts": [{
"text": "What is the current Google stock price?"
}]
}],
"tools": [{
"google_search_retrieval": {
"dynamic_retrieval_config": {
"mode": "MODE_DYNAMIC",
"dynamic_threshold": 0.6
}
}
}]
}
response = requests.post(
f"{API_BASE}/v1beta/models/{MODEL}:generateContent?key={API_KEY}",
json=payload,
headers={"Content-Type": "application/json"}
)
return response.json()
# Example usage
try:
response = generate_content()
print('Full Response:', json.dumps(response, indent=2))
except Exception as e:
print(f"An error occurred: {e}")Learn More at: https://ai.google.dev/gemini-api/docs
✨ Gemini
Model Name:
gemini-2.0-flash-thinking-exp-1219
Discount:
60% off
Input:
$0.03 / 1M Tokens
Output:
$0.12 / 1M Tokens
Context Length:
32,767
Moderation:
Unfiltered
Capabilities:
Image Input ✅Audio Input ✅Video Input ✅File Input ✅
Model Name:
gemini-2.0-flash-exp
Discount:
60% off
Prompt upto 128K:
$0.03 / 1M Tokens$0.12 / 1M Tokens
Prompts longer than 128K:
$0.06 / 1M Tokens$0.24 / 1M Tokens
Context Length:
1,048,576
Moderation:
Unfiltered
Capabilities:
Image Input ✅Audio Input ✅Video Input ✅File Input ✅Structured Output ✅Function Calling ✅Code Execution ✅Grounding ✅
Model Name:
gemini-exp-1206gemini-exp-1121gemini-exp-1114
Discount:
60% off
Input:
$0.5 / 1M Tokens
Output:
$2 / 1M Tokens
Context Length:
2,097,152
Moderation:
Unfiltered
Capabilities:
Image Input ✅Audio Input ✅Video Input ✅File Input ✅Structured Output ✅Function Calling ✅Code Execution ✅Grounding ✅
Model Name:
gemini-1.5-progemini-1.5-pro-002gemini-1.5-pro-exp-0827gemini-1.5-pro-exp-0801
Discount:
60% off
Prompt upto 128K:
$0.5 / 1M Tokens$2 / 1M Tokens
Prompts longer than 128K:
$1 / 1M Tokens$4 / 1M Tokens
Context Length:
2,097,152
Moderation:
Unfiltered
Capabilities:
Image Input ✅Audio Input ✅Video Input ✅File Input ✅Structured Output ✅Function Calling ✅Code Execution ✅Grounding ✅
Model Name:
gemini-1.5-flashgemini-1.5-flash-002gemini-1.5-flash-exp-0827
Discount:
60% off
Prompt upto 128K:
$0.03 / 1M Tokens$0.12 / 1M Tokens
Prompts longer than 128K:
$0.06 / 1M Tokens$0.24 / 1M Tokens
Context Length:
1,048,576
Moderation:
Unfiltered
Capabilities:
Image Input ✅Audio Input ✅Video Input ✅File Input ✅Structured Output ✅Function Calling ✅Code Execution ✅Grounding ✅
Model Name:
gemini-1.5-flash-8bgemini-1.5-flash-8b-exp-0924gemini-1.5-flash-8b-exp-0827
Discount:
60% off
Prompt upto 128K:
$0.015 / 1M Tokens$0.06 / 1M Tokens
Prompts longer than 128K:
$0.03 / 1M Tokens$0.12 / 1M Tokens
Context Length:
1,048,576
Moderation:
Unfiltered
Capabilities:
Image Input ✅Audio Input ✅Video Input ✅File Input ✅Structured Output ✅Function Calling ✅Code Execution ✅Grounding ✅
Last updated
