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 Google Colab में चलाएं
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 GitHub पर सोर्स देखें
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PaLM API को तुरंत आज़माने के लिए, कर्ल कमांड इस्तेमाल करें. इससे REST API में मौजूद तरीकों को कॉल किया जा सकता है. नीचे दिए गए उदाहरणों में, एपीआई के हर तरीके के लिए कॉल दिखाए गए हैं. हर कर्ल कमांड के लिए, आपको मॉडल का नाम और एपीआई पासकोड बताना होगा. अगर आपके पास पहले से कोई एपीआई पासकोड नहीं है, तो एपीआई पासकोड पाएं पेज देखें.
"""
Add your API key and run this cell to set the PALM_API_KEY variable if
running in Colab.
(In a terminal you can just run PALM_API_KEY=<your API key>)
"""
import os
os.environ['PALM_API_KEY'] = ""
टेक्स्ट जनरेट करें
इनपुट मैसेज में दिए गए मॉडल से जवाब जनरेट करने के लिए, generate_text तरीके का इस्तेमाल करें.
!curl https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001:generateText?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": { \
"text": "Write a story about a magic backpack." \
} \
}'
{
"candidates": [
{
"output": "Once upon a time, there was a young girl named Lily who loved to explore. She would spend hours wandering through the forest near her house, looking for new and exciting things. One day, Lily was exploring a particularly dense part of the forest when she came across a strange backpack. It was sitting on a rock, and it looked like it had been abandoned.\n\nLily picked up the backpack and examined it. It was made of a strange, silvery material that she had never seen before. There were no zippers or buttons, but the backpack seemed to be open. Lily reached inside, and she was surprised to find that it was full of all sorts of amazing things.\n\nThere were books that could tell her anything she wanted to know, tools that could fix anything she broke, and clothes that could keep her warm or cool no matter what the weather. Lily was amazed by the backpack's contents, and she knew that she had found something truly special.\n\nLily decided to take the backpack home with her, and she quickly discovered that it was even more magical than she had thought. The backpack could transport her to any place she wanted to go, and it could provide her with anything she needed. Lily used the backpack to travel the world, and she had many amazing adventures.\n\nOne day, Lily was using the backpack to explore a new planet when she came across a group of people who were in trouble. The people were being held captive by a cruel wizard, and Lily knew that she had to help them. She used the backpack to create a distraction, and then she rescued the people and led them to safety.\n\nThe people were so grateful to Lily for saving them, and they told her that she was a true hero. Lily was happy to have helped, and she knew that she would continue to use the backpack to help others in need.\n\nLily's magic backpack continued to accompany her on many more adventures. She used it to help people in need, to explore new worlds, and to learn about all sorts of amazing things. Lily's backpack was a constant source of joy and inspiration, and she was grateful for the many ways that it had enriched her life.",
"safetyRatings": [
{
"category": "HARM_CATEGORY_DEROGATORY",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_TOXICITY",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_VIOLENCE",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_SEXUAL",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_MEDICAL",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_DANGEROUS",
"probability": "NEGLIGIBLE"
}
]
}
]
}
यहां दिए गए उदाहरण में, generate_text तरीके के सभी पैरामीटर की वैल्यू बताई गई है.
!curl https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001:generateText?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": { \
"text": "Give an example of a title for a story about a magic backpack. \
Title: " \
}, \
"safetySettings": [ \
{ \
"category": "HARM_CATEGORY_TOXICITY", \
"threshold": "BLOCK_ONLY_HIGH" \
} \
], \
"stopSequences": [ \
"Title" \
], \
"temperature": 1.0, \
"candidate_count": 3, \
"maxOutputTokens": 800, \
"topP": 0.8, \
"topK": 10 \
}'
{
"candidates": [
{
"output": "The Backpack of Holding",
"safetyRatings": [
{
"category": "HARM_CATEGORY_DEROGATORY",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_TOXICITY",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_VIOLENCE",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_SEXUAL",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_MEDICAL",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_DANGEROUS",
"probability": "NEGLIGIBLE"
}
]
},
{
"output": "The Backpack of Holding",
"safetyRatings": [
{
"category": "HARM_CATEGORY_DEROGATORY",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_TOXICITY",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_VIOLENCE",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_SEXUAL",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_MEDICAL",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_DANGEROUS",
"probability": "NEGLIGIBLE"
}
]
},
{
"output": "The Backpack of Holding",
"safetyRatings": [
{
"category": "HARM_CATEGORY_DEROGATORY",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_TOXICITY",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_VIOLENCE",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_SEXUAL",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_MEDICAL",
"probability": "NEGLIGIBLE"
},
{
"category": "HARM_CATEGORY_DANGEROUS",
"probability": "NEGLIGIBLE"
}
]
}
]
}
पैरामीटर वैल्यू का यह मतलब होता है:
safetySettings: बुरे बर्ताव की जांच के लिए सुरक्षा थ्रेशोल्ड कम करें, ताकि बुरे बर्ताव के उन मामलों को ही ब्लॉक किया जा सके जिनकी संभावना ज़्यादा होती हैstopSequences:Titleके अगले इंस्टेंस पर आउटपुट को रोककर, सिर्फ़ एक टाइटल जनरेट करने के लिए स्टॉप सीक्वेंस का इस्तेमाल करें.temperature: रिस्पॉन्स जनरेट करते समय, तापमान को 1.0 पर सेट करें.candidate_count: सिर्फ़ तीन कैंडिडेट के जवाब दिखाएं.maxOutputTokens: ज़्यादा से ज़्यादा 800 टोकन दिखाएं.topP: मॉडल से मिले टॉप 80% टोकन का ही इस्तेमाल करें.topK: सैंपलिंग करते समय, सबसे अच्छे 10 टोकन का ध्यान रखें.
generateText तरीके के लिए, एपीआई रेफ़रंस में इन पैरामीटर के बारे में ज़्यादा जानें.
मैसेज जनरेट करें
दिए गए मॉडल MessagePrompt से जवाब जनरेट करने के लिए, generateMessage तरीके का इस्तेमाल करें.
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": {"messages": [{"content":"hi"}]} \
}'
{
"candidates": [
{
"author": "1",
"content": "Hi! How can I help you today?"
}
],
"messages": [
{
"author": "0",
"content": "hi"
}
]
}
इस उदाहरण में, पैरामीटर के लिए अलग-अलग वैल्यू के साथ एक कॉल दिखाया गया है.
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": {"messages": [{"content":"hi"}]}, \
"temperature": 0.1, \
"candidate_count": 1, \
"topP": 0.8, \
"topK": 10}'
{
"candidates": [
{
"author": "1",
"content": "Hi! How can I help you today?"
}
],
"messages": [
{
"author": "0",
"content": "hi"
}
]
}
पैरामीटर वैल्यू का यह मतलब होता है:
temperature: रिस्पॉन्स जनरेट करते समय, तापमान को 0.1 पर सेट करें.candidate_count: सिर्फ़ एक कैंडिडेट का जवाब दें.topP: मॉडल से मिले टॉप 80% टोकन का ही इस्तेमाल करें.topK: सैंपलिंग करते समय, सबसे अच्छे 10 टोकन का ध्यान रखें.
generateMessage तरीके के लिए, एपीआई रेफ़रंस में इन पैरामीटर के बारे में ज़्यादा जानें.
टेक्स्ट एम्बेड करें
दिए गए इनपुट मैसेज से एम्बेड किए गए मॉडल को जनरेट करने के लिए, embedText तरीके का इस्तेमाल करें.
!curl https://generativelanguage.googleapis.com/v1beta2/models/embedding-gecko-001:embedText?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{"text": "say something nice!"}'
{
"embedding": {
"value": [
0.0011238843,
-0.040586308,
-0.013174802,
0.015497498,
0.04383781,
0.012527679,
0.017876161,
0.031339817,
-0.0042566974,
-0.024129443,
-0.023050068,
-0.015625203,
0.03501345,
-0.006033779,
-0.011984176,
-0.033368077,
-0.040653296,
0.022117265,
-0.02034076,
-0.040752005,
-0.12748374,
0.029760985,
0.00084632,
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}
}
मैसेज टोकन गिनें
मैसेज प्रॉम्प्ट स्ट्रिंग पर मॉडल के टोकनाइज़र को चलाने और टोकन की गिनती पाने के लिए, countMessageTokens तरीके का इस्तेमाल करें.
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:countMessageTokens?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": { \
"messages": [ \
{"content":"How many tokens?"}, \
{"content":"For this whole conversation?"} \
] \
} \
}'
{
"tokenCount": 23
}
मॉडल पाएं
किसी खास मॉडल के बारे में जानकारी पाने के लिए, get वाला तरीका इस्तेमाल करें.
जैसे, वर्शन, डिसप्ले नेम, इनपुट टोकन की सीमा वगैरह.
curl https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001?key=$PALM_API_KEY
{
"name": "models/text-bison-001",
"version": "001",
"displayName": "Text Bison",
"description": "Model targeted for text generation.",
"inputTokenLimit": 8196,
"outputTokenLimit": 1024,
"supportedGenerationMethods": [
"generateText"
],
"temperature": 0.7,
"topP": 0.95,
"topK": 40
}
मॉडल की सूची बनाएं
PaLM API के ज़रिए उपलब्ध सभी मॉडल की सूची बनाने के लिए, list तरीके का इस्तेमाल करें.
curl https://generativelanguage.googleapis.com/v1beta2/models?key=$PALM_API_KEY
{
"models": [
{
"name": "models/chat-bison-001",
"version": "001",
"displayName": "Chat Bison",
"description": "Chat-optimized generative language model.",
"inputTokenLimit": 4096,
"outputTokenLimit": 1024,
"supportedGenerationMethods": [
"generateMessage",
"countMessageTokens"
],
"temperature": 0.25,
"topP": 0.95,
"topK": 40
},
{
"name": "models/text-bison-001",
"version": "001",
"displayName": "Text Bison",
"description": "Model targeted for text generation.",
"inputTokenLimit": 8196,
"outputTokenLimit": 1024,
"supportedGenerationMethods": [
"generateText"
],
"temperature": 0.7,
"topP": 0.95,
"topK": 40
},
{
"name": "models/embedding-gecko-001",
"version": "001",
"displayName": "Embedding Gecko",
"description": "Obtain a distributed representation of a text.",
"inputTokenLimit": 1024,
"outputTokenLimit": 1,
"supportedGenerationMethods": [
"embedText"
]
}
]
}