 ai.google.dev-এ দেখুন |  Google Colab-এ চালান |  GitHub-এ উৎস দেখুন |
আপনি যদি দ্রুত PaLM API ব্যবহার করে দেখতে চান, তাহলে আপনি REST API-এর পদ্ধতিগুলি কল করতে কার্ল কমান্ড ব্যবহার করতে পারেন। নিম্নলিখিত উদাহরণগুলি প্রতিটি API পদ্ধতির জন্য কল দেখায়। প্রতিটি কার্ল কমান্ডের জন্য, আপনাকে অবশ্যই মডেলের নাম এবং আপনার API কী উল্লেখ করতে হবে। আপনার যদি ইতিমধ্যে একটি না থাকে তবে একটি API কী পৃষ্ঠা পান দেখুন।
"""
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'] = ""
পাঠ্য তৈরি করুন
একটি ইনপুট বার্তা প্রদত্ত মডেল থেকে একটি প্রতিক্রিয়া তৈরি করতে generate_text পদ্ধতি ব্যবহার করুন।
!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"
}
]
}
]
}
নিম্নলিখিত উদাহরণটি generate_text পদ্ধতির সমস্ত প্যারামিটারের জন্য মান নির্দিষ্ট করে।
!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"
}
]
}
]
}
পরামিতি মান নিম্নলিখিত অর্থ আছে:
-
safetySettings: শুধুমাত্র অত্যন্ত সম্ভাব্য বিষাক্ত আউটপুটগুলিকে ব্লক করতে বিষাক্ততার জন্য নিরাপত্তা থ্রেশহোল্ড কম করুন -
stopSequences:Titleপরবর্তী উদাহরণে আউটপুট বন্ধ করে শুধুমাত্র 1টি শিরোনাম তৈরি করতে স্টপ সিকোয়েন্স ব্যবহার করুন। -
temperature: প্রতিক্রিয়া তৈরি করার সময় তাপমাত্রা 1.0 এ সেট করুন। -
candidate_count: শুধুমাত্র 3 জন প্রার্থীর প্রতিক্রিয়া ফেরত দিন। -
maxOutputTokens: সর্বাধিক 800 টোকেন ফেরত দিন। -
topP: মডেল দ্বারা প্রত্যাবর্তিত টোকেনগুলির শুধুমাত্র শীর্ষ 80% বিবেচনা করুন৷ -
topK: নমুনা নেওয়ার সময় শীর্ষ 10টি টোকেন বিবেচনা করুন।
generateText পদ্ধতির জন্য API রেফারেন্সে এই পরামিতিগুলি সম্পর্কে আরও জানুন।
বার্তা তৈরি করুন
একটি ইনপুট MessagePrompt প্রদত্ত মডেল থেকে একটি প্রতিক্রিয়া তৈরি করতে generateMessage পদ্ধতি ব্যবহার করুন।
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": {"messages": [{"content":"hi"}]} \
}'
{
"candidates": [
{
"author": "1",
"content": "Hi! How can I help you today?"
}
],
"messages": [
{
"author": "0",
"content": "hi"
}
]
}
নিম্নলিখিত উদাহরণটি পরামিতিগুলির জন্য বিভিন্ন মান সহ একটি কল দেখায়।
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage?key=$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"
}
]
}
পরামিতি মান নিম্নলিখিত অর্থ আছে:
-
temperature: প্রতিক্রিয়া তৈরি করার সময় তাপমাত্রা 0.1 এ সেট করুন। -
candidate_count: শুধুমাত্র 1 জন প্রার্থীর প্রতিক্রিয়া প্রদান করুন। -
topP: মডেল দ্বারা প্রত্যাবর্তিত টোকেনগুলির শুধুমাত্র শীর্ষ 80% বিবেচনা করুন৷ -
topK: নমুনা নেওয়ার সময় শীর্ষ 10টি টোকেন বিবেচনা করুন।
generateMessage পদ্ধতির জন্য API রেফারেন্সে এই পরামিতিগুলি সম্পর্কে আরও জানুন।
পাঠ্য এম্বেড করুন
একটি ইনপুট বার্তা দেওয়া মডেল থেকে একটি এমবেডিং তৈরি করতে embedText পদ্ধতি ব্যবহার করুন।
!curl https://generativelanguage.googleapis.com/v1beta2/models/embedding-gecko-001:embedText?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{"text": "say something nice!"}'
{
"embedding": {
"value": [
0.0011238843,
-0.040586308,
-0.013174802,
0.015497498,
0.04383781,
0.012527679,
0.017876161,
0.031339817,
-0.0042566974,
-0.024129443,
-0.023050068,
-0.015625203,
0.03501345,
-0.006033779,
-0.011984176,
-0.033368077,
-0.040653296,
0.022117265,
-0.02034076,
-0.040752005,
-0.12748374,
0.029760985,
0.00084632,
-0.017502416,
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0.0609997,
-0.0046266303,
-0.044301335,
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0.023920823,
0.0020489343,
-0.0048049283,
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0.007275116,
0.018562535,
0.017131427,
-0.00043720857,
0.02810143,
0.053296003,
0.031831037,
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0.015640317,
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-0.07687204,
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-0.015533608,
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}
}
বার্তা টোকেন গণনা
একটি বার্তা প্রম্পট স্ট্রিং এ একটি মডেলের টোকেনাইজার চালানোর জন্য countMessageTokens পদ্ধতি ব্যবহার করুন এবং একটি টোকেন গণনা পান।
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:countMessageTokens?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": { \
"messages": [ \
{"content":"How many tokens?"}, \
{"content":"For this whole conversation?"} \
] \
} \
}'
{
"tokenCount": 23
}
মডেল পান
একটি নির্দিষ্ট মডেল যেমন সংস্করণ, প্রদর্শন নাম, ইনপুট টোকেন সীমা, ইত্যাদি সম্পর্কে তথ্য পেতে get পদ্ধতি ব্যবহার করুন।
curl https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001?key=$PALM_API_KEY
{
"name": "models/text-bison-001",
"version": "001",
"displayName": "Text Bison",
"description": "Model targeted for text generation.",
"inputTokenLimit": 8196,
"outputTokenLimit": 1024,
"supportedGenerationMethods": [
"generateText"
],
"temperature": 0.7,
"topP": 0.95,
"topK": 40
}
তালিকা মডেল
PaLM API এর মাধ্যমে উপলব্ধ সমস্ত মডেলের তালিকা করতে list পদ্ধতি ব্যবহার করুন।
curl https://generativelanguage.googleapis.com/v1beta2/models?key=$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"
]
}
]
}