 前往 ai.google.dev 查看
|
 在 Google Colab 中執行
|
 前往 GitHub 查看原始碼
|
如果想快速試用 PaLM API 使用 curl 指令呼叫 REST API 中的方法。下列範例 會顯示每個 API 方法的呼叫。您必須為每個 curl 指令指定 模型名稱和 API 金鑰請參閱取得 API 金鑰 頁面 (如果還沒有頁面的話)。
"""
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'] = ""
生成文字
使用 generate_text 方法
，根據輸入訊息從模型生成回應
!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"
}
]
}
]
}
下列範例指定
generate_text 方法。
!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"
}
]
}
]
}
參數值的意義如下：
safetySettings：降低惡意程度的安全性門檻，僅封鎖高度可能的惡意內容 輸出內容stopSequences：使用停止序列只產生 1 部標題，方法是停止輸出到 下一個Title例項。temperature：產生回應時溫度設為 1.0。candidate_count：只傳回 3 個候選人回覆。maxOutputTokens：最多傳回 800 個符記。topP：只考慮模型傳回的前 80% 符記。topK：取樣時，請考慮前 10 個符記。
參閱 API 參考資料進一步瞭解這些參數
適用於 generateText
方法。
產生訊息
使用 generateMessage
對模型產生回應的方法
特定輸入內容 MessagePrompt 時，就會觸發這些事件。
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": {"messages": [{"content":"hi"}]} \
}'
{
"candidates": [
{
"author": "1",
"content": "Hi! How can I help you today?"
}
],
"messages": [
{
"author": "0",
"content": "hi"
}
]
}
以下範例說明具有不同參數值的呼叫。
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage?key=$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"
}
]
}
參數值的意義如下：
temperature：產生回覆時溫度設為 0.1。candidate_count：只傳回 1 位候選人回應。topP：只考慮模型傳回的前 80% 符記。topK：取樣時，請考慮前 10 個符記。
參閱 API 參考資料進一步瞭解這些參數
適用於 generateMessage
方法。
嵌入文字
使用 embedText 方法：
根據輸入訊息從模型生成嵌入
!curl https://generativelanguage.googleapis.com/v1beta2/models/embedding-gecko-001:embedText?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{"text": "say something nice!"}'
{
"embedding": {
"value": [
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-0.040586308,
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0.015497498,
0.04383781,
0.012527679,
0.017876161,
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-0.0042566974,
-0.024129443,
-0.023050068,
-0.015625203,
0.03501345,
-0.006033779,
-0.011984176,
-0.033368077,
-0.040653296,
0.022117265,
-0.02034076,
-0.040752005,
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0.029760985,
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-0.008121683,
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0.0131343175,
0.025023215,
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-0.0301649,
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]
}
}
計算訊息符記數量
使用
countMessageTokens
對訊息執行模型權杖化工具的方法
提示字串，然後取得符記數量。
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:countMessageTokens?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": { \
"messages": [ \
{"content":"How many tokens?"}, \
{"content":"For this whole conversation?"} \
] \
} \
}'
{
"tokenCount": 23
}
可取得模型
使用 get 方法取得特定模型的相關資訊，例如
版本、顯示名稱、輸入符記限制等
curl https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001?key=$PALM_API_KEY
{
"name": "models/text-bison-001",
"version": "001",
"displayName": "Text Bison",
"description": "Model targeted for text generation.",
"inputTokenLimit": 8196,
"outputTokenLimit": 1024,
"supportedGenerationMethods": [
"generateText"
],
"temperature": 0.7,
"topP": 0.95,
"topK": 40
}
列出模型
使用 list 方法，列出可透過該指令取得的所有模型
PaLM API
curl https://generativelanguage.googleapis.com/v1beta2/models?key=$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"
]
}
]
}