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|
 Exécuter dans Google Colab
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 Afficher la source sur GitHub
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Si vous souhaitez essayer rapidement l'API PaLM, vous pouvez utiliser des commandes curl pour appeler les méthodes dans l'API REST. Les exemples suivants illustrent des appels pour chaque méthode API. Pour chaque commande curl, vous devez spécifier le nom du modèle et votre clé API. Consultez la page Obtenir une clé API si vous n'en avez pas déjà une.
"""
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'] = ""
Générer du texte
Utilisez la méthode generate_text pour générer une réponse à partir du modèle à partir d'un message d'entrée.
!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"
}
]
}
]
}
L'exemple suivant spécifie les valeurs de tous les paramètres de la méthode generate_text.
!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"
}
]
}
]
}
Les valeurs des paramètres ont la signification suivante:
safetySettings: abaisser le seuil de sécurité de la toxicité pour ne bloquer que les sorties toxiques hautement probablesstopSequences: utilisez la séquence d'arrêt pour générer un seul titre en arrêtant la sortie à l'instance suivante deTitle.temperature: définit la température sur 1,0 lors de la génération de réponses.candidate_count: renvoie seulement trois réponses candidates.maxOutputTokens: renvoie un maximum de 800 jetons.topP: ne prend en compte que les 80% de jetons les plus élevés renvoyés par le modèle.topK: prend en compte les 10 principaux jetons lors de l'échantillonnage.
Pour en savoir plus sur ces paramètres, consultez la documentation de référence de l'API pour la méthode generateText.
Générer un message
Utilisez la méthode generateMessage pour générer une réponse à partir du modèle en fonction d'une entrée MessagePrompt.
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": {"messages": [{"content":"hi"}]} \
}'
{
"candidates": [
{
"author": "1",
"content": "Hi! How can I help you today?"
}
],
"messages": [
{
"author": "0",
"content": "hi"
}
]
}
L'exemple suivant montre un appel avec différentes valeurs pour les paramètres.
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:generateMessage?key=$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"
}
]
}
Les valeurs des paramètres ont la signification suivante:
temperature: définit la température sur 0,1 lors de la génération de réponses.candidate_count: renvoie une seule réponse de candidat.topP: ne prend en compte que les 80% de jetons les plus élevés renvoyés par le modèle.topK: prend en compte les 10 principaux jetons lors de l'échantillonnage.
Pour en savoir plus sur ces paramètres, consultez la documentation de référence de l'API pour la méthode generateMessage.
Intégrer du texte
Utilisez la méthode embedText pour générer une représentation vectorielle continue à partir du modèle à partir d'un message d'entrée.
!curl https://generativelanguage.googleapis.com/v1beta2/models/embedding-gecko-001:embedText?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{"text": "say something nice!"}'
{
"embedding": {
"value": [
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}
}
Compter les jetons de message
Utilisez la méthode countMessageTokens pour exécuter la fonction de tokenisation d'un modèle sur une chaîne d'invite de message et obtenir le nombre de jetons.
!curl https://generativelanguage.googleapis.com/v1beta2/models/chat-bison-001:countMessageTokens?key=$PALM_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{ \
"prompt": { \
"messages": [ \
{"content":"How many tokens?"}, \
{"content":"For this whole conversation?"} \
] \
} \
}'
{
"tokenCount": 23
}
Obtenir le modèle
Utilisez la méthode get pour obtenir des informations sur un modèle spécifique, telles que la version, le nom à afficher, la limite de jetons d'entrée, etc.
curl https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001?key=$PALM_API_KEY
{
"name": "models/text-bison-001",
"version": "001",
"displayName": "Text Bison",
"description": "Model targeted for text generation.",
"inputTokenLimit": 8196,
"outputTokenLimit": 1024,
"supportedGenerationMethods": [
"generateText"
],
"temperature": 0.7,
"topP": 0.95,
"topK": 40
}
Répertorier les modèles
Utilisez la méthode list pour répertorier tous les modèles disponibles via l'API PaLM.
curl https://generativelanguage.googleapis.com/v1beta2/models?key=$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"
]
}
]
}