import requests
url = "https://application_id.applications.lucidworks.com/ai/prediction/rag/{MODEL_ID}"
payload = { "batch": [
{
"text": "Why did I go to Germany?",
"documents": [
{
"body": "I'm off to Germany to go to the Oktoberfest!",
"source": "http://example.com/112",
"title": "Off to Germany!",
"date": "2022-01-31T19:31:34Z"
}
]
}
] }
headers = {
"Authorization": "<authorization>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text){
"predictions": [
{
"tokensUsed": {
"promptTokens": 606,
"completionTokens": 23,
"totalTokens": 629
},
"answer": "The reason for going to Germany was to attend Oktoberfest.",
"answerFound": true,
"sources": [
"http://example.com/112"
],
"memoryUuid": "53417d2f-6b0e-47e4-8610-e6842b84a87b",
"response": "SOURCES:\n- 0\nANSWER: The reason for going to Germany was to attend Oktoberfest."
}
]
}RAG use case
The rag use case uses candidate documents that are inserted into a LLM’s context to ground the generated response to those documents instead of generating an answer from details stored in the LLM’s trained weights. This type of search adds guardrails so the LLM can search private data collections.
The RAG search can perform queries against external documents passed in as part of the request.
import requests
url = "https://application_id.applications.lucidworks.com/ai/prediction/rag/{MODEL_ID}"
payload = { "batch": [
{
"text": "Why did I go to Germany?",
"documents": [
{
"body": "I'm off to Germany to go to the Oktoberfest!",
"source": "http://example.com/112",
"title": "Off to Germany!",
"date": "2022-01-31T19:31:34Z"
}
]
}
] }
headers = {
"Authorization": "<authorization>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text){
"predictions": [
{
"tokensUsed": {
"promptTokens": 606,
"completionTokens": 23,
"totalTokens": 629
},
"answer": "The reason for going to Germany was to attend Oktoberfest.",
"answerFound": true,
"sources": [
"http://example.com/112"
],
"memoryUuid": "53417d2f-6b0e-47e4-8610-e6842b84a87b",
"response": "SOURCES:\n- 0\nANSWER: The reason for going to Germany was to attend Oktoberfest."
}
]
}Headers
Bearer token used for authentication. Format: Authorization: Bearer ACCESS_TOKEN.
application/json
"application/json"
Path Parameters
Unique identifier for the model.
Body
Show child attributes
Show child attributes
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Provides fields and values that specify ranges for tokens. Fields used for specific use cases and models are specified. The default values are used if other values are not specified.
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Show child attributes
Response
OK
Show child attributes
Show child attributes
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