Chilkat Online Tools

GetRecommendations Python Example

Amazon Wisdom

import sys
import chilkat2

# This example requires the Chilkat API to have been previously unlocked.
# See Global Unlock Sample for sample code.

rest = chilkat2.Rest()

authAws = chilkat2.AuthAws()
authAws.AccessKey = "AWS_ACCESS_KEY"
authAws.SecretKey = "AWS_SECRET_KEY"

# Don't forget to change the region to your particular region. (Also make the same change in the call to Connect below.)
authAws.Region = "us-west-2"
authAws.ServiceName = "wisdom"
# SetAuthAws causes Chilkat to automatically add the following headers: Authorization, X-Amz-Date
rest.SetAuthAws(authAws)

# URL: https://wisdom.us-west-2.amazonaws.com/
# Use the same region as specified above.
success = rest.Connect("wisdom.us-west-2.amazonaws.com",443,True,True)
if (success != True):
    print("ConnectFailReason: " + str(rest.ConnectFailReason))
    print(rest.LastErrorText)
    sys.exit()

rest.AddHeader("Content-Type","application/x-amz-json-1.1")
rest.AddHeader("X-Amz-Target","GetRecommendations")

sbResponseBody = chilkat2.StringBuilder()
success = rest.FullRequestNoBodySb("GET","/assistants/{assistantId}/sessions/{sessionId}/recommendations",sbResponseBody)
if (success != True):
    print(rest.LastErrorText)
    sys.exit()

respStatusCode = rest.ResponseStatusCode
print("response status code = " + str(respStatusCode))
if (respStatusCode != 200):
    print("Response Header:")
    print(rest.ResponseHeader)
    print("Response Body:")
    print(sbResponseBody.GetAsString())
    sys.exit()

jResp = chilkat2.JsonObject()
jResp.LoadSb(sbResponseBody)

# The following code parses the JSON response.
# A sample JSON response is shown below the sample code.

# Use this online tool to generate parsing code from sample JSON:
# Generate Parsing Code from JSON

i = 0
count_i = jResp.SizeOfArray("recommendations")
while i < count_i :
    jResp.I = i
    ContentArn = jResp.StringOf("recommendations[i].document.contentReference.contentArn")
    ContentId = jResp.StringOf("recommendations[i].document.contentReference.contentId")
    KnowledgeBaseArn = jResp.StringOf("recommendations[i].document.contentReference.knowledgeBaseArn")
    KnowledgeBaseId = jResp.StringOf("recommendations[i].document.contentReference.knowledgeBaseId")
    Text = jResp.StringOf("recommendations[i].document.excerpt.text")
    TitleText = jResp.StringOf("recommendations[i].document.title.text")
    recommendationId = jResp.StringOf("recommendations[i].recommendationId")
    relevanceLevel = jResp.StringOf("recommendations[i].relevanceLevel")
    relevanceScore = jResp.IntOf("recommendations[i].relevanceScore")
    j = 0
    count_j = jResp.SizeOfArray("recommendations[i].document.excerpt.highlights")
    while j < count_j :
        jResp.J = j
        beginOffsetInclusive = jResp.IntOf("recommendations[i].document.excerpt.highlights[j].beginOffsetInclusive")
        endOffsetExclusive = jResp.IntOf("recommendations[i].document.excerpt.highlights[j].endOffsetExclusive")
        j = j + 1

    j = 0
    count_j = jResp.SizeOfArray("recommendations[i].document.title.highlights")
    while j < count_j :
        jResp.J = j
        beginOffsetInclusive = jResp.IntOf("recommendations[i].document.title.highlights[j].beginOffsetInclusive")
        endOffsetExclusive = jResp.IntOf("recommendations[i].document.title.highlights[j].endOffsetExclusive")
        j = j + 1

    i = i + 1

# A sample JSON response body parsed by the above code:

# {
#   "recommendations": [
#     {
#       "document": {
#         "contentReference": {
#           "contentArn": "string",
#           "contentId": "string",
#           "knowledgeBaseArn": "string",
#           "knowledgeBaseId": "string"
#         },
#         "excerpt": {
#           "highlights": [
#             {
#               "beginOffsetInclusive": number,
#               "endOffsetExclusive": number
#             }
#           ],
#           "text": "string"
#         },
#         "title": {
#           "highlights": [
#             {
#               "beginOffsetInclusive": number,
#               "endOffsetExclusive": number
#             }
#           ],
#           "text": "string"
#         }
#       },
#       "recommendationId": "string",
#       "relevanceLevel": "string",
#       "relevanceScore": number
#     }
#   ]
# }