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Knowledge Bases

Operations for the Knowledge Bases service collection.

LanguageLast Update
Pythonv1.6.5
PowerShell
Gov0.22.0
TypeScriptv0.6.0
Rust
Rubyv1.4.0


OperationDescription
CombinedKnowledgeBasesV1
combined_knowledge_bases_v1
Search for knowledge bases with filtering and return full entity details in a single response.
EntitiesKnowledgeBasesCreateV1
entities_knowledge_bases_create_v1
Create or update a knowledge base.
EntitiesKnowledgeBasesUpdateV1
entities_knowledge_bases_update_v1
Update an existing knowledge base.
EntitiesKnowledgeBasesV1
entities_knowledge_bases_v1
Retrieve knowledge base entities for the provided id.
QueriesKnowledgeBasesV1
queries_knowledge_bases_v1
Query knowledge bases based on the provided filters.

Search for knowledge bases with filtering and return full entity details in a single response.

Method GET
Route /agentic-studio/combined/knowledge_bases/v1
Scope Charlotte AI Agent Definition: READ
PEP 8 combined_knowledge_bases_v1
offset query · integer
Starting index of overall result set from which to return ids.
limit query · integer
Number of ids to return. Offset + limit should NOT be above 10K.
sort query · string
Possible order by fields:
Available values (2)
namecreated_at
filter query · string
FQL query specifying the filter parameters.
include_deleted query · boolean
Include deleted knowledge bases in the result. Defaults to false.
parameters query · dictionary
Full query string parameters payload in JSON format. Not required when using other keywords.
from falconpy import KnowledgeBases
falcon = KnowledgeBases(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.combined_knowledge_bases_v1(offset=integer,
limit=integer,
sort="string",
filter="string",
include_deleted=boolean)
print(response)
[
{
"created_at": "string",
"created_by": {},
"description": "string",
"embedding_model": "string",
"files_count": 0,
"id": "string",
"is_deleted": false,
"name": "string",
"updated_at": "string",
"updated_by": {}
}
]


Create or update a knowledge base.

Method POST
Route /agentic-studio/entities/knowledge_bases/v1
Scope Charlotte AI Agent Definition: WRITE
PEP 8 entities_knowledge_bases_create_v1
body body · dictionary
Full body payload as JSON formatted dictionary.
created_at body · string
The created_at value.
created_by body · object
The created_by value.
description body · string
The description value.
embedding_model body · string
The embedding_model value.
files_count body · integer
The files_count value.
id body · string
The id value.
is_deleted body · boolean
The is_deleted value.
name body · string
The name value.
updated_at body · string
The updated_at value.
updated_by body · object
The updated_by value.
from falconpy import KnowledgeBases
falcon = KnowledgeBases(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
created_by = {
"cid": "string",
"created_at": "string",
"factors": [
"string"
],
"first_name": "string",
"last_login_at": "string",
"last_name": "string",
"status": "string",
"uid": "string",
"updated_at": "string",
"user_type": "string",
"uuid": "string"
}
updated_by = {
"cid": "string",
"created_at": "string",
"factors": [
"string"
],
"first_name": "string",
"last_login_at": "string",
"last_name": "string",
"status": "string",
"uid": "string",
"updated_at": "string",
"user_type": "string",
"uuid": "string"
}
response = falcon.entities_knowledge_bases_create_v1(created_at="string",
created_by=created_by,
description="string",
embedding_model="string",
files_count=integer,
id="string",
is_deleted=boolean,
name="string",
updated_at="string",
updated_by=updated_by)
print(response)
[
{
"created_at": "string",
"created_by": {},
"description": "string",
"embedding_model": "string",
"files_count": 0,
"id": "string",
"is_deleted": false,
"name": "string",
"updated_at": "string",
"updated_by": {}
}
]


Update an existing knowledge base.

Method PATCH
Route /agentic-studio/entities/knowledge_bases/v1
Scope Charlotte AI Agent Definition: WRITE
PEP 8 entities_knowledge_bases_update_v1
body body · dictionary
Full body payload as JSON formatted dictionary.
created_at body · string
The created_at value.
created_by body · object
The created_by value.
description body · string
The description value.
embedding_model body · string
The embedding_model value.
files_count body · integer
The files_count value.
id body · string
The id value.
is_deleted body · boolean
The is_deleted value.
name body · string
The name value.
updated_at body · string
The updated_at value.
updated_by body · object
The updated_by value.
from falconpy import KnowledgeBases
falcon = KnowledgeBases(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
created_by = {
"cid": "string",
"created_at": "string",
"factors": [
"string"
],
"first_name": "string",
"last_login_at": "string",
"last_name": "string",
"status": "string",
"uid": "string",
"updated_at": "string",
"user_type": "string",
"uuid": "string"
}
updated_by = {
"cid": "string",
"created_at": "string",
"factors": [
"string"
],
"first_name": "string",
"last_login_at": "string",
"last_name": "string",
"status": "string",
"uid": "string",
"updated_at": "string",
"user_type": "string",
"uuid": "string"
}
response = falcon.entities_knowledge_bases_update_v1(created_at="string",
created_by=created_by,
description="string",
embedding_model="string",
files_count=integer,
id="string",
is_deleted=boolean,
name="string",
updated_at="string",
updated_by=updated_by)
print(response)
[
{
"created_at": "string",
"created_by": {},
"description": "string",
"embedding_model": "string",
"files_count": 0,
"id": "string",
"is_deleted": false,
"name": "string",
"updated_at": "string",
"updated_by": {}
}
]


Retrieve knowledge base entities for the provided id.

Method GET
Route /agentic-studio/entities/knowledge_bases/v1
Scope Charlotte AI Agent Definition: READ
PEP 8 entities_knowledge_bases_v1
ids query · string or list of strings
IDs of entities to retrieve.
include_deleted query · boolean
Include deleted knowledge bases in the result. Defaults to false.
parameters query · dictionary
Full query string parameters payload in JSON format. Not required when using other keywords.
from falconpy import KnowledgeBases
falcon = KnowledgeBases(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
id_list = 'ID1,ID2,ID3' # Can also pass a list here: ['ID1', 'ID2', 'ID3']
response = falcon.entities_knowledge_bases_v1(ids=id_list,
include_deleted=boolean)
print(response)
[
{
"created_at": "string",
"created_by": {},
"description": "string",
"embedding_model": "string",
"files_count": 0,
"id": "string",
"is_deleted": false,
"name": "string",
"updated_at": "string",
"updated_by": {}
}
]


Query knowledge bases based on the provided filters.

Method GET
Route /agentic-studio/queries/knowledge_bases/v1
Scope Charlotte AI Agent Definition: READ
PEP 8 queries_knowledge_bases_v1
offset query · integer
Starting index of overall result set from which to return ids.
limit query · integer
Number of IDs to return. Offset + limit should NOT be above 10K.
sort query · string
asc’.
filter query · string
FQL query specifying the filter parameters.
include_deleted query · boolean
Include deleted knowledge bases in the result. Defaults to false.
parameters query · dictionary
Full query string parameters payload in JSON format. Not required when using other keywords.
from falconpy import KnowledgeBases
falcon = KnowledgeBases(client_id=CLIENT_ID,
client_secret=CLIENT_SECRET
)
response = falcon.queries_knowledge_bases_v1(offset=integer,
limit=integer,
sort="string",
filter="string",
include_deleted=boolean)
print(response)
[
"string"
]