# Claro AI python client
API for data ingestion
project:
- API version: 1.0.0
- Package version: 0.0.b0
## Requirements.
Python 3.7+
## Installation & Usage
### pip install
```sh
pip install claroai
```
Then import the package:
```python
import claroai
```
## Getting Started
```python
import claroai
from pprint import pprint
from claroai.rest import ApiException
configuration = claroai.Configuration(username="test", password="test")
with claroai.ApiClient(configuration) as api_client:
# Create an instance of the API class
conversation_api_instance = claroai.ConversationApi(api_client)
conversation_data_schema = claroai.ConversationData(
[ # List[claroai.ConversationSchema] or claroai.ConversationSchema
claroai.ConversationSchema(
conversation_id="1",
conversation_created_at="2021-01-01T00:00:00Z",
user_id="1",
messages=[
{
"id": "Thiyagu",
"role": "user",
"body": "What time does the team arrive?",
"created_at": "2020-02-20T20:19:34Z",
}
],
),
claroai.ConversationSchema(
conversation_id="2",
conversation_created_at="2021-01-01T00:00:00Z",
user_id="1",
messages=[
{
"id": "Thiyagu 2",
"role": "user",
"body": "What time does the team arrive?",
"created_at": "2020-02-20T20:19:34Z",
}
],
),
]
)
interaction_api_instance = claroai.InteractionApi(api_client)
interaction_data_schema = claroai.InteractionData(
claroai.InteractionSchema( # claroai.InteractionSchema or List[claroai.InteractionSchema]
conversation_id="1",
interaction_id="1",
user_id="1",
content="What time does the team arrive?",
created_at="2020-02-20T20:19:34Z",
interacted_at="2020-02-20T20:19:34Z",
)
)
try:
# Log a batch of conversations to BigQuery
conversation_api_response = conversation_api_instance.ingest_conversation(
conversation_data_schema
)
print("The response of ConversationApi->ingest_conversations:\n")
pprint(conversation_api_response)
# Log a batch of interactions to BigQuery
interaction_api_response = interaction_api_instance.ingest_interaction(
interaction_data_schema
)
print("The response of ConversationApi->ingest_interactions:\n")
pprint(interaction_api_response)
except ApiException as e:
print("Exception when ingesting data: %s\n" % e)
Raw data
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"description": "# Claro AI python client\nAPI for data ingestion\n\nproject:\n\n- API version: 1.0.0\n- Package version: 0.0.b0\n\n## Requirements.\n\nPython 3.7+\n\n## Installation & Usage\n### pip install\n\n```sh\npip install claroai\n```\n\n\nThen import the package:\n```python\nimport claroai\n```\n\n## Getting Started\n\n\n\n```python\nimport claroai\n\nfrom pprint import pprint\n\nfrom claroai.rest import ApiException\n\n\nconfiguration = claroai.Configuration(username=\"test\", password=\"test\")\n\n\nwith claroai.ApiClient(configuration) as api_client:\n # Create an instance of the API class\n conversation_api_instance = claroai.ConversationApi(api_client)\n\n conversation_data_schema = claroai.ConversationData(\n [ # List[claroai.ConversationSchema] or claroai.ConversationSchema\n claroai.ConversationSchema(\n conversation_id=\"1\",\n conversation_created_at=\"2021-01-01T00:00:00Z\",\n user_id=\"1\",\n messages=[\n {\n \"id\": \"Thiyagu\",\n \"role\": \"user\",\n \"body\": \"What time does the team arrive?\",\n \"created_at\": \"2020-02-20T20:19:34Z\",\n }\n ],\n ),\n claroai.ConversationSchema(\n conversation_id=\"2\",\n conversation_created_at=\"2021-01-01T00:00:00Z\",\n user_id=\"1\",\n messages=[\n {\n \"id\": \"Thiyagu 2\",\n \"role\": \"user\",\n \"body\": \"What time does the team arrive?\",\n \"created_at\": \"2020-02-20T20:19:34Z\",\n }\n ],\n ),\n ]\n )\n\n interaction_api_instance = claroai.InteractionApi(api_client)\n\n interaction_data_schema = claroai.InteractionData(\n claroai.InteractionSchema( # claroai.InteractionSchema or List[claroai.InteractionSchema]\n conversation_id=\"1\",\n interaction_id=\"1\",\n user_id=\"1\",\n content=\"What time does the team arrive?\",\n created_at=\"2020-02-20T20:19:34Z\",\n interacted_at=\"2020-02-20T20:19:34Z\",\n )\n )\n try:\n # Log a batch of conversations to BigQuery\n conversation_api_response = conversation_api_instance.ingest_conversation(\n conversation_data_schema\n )\n\n print(\"The response of ConversationApi->ingest_conversations:\\n\")\n pprint(conversation_api_response)\n\n # Log a batch of interactions to BigQuery\n interaction_api_response = interaction_api_instance.ingest_interaction(\n interaction_data_schema\n )\n print(\"The response of ConversationApi->ingest_interactions:\\n\")\n pprint(interaction_api_response)\n\n except ApiException as e:\n print(\"Exception when ingesting data: %s\\n\" % e)\n",
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