QGPT API

All URIs are relative to http://localhost:1000

Method	HTTP request	Description
hints	POST /qgpt/hints	/qgpt/hints [POST]
persons_related	POST /qgpt/persons/related	/qgpt/persons/related [POST]
qgpt_stream	GET /qgpt/stream	/qgpt/stream [WS]
question	POST /qgpt/question	/qgpt/question [POST]
relevance	POST /qgpt/relevance	/qgpt/relevance [POST]
reprompt	POST /qgpt/reprompt	/qgpt/reprompt [POST]

hints

QGPTQuestionOutput hints(qgpt_hints_input=qgpt_hints_input)

/qgpt/hints [POST]

Generates suggested questions that users can ask. It accepts the answer displayed to the user, relevant code snippets used for the answer, and the previous query as inputs. In return, it provides a list of questions that can be presented to the user.

Example

import pieces_os_client
from pieces_os_client.models.qgpt_hints_input import QGPTHintsInput
from pieces_os_client.models.qgpt_question_output import QGPTQuestionOutput
from pieces_os_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:1000
# See configuration.py for a list of all supported configuration parameters.
configuration = pieces_os_client.Configuration(
    host = "http://localhost:1000"
)


# Enter a context with an instance of the API client
with pieces_os_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = QGPT API(api_client)
    qgpt_hints_input = pieces_os_client.QGPTHintsInput() # QGPTHintsInput |  (optional)

    try:
        # /qgpt/hints [POST]
        api_response = api_instance.hints(qgpt_hints_input=qgpt_hints_input)
        print("The response of QGPTApi->hints:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling QGPTApi->hints: %s\n" % e)

Parameters

Name	Type	Description	Notes
qgpt_hints_input	QGPTHintsInput		[optional]

Return type

QGPTQuestionOutput

Authorization

No authorization required

HTTP request headers

Content-Type: application/json
Accept: application/json, text/plain

HTTP response details

Status code	Description	Response headers
200	OK	-
500	Internal Server Error	-

persons_related

QGPTPersonsRelatedOutput persons_related(transferables=transferables, qgpt_persons_related_input=qgpt_persons_related_input)

/qgpt/persons/related [POST]

Utilize this endpoint for Who Support, identifying individuals who can provide assistance when given context such as a Seed or a QGPT Conversation, for example. Input: - (optional) seed: Seed - Only supports fragments for now. - (optional) conversation: QGPTConversation. Output: - persons: Persons

Example

import pieces_os_client
from pieces_os_client.models.qgpt_persons_related_input import QGPTPersonsRelatedInput
from pieces_os_client.models.qgpt_persons_related_output import QGPTPersonsRelatedOutput
from pieces_os_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:1000
# See configuration.py for a list of all supported configuration parameters.
configuration = pieces_os_client.Configuration(
    host = "http://localhost:1000"
)


# Enter a context with an instance of the API client
with pieces_os_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = QGPT API(api_client)
    transferables = True # bool | This is a boolean that will decided if we are want to return the transferable data (default) or not(performance enhancement) (optional)
    qgpt_persons_related_input = pieces_os_client.QGPTPersonsRelatedInput() # QGPTPersonsRelatedInput |  (optional)

    try:
        # /qgpt/persons/related [POST]
        api_response = api_instance.persons_related(transferables=transferables, qgpt_persons_related_input=qgpt_persons_related_input)
        print("The response of QGPTApi->persons_related:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling QGPTApi->persons_related: %s\n" % e)

Parameters

Name	Type	Description	Notes
transferables	bool	This is a boolean that will decided if we are want to return the transferable data (default) or not(performance enhancement)	[optional]
qgpt_persons_related_input	QGPTPersonsRelatedInput		[optional]

Return type

QGPTPersonsRelatedOutput

Authorization

No authorization required

HTTP request headers

Content-Type: application/json
Accept: application/json, text/plain

HTTP response details

Status code	Description	Response headers
200	OK	-
500	Internal Server Error	-

qgpt_stream

QGPTStreamOutput qgpt_stream(qgpt_stream_input=qgpt_stream_input)

/qgpt/stream [WS]

Provides a WebSocket connection that streams inputs to the qGPT model. It handles relevance and questions, but will throw an error if both are passed in simultaneously. However, if you wish to utilize both question and relevance, you can obtain stream results by passing relevance with the option 'question:true'. It is designed to manage multiple conversations.

Example

import pieces_os_client
from pieces_os_client.models.qgpt_stream_input import QGPTStreamInput
from pieces_os_client.models.qgpt_stream_output import QGPTStreamOutput
from pieces_os_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:1000
# See configuration.py for a list of all supported configuration parameters.
configuration = pieces_os_client.Configuration(
    host = "http://localhost:1000"
)


# Enter a context with an instance of the API client
with pieces_os_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = QGPT API(api_client)
    qgpt_stream_input = pieces_os_client.QGPTStreamInput() # QGPTStreamInput |  (optional)

    try:
        # /qgpt/stream [WS]
        api_response = api_instance.qgpt_stream(qgpt_stream_input=qgpt_stream_input)
        print("The response of QGPTApi->qgpt_stream:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling QGPTApi->qgpt_stream: %s\n" % e)

Parameters

Name	Type	Description	Notes
qgpt_stream_input	QGPTStreamInput		[optional]

Return type

QGPTStreamOutput

Authorization

No authorization required

HTTP request headers

Content-Type: application/json
Accept: application/json, text/plain

HTTP response details

Status code	Description	Response headers
200	OK	-
401	Invalid Authentication, Incorrect API key provided or organization	-
429	Rate limit/Quota exceeded	-
500	Internal Server Error	-
503	The engine is currently overloaded	-

question

QGPTQuestionOutput question(qgpt_question_input=qgpt_question_input)

/qgpt/question [POST]

Processes relevant code snippets or UUIDs returned from the /qgpt/relevance endpoint, along with a question query, to provide possible answers. Note: - Relevant seeds must either include an ID used within the /qgpt/relevance endpoint or a seed with a fragment/string; otherwise, an error will be thrown. - This endpoint utilizes your query and relevant snippets to generate multiple answers, each accompanied by a score.

Example

import pieces_os_client
from pieces_os_client.models.qgpt_question_input import QGPTQuestionInput
from pieces_os_client.models.qgpt_question_output import QGPTQuestionOutput
from pieces_os_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:1000
# See configuration.py for a list of all supported configuration parameters.
configuration = pieces_os_client.Configuration(
    host = "http://localhost:1000"
)


# Enter a context with an instance of the API client
with pieces_os_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = QGPT API(api_client)
    qgpt_question_input = pieces_os_client.QGPTQuestionInput() # QGPTQuestionInput |  (optional)

    try:
        # /qgpt/question [POST]
        api_response = api_instance.question(qgpt_question_input=qgpt_question_input)
        print("The response of QGPTApi->question:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling QGPTApi->question: %s\n" % e)

Parameters

Name	Type	Description	Notes
qgpt_question_input	QGPTQuestionInput		[optional]

Return type

QGPTQuestionOutput

Authorization

No authorization required

HTTP request headers

Content-Type: application/json
Accept: application/json, text/plain

HTTP response details

Status code	Description	Response headers
200	OK	-
401	Invalid Authentication, Incorrect API key provided or organization	-
429	Too Many Requests (Rate limit or quota exceeded)	-
500	Internal Server Error	-
503	Service Unavailable, (engine is currently overloaded)	-

relevance

QGPTRelevanceOutput relevance(qgpt_relevance_input=qgpt_relevance_input)

/qgpt/relevance [POST]

This is the first phase to the QGPT flow. Please one of the following. 1. provide an absolute path on the users machine that we can use locally. 2. provide Seeds that you want to compare to, which will be ONLY fragment/string values(all other values will be ignored) 3. provide assets, here you can provide an iterable of the asset id, and we will do the rest 4. you can set your database boolean to true which will tell us to use your entire DB as the query space. required - query: string; This is the question of the user. optional - question: boolean; This will by-pass the second endpoint and just ask the question and return the results(as an ease of use bool) This endpoint will embed everything. and will return the relevance snippets that we will use in the next phase, to answer your question. on the UI: we can show this to users (around this is the snippets we used to answer your question.) Next: feed this information to the /qgpt/question [POST] endpoint to get your question answered.(unless you included the question:true optional boolean, then you will get the results from here.)

Example

import pieces_os_client
from pieces_os_client.models.qgpt_relevance_input import QGPTRelevanceInput
from pieces_os_client.models.qgpt_relevance_output import QGPTRelevanceOutput
from pieces_os_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:1000
# See configuration.py for a list of all supported configuration parameters.
configuration = pieces_os_client.Configuration(
    host = "http://localhost:1000"
)


# Enter a context with an instance of the API client
with pieces_os_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = QGPT API(api_client)
    qgpt_relevance_input = pieces_os_client.QGPTRelevanceInput() # QGPTRelevanceInput |  (optional)

    try:
        # /qgpt/relevance [POST]
        api_response = api_instance.relevance(qgpt_relevance_input=qgpt_relevance_input)
        print("The response of QGPTApi->relevance:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling QGPTApi->relevance: %s\n" % e)

Parameters

Name	Type	Description	Notes
qgpt_relevance_input	QGPTRelevanceInput		[optional]

Return type

QGPTRelevanceOutput

Authorization

No authorization required

HTTP request headers

Content-Type: application/json
Accept: application/json, text/plain

HTTP response details

Status code	Description	Response headers
200	OK	-
401	Invalid Authentication, Incorrect API key provided or organization	-
429	Too Many Requests (Rate limit or quota exceeded)	-
500	Internal Server Error	-
503	Service Unavailable, (engine is currently overloaded)	-

reprompt

QGPTRepromptOutput reprompt(qgpt_reprompt_input=qgpt_reprompt_input)

/qgpt/reprompt [POST]

This will take in a followup question and the history of the conversation, and emit your a prompt or query that you can pass to the /qgpt/relevance and then the /qgpt/question endpoint to get your next answer.

Example

import pieces_os_client
from pieces_os_client.models.qgpt_reprompt_input import QGPTRepromptInput
from pieces_os_client.models.qgpt_reprompt_output import QGPTRepromptOutput
from pieces_os_client.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to http://localhost:1000
# See configuration.py for a list of all supported configuration parameters.
configuration = pieces_os_client.Configuration(
    host = "http://localhost:1000"
)


# Enter a context with an instance of the API client
with pieces_os_client.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = QGPT API(api_client)
    qgpt_reprompt_input = pieces_os_client.QGPTRepromptInput() # QGPTRepromptInput |  (optional)

    try:
        # /qgpt/reprompt [POST]
        api_response = api_instance.reprompt(qgpt_reprompt_input=qgpt_reprompt_input)
        print("The response of QGPTApi->reprompt:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling QGPTApi->reprompt: %s\n" % e)

Parameters

Name	Type	Description	Notes
qgpt_reprompt_input	QGPTRepromptInput		[optional]

Return type

QGPTRepromptOutput

Authorization

No authorization required

HTTP request headers

Content-Type: application/json
Accept: application/json, text/plain

HTTP response details

Status code	Description	Response headers
200	OK	-
500	Internal Server Error	-

QGPT API

hints​

Example​

Parameters​

Return type​

Authorization​

HTTP request headers​

HTTP response details​

persons_related​

Example​

Parameters​

Return type​

Authorization​

HTTP request headers​

HTTP response details​

qgpt_stream​

Example​

Parameters​

Return type​

Authorization​

HTTP request headers​

HTTP response details​

question​

Example​

Parameters​

Return type​

Authorization​

HTTP request headers​

HTTP response details​

relevance​

Example​

Parameters​

Return type​

Authorization​

HTTP request headers​

HTTP response details​

reprompt​

Example​

Parameters​

Return type​

Authorization​

HTTP request headers​

HTTP response details​

hints

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

persons_related

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

qgpt_stream

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

question

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

relevance

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

reprompt

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details