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Chat

Conversational pipelines: build a Question, send it with client.chat(), and parse the response with Answer. Class tables in the API reference.

Chat is the conversational lane: it works against chat, webhook, and dropper pipeline sources. Under the hood the client opens a pipe with MIME type application/rocketride-question, writes the serialized Question, closes the pipe, and returns the server result.

Build a Question​

from rocketride.schema import Question

question = Question(expectJson=True)
question.addInstruction('Format', 'Return a JSON object with keys: summary, keywords.')
question.addExample('Summarize X', {'summary': '...', 'keywords': ['a', 'b']})
question.addQuestion('Summarize the main points and list keywords.')

Question(type=QuestionType.QUESTION, filter=DocFilter(), expectJson=False, role='') — QuestionType is one of QUESTION, SEMANTIC, KEYWORD, GET, PROMPT. Steer the model with addInstruction, addExample, addContext, addHistory (for multi-turn), addDocuments, addGoal, and addQuestion.

Send it​

response = await client.chat(token=token, question=question)

chat(*, token, question, on_sse=None) is keyword-only; the optional on_sse callback streams server-sent events (token-by-token output) as they arrive. The final answer is in the result body.

Parse the response with Answer​

Answer extracts structure from AI text, which often arrives wrapped in markdown or code fences. The client does not attach an Answer to the result — you read the body and feed it in:

from rocketride.schema import Answer

answer_text = (response.get('answers') or [None])[0]
answer = Answer(expectJson=True)
answer.setAnswer(answer_text or '')
if answer.isJson():
    structured = answer.getJson()
else:
    structured = answer.getText()

Semantics worth knowing:

  • setAnswer(value) stores the response, validating/parsing it as JSON when expectJson is True.
  • isJson() returns the expectJson flag — it does not inspect the content.
  • getJson() returns the parsed JSON; it returns None only when no answer has been set, and raises ValueError if the stored answer is not valid JSON.
  • getText() returns the answer as plain text; parsePython(value) extracts Python code from a code block.
  • answer.tokens carries the turn-total LLM token usage reported by the server.

A complete chat program is example 6.

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