5a9d6f75be
- Migrate the MVP into kotaemon. - Preliminary include the pipeline within chatbot interface. - Organize MVP as an application. Todo: - Add an info panel to view the planning of agents -> Fix streaming agents' output. Resolve: #60 Resolve: #61 Resolve: #62
63 lines
2.9 KiB
Python
63 lines
2.9 KiB
Python
# flake8: noqa
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from unittest.mock import patch
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import pytest
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from openai.types.chat.chat_completion import ChatCompletion
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from kotaemon.indices.qa import CitationPipeline
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from kotaemon.llms import AzureChatOpenAI
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function_output = '{\n "question": "What is the provided _example_ benefits?",\n "answer": [\n {\n "fact": "特約死亡保険金: 被保険者がこの特約の保険期間中に死亡したときに支払います。",\n "substring_quote": ["特約死亡保険金"]\n },\n {\n "fact": "特約特定疾病保険金: 被保険者がこの特約の保険期間中に特定の疾病（悪性新生物（がん）、急性心筋梗塞または脳卒中）により所定の状態に該当したときに支払います。",\n "substring_quote": ["特約特定疾病保険金"]\n },\n {\n "fact": "特約障害保険金: 被保険者がこの特約の保険期間中に傷害もしくは疾病により所定の身体障害の状態に該当したとき、または不慮の事故により所定の身体障害の状態に該当したときに支払います。",\n "substring_quote": ["特約障害保険金"]\n },\n {\n "fact": "特約介護保険金: 被保険者がこの特約の保険期間中に傷害または疾病により所定の要介護状態に該当したときに支払います。",\n "substring_quote": ["特約介護保険金"]\n }\n ]\n}'
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_openai_chat_completion_response = [
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ChatCompletion.parse_obj(
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{
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"id": "chatcmpl-7qyuw6Q1CFCpcKsMdFkmUPUa7JP2x",
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"object": "chat.completion",
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"created": 1692338378,
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"model": "gpt-35-turbo",
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"system_fingerprint": None,
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"choices": [
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{
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"index": 0,
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"finish_reason": "function_call",
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"message": {
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"role": "assistant",
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"content": None,
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"function_call": {
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"arguments": function_output,
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"name": "QuestionAnswer",
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},
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"tool_calls": None,
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},
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"logprobs": None,
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}
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],
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"usage": {"completion_tokens": 9, "prompt_tokens": 10, "total_tokens": 19},
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}
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)
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]
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@pytest.fixture
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def llm():
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return AzureChatOpenAI(
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azure_endpoint="https://dummy.openai.azure.com/",
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openai_api_key="dummy",
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openai_api_version="2023-03-15-preview",
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temperature=0,
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)
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@patch(
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"openai.resources.chat.completions.Completions.create",
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side_effect=_openai_chat_completion_response,
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)
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def test_citation(openai_completion, llm):
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question = "test query"
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context = "document context"
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citation = CitationPipeline(llm=llm)
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result = citation(context, question)
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assert len(result.answer) == 4
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