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chatperplexity stream-citations in additional kwargs (#29273)
chatperplexity stream-citations in additional kwargs --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>
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@ -223,15 +223,21 @@ class ChatPerplexity(BaseChatModel):
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stream_resp = self.client.chat.completions.create(
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messages=message_dicts, stream=True, **params
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)
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first_chunk = True
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for chunk in stream_resp:
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if not isinstance(chunk, dict):
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chunk = chunk.dict()
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if len(chunk["choices"]) == 0:
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continue
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choice = chunk["choices"][0]
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citations = chunk.get("citations", [])
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chunk = self._convert_delta_to_message_chunk(
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choice["delta"], default_chunk_class
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)
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if first_chunk:
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chunk.additional_kwargs |= {"citations": citations}
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first_chunk = False
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finish_reason = choice.get("finish_reason")
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generation_info = (
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dict(finish_reason=finish_reason) if finish_reason is not None else None
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@ -1,8 +1,12 @@
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"""Test Perplexity Chat API wrapper."""
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import os
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from typing import Any, Dict, List, Optional
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from unittest.mock import MagicMock
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import pytest
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from langchain_core.messages import AIMessageChunk, BaseMessageChunk
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from pytest_mock import MockerFixture
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from langchain_community.chat_models import ChatPerplexity
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@ -40,3 +44,58 @@ def test_perplexity_initialization() -> None:
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]:
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assert model.request_timeout == 1
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assert model.pplx_api_key == "test"
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@pytest.mark.requires("openai")
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def test_perplexity_stream_includes_citations(mocker: MockerFixture) -> None:
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"""Test that the stream method includes citations in the additional_kwargs."""
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llm = ChatPerplexity(
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model="test",
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timeout=30,
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verbose=True,
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)
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mock_chunk_0 = {
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"choices": [
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{
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"delta": {
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"content": "Hello ",
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},
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"finish_reason": None,
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}
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],
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"citations": ["example.com", "example2.com"],
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}
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mock_chunk_1 = {
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"choices": [
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{
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"delta": {
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"content": "Perplexity",
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},
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"finish_reason": None,
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}
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],
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"citations": ["example.com", "example2.com"],
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}
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mock_chunks: List[Dict[str, Any]] = [mock_chunk_0, mock_chunk_1]
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mock_stream = MagicMock()
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mock_stream.__iter__.return_value = mock_chunks
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patcher = mocker.patch.object(
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llm.client.chat.completions, "create", return_value=mock_stream
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)
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stream = llm.stream("Hello langchain")
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full: Optional[BaseMessageChunk] = None
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for i, chunk in enumerate(stream):
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full = chunk if full is None else full + chunk
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assert chunk.content == mock_chunks[i]["choices"][0]["delta"]["content"]
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if i == 0:
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assert chunk.additional_kwargs["citations"] == [
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"example.com",
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"example2.com",
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]
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else:
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assert "citations" not in chunk.additional_kwargs
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assert isinstance(full, AIMessageChunk)
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assert full.content == "Hello Perplexity"
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assert full.additional_kwargs == {"citations": ["example.com", "example2.com"]}
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patcher.assert_called_once()
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