diff --git a/backend/uv.lock b/backend/uv.lock
index d8d9707f13..5d6bce3717 100644
--- a/backend/uv.lock
+++ b/backend/uv.lock
@@ -3996,6 +3996,7 @@ docs = [{ name = "lazydocs", specifier = "~=0.4.8" }]
 test = [
     { name = "parameterized", specifier = "==0.9.0" },
     { name = "pytest", specifier = "==8.3.3" },
+    { name = "pytest-asyncio", specifier = ">=0.23.0" },
     { name = "pytest-cov", specifier = ">=6.0.0" },
     { name = "pytest-md-report", specifier = ">=0.6.2" },
     { name = "pytest-mock", specifier = "==3.14.0" },
diff --git a/platform-service/uv.lock b/platform-service/uv.lock
index 118257ff54..71d0bc6a66 100644
--- a/platform-service/uv.lock
+++ b/platform-service/uv.lock
@@ -2743,6 +2743,7 @@ docs = [{ name = "lazydocs", specifier = "~=0.4.8" }]
 test = [
     { name = "parameterized", specifier = "==0.9.0" },
     { name = "pytest", specifier = "==8.3.3" },
+    { name = "pytest-asyncio", specifier = ">=0.23.0" },
     { name = "pytest-cov", specifier = ">=6.0.0" },
     { name = "pytest-md-report", specifier = ">=0.6.2" },
     { name = "pytest-mock", specifier = "==3.14.0" },
diff --git a/prompt-service/pyproject.toml b/prompt-service/pyproject.toml
index 588cb79c4e..ae32c95201 100644
--- a/prompt-service/pyproject.toml
+++ b/prompt-service/pyproject.toml
@@ -29,8 +29,10 @@ unstract-sdk1 = { path = "../unstract/sdk1", editable = true }
 [dependency-groups]
 test = [
     "pytest~=8.0.1",
+    "pytest-asyncio>=0.23.0",
     "pytest-dotenv==0.5.2",
     "pytest-mock~=3.14.0",
+    "pytest-md-report>=0.6.2",
     "python-dotenv==1.0.1",
     "flask-WTF~=1.1",
 ]
diff --git a/prompt-service/src/unstract/prompt_service/core/retrievers/base_retriever.py b/prompt-service/src/unstract/prompt_service/core/retrievers/base_retriever.py
index 5eb34cb73a..288223c00a 100644
--- a/prompt-service/src/unstract/prompt_service/core/retrievers/base_retriever.py
+++ b/prompt-service/src/unstract/prompt_service/core/retrievers/base_retriever.py
@@ -1,3 +1,4 @@
+from unstract.prompt_service.core.retrievers.retriever_llm import RetrieverLLM
 from unstract.sdk1.llm import LLM
 from unstract.sdk1.vector_db import VectorDB
 
@@ -23,7 +24,37 @@ def __init__(
         self.prompt = prompt
         self.doc_id = doc_id
         self.top_k = top_k
-        self.llm = llm if llm else None
+        self._llm: LLM | None = llm
+        self._retriever_llm: RetrieverLLM | None = None
+
+    @property
+    def llm(self) -> RetrieverLLM | None:
+        """Return a llama-index compatible LLM, lazily created on first access.
+
+        Avoids the cost of RetrieverLLM construction (adapter init,
+        CallbackManager setup) for retrievers that never use the LLM
+        (Simple, Automerging, Recursive).
+        """
+        if self._llm is None:
+            return None
+        if self._retriever_llm is None:
+            self._retriever_llm = RetrieverLLM(llm=self._llm)
+        return self._retriever_llm
+
+    def require_llm(self) -> RetrieverLLM:
+        """Return the llama-index LLM or raise if not configured.
+
+        Call this in retrievers that need an LLM (KeywordTable, Fusion,
+        Subquestion) to fail early with a clear message instead of
+        letting llama-index silently fall back to its default OpenAI LLM.
+        """
+        llm = self.llm
+        if llm is None:
+            raise ValueError(
+                f"{type(self).__name__} requires an LLM. "
+                "Pass llm= when constructing the retriever."
+            )
+        return llm
 
     @staticmethod
     def retrieve() -> set[str]:
diff --git a/prompt-service/src/unstract/prompt_service/core/retrievers/fusion.py b/prompt-service/src/unstract/prompt_service/core/retrievers/fusion.py
index 99f24516e6..5fd7870f01 100644
--- a/prompt-service/src/unstract/prompt_service/core/retrievers/fusion.py
+++ b/prompt-service/src/unstract/prompt_service/core/retrievers/fusion.py
@@ -24,6 +24,7 @@ def retrieve(self) -> set[str]:
             set[str]: A set of text chunks retrieved from the database.
         """
         try:
+            llm = self.require_llm()
             logger.info(
                 f"Retrieving chunks for {self.doc_id} using LlamaIndex QueryFusionRetriever."
             )
@@ -64,7 +65,7 @@ def retrieve(self) -> set[str]:
                 mode="simple",  # Use simple fusion mode (reciprocal rank fusion)
                 use_async=False,
                 verbose=True,
-                llm=self.llm,  # LLM generates query variations
+                llm=llm,
             )
 
             # Retrieve nodes using fusion technique
diff --git a/prompt-service/src/unstract/prompt_service/core/retrievers/keyword_table.py b/prompt-service/src/unstract/prompt_service/core/retrievers/keyword_table.py
index 8d92a71544..d17e507b50 100644
--- a/prompt-service/src/unstract/prompt_service/core/retrievers/keyword_table.py
+++ b/prompt-service/src/unstract/prompt_service/core/retrievers/keyword_table.py
@@ -20,6 +20,7 @@ def retrieve(self) -> set[str]:
             set[str]: A set of text chunks retrieved from the database.
         """
         try:
+            llm = self.require_llm()
             logger.info(
                 f"Retrieving chunks for {self.doc_id} using LlamaIndex KeywordTableIndex."
             )
@@ -48,7 +49,7 @@ def retrieve(self) -> set[str]:
             keyword_index = KeywordTableIndex(
                 nodes=[node.node for node in all_nodes],
                 show_progress=True,
-                llm=self.llm,  # Use the provided LLM instead of defaulting to OpenAI
+                llm=llm,
             )
 
             # Create retriever from keyword index
diff --git a/prompt-service/src/unstract/prompt_service/core/retrievers/retriever_llm.py b/prompt-service/src/unstract/prompt_service/core/retrievers/retriever_llm.py
new file mode 100644
index 0000000000..c2038f9181
--- /dev/null
+++ b/prompt-service/src/unstract/prompt_service/core/retrievers/retriever_llm.py
@@ -0,0 +1,126 @@
+from collections.abc import Sequence
+from typing import Any
+
+from llama_index.core.base.llms.types import (
+    ChatMessage,
+    ChatResponse,
+    ChatResponseAsyncGen,
+    ChatResponseGen,
+    CompletionResponse,
+    CompletionResponseAsyncGen,
+    CompletionResponseGen,
+    LLMMetadata,
+    MessageRole,
+)
+from llama_index.core.llms.llm import LLM as LlamaIndexBaseLLM  # noqa: N811
+from pydantic import PrivateAttr
+
+from unstract.sdk1.llm import LLM, LLMCompat
+
+
+class RetrieverLLM(LlamaIndexBaseLLM):
+    """Bridges SDK1's LLMCompat with llama-index's LLM for retriever use.
+
+    Llama-index's ``resolve_llm()`` asserts ``isinstance(llm, LLM)``
+    where ``LLM`` is ``llama_index.core.llms.llm.LLM``. Since SDK1's
+    ``LLMCompat`` is a plain class without llama-index inheritance,
+    it fails this check.
+
+    ``RetrieverLLM`` inherits from llama-index's ``LLM`` base class
+    (passing the isinstance check) and delegates all LLM calls to an
+    internal ``LLMCompat`` instance.
+    """
+
+    _compat: LLMCompat = PrivateAttr()
+
+    def __init__(self, llm: LLM, **kwargs: Any) -> None:  # noqa: ANN401
+        """Initialize with an SDK1 LLM instance."""
+        super().__init__(**kwargs)
+        self._compat = LLMCompat.from_llm(llm)
+
+    @property
+    def metadata(self) -> LLMMetadata:
+        return LLMMetadata(
+            is_chat_model=True,
+            model_name=self._compat.get_model_name(),
+        )
+
+    # ── Sync ─────────────────────────────────────────────────────────────────
+
+    def chat(
+        self,
+        messages: Sequence[ChatMessage],
+        **kwargs: Any,  # noqa: ANN401
+    ) -> ChatResponse:
+        result = self._compat.chat(messages, **kwargs)
+        return ChatResponse(
+            message=ChatMessage(
+                role=MessageRole.ASSISTANT,
+                content=result.message.content,
+            ),
+            raw=result.raw,
+        )
+
+    def complete(
+        self,
+        prompt: str,
+        formatted: bool = False,
+        **kwargs: Any,  # noqa: ANN401
+    ) -> CompletionResponse:
+        result = self._compat.complete(prompt, formatted=formatted, **kwargs)
+        return CompletionResponse(text=result.text, raw=result.raw)
+
+    def stream_chat(
+        self,
+        messages: Sequence[ChatMessage],
+        **kwargs: Any,  # noqa: ANN401
+    ) -> ChatResponseGen:
+        raise NotImplementedError("stream_chat is not supported.")
+
+    def stream_complete(
+        self,
+        prompt: str,
+        formatted: bool = False,
+        **kwargs: Any,  # noqa: ANN401
+    ) -> CompletionResponseGen:
+        raise NotImplementedError("stream_complete is not supported.")
+
+    # ── Async ────────────────────────────────────────────────────────────────
+
+    async def achat(
+        self,
+        messages: Sequence[ChatMessage],
+        **kwargs: Any,  # noqa: ANN401
+    ) -> ChatResponse:
+        result = await self._compat.achat(messages, **kwargs)
+        return ChatResponse(
+            message=ChatMessage(
+                role=MessageRole.ASSISTANT,
+                content=result.message.content,
+            ),
+            raw=result.raw,
+        )
+
+    async def acomplete(
+        self,
+        prompt: str,
+        formatted: bool = False,
+        **kwargs: Any,  # noqa: ANN401
+    ) -> CompletionResponse:
+        result = await self._compat.acomplete(prompt, formatted=formatted, **kwargs)
+        return CompletionResponse(text=result.text, raw=result.raw)
+
+    async def astream_chat(
+        self,
+        messages: Sequence[ChatMessage],
+        **kwargs: Any,  # noqa: ANN401
+    ) -> ChatResponseAsyncGen:
+        raise NotImplementedError("astream_chat is not supported.")
+
+    async def astream_complete(
+        self,
+        prompt: str,
+        formatted: bool = False,
+        **kwargs: Any,  # noqa: ANN401
+    ) -> CompletionResponseAsyncGen:
+        raise NotImplementedError("astream_complete is not supported.")
diff --git a/prompt-service/src/unstract/prompt_service/core/retrievers/subquestion.py b/prompt-service/src/unstract/prompt_service/core/retrievers/subquestion.py
index af44b76eb6..6930bc131b 100644
--- a/prompt-service/src/unstract/prompt_service/core/retrievers/subquestion.py
+++ b/prompt-service/src/unstract/prompt_service/core/retrievers/subquestion.py
@@ -1,6 +1,7 @@
 import logging
 
 from llama_index.core.query_engine import SubQuestionQueryEngine
+from llama_index.core.question_gen.llm_generators import LLMQuestionGenerator
 from llama_index.core.schema import QueryBundle
 from llama_index.core.tools import QueryEngineTool, ToolMetadata
 
@@ -22,9 +23,10 @@ def retrieve(self) -> set[str]:
             set[str]: A set of text chunks retrieved from the database.
         """
         try:
+            llm = self.require_llm()
             logger.info("Initialising vector query engine...")
             vector_query_engine = self.vector_db.get_vector_store_index().as_query_engine(
-                llm=self.llm, similarity_top_k=self.top_k
+                llm=llm, similarity_top_k=self.top_k
             )
             logger.info(
                 f"Retrieving chunks for {self.doc_id} using SubQuestionQueryEngine."
@@ -39,10 +41,14 @@ def retrieve(self) -> set[str]:
             ]
             query_bundle = QueryBundle(query_str=self.prompt)
 
+            question_gen = LLMQuestionGenerator.from_defaults(
+                llm=llm,
+            )
             query_engine = SubQuestionQueryEngine.from_defaults(
                 query_engine_tools=query_engine_tools,
+                question_gen=question_gen,
                 use_async=True,
-                llm=self.llm,
+                llm=llm,
             )
 
             response = query_engine.query(str_or_query_bundle=query_bundle)
diff --git a/prompt-service/src/unstract/prompt_service/tests/unit/__init__.py b/prompt-service/src/unstract/prompt_service/tests/unit/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/prompt-service/src/unstract/prompt_service/tests/unit/conftest.py b/prompt-service/src/unstract/prompt_service/tests/unit/conftest.py
new file mode 100644
index 0000000000..b78a6985a1
--- /dev/null
+++ b/prompt-service/src/unstract/prompt_service/tests/unit/conftest.py
@@ -0,0 +1,12 @@
+"""Pytest configuration for unit tests.
+
+Unit tests should not require external dependencies or the full app.
+This conftest intentionally does NOT import Flask app components.
+
+WARNING: This file is NOT auto-loaded when running via tox because
+--noconftest is used to skip the parent tests/conftest.py (which
+imports Flask blueprints and triggers the full adapter import chain).
+If you add shared fixtures here, either remove --noconftest from
+tox.ini and fix the parent conftest's eager imports, or define
+fixtures directly in test files.
+"""
diff --git a/prompt-service/src/unstract/prompt_service/tests/unit/test_retriever_llm.py b/prompt-service/src/unstract/prompt_service/tests/unit/test_retriever_llm.py
new file mode 100644
index 0000000000..377988b20c
--- /dev/null
+++ b/prompt-service/src/unstract/prompt_service/tests/unit/test_retriever_llm.py
@@ -0,0 +1,315 @@
+"""Unit tests for RetrieverLLM bridge class and BaseRetriever.llm property."""
+
+import sys
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from llama_index.core.base.llms.types import (
+    ChatMessage,
+    ChatResponse,
+    CompletionResponse,
+    LLMMetadata,
+    MessageRole,
+)
+from llama_index.core.llms.llm import LLM as LlamaIndexBaseLLM  # noqa: N811
+from unstract.prompt_service.core.retrievers.retriever_llm import RetrieverLLM
+from unstract.sdk1.llm import LLM, LLMCompat
+from unstract.sdk1.llm import ChatMessage as EmulatedChatMessage
+from unstract.sdk1.llm import ChatResponse as EmulatedChatResponse
+from unstract.sdk1.llm import CompletionResponse as EmulatedCompletionResponse
+from unstract.sdk1.llm import LLMMetadata as EmulatedLLMMetadata
+from unstract.sdk1.llm import MessageRole as EmulatedMessageRole
+
+# ── Fixtures ─────────────────────────────────────────────────────────────────
+
+
+@pytest.fixture
+def mock_sdk1_llm():
+    """Create a mock SDK1 LLM instance with adapter attributes."""
+    llm = MagicMock(spec=LLM)
+    llm._adapter_id = "openai"
+    llm._adapter_metadata = {"api_key": "test-key"}
+    llm._adapter_instance_id = "inst-123"
+    llm._tool = MagicMock()
+    llm._usage_kwargs = {"run_id": "test-run"}
+    llm._capture_metrics = False
+    llm.get_model_name.return_value = "gpt-4"
+    llm.platform_kwargs = {"run_id": "test-run"}
+    return llm
+
+
+@pytest.fixture
+def mock_compat():
+    """Create a mock LLMCompat instance."""
+    compat = MagicMock(spec=LLMCompat)
+    compat.get_model_name.return_value = "gpt-4"
+    compat.metadata = EmulatedLLMMetadata(
+        is_chat_model=True, model_name="gpt-4"
+    )
+    return compat
+
+
+# ── BaseRetriever.llm property tests ────────────────────────────────────────
+# BaseRetriever imports VectorDB which triggers the full adapter registration
+# chain (Pinecone, Milvus, etc.). We stub unstract.sdk1.vector_db in
+# sys.modules so that BaseRetriever can be imported without those heavy deps.
+
+
+@pytest.fixture
+def _stub_vector_db():
+    """Temporarily stub VectorDB module for BaseRetriever import."""
+    stub = MagicMock()
+    key = "unstract.sdk1.vector_db"
+    original = sys.modules.get(key)
+    sys.modules[key] = stub
+    # Also ensure the base_retriever module is re-imported with the stub.
+    mod_key = (
+        "unstract.prompt_service.core.retrievers.base_retriever"
+    )
+    sys.modules.pop(mod_key, None)
+    yield stub
+    # Restore original module (or remove stub).
+    if original is not None:
+        sys.modules[key] = original
+    else:
+        sys.modules.pop(key, None)
+    sys.modules.pop(mod_key, None)
+
+
+@pytest.fixture
+def base_retriever_cls(_stub_vector_db):
+    """Import and return BaseRetriever with VectorDB stubbed."""
+    from unstract.prompt_service.core.retrievers.base_retriever import (
+        BaseRetriever,
+    )
+
+    return BaseRetriever
+
+
+class TestBaseRetrieverLlmProperty:
+    """Tests for BaseRetriever.llm lazy property."""
+
+    def test_returns_none_when_no_llm_provided(
+        self, base_retriever_cls
+    ):
+        """llm property should return None when constructed without LLM."""
+        retriever = base_retriever_cls(
+            vector_db=MagicMock(),
+            prompt="test",
+            doc_id="doc-1",
+            top_k=5,
+        )
+        assert retriever.llm is None
+
+    def test_returns_retriever_llm_instance(
+        self, base_retriever_cls, mock_sdk1_llm
+    ):
+        """llm property should return a RetrieverLLM wrapping SDK1 LLM."""
+        with patch.object(LLMCompat, "from_llm", return_value=MagicMock()):
+            retriever = base_retriever_cls(
+                vector_db=MagicMock(),
+                prompt="test",
+                doc_id="doc-1",
+                top_k=5,
+                llm=mock_sdk1_llm,
+            )
+            result = retriever.llm
+
+            assert isinstance(result, RetrieverLLM)
+            assert isinstance(result, LlamaIndexBaseLLM)
+
+    def test_lazily_creates_retriever_llm(
+        self, base_retriever_cls, mock_sdk1_llm
+    ):
+        """RetrieverLLM should not be created until .llm is accessed."""
+        retriever = base_retriever_cls(
+            vector_db=MagicMock(),
+            prompt="test",
+            doc_id="doc-1",
+            top_k=5,
+            llm=mock_sdk1_llm,
+        )
+        # Before accessing .llm, the internal cache should be None.
+        assert retriever._retriever_llm is None
+
+        with patch.object(LLMCompat, "from_llm", return_value=MagicMock()):
+            _ = retriever.llm
+
+        # After access, it should be populated.
+        assert retriever._retriever_llm is not None
+
+    def test_caches_retriever_llm_across_accesses(
+        self, base_retriever_cls, mock_sdk1_llm
+    ):
+        """Repeated .llm accesses should return the same instance."""
+        with patch.object(LLMCompat, "from_llm", return_value=MagicMock()):
+            retriever = base_retriever_cls(
+                vector_db=MagicMock(),
+                prompt="test",
+                doc_id="doc-1",
+                top_k=5,
+                llm=mock_sdk1_llm,
+            )
+            first = retriever.llm
+            second = retriever.llm
+
+            assert first is second
+
+    def test_from_llm_called_once_on_repeated_access(
+        self, base_retriever_cls, mock_sdk1_llm
+    ):
+        """LLMCompat.from_llm should only be called once across accesses."""
+        with patch.object(
+            LLMCompat, "from_llm", return_value=MagicMock()
+        ) as mock_factory:
+            retriever = base_retriever_cls(
+                vector_db=MagicMock(),
+                prompt="test",
+                doc_id="doc-1",
+                top_k=5,
+                llm=mock_sdk1_llm,
+            )
+            _ = retriever.llm
+            _ = retriever.llm
+            _ = retriever.llm
+
+            mock_factory.assert_called_once()
+
+    def test_raw_llm_still_accessible(
+        self, base_retriever_cls, mock_sdk1_llm
+    ):
+        """The raw SDK1 LLM should remain accessible via _llm."""
+        retriever = base_retriever_cls(
+            vector_db=MagicMock(),
+            prompt="test",
+            doc_id="doc-1",
+            top_k=5,
+            llm=mock_sdk1_llm,
+        )
+        assert retriever._llm is mock_sdk1_llm
+
+
+# ── RetrieverLLM tests ───────────────────────────────────────────────────────
+
+
+class TestRetrieverLLM:
+    """Tests for the RetrieverLLM bridge class."""
+
+    def test_isinstance_llama_index_llm(self, mock_sdk1_llm):
+        """RetrieverLLM must pass llama-index's isinstance check."""
+        with patch.object(LLMCompat, "from_llm", return_value=MagicMock()):
+            retriever_llm = RetrieverLLM(llm=mock_sdk1_llm)
+            assert isinstance(retriever_llm, LlamaIndexBaseLLM)
+
+    def test_uses_from_llm_factory(self, mock_sdk1_llm):
+        """RetrieverLLM should use LLMCompat.from_llm, not private attrs."""
+        with patch.object(
+            LLMCompat, "from_llm", return_value=MagicMock()
+        ) as mock_factory:
+            RetrieverLLM(llm=mock_sdk1_llm)
+            mock_factory.assert_called_once_with(mock_sdk1_llm)
+
+    def test_metadata_returns_llama_index_type(
+        self, mock_sdk1_llm, mock_compat
+    ):
+        """Metadata property should return llama-index LLMMetadata."""
+        with patch.object(LLMCompat, "from_llm", return_value=mock_compat):
+            retriever_llm = RetrieverLLM(llm=mock_sdk1_llm)
+            meta = retriever_llm.metadata
+            assert isinstance(meta, LLMMetadata)
+            assert meta.is_chat_model is True
+            assert meta.model_name == "gpt-4"
+
+    def test_chat_delegates_and_converts_types(
+        self, mock_sdk1_llm, mock_compat
+    ):
+        """chat() should delegate to compat and return llama-index types."""
+        mock_compat.chat.return_value = EmulatedChatResponse(
+            message=EmulatedChatMessage(
+                role=EmulatedMessageRole.ASSISTANT,
+                content="Hello from LLM",
+            ),
+            raw={"id": "resp-1"},
+        )
+        with patch.object(LLMCompat, "from_llm", return_value=mock_compat):
+            retriever_llm = RetrieverLLM(llm=mock_sdk1_llm)
+            messages = [
+                ChatMessage(role=MessageRole.USER, content="Hi")
+            ]
+            result = retriever_llm.chat(messages)
+
+            assert isinstance(result, ChatResponse)
+            assert result.message.content == "Hello from LLM"
+            assert result.raw == {"id": "resp-1"}
+            mock_compat.chat.assert_called_once()
+
+    def test_complete_delegates_and_converts_types(
+        self, mock_sdk1_llm, mock_compat
+    ):
+        """complete() should delegate to compat and return llama-index types."""
+        mock_compat.complete.return_value = EmulatedCompletionResponse(
+            text="Completed text", raw={"id": "resp-2"}
+        )
+        with patch.object(LLMCompat, "from_llm", return_value=mock_compat):
+            retriever_llm = RetrieverLLM(llm=mock_sdk1_llm)
+            result = retriever_llm.complete("Test prompt")
+
+            assert isinstance(result, CompletionResponse)
+            assert result.text == "Completed text"
+            assert result.raw == {"id": "resp-2"}
+            mock_compat.complete.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_achat_delegates_and_converts_types(
+        self, mock_sdk1_llm, mock_compat
+    ):
+        """achat() should delegate to compat and return llama-index types."""
+        mock_compat.achat = AsyncMock(
+            return_value=EmulatedChatResponse(
+                message=EmulatedChatMessage(
+                    role=EmulatedMessageRole.ASSISTANT,
+                    content="Async hello",
+                ),
+                raw={"id": "resp-3"},
+            )
+        )
+        with patch.object(LLMCompat, "from_llm", return_value=mock_compat):
+            retriever_llm = RetrieverLLM(llm=mock_sdk1_llm)
+            messages = [
+                ChatMessage(role=MessageRole.USER, content="Hi async")
+            ]
+            result = await retriever_llm.achat(messages)
+
+            assert isinstance(result, ChatResponse)
+            assert result.message.content == "Async hello"
+
+    @pytest.mark.asyncio
+    async def test_acomplete_delegates_and_converts_types(
+        self, mock_sdk1_llm, mock_compat
+    ):
+        """acomplete() should delegate to compat and return llama-index types."""
+        mock_compat.acomplete = AsyncMock(
+            return_value=EmulatedCompletionResponse(
+                text="Async completed", raw={"id": "resp-4"}
+            )
+        )
+        with patch.object(LLMCompat, "from_llm", return_value=mock_compat):
+            retriever_llm = RetrieverLLM(llm=mock_sdk1_llm)
+            result = await retriever_llm.acomplete("Async prompt")
+
+            assert isinstance(result, CompletionResponse)
+            assert result.text == "Async completed"
+
+    def test_stream_chat_not_implemented(self, mock_sdk1_llm):
+        """stream_chat() should raise NotImplementedError."""
+        with patch.object(LLMCompat, "from_llm", return_value=MagicMock()):
+            retriever_llm = RetrieverLLM(llm=mock_sdk1_llm)
+            with pytest.raises(NotImplementedError):
+                retriever_llm.stream_chat([])
+
+    def test_stream_complete_not_implemented(self, mock_sdk1_llm):
+        """stream_complete() should raise NotImplementedError."""
+        with patch.object(LLMCompat, "from_llm", return_value=MagicMock()):
+            retriever_llm = RetrieverLLM(llm=mock_sdk1_llm)
+            with pytest.raises(NotImplementedError):
+                retriever_llm.stream_complete("prompt")
diff --git a/prompt-service/uv.lock b/prompt-service/uv.lock
index a8e18bfceb..a18282c9cf 100644
--- a/prompt-service/uv.lock
+++ b/prompt-service/uv.lock
@@ -363,6 +363,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/95/31/9f7f93ad2f8eff1dbc1c3656d7ca5bfd8fb52c9d786b4dcf19b2d02217fa/cffi-2.0.0-cp312-cp312-win_arm64.whl", hash = "sha256:4671d9dd5ec934cb9a73e7ee9676f9362aba54f7f34910956b84d727b0d73fb6", size = 177762, upload-time = "2025-09-08T23:22:59.668Z" },
 ]
 
+[[package]]
+name = "chardet"
+version = "5.2.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/f3/0d/f7b6ab21ec75897ed80c17d79b15951a719226b9fababf1e40ea74d69079/chardet-5.2.0.tar.gz", hash = "sha256:1b3b6ff479a8c414bc3fa2c0852995695c4a026dcd6d0633b2dd092ca39c1cf7", size = 2069618 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/38/6f/f5fbc992a329ee4e0f288c1fe0e2ad9485ed064cac731ed2fe47dcc38cbf/chardet-5.2.0-py3-none-any.whl", hash = "sha256:e1cf59446890a00105fe7b7912492ea04b6e6f06d4b742b2c788469e34c82970", size = 199385 },
+]
+
 [[package]]
 name = "charset-normalizer"
 version = "3.4.3"
@@ -458,6 +467,19 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c3/be/d0d44e092656fe7a06b55e6103cbce807cdbdee17884a5367c68c9860853/dataclasses_json-0.6.7-py3-none-any.whl", hash = "sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a", size = 28686, upload-time = "2024-06-09T16:20:16.715Z" },
 ]
 
+[[package]]
+name = "dataproperty"
+version = "1.1.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "mbstrdecoder" },
+    { name = "typepy", extra = ["datetime"] },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/0b/81/8c8b64ae873cb9014815214c07b63b12e3b18835780fb342223cfe3fe7d8/dataproperty-1.1.0.tar.gz", hash = "sha256:b038437a4097d1a1c497695c3586ea34bea67fdd35372b9a50f30bf044d77d04", size = 42574 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/21/c2/e12e95e289e6081a40454199ab213139ef16a528c7c86432de545b05a23a/DataProperty-1.1.0-py3-none-any.whl", hash = "sha256:c61fcb2e2deca35e6d1eb1f251a7f22f0dcde63e80e61f0cc18c19f42abfd25b", size = 27581 },
+]
+
 [[package]]
 name = "debugpy"
 version = "1.8.17"
@@ -1451,6 +1473,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/34/75/51952c7b2d3873b44a0028b1bd26a25078c18f92f256608e8d1dc61b39fd/marshmallow-3.26.1-py3-none-any.whl", hash = "sha256:3350409f20a70a7e4e11a27661187b77cdcaeb20abca41c1454fe33636bea09c", size = 50878, upload-time = "2025-02-03T15:32:22.295Z" },
 ]
 
+[[package]]
+name = "mbstrdecoder"
+version = "1.1.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "chardet" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/31/ab/05ae008357c8bdb6245ebf8a101d99f26c096e0ea20800b318153da23796/mbstrdecoder-1.1.4.tar.gz", hash = "sha256:8105ef9cf6b7d7d69fe7fd6b68a2d8f281ca9b365d7a9b670be376b2e6c81b21", size = 14527 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/30/ac/5ce64a1d4cce00390beab88622a290420401f1cabf05caf2fc0995157c21/mbstrdecoder-1.1.4-py3-none-any.whl", hash = "sha256:03dae4ec50ec0d2ff4743e63fdbd5e0022815857494d35224b60775d3d934a8c", size = 7933 },
+]
+
 [[package]]
 name = "milvus-lite"
 version = "2.5.1"
@@ -1774,6 +1808,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/aa/18/a8444036c6dd65ba3624c63b734d3ba95ba63ace513078e1580590075d21/pastel-0.2.1-py2.py3-none-any.whl", hash = "sha256:4349225fcdf6c2bb34d483e523475de5bb04a5c10ef711263452cb37d7dd4364", size = 5955, upload-time = "2020-09-16T19:21:11.409Z" },
 ]
 
+[[package]]
+name = "pathvalidate"
+version = "3.3.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/fa/2a/52a8da6fe965dea6192eb716b357558e103aea0a1e9a8352ad575a8406ca/pathvalidate-3.3.1.tar.gz", hash = "sha256:b18c07212bfead624345bb8e1d6141cdcf15a39736994ea0b94035ad2b1ba177", size = 63262 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/9a/70/875f4a23bfc4731703a5835487d0d2fb999031bd415e7d17c0ae615c18b7/pathvalidate-3.3.1-py3-none-any.whl", hash = "sha256:5263baab691f8e1af96092fa5137ee17df5bdfbd6cff1fcac4d6ef4bc2e1735f", size = 24305 },
+]
+
 [[package]]
 name = "pdfminer-six"
 version = "20250506"
@@ -2108,6 +2151,24 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/be/7a/097801205b991bc3115e8af1edb850d30aeaf0118520b016354cf5ccd3f6/pypdfium2-4.30.0-py3-none-win_arm64.whl", hash = "sha256:119b2969a6d6b1e8d55e99caaf05290294f2d0fe49c12a3f17102d01c441bd29", size = 2752118, upload-time = "2024-05-09T18:33:15.489Z" },
 ]
 
+[[package]]
+name = "pytablewriter"
+version = "1.2.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "dataproperty" },
+    { name = "mbstrdecoder" },
+    { name = "pathvalidate" },
+    { name = "setuptools" },
+    { name = "tabledata" },
+    { name = "tcolorpy" },
+    { name = "typepy", extra = ["datetime"] },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f6/a1/617730f290f04d347103ab40bf67d317df6691b14746f6e1ea039fb57062/pytablewriter-1.2.1.tar.gz", hash = "sha256:7bd0f4f397e070e3b8a34edcf1b9257ccbb18305493d8350a5dbc9957fced959", size = 619241 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/21/4c/c199512f01c845dfe5a7840ab3aae6c60463b5dc2a775be72502dfd9170a/pytablewriter-1.2.1-py3-none-any.whl", hash = "sha256:e906ff7ff5151d70a5f66e0f7b75642a7f2dce8d893c265b79cc9cf6bc04ddb4", size = 91083 },
+]
+
 [[package]]
 name = "pytest"
 version = "8.0.2"
@@ -2123,6 +2184,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a7/ea/d0ab9595a0d4b2320483e634123171deaf50885e29d442180efcbf2ed0b2/pytest-8.0.2-py3-none-any.whl", hash = "sha256:edfaaef32ce5172d5466b5127b42e0d6d35ebbe4453f0e3505d96afd93f6b096", size = 333984, upload-time = "2024-02-24T22:21:27.561Z" },
 ]
 
+[[package]]
+name = "pytest-asyncio"
+version = "0.23.8"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pytest" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/de/b4/0b378b7bf26a8ae161c3890c0b48a91a04106c5713ce81b4b080ea2f4f18/pytest_asyncio-0.23.8.tar.gz", hash = "sha256:759b10b33a6dc61cce40a8bd5205e302978bbbcc00e279a8b61d9a6a3c82e4d3", size = 46920 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/ee/82/62e2d63639ecb0fbe8a7ee59ef0bc69a4669ec50f6d3459f74ad4e4189a2/pytest_asyncio-0.23.8-py3-none-any.whl", hash = "sha256:50265d892689a5faefb84df80819d1ecef566eb3549cf915dfb33569359d1ce2", size = 17663 },
+]
+
 [[package]]
 name = "pytest-dotenv"
 version = "0.5.2"
@@ -2136,6 +2209,21 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d0/da/9da67c67b3d0963160e3d2cbc7c38b6fae342670cc8e6d5936644b2cf944/pytest_dotenv-0.5.2-py3-none-any.whl", hash = "sha256:40a2cece120a213898afaa5407673f6bd924b1fa7eafce6bda0e8abffe2f710f", size = 3993, upload-time = "2020-06-16T12:38:01.139Z" },
 ]
 
+[[package]]
+name = "pytest-md-report"
+version = "0.7.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pytablewriter" },
+    { name = "pytest" },
+    { name = "tcolorpy" },
+    { name = "typepy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f6/63/80d92406f952eee7856114c18ad269192ce179d576343fbcf0679c9a2bdd/pytest_md_report-0.7.0.tar.gz", hash = "sha256:3b832eaf660b470b5742e58d9c9a5e312b0712a7012d251cc04e908a81ce3c96", size = 284275 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/de/96/6125a1a963b3864b4a3981c9fce27df60370a889c2e79071e33d325f14d9/pytest_md_report-0.7.0-py3-none-any.whl", hash = "sha256:90ccb3b5b9587d064ec83974db34619addd11d3de6ec7056fab4feb3af69ae94", size = 14250 },
+]
+
 [[package]]
 name = "pytest-mock"
 version = "3.14.1"
@@ -2449,6 +2537,28 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a3/cf/0fea4f4ba3fc2772ac2419278aa9f6964124d4302117d61bc055758e000c/striprtf-0.0.26-py3-none-any.whl", hash = "sha256:8c8f9d32083cdc2e8bfb149455aa1cc5a4e0a035893bedc75db8b73becb3a1bb", size = 6914, upload-time = "2023-07-20T14:30:35.338Z" },
 ]
 
+[[package]]
+name = "tabledata"
+version = "1.3.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "dataproperty" },
+    { name = "typepy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/b2/35/171c8977162f1163368406deddde4c59673b62bd0cb2f34948a02effb075/tabledata-1.3.4.tar.gz", hash = "sha256:e9649cab129d718f3bff4150083b77f8a78c30f6634a30caf692b10fdc60cb97", size = 25074 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/08/64/fa4160151976ee4b2cf0c1217a99443ffaeb991956feddfeac9eee9952f8/tabledata-1.3.4-py3-none-any.whl", hash = "sha256:1f56e433bfdeb89f4487abfa48c4603a3b07c5d3a3c7e05ff73dd018c24bd0d4", size = 11820 },
+]
+
+[[package]]
+name = "tcolorpy"
+version = "0.1.7"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/80/cc/44f2d81d8f9093aad81c3467a5bf5718d2b5f786e887b6e4adcfc17ec6b9/tcolorpy-0.1.7.tar.gz", hash = "sha256:0fbf6bf238890bbc2e32662aa25736769a29bf6d880328f310c910a327632614", size = 299437 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/05/a2/ed023f2edd1e011b4d99b6727bce8253842d66c3fbf9ed0a26fc09a92571/tcolorpy-0.1.7-py3-none-any.whl", hash = "sha256:26a59d52027e175a37e0aba72efc99dda43f074db71f55b316d3de37d3251378", size = 8096 },
+]
+
 [[package]]
 name = "tenacity"
 version = "9.1.2"
@@ -2511,6 +2621,25 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d0/30/dc54f88dd4a2b5dc8a0279bdd7270e735851848b762aeb1c1184ed1f6b14/tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2", size = 78540, upload-time = "2024-11-24T20:12:19.698Z" },
 ]
 
+[[package]]
+name = "typepy"
+version = "1.3.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "mbstrdecoder" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/79/59/4c39942077d7de285f762a91024dbda731be693591732977358f77d120fb/typepy-1.3.4.tar.gz", hash = "sha256:89c1f66de6c6133209c43a94d23431d320ba03ef5db18f241091ea594035d9de", size = 39558 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/ee/31/e393c3830bdedd01735bd195c85ac3034b6bcaf6c18142bab60a4047ca36/typepy-1.3.4-py3-none-any.whl", hash = "sha256:d5ed3e0c7f49521bff0603dd08cf8d453371cf68d65a29d3d0038552ccc46e2e", size = 31449 },
+]
+
+[package.optional-dependencies]
+datetime = [
+    { name = "packaging" },
+    { name = "python-dateutil" },
+    { name = "pytz" },
+]
+
 [[package]]
 name = "typing-extensions"
 version = "4.15.0"
@@ -2642,7 +2771,9 @@ dev = [
 test = [
     { name = "flask-wtf" },
     { name = "pytest" },
+    { name = "pytest-asyncio" },
     { name = "pytest-dotenv" },
+    { name = "pytest-md-report" },
     { name = "pytest-mock" },
     { name = "python-dotenv" },
 ]
@@ -2675,7 +2806,9 @@ dev = [
 test = [
     { name = "flask-wtf", specifier = "~=1.1" },
     { name = "pytest", specifier = "~=8.0.1" },
+    { name = "pytest-asyncio", specifier = ">=0.23.0" },
     { name = "pytest-dotenv", specifier = "==0.5.2" },
+    { name = "pytest-md-report", specifier = ">=0.6.2" },
     { name = "pytest-mock", specifier = "~=3.14.0" },
     { name = "python-dotenv", specifier = "==1.0.1" },
 ]
@@ -2761,6 +2894,7 @@ docs = [{ name = "lazydocs", specifier = "~=0.4.8" }]
 test = [
     { name = "parameterized", specifier = "==0.9.0" },
     { name = "pytest", specifier = "==8.3.3" },
+    { name = "pytest-asyncio", specifier = ">=0.23.0" },
     { name = "pytest-cov", specifier = ">=6.0.0" },
     { name = "pytest-md-report", specifier = ">=0.6.2" },
     { name = "pytest-mock", specifier = "==3.14.0" },
diff --git a/tox.ini b/tox.ini
index dd13211aef..c684321ed7 100644
--- a/tox.ini
+++ b/tox.ini
@@ -1,5 +1,5 @@
 [tox]
-env_list = py{312}, runner, sdk1
+env_list = py{312}, runner, sdk1, prompt-service
 requires =
     tox-uv>=0.2.0
 
@@ -45,3 +45,18 @@ commands_pre =
     uv sync --group test
 commands =
     uv run pytest -v -m "not slow" --cov=src/unstract/sdk1 --cov-report=term --cov-report=html --md-report-verbose=1 --md-report --md-report-flavor gfm --md-report-output ../../sdk1-report.md
+
+[testenv:prompt-service]
+changedir = prompt-service
+deps = uv
+allowlist_externals=
+    sh
+    uv
+    pytest
+commands_pre =
+    uv sync --group test
+commands =
+    # --noconftest is required because the parent tests/conftest.py imports
+    # Flask blueprints which trigger the full adapter chain (pinecone etc.).
+    # Unit tests must not depend on integration fixtures.
+    uv run pytest src/unstract/prompt_service/tests/unit/ -v -m "not slow" --noconftest --md-report-verbose=1 --md-report --md-report-flavor gfm --md-report-output ../prompt-service-report.md
diff --git a/unstract/filesystem/uv.lock b/unstract/filesystem/uv.lock
index 78983ce0e6..14bd11c9a6 100644
--- a/unstract/filesystem/uv.lock
+++ b/unstract/filesystem/uv.lock
@@ -1879,6 +1879,7 @@ docs = [{ name = "lazydocs", specifier = "~=0.4.8" }]
 test = [
     { name = "parameterized", specifier = "==0.9.0" },
     { name = "pytest", specifier = "==8.3.3" },
+    { name = "pytest-asyncio", specifier = ">=0.23.0" },
     { name = "pytest-cov", specifier = ">=6.0.0" },
     { name = "pytest-md-report", specifier = ">=0.6.2" },
     { name = "pytest-mock", specifier = "==3.14.0" },
diff --git a/unstract/sdk1/pyproject.toml b/unstract/sdk1/pyproject.toml
index 9d863a68c4..9bf8299d32 100644
--- a/unstract/sdk1/pyproject.toml
+++ b/unstract/sdk1/pyproject.toml
@@ -71,6 +71,7 @@ docs = ["lazydocs~=0.4.8"]
 test = [
     "parameterized==0.9.0",
     "pytest==8.3.3",
+    "pytest-asyncio>=0.23.0",
     "pytest-mock==3.14.0",
     "pytest-cov>=6.0.0",
     "pytest-md-report>=0.6.2",
diff --git a/unstract/sdk1/src/unstract/sdk1/embedding.py b/unstract/sdk1/src/unstract/sdk1/embedding.py
index 758aa0e1cc..7ff5458c0a 100644
--- a/unstract/sdk1/src/unstract/sdk1/embedding.py
+++ b/unstract/sdk1/src/unstract/sdk1/embedding.py
@@ -16,6 +16,8 @@
 if TYPE_CHECKING:
     from unstract.sdk1.tool.base import BaseTool
 
+litellm.drop_params = True
+
 
 class Embedding:
     """Unified embedding interface powered by LiteLLM.
@@ -104,8 +106,6 @@ def get_embedding(self, text: str) -> list[float]:
             kwargs = self.kwargs.copy()
             model = kwargs.pop("model")
 
-            litellm.drop_params = True
-
             resp = litellm.embedding(model=model, input=[text], **kwargs)
 
             return resp["data"][0]["embedding"]
diff --git a/unstract/sdk1/src/unstract/sdk1/llm.py b/unstract/sdk1/src/unstract/sdk1/llm.py
index b907cd3961..516b6a0241 100644
--- a/unstract/sdk1/src/unstract/sdk1/llm.py
+++ b/unstract/sdk1/src/unstract/sdk1/llm.py
@@ -1,8 +1,10 @@
 import logging
 import os
 import re
-from collections.abc import Callable, Generator, Mapping
-from typing import cast
+from collections.abc import Callable, Generator, Mapping, Sequence
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import Any, cast
 
 import litellm
 
@@ -24,6 +26,68 @@
 
 logger = logging.getLogger(__name__)
 
+# Drop unsupported params rather than raising errors.
+# Set once at module level instead of per-call to avoid repeated
+# global mutation in concurrent environments.
+litellm.drop_params = True
+
+
+# ── Emulated llama-index types ───────────────────────────────────────────────
+# These types emulate the llama-index interface without requiring the dependency.
+# This allows LLMCompat to work with llama-index components like
+# SubQuestionQueryEngine, QueryFusionRetriever, etc.
+
+
+class MessageRole(str, Enum):
+    """Emulates llama_index.core.base.llms.types.MessageRole."""
+
+    SYSTEM = "system"
+    USER = "user"
+    ASSISTANT = "assistant"
+    FUNCTION = "function"
+    TOOL = "tool"
+
+
+@dataclass
+class ChatMessage:
+    """Emulates llama_index.core.base.llms.types.ChatMessage."""
+
+    role: MessageRole = MessageRole.USER
+    content: str | None = None
+    additional_kwargs: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class ChatResponse:
+    """Emulates llama_index.core.base.llms.types.ChatResponse."""
+
+    message: ChatMessage = field(default_factory=ChatMessage)
+    raw: Any = None
+    delta: str | None = None
+    additional_kwargs: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class CompletionResponse:
+    """Emulates llama_index.core.base.llms.types.CompletionResponse."""
+
+    text: str = ""
+    raw: Any = None
+    delta: str | None = None
+    additional_kwargs: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class LLMMetadata:
+    """Emulates llama_index.core.base.llms.types.LLMMetadata."""
+
+    context_window: int = 4096
+    num_output: int = 256
+    is_chat_model: bool = True
+    is_function_calling_model: bool = False
+    model_name: str = ""
+    system_role: MessageRole = MessageRole.SYSTEM
+
 
 class LLM:
     """Unified LLM interface powered by LiteLLM.
@@ -195,8 +259,6 @@ def complete(self, prompt: str, **kwargs: object) -> dict[str, object]:
                 any processed output, and the captured metrics (if applicable).
         """
         try:
-            litellm.drop_params = True  # drop params that are not supported by the model
-
             messages: list[dict[str, str]] = [
                 {"role": "system", "content": self._system_prompt},
                 {"role": "user", "content": prompt},
@@ -520,3 +582,271 @@ def _post_process_response(
                 post_processed_output = {}
 
         return (response_text, post_processed_output)
+
+
+class LLMCompat:
+    """Compatibility wrapper that emulates the llama-index LLM interface.
+
+    This class emulates ``llama_index.core.llms.llm.LLM`` without requiring
+    the llama-index dependency. It allows llama-index components like
+    SubQuestionQueryEngine, QueryFusionRetriever, and RouterQueryEngine
+    to work with SDK1's LLM.
+
+    Unlike :class:`EmbeddingCompat` (which inherits from llama-index's
+    ``BaseEmbedding``), this class is a plain Python object with no
+    llama-index inheritance. The prompt-service's ``RetrieverLLM``
+    provides the llama-index base class and delegates to this wrapper.
+
+    Prefer :meth:`from_llm` when an SDK1 ``LLM`` instance already
+    exists — it reuses the instance directly, bypassing ``__init__``.
+    """
+
+    def __init__(
+        self,
+        adapter_id: str = "",
+        adapter_metadata: dict[str, object] | None = None,
+        adapter_instance_id: str = "",
+        tool: BaseTool | None = None,
+        usage_kwargs: dict[str, object] | None = None,
+        system_prompt: str = "",
+        kwargs: dict[str, object] | None = None,
+        capture_metrics: bool = False,
+    ) -> None:
+        """Initialize the LLMCompat wrapper for compatibility.
+
+        Args:
+            adapter_id: Adapter identifier for LLM model
+            adapter_metadata: Configuration metadata for the adapter
+            adapter_instance_id: Instance identifier for the adapter
+            tool: BaseTool instance for tool-specific operations
+            usage_kwargs: Usage tracking parameters
+            system_prompt: System prompt for the LLM
+            kwargs: Additional keyword arguments for configuration
+            capture_metrics: Whether to capture performance metrics
+        """
+        adapter_metadata = adapter_metadata or {}
+        usage_kwargs = usage_kwargs or {}
+        kwargs = kwargs or {}
+
+        self._llm_instance = LLM(
+            adapter_id=adapter_id,
+            adapter_metadata=adapter_metadata,
+            adapter_instance_id=adapter_instance_id,
+            tool=tool,
+            usage_kwargs=usage_kwargs,
+            system_prompt=system_prompt,
+            kwargs=kwargs,
+            capture_metrics=capture_metrics,
+        )
+        self._tool = tool
+        self._adapter_instance_id = adapter_instance_id
+
+        # For compatibility with SDK Callback Manager.
+        self.model_name = self._llm_instance.get_model_name()
+        self.callback_manager = None
+
+        if not PlatformHelper.is_public_adapter(adapter_id=adapter_instance_id):
+            if self._tool:
+                platform_api_key = self._tool.get_env_or_die(ToolEnv.PLATFORM_API_KEY)
+            else:
+                platform_api_key = os.environ.get(ToolEnv.PLATFORM_API_KEY, "")
+
+            from unstract.sdk1.utils.callback_manager import CallbackManager
+
+            CallbackManager.set_callback(
+                platform_api_key=platform_api_key,
+                model=self,
+                kwargs={
+                    **self._llm_instance.platform_kwargs,
+                    "adapter_instance_id": adapter_instance_id,
+                },
+            )
+
+    # ── Properties (llama-index interface) ───────────────────────────────────
+
+    @property
+    def metadata(self) -> LLMMetadata:
+        """Return LLM metadata for llama-index compatibility."""
+        return LLMMetadata(
+            is_chat_model=True,
+            model_name=self._llm_instance.get_model_name(),
+        )
+
+    # ── Sync methods (llama-index interface) ─────────────────────────────────
+    # All LLM calls delegate to self._llm_instance (SDK1 LLM) so that
+    # litellm invocation, error handling, and usage auditing stay in one
+    # place.
+
+    def chat(
+        self,
+        messages: Sequence[ChatMessage],
+        **kwargs: Any,  # noqa: ANN401
+    ) -> ChatResponse:
+        """Synchronous chat completion.
+
+        Extracts the last user message as the prompt and delegates to
+        ``LLM.complete()``.
+        """
+        prompt = self._messages_to_prompt(messages)
+        result = self._llm_instance.complete(prompt, **kwargs)
+        resp = result["response"]
+        return ChatResponse(
+            message=ChatMessage(role=MessageRole.ASSISTANT, content=resp.text),
+            raw=resp.raw,
+        )
+
+    def complete(
+        self,
+        prompt: str,
+        formatted: bool = False,
+        **kwargs: Any,  # noqa: ANN401
+    ) -> CompletionResponse:
+        """Synchronous completion."""
+        result = self._llm_instance.complete(prompt, **kwargs)
+        resp = result["response"]
+        return CompletionResponse(text=resp.text, raw=resp.raw)
+
+    def stream_chat(
+        self,
+        messages: Sequence[ChatMessage],
+        **kwargs: Any,  # noqa: ANN401
+    ) -> Generator[ChatResponse, None, None]:
+        """Streaming chat - not implemented."""
+        raise NotImplementedError("stream_chat is not supported by LLMCompat.")
+
+    def stream_complete(
+        self,
+        prompt: str,
+        formatted: bool = False,
+        **kwargs: Any,  # noqa: ANN401
+    ) -> Generator[CompletionResponse, None, None]:
+        """Streaming completion - not implemented."""
+        raise NotImplementedError("stream_complete is not supported by LLMCompat.")
+
+    # ── Async methods (llama-index interface) ────────────────────────────────
+
+    async def achat(
+        self,
+        messages: Sequence[ChatMessage],
+        **kwargs: Any,  # noqa: ANN401
+    ) -> ChatResponse:
+        """Asynchronous chat completion.
+
+        Extracts the last user message as the prompt and delegates to
+        ``LLM.acomplete()``.
+        """
+        prompt = self._messages_to_prompt(messages)
+        result = await self._llm_instance.acomplete(prompt, **kwargs)
+        resp = result["response"]
+        return ChatResponse(
+            message=ChatMessage(role=MessageRole.ASSISTANT, content=resp.text),
+            raw=resp.raw,
+        )
+
+    async def acomplete(
+        self,
+        prompt: str,
+        formatted: bool = False,
+        **kwargs: Any,  # noqa: ANN401
+    ) -> CompletionResponse:
+        """Asynchronous completion."""
+        result = await self._llm_instance.acomplete(prompt, **kwargs)
+        resp = result["response"]
+        return CompletionResponse(text=resp.text, raw=resp.raw)
+
+    async def astream_chat(
+        self,
+        messages: Sequence[ChatMessage],
+        **kwargs: Any,  # noqa: ANN401
+    ) -> Any:  # noqa: ANN401
+        """Async streaming chat - not implemented."""
+        raise NotImplementedError("astream_chat is not supported by LLMCompat.")
+
+    async def astream_complete(
+        self,
+        prompt: str,
+        formatted: bool = False,
+        **kwargs: Any,  # noqa: ANN401
+    ) -> Any:  # noqa: ANN401
+        """Async streaming completion - not implemented."""
+        raise NotImplementedError("astream_complete is not supported by LLMCompat.")
+
+    # ── Helper methods ───────────────────────────────────────────────────────
+
+    @staticmethod
+    def _messages_to_prompt(messages: Sequence[ChatMessage]) -> str:
+        """Flatten a message sequence into a single prompt string.
+
+        Concatenates all messages with role prefixes so that
+        system-level task instructions (e.g. from llama-index's
+        ``LLMQuestionGenerator`` or ``KeywordTableIndex``) are
+        preserved when forwarded to ``LLM.complete()``.
+        """
+        parts: list[str] = []
+        for msg in messages:
+            role = getattr(msg.role, "value", str(msg.role))
+            content = msg.content or ""
+            parts.append(f"{role}: {content}")
+        return "\n".join(parts)
+
+    # ── Factory methods ────────────────────────────────────────────────────
+
+    @classmethod
+    def from_llm(cls, llm: "LLM") -> "LLMCompat":
+        """Create an LLMCompat instance reusing an existing SDK1 LLM.
+
+        Reuses the already-initialised ``LLM`` object directly, avoiding
+        redundant adapter validation and ``PlatformHelper`` calls that
+        would occur if we re-created the instance from scratch.
+
+        Args:
+            llm: An SDK1 LLM instance.
+
+        Returns:
+            A new LLMCompat wrapping the same LLM instance.
+        """
+        instance = cls.__new__(cls)
+        instance._llm_instance = llm
+        instance._tool = llm._tool
+        instance._adapter_instance_id = llm._adapter_instance_id
+
+        # For compatibility with SDK Callback Manager.
+        instance.model_name = llm.get_model_name()
+        instance.callback_manager = None
+
+        if not PlatformHelper.is_public_adapter(adapter_id=llm._adapter_instance_id):
+            if llm._tool:
+                platform_api_key = llm._tool.get_env_or_die(ToolEnv.PLATFORM_API_KEY)
+            else:
+                platform_api_key = os.environ.get(ToolEnv.PLATFORM_API_KEY, "")
+
+            from unstract.sdk1.utils.callback_manager import CallbackManager
+
+            CallbackManager.set_callback(
+                platform_api_key=platform_api_key,
+                model=instance,
+                kwargs={
+                    **llm.platform_kwargs,
+                    "adapter_instance_id": llm._adapter_instance_id,
+                },
+            )
+
+        return instance
+
+    # ── SDK1 compatibility methods ───────────────────────────────────────────
+
+    def get_model_name(self) -> str:
+        """Gets the name of the LLM model."""
+        return self._llm_instance.get_model_name()
+
+    def get_metrics(self) -> dict[str, object]:
+        """Get captured metrics."""
+        return self._llm_instance.get_metrics()
+
+    def get_usage_reason(self) -> object:
+        """Get usage reason from platform kwargs."""
+        return self._llm_instance.get_usage_reason()
+
+    def test_connection(self) -> bool:
+        """Test connection to the LLM provider."""
+        return self._llm_instance.test_connection()
diff --git a/unstract/sdk1/tests/test_llm_compat.py b/unstract/sdk1/tests/test_llm_compat.py
new file mode 100644
index 0000000000..c9eac4095d
--- /dev/null
+++ b/unstract/sdk1/tests/test_llm_compat.py
@@ -0,0 +1,373 @@
+"""Unit tests for LLMCompat, emulated types, and _messages_to_prompt."""
+
+from typing import Self
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from unstract.sdk1.llm import (
+    LLM,
+    ChatMessage,
+    ChatResponse,
+    CompletionResponse,
+    LLMCompat,
+    LLMMetadata,
+    MessageRole,
+)
+from unstract.sdk1.utils.common import LLMResponseCompat
+
+# ── Fixtures ─────────────────────────────────────────────────────────────────
+
+
+@pytest.fixture
+def mock_sdk1_llm() -> MagicMock:
+    """Create a mock SDK1 LLM instance with adapter attributes."""
+    llm = MagicMock(spec=LLM)
+    llm._adapter_id = "openai"
+    llm._adapter_metadata = {"api_key": "test-key"}
+    llm._adapter_instance_id = "inst-123"
+    llm._tool = MagicMock()
+    llm._usage_kwargs = {"run_id": "test-run"}
+    llm._system_prompt = ""
+    llm._capture_metrics = False
+    llm.get_model_name.return_value = "gpt-4"
+    llm.platform_kwargs = {"run_id": "test-run"}
+    return llm
+
+
+@pytest.fixture
+def compat_from_mock(mock_sdk1_llm: MagicMock) -> LLMCompat:
+    """Create an LLMCompat via from_llm() with PlatformHelper mocked."""
+    with patch("unstract.sdk1.llm.PlatformHelper") as mock_ph:
+        mock_ph.is_public_adapter.return_value = True
+        return LLMCompat.from_llm(mock_sdk1_llm)
+
+
+# ── LLMCompat.from_llm tests ────────────────────────────────────────────────
+
+
+class TestLLMCompatFromLlm:
+    """Tests for the LLMCompat.from_llm factory method."""
+
+    @patch("unstract.sdk1.llm.PlatformHelper")
+    def test_from_llm_reuses_llm_instance(
+        self: Self,
+        mock_platform_helper: MagicMock,
+        mock_sdk1_llm: MagicMock,
+    ) -> None:
+        """Verify from_llm reuses the existing LLM, not re-creating one."""
+        mock_platform_helper.is_public_adapter.return_value = True
+        result = LLMCompat.from_llm(mock_sdk1_llm)
+
+        assert result._llm_instance is mock_sdk1_llm
+
+    @patch("unstract.sdk1.llm.PlatformHelper")
+    def test_from_llm_returns_llmcompat_instance(
+        self: Self,
+        mock_platform_helper: MagicMock,
+        mock_sdk1_llm: MagicMock,
+    ) -> None:
+        """Verify from_llm returns an LLMCompat instance."""
+        mock_platform_helper.is_public_adapter.return_value = True
+        result = LLMCompat.from_llm(mock_sdk1_llm)
+        assert isinstance(result, LLMCompat)
+
+    @patch("unstract.sdk1.llm.PlatformHelper")
+    def test_from_llm_sets_model_name(
+        self: Self,
+        mock_platform_helper: MagicMock,
+        mock_sdk1_llm: MagicMock,
+    ) -> None:
+        """Verify from_llm sets model_name from the LLM instance."""
+        mock_platform_helper.is_public_adapter.return_value = True
+        result = LLMCompat.from_llm(mock_sdk1_llm)
+        assert result.model_name == "gpt-4"
+
+    @patch("unstract.sdk1.llm.PlatformHelper")
+    def test_from_llm_does_not_call_init(
+        self: Self,
+        mock_platform_helper: MagicMock,
+        mock_sdk1_llm: MagicMock,
+    ) -> None:
+        """Verify from_llm bypasses __init__ (no redundant LLM creation)."""
+        mock_platform_helper.is_public_adapter.return_value = True
+        with patch.object(LLMCompat, "__init__") as mock_init:
+            LLMCompat.from_llm(mock_sdk1_llm)
+            mock_init.assert_not_called()
+
+
+# ── LLMCompat delegation tests ──────────────────────────────────────────────
+
+
+class TestLLMCompatDelegation:
+    """Tests verifying LLMCompat delegates to LLM.complete/acomplete."""
+
+    def _make_llm_response(
+        self: Self,
+        text: str = "response text",
+        raw: object = None,
+    ) -> dict[str, object]:
+        """Build a dict matching LLM.complete() return shape."""
+        resp = LLMResponseCompat(text)
+        resp.raw = raw or {"id": "test-resp"}
+        return {"response": resp}
+
+    def test_complete_delegates_to_llm(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """complete() should call LLM.complete() and wrap the result."""
+        llm_mock = compat_from_mock._llm_instance
+        llm_mock.complete.return_value = self._make_llm_response("done", {"id": "r1"})
+
+        result = compat_from_mock.complete("test prompt")
+
+        llm_mock.complete.assert_called_once_with("test prompt")
+        assert isinstance(result, CompletionResponse)
+        assert result.text == "done"
+        assert result.raw == {"id": "r1"}
+
+    def test_chat_delegates_to_llm_complete(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """chat() should flatten messages and delegate to LLM.complete()."""
+        llm_mock = compat_from_mock._llm_instance
+        llm_mock.complete.return_value = self._make_llm_response(
+            "chat reply", {"id": "r2"}
+        )
+
+        messages = [
+            ChatMessage(role=MessageRole.SYSTEM, content="Be helpful"),
+            ChatMessage(role=MessageRole.USER, content="Hello"),
+        ]
+        result = compat_from_mock.chat(messages)
+
+        # Should concatenate all messages with role prefixes.
+        expected = "system: Be helpful\nuser: Hello"
+        llm_mock.complete.assert_called_once_with(expected)
+        assert isinstance(result, ChatResponse)
+        assert result.message.role == MessageRole.ASSISTANT
+        assert result.message.content == "chat reply"
+        assert result.raw == {"id": "r2"}
+
+    def test_chat_forwards_kwargs_to_llm(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """chat() should forward extra kwargs to LLM.complete()."""
+        llm_mock = compat_from_mock._llm_instance
+        llm_mock.complete.return_value = self._make_llm_response()
+
+        messages = [ChatMessage(role=MessageRole.USER, content="Hi")]
+        compat_from_mock.chat(messages, temperature=0.5)
+
+        llm_mock.complete.assert_called_once_with("user: Hi", temperature=0.5)
+
+    def test_complete_forwards_kwargs_to_llm(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """complete() should forward extra kwargs to LLM.complete()."""
+        llm_mock = compat_from_mock._llm_instance
+        llm_mock.complete.return_value = self._make_llm_response()
+
+        compat_from_mock.complete("prompt", max_tokens=100)
+
+        llm_mock.complete.assert_called_once_with("prompt", max_tokens=100)
+
+    @pytest.mark.asyncio
+    async def test_acomplete_delegates_to_llm(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """acomplete() should call LLM.acomplete() and wrap the result."""
+        llm_mock = compat_from_mock._llm_instance
+        llm_mock.acomplete = AsyncMock(
+            return_value=self._make_llm_response("async done", {"id": "r3"})
+        )
+
+        result = await compat_from_mock.acomplete("async prompt")
+
+        llm_mock.acomplete.assert_called_once_with("async prompt")
+        assert isinstance(result, CompletionResponse)
+        assert result.text == "async done"
+        assert result.raw == {"id": "r3"}
+
+    @pytest.mark.asyncio
+    async def test_achat_delegates_to_llm_acomplete(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """achat() should extract prompt and delegate to LLM.acomplete()."""
+        llm_mock = compat_from_mock._llm_instance
+        llm_mock.acomplete = AsyncMock(
+            return_value=self._make_llm_response("async chat reply", {"id": "r4"})
+        )
+
+        messages = [
+            ChatMessage(role=MessageRole.USER, content="Async hello"),
+        ]
+        result = await compat_from_mock.achat(messages)
+
+        llm_mock.acomplete.assert_called_once_with("user: Async hello")
+        assert isinstance(result, ChatResponse)
+        assert result.message.role == MessageRole.ASSISTANT
+        assert result.message.content == "async chat reply"
+
+    def test_stream_chat_not_implemented(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """stream_chat() should raise NotImplementedError."""
+        with pytest.raises(NotImplementedError):
+            compat_from_mock.stream_chat([])
+
+    def test_stream_complete_not_implemented(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """stream_complete() should raise NotImplementedError."""
+        with pytest.raises(NotImplementedError):
+            compat_from_mock.stream_complete("prompt")
+
+    @pytest.mark.asyncio
+    async def test_astream_chat_not_implemented(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """astream_chat() should raise NotImplementedError."""
+        with pytest.raises(NotImplementedError):
+            await compat_from_mock.astream_chat([])
+
+    @pytest.mark.asyncio
+    async def test_astream_complete_not_implemented(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """astream_complete() should raise NotImplementedError."""
+        with pytest.raises(NotImplementedError):
+            await compat_from_mock.astream_complete("prompt")
+
+    def test_metadata_returns_emulated_type(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """Metadata property should return emulated LLMMetadata."""
+        meta = compat_from_mock.metadata
+        assert isinstance(meta, LLMMetadata)
+        assert meta.is_chat_model is True
+        assert meta.model_name == "gpt-4"
+
+    def test_get_model_name_delegates(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """get_model_name() should delegate to LLM instance."""
+        assert compat_from_mock.get_model_name() == "gpt-4"
+        compat_from_mock._llm_instance.get_model_name.assert_called()
+
+    def test_get_metrics_delegates(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """get_metrics() should delegate to LLM instance."""
+        compat_from_mock._llm_instance.get_metrics.return_value = {"time": 1.5}
+        assert compat_from_mock.get_metrics() == {"time": 1.5}
+
+    def test_test_connection_delegates(
+        self: Self,
+        compat_from_mock: LLMCompat,
+    ) -> None:
+        """test_connection() should delegate to LLM instance."""
+        compat_from_mock._llm_instance.test_connection.return_value = True
+        assert compat_from_mock.test_connection() is True
+
+
+# ── Emulated types tests ────────────────────────────────────────────────────
+
+
+class TestEmulatedTypes:
+    """Tests for the emulated llama-index types in SDK1."""
+
+    def test_message_role_values(self: Self) -> None:
+        """Emulated MessageRole should have correct string values."""
+        assert MessageRole.USER.value == "user"
+        assert MessageRole.ASSISTANT.value == "assistant"
+        assert MessageRole.SYSTEM.value == "system"
+        assert MessageRole.FUNCTION.value == "function"
+        assert MessageRole.TOOL.value == "tool"
+
+    def test_chat_message_defaults(self: Self) -> None:
+        """ChatMessage should default to USER role with None content."""
+        msg = ChatMessage()
+        assert msg.role == MessageRole.USER
+        assert msg.content is None
+
+    def test_chat_response_message_access(self: Self) -> None:
+        """ChatResponse.message.content should be accessible."""
+        resp = ChatResponse(
+            message=ChatMessage(role=MessageRole.ASSISTANT, content="test")
+        )
+        assert resp.message.content == "test"
+        assert resp.message.role == MessageRole.ASSISTANT
+
+    def test_completion_response_text(self: Self) -> None:
+        """CompletionResponse.text should be accessible."""
+        resp = CompletionResponse(text="completed")
+        assert resp.text == "completed"
+
+    def test_llm_metadata_defaults(self: Self) -> None:
+        """LLMMetadata should default to chat model."""
+        meta = LLMMetadata()
+        assert meta.is_chat_model is True
+        assert meta.model_name == ""
+
+
+# ── _messages_to_prompt tests ────────────────────────────────────────────────
+
+
+class TestMessagesToPrompt:
+    """Tests for LLMCompat._messages_to_prompt flattening."""
+
+    def test_single_user_message(self: Self) -> None:
+        """Should format a single user message with role prefix."""
+        messages = [ChatMessage(role=MessageRole.USER, content="hello")]
+        assert LLMCompat._messages_to_prompt(messages) == "user: hello"
+
+    def test_none_content_becomes_empty_string(self: Self) -> None:
+        """None content should be converted to empty string."""
+        messages = [ChatMessage(role=MessageRole.USER, content=None)]
+        assert LLMCompat._messages_to_prompt(messages) == "user: "
+
+    def test_preserves_all_messages(self: Self) -> None:
+        """Should concatenate all messages preserving system instructions."""
+        messages = [
+            ChatMessage(role=MessageRole.SYSTEM, content="You are helpful"),
+            ChatMessage(role=MessageRole.USER, content="Question"),
+        ]
+        expected = "system: You are helpful\nuser: Question"
+        assert LLMCompat._messages_to_prompt(messages) == expected
+
+    def test_multi_turn_conversation(self: Self) -> None:
+        """Should preserve all turns in a multi-turn conversation."""
+        messages = [
+            ChatMessage(role=MessageRole.SYSTEM, content="Be concise"),
+            ChatMessage(role=MessageRole.USER, content="First"),
+            ChatMessage(role=MessageRole.ASSISTANT, content="Answer"),
+            ChatMessage(role=MessageRole.USER, content="Follow-up"),
+        ]
+        result = LLMCompat._messages_to_prompt(messages)
+        assert result == (
+            "system: Be concise\n" "user: First\n" "assistant: Answer\n" "user: Follow-up"
+        )
+
+    def test_empty_messages_returns_empty_string(self: Self) -> None:
+        """Should return empty string for empty message list."""
+        assert LLMCompat._messages_to_prompt([]) == ""
+
+    def test_string_role_fallback(self: Self) -> None:
+        """Should handle non-enum role via getattr fallback."""
+        msg = MagicMock()
+        msg.role = "user"
+        msg.content = "test"
+        assert LLMCompat._messages_to_prompt([msg]) == "user: test"
diff --git a/unstract/sdk1/uv.lock b/unstract/sdk1/uv.lock
index f153075269..a967916f20 100644
--- a/unstract/sdk1/uv.lock
+++ b/unstract/sdk1/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 1
+revision = 2
 requires-python = "==3.12.*"
 
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diff --git a/workers/uv.lock b/workers/uv.lock
index d4ff0bb8e1..d4d26d17c7 100644
--- a/workers/uv.lock
+++ b/workers/uv.lock
@@ -4758,6 +4758,7 @@ docs = [{ name = "lazydocs", specifier = "~=0.4.8" }]
 test = [
     { name = "parameterized", specifier = "==0.9.0" },
     { name = "pytest", specifier = "==8.3.3" },
+    { name = "pytest-asyncio", specifier = ">=0.23.0" },
     { name = "pytest-cov", specifier = ">=6.0.0" },
     { name = "pytest-md-report", specifier = ">=0.6.2" },
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