fix: re-enable tests and fix legacy test interface (#208)

* fix: re-enable tests and fix legacy test interface

* fix: skip llamacpp based on installed status

* fix: minor fix

.github/workflows/unit-test.yaml

@@ -11,9 +11,9 @@ env:
 
 jobs:
   unit-test:
-    if: false # temporary disable this job due to legacy interface
+    # if: false # temporary disable this job due to legacy interface
     #TODO: enable this job after the new interface is ready
-    # if: ${{ !cancelled() }}
+    if: ${{ !cancelled() }}
     runs-on: ${{ matrix.os }}
     timeout-minutes: 20
     defaults:

libs/kotaemon/kotaemon/indices/ingests/files.py

@@ -3,6 +3,7 @@ from typing import Type
 
 from decouple import config
 from llama_index.core.readers.base import BaseReader
+from llama_index.readers.file import PDFReader
 from theflow.settings import settings as flowsettings
 
 from kotaemon.base import BaseComponent, Document, Param
@@ -91,7 +92,7 @@ class DocumentIngestor(BaseComponent):
             file_extractors[ext] = cls()
 
         if self.pdf_mode == "normal":
-            pass  # use default loader of llama-index which is pypdf
+            file_extractors[".pdf"] = PDFReader()
         elif self.pdf_mode == "ocr":
             file_extractors[".pdf"] = OCRReader()
         elif self.pdf_mode == "multimodal":

libs/kotaemon/tests/conftest.py

@@ -24,6 +24,62 @@ def if_haystack_not_installed():
         return False
 
 
+def if_sentence_bert_not_installed():
+    try:
+        import sentence_transformers  # noqa: F401
+    except ImportError:
+        return True
+    else:
+        return False
+
+
+def if_sentence_fastembed_not_installed():
+    try:
+        import fastembed  # noqa: F401
+    except ImportError:
+        return True
+    else:
+        return False
+
+
+def if_unstructured_not_installed():
+    try:
+        import unstructured  # noqa: F401
+    except ImportError:
+        return True
+    else:
+        return False
+
+
+def if_llama_cpp_not_installed():
+    try:
+        import llama_cpp  # noqa: F401
+    except ImportError:
+        return True
+    else:
+        return False
+
+
 skip_when_haystack_not_installed = pytest.mark.skipif(
     if_haystack_not_installed(), reason="Haystack is not installed"
 )
+
+skip_when_sentence_bert_not_installed = pytest.mark.skipif(
+    if_sentence_bert_not_installed(), reason="SBert is not installed"
+)
+
+skip_when_fastembed_not_installed = pytest.mark.skipif(
+    if_sentence_fastembed_not_installed(), reason="fastembed is not installed"
+)
+
+skip_when_unstructured_not_installed = pytest.mark.skipif(
+    if_unstructured_not_installed(), reason="unstructured is not installed"
+)
+
+skip_openai_lc_wrapper_test = pytest.mark.skipif(
+    True, reason="OpenAI LC wrapper test is skipped"
+)
+
+skip_llama_cpp_not_installed = pytest.mark.skipif(
+    if_llama_cpp_not_installed(), reason="llama_cpp is not installed"
+)

libs/kotaemon/tests/test_agent.py

@@ -13,7 +13,9 @@ from kotaemon.agents import (
     RewooAgent,
     WikipediaTool,
 )
-from kotaemon.llms import LCAzureChatOpenAI
+from kotaemon.llms import AzureChatOpenAI
+
+from .conftest import skip_openai_lc_wrapper_test
 
 FINAL_RESPONSE_TEXT = "Final Answer: Hello Cinnamon AI!"
 REWOO_VALID_PLAN = (
@@ -112,12 +114,11 @@ _openai_chat_completion_responses_react_langchain_tool = [
 
 @pytest.fixture
 def llm():
-    return LCAzureChatOpenAI(
-        azure_endpoint="https://dummy.openai.azure.com/",
-        openai_api_key="dummy",
-        openai_api_version="2023-03-15-preview",
-        deployment_name="dummy-q2",
-        temperature=0,
+    return AzureChatOpenAI(
+        api_key="dummy",
+        api_version="2024-05-01-preview",
+        azure_deployment="gpt-4o",
+        azure_endpoint="https://test.openai.azure.com/",
     )
 
 
@@ -175,6 +176,7 @@ def test_react_agent(openai_completion, llm, mock_google_search):
     assert response.text == FINAL_RESPONSE_TEXT
 
 
+@skip_openai_lc_wrapper_test
 @patch(
     "openai.resources.chat.completions.Completions.create",
     side_effect=_openai_chat_completion_responses_react,
@@ -199,6 +201,7 @@ def test_react_agent_langchain(openai_completion, llm, mock_google_search):
     assert response
 
 
+@skip_openai_lc_wrapper_test
 @patch(
     "openai.resources.chat.completions.Completions.create",
     side_effect=_openai_chat_completion_responses_react,

libs/kotaemon/tests/test_composite.py

@@ -4,10 +4,10 @@ import pytest
 from openai.types.chat.chat_completion import ChatCompletion
 
 from kotaemon.llms import (
+    AzureChatOpenAI,
     BasePromptComponent,
     GatedBranchingPipeline,
     GatedLinearPipeline,
-    LCAzureChatOpenAI,
     SimpleBranchingPipeline,
     SimpleLinearPipeline,
 )
@@ -40,12 +40,11 @@ _openai_chat_completion_response = ChatCompletion.parse_obj(
 
 @pytest.fixture
 def mock_llm():
-    return LCAzureChatOpenAI(
-        azure_endpoint="OPENAI_API_BASE",
-        openai_api_key="OPENAI_API_KEY",
-        openai_api_version="OPENAI_API_VERSION",
-        deployment_name="dummy-q2-gpt35",
-        temperature=0,
+    return AzureChatOpenAI(
+        api_key="dummy",
+        api_version="2024-05-01-preview",
+        azure_deployment="gpt-4o",
+        azure_endpoint="https://test.openai.azure.com/",
     )
 
 

libs/kotaemon/tests/test_cot.py

@@ -2,7 +2,7 @@ from unittest.mock import patch
 
 from openai.types.chat.chat_completion import ChatCompletion
 
-from kotaemon.llms import LCAzureChatOpenAI
+from kotaemon.llms import AzureChatOpenAI
 from kotaemon.llms.cot import ManualSequentialChainOfThought, Thought
 
 _openai_chat_completion_response = [
@@ -38,12 +38,11 @@ _openai_chat_completion_response = [
     side_effect=_openai_chat_completion_response,
 )
 def test_cot_plus_operator(openai_completion):
-    llm = LCAzureChatOpenAI(
-        azure_endpoint="https://dummy.openai.azure.com/",
-        openai_api_key="dummy",
-        openai_api_version="2023-03-15-preview",
-        deployment_name="dummy-q2",
-        temperature=0,
+    llm = AzureChatOpenAI(
+        api_key="dummy",
+        api_version="2024-05-01-preview",
+        azure_deployment="gpt-4o",
+        azure_endpoint="https://test.openai.azure.com/",
     )
     thought1 = Thought(
         prompt="Word {word} in {language} is ",
@@ -70,12 +69,11 @@ def test_cot_plus_operator(openai_completion):
     side_effect=_openai_chat_completion_response,
 )
 def test_cot_manual(openai_completion):
-    llm = LCAzureChatOpenAI(
-        azure_endpoint="https://dummy.openai.azure.com/",
-        openai_api_key="dummy",
-        openai_api_version="2023-03-15-preview",
-        deployment_name="dummy-q2",
-        temperature=0,
+    llm = AzureChatOpenAI(
+        api_key="dummy",
+        api_version="2024-05-01-preview",
+        azure_deployment="gpt-4o",
+        azure_endpoint="https://test.openai.azure.com/",
     )
     thought1 = Thought(
         prompt="Word {word} in {language} is ",
@@ -100,12 +98,11 @@ def test_cot_manual(openai_completion):
     side_effect=_openai_chat_completion_response,
 )
 def test_cot_with_termination_callback(openai_completion):
-    llm = LCAzureChatOpenAI(
-        azure_endpoint="https://dummy.openai.azure.com/",
-        openai_api_key="dummy",
-        openai_api_version="2023-03-15-preview",
-        deployment_name="dummy-q2",
-        temperature=0,
+    llm = AzureChatOpenAI(
+        api_key="dummy",
+        api_version="2024-05-01-preview",
+        azure_deployment="gpt-4o",
+        azure_endpoint="https://test.openai.azure.com/",
     )
     thought1 = Thought(
         prompt="Word {word} in {language} is ",

libs/kotaemon/tests/test_embedding_models.py

@@ -8,12 +8,16 @@ from kotaemon.base import Document
 from kotaemon.embeddings import (
     AzureOpenAIEmbeddings,
     FastEmbedEmbeddings,
-    LCAzureOpenAIEmbeddings,
     LCCohereEmbeddings,
     LCHuggingFaceEmbeddings,
     OpenAIEmbeddings,
 )
 
+from .conftest import (
+    skip_when_fastembed_not_installed,
+    skip_when_sentence_bert_not_installed,
+)
+
 with open(Path(__file__).parent / "resources" / "embedding_openai_batch.json") as f:
     openai_embedding_batch = CreateEmbeddingResponse.model_validate(json.load(f))
 
@@ -32,12 +36,12 @@ def assert_embedding_result(output):
     "openai.resources.embeddings.Embeddings.create",
     side_effect=lambda *args, **kwargs: openai_embedding,
 )
-def test_lcazureopenai_embeddings_raw(openai_embedding_call):
-    model = LCAzureOpenAIEmbeddings(
-        model="text-embedding-ada-002",
-        deployment="embedding-deployment",
+def test_azureopenai_embeddings_raw(openai_embedding_call):
+    model = AzureOpenAIEmbeddings(
+        azure_deployment="embedding-deployment",
         azure_endpoint="https://test.openai.azure.com/",
-        openai_api_key="some-key",
+        api_key="some-key",
+        api_version="version",
     )
     output = model("Hello world")
     assert_embedding_result(output)
@@ -49,29 +53,13 @@ def test_lcazureopenai_embeddings_raw(openai_embedding_call):
     side_effect=lambda *args, **kwargs: openai_embedding_batch,
 )
 def test_lcazureopenai_embeddings_batch_raw(openai_embedding_call):
-    model = LCAzureOpenAIEmbeddings(
-        model="text-embedding-ada-002",
-        deployment="embedding-deployment",
-        azure_endpoint="https://test.openai.azure.com/",
-        openai_api_key="some-key",
-    )
-    output = model(["Hello world", "Goodbye world"])
-    assert_embedding_result(output)
-    openai_embedding_call.assert_called()
-
-
-@patch(
-    "openai.resources.embeddings.Embeddings.create",
-    side_effect=lambda *args, **kwargs: openai_embedding,
-)
-def test_azureopenai_embeddings_raw(openai_embedding_call):
     model = AzureOpenAIEmbeddings(
+        azure_deployment="embedding-deployment",
         azure_endpoint="https://test.openai.azure.com/",
         api_key="some-key",
         api_version="version",
-        azure_deployment="text-embedding-ada-002",
     )
-    output = model("Hello world")
+    output = model(["Hello world", "Goodbye world"])
     assert_embedding_result(output)
     openai_embedding_call.assert_called()
 
@@ -82,10 +70,10 @@ def test_azureopenai_embeddings_raw(openai_embedding_call):
 )
 def test_azureopenai_embeddings_batch_raw(openai_embedding_call):
     model = AzureOpenAIEmbeddings(
+        azure_deployment="text-embedding-ada-002",
         azure_endpoint="https://test.openai.azure.com/",
         api_key="some-key",
         api_version="version",
-        azure_deployment="text-embedding-ada-002",
     )
     output = model(["Hello world", "Goodbye world"])
     assert_embedding_result(output)
@@ -120,6 +108,7 @@ def test_openai_embeddings_batch_raw(openai_embedding_call):
     openai_embedding_call.assert_called()
 
 
+@skip_when_sentence_bert_not_installed
 @patch(
     "sentence_transformers.SentenceTransformer",
     side_effect=lambda *args, **kwargs: None,
@@ -149,7 +138,9 @@ def test_lchuggingface_embeddings(
 )
 def test_lccohere_embeddings(langchain_cohere_embedding_call):
     model = LCCohereEmbeddings(
-        model="embed-english-light-v2.0", cohere_api_key="my-api-key"
+        model="embed-english-light-v2.0",
+        cohere_api_key="my-api-key",
+        user_agent="test",
     )
 
     output = model("Hello World")
@@ -157,6 +148,7 @@ def test_lccohere_embeddings(langchain_cohere_embedding_call):
     langchain_cohere_embedding_call.assert_called()
 
 
+@skip_when_fastembed_not_installed
 def test_fastembed_embeddings():
     model = FastEmbedEmbeddings()
     output = model("Hello World")

libs/kotaemon/tests/test_indexing_retrieval.py

@@ -1,32 +1,31 @@
 import json
 from pathlib import Path
 from typing import cast
+from unittest.mock import patch
 
-import pytest
-from openai.resources.embeddings import Embeddings
+from openai.types.create_embedding_response import CreateEmbeddingResponse
 
 from kotaemon.base import Document
-from kotaemon.embeddings import LCAzureOpenAIEmbeddings
+from kotaemon.embeddings import AzureOpenAIEmbeddings
 from kotaemon.indices import VectorIndexing, VectorRetrieval
 from kotaemon.storages import ChromaVectorStore, InMemoryDocumentStore
 
 with open(Path(__file__).parent / "resources" / "embedding_openai.json") as f:
-    openai_embedding = json.load(f)
+    openai_embedding = CreateEmbeddingResponse.model_validate(json.load(f))
 
 
-@pytest.fixture(scope="function")
-def mock_openai_embedding(monkeypatch):
-    monkeypatch.setattr(Embeddings, "create", lambda *args, **kwargs: openai_embedding)
-
-
-def test_indexing(mock_openai_embedding, tmp_path):
+@patch(
+    "openai.resources.embeddings.Embeddings.create",
+    side_effect=lambda *args, **kwargs: openai_embedding,
+)
+def test_indexing(tmp_path):
     db = ChromaVectorStore(path=str(tmp_path))
     doc_store = InMemoryDocumentStore()
-    embedding = LCAzureOpenAIEmbeddings(
-        model="text-embedding-ada-002",
-        deployment="embedding-deployment",
+    embedding = AzureOpenAIEmbeddings(
+        azure_deployment="text-embedding-ada-002",
         azure_endpoint="https://test.openai.azure.com/",
-        openai_api_key="some-key",
+        api_key="some-key",
+        api_version="version",
     )
 
     pipeline = VectorIndexing(vector_store=db, embedding=embedding, doc_store=doc_store)
@@ -39,14 +38,18 @@ def test_indexing(mock_openai_embedding, tmp_path):
     assert len(pipeline.doc_store._store) == 1, "Expected 1 document"
 
 
-def test_retrieving(mock_openai_embedding, tmp_path):
+@patch(
+    "openai.resources.embeddings.Embeddings.create",
+    side_effect=lambda *args, **kwargs: openai_embedding,
+)
+def test_retrieving(tmp_path):
     db = ChromaVectorStore(path=str(tmp_path))
     doc_store = InMemoryDocumentStore()
-    embedding = LCAzureOpenAIEmbeddings(
-        model="text-embedding-ada-002",
-        deployment="embedding-deployment",
+    embedding = AzureOpenAIEmbeddings(
+        azure_deployment="text-embedding-ada-002",
         azure_endpoint="https://test.openai.azure.com/",
-        openai_api_key="some-key",
+        api_key="some-key",
+        api_version="version",
     )
 
     index_pipeline = VectorIndexing(

libs/kotaemon/tests/test_llms_chat_models.py

@@ -4,15 +4,17 @@ from unittest.mock import patch
 import pytest
 
 from kotaemon.base.schema import AIMessage, HumanMessage, LLMInterface, SystemMessage
-from kotaemon.llms import LCAzureChatOpenAI, LlamaCppChat
+from kotaemon.llms import AzureChatOpenAI, LlamaCppChat
 
 try:
-    from langchain_openai import AzureChatOpenAI as AzureChatOpenAILC
+    pass
 except ImportError:
-    from langchain.chat_models import AzureChatOpenAI as AzureChatOpenAILC
+    pass
 
 from openai.types.chat.chat_completion import ChatCompletion
 
+from .conftest import skip_llama_cpp_not_installed
+
 _openai_chat_completion_response = ChatCompletion.parse_obj(
     {
         "id": "chatcmpl-7qyuw6Q1CFCpcKsMdFkmUPUa7JP2x",
@@ -43,17 +45,12 @@ _openai_chat_completion_response = ChatCompletion.parse_obj(
     side_effect=lambda *args, **kwargs: _openai_chat_completion_response,
 )
 def test_azureopenai_model(openai_completion):
-    model = LCAzureChatOpenAI(
+    model = AzureChatOpenAI(
+        api_key="dummy",
+        api_version="2024-05-01-preview",
+        azure_deployment="gpt-4o",
         azure_endpoint="https://test.openai.azure.com/",
-        openai_api_key="some-key",
-        openai_api_version="2023-03-15-preview",
-        deployment_name="gpt35turbo",
-        temperature=0,
     )
-    assert isinstance(
-        model.to_langchain_format(), AzureChatOpenAILC
-    ), "Agent not wrapped in Langchain's AzureChatOpenAI"
-
     # test for str input - stream mode
     output = model("hello world")
     assert isinstance(
@@ -76,6 +73,7 @@ def test_azureopenai_model(openai_completion):
     openai_completion.assert_called()
 
 
+@skip_llama_cpp_not_installed
 def test_llamacpp_chat():
     from llama_cpp import Llama
 

libs/kotaemon/tests/test_llms_completion_models.py

@@ -13,6 +13,8 @@ except ImportError:
 
 from openai.types.completion import Completion
 
+from .conftest import skip_llama_cpp_not_installed, skip_openai_lc_wrapper_test
+
 _openai_completion_response = Completion.parse_obj(
     {
         "id": "cmpl-7qyNoIo6gRSCJR0hi8o3ZKBH4RkJ0",
@@ -33,6 +35,7 @@ _openai_completion_response = Completion.parse_obj(
 )
 
 
+@skip_openai_lc_wrapper_test
 @patch(
     "openai.resources.completions.Completions.create",
     side_effect=lambda *args, **kwargs: _openai_completion_response,
@@ -79,6 +82,7 @@ def test_openai_model(openai_completion):
     ), "Output for single text is not LLMInterface"
 
 
+@skip_llama_cpp_not_installed
 def test_llamacpp_model():
     weight_path = Path(__file__).parent / "resources" / "ggml-vocab-llama.gguf"
 

libs/kotaemon/tests/test_reader.py

@@ -14,6 +14,8 @@ from kotaemon.loaders import (
     UnstructuredReader,
 )
 
+from .conftest import skip_when_unstructured_not_installed
+
 
 def test_docx_reader():
     reader = DocxReader()
@@ -52,6 +54,7 @@ def test_pdf_reader():
     assert len(nodes) > 0
 
 
+@skip_when_unstructured_not_installed
 def test_unstructured_pdf_reader():
     reader = UnstructuredReader()
     dirpath = Path(__file__).parent

libs/kotaemon/tests/test_reranking.py

@@ -5,7 +5,7 @@ from openai.types.chat.chat_completion import ChatCompletion
 
 from kotaemon.base import Document
 from kotaemon.indices.rankings import LLMReranking
-from kotaemon.llms import LCAzureChatOpenAI
+from kotaemon.llms import AzureChatOpenAI
 
 _openai_chat_completion_responses = [
     ChatCompletion.parse_obj(
@@ -41,11 +41,11 @@ _openai_chat_completion_responses = [
 
 @pytest.fixture
 def llm():
-    return LCAzureChatOpenAI(
-        azure_endpoint="https://dummy.openai.azure.com/",
-        openai_api_key="dummy",
-        openai_api_version="2023-03-15-preview",
-        temperature=0,
+    return AzureChatOpenAI(
+        api_key="dummy",
+        api_version="2024-05-01-preview",
+        azure_deployment="gpt-4o",
+        azure_endpoint="https://test.openai.azure.com/",
     )
 
 

libs/kotaemon/tests/test_table_reader.py

@@ -5,6 +5,8 @@ import pytest
 
 from kotaemon.loaders import MathpixPDFReader, OCRReader, PandasExcelReader
 
+from .conftest import skip_when_unstructured_not_installed
+
 input_file = Path(__file__).parent / "resources" / "table.pdf"
 input_file_excel = Path(__file__).parent / "resources" / "dummy.xlsx"
 
@@ -26,6 +28,7 @@ def mathpix_output():
     return content
 
 
+@skip_when_unstructured_not_installed
 def test_ocr_reader(fullocr_output):
     reader = OCRReader()
     documents = reader.load_data(input_file, response_content=fullocr_output)

libs/kotaemon/tests/test_tools.py

@@ -1,22 +1,17 @@
 import json
 from pathlib import Path
+from unittest.mock import patch
 
-import pytest
-from openai.resources.embeddings import Embeddings
+from openai.types.create_embedding_response import CreateEmbeddingResponse
 
 from kotaemon.agents.tools import ComponentTool, GoogleSearchTool, WikipediaTool
 from kotaemon.base import Document
-from kotaemon.embeddings import LCAzureOpenAIEmbeddings
+from kotaemon.embeddings import AzureOpenAIEmbeddings
 from kotaemon.indices.vectorindex import VectorIndexing, VectorRetrieval
 from kotaemon.storages import ChromaVectorStore, InMemoryDocumentStore
 
 with open(Path(__file__).parent / "resources" / "embedding_openai.json") as f:
-    openai_embedding = json.load(f)
-
-
-@pytest.fixture(scope="function")
-def mock_openai_embedding(monkeypatch):
-    monkeypatch.setattr(Embeddings, "create", lambda *args, **kwargs: openai_embedding)
+    openai_embedding = CreateEmbeddingResponse.model_validate(json.load(f))
 
 
 def test_google_tool(mock_google_search):
@@ -35,14 +30,18 @@ def test_wikipedia_tool():
     assert output
 
 
-def test_pipeline_tool(mock_openai_embedding, tmp_path):
+@patch(
+    "openai.resources.embeddings.Embeddings.create",
+    side_effect=lambda *args, **kwargs: openai_embedding,
+)
+def test_pipeline_tool(tmp_path):
     db = ChromaVectorStore(path=str(tmp_path))
     doc_store = InMemoryDocumentStore()
-    embedding = LCAzureOpenAIEmbeddings(
-        model="text-embedding-ada-002",
-        deployment="embedding-deployment",
+    embedding = AzureOpenAIEmbeddings(
+        azure_deployment="embedding-deployment",
         azure_endpoint="https://test.openai.azure.com/",
-        openai_api_key="some-key",
+        api_key="some-key",
+        api_version="version",
     )
 
     index_pipeline = VectorIndexing(

libs/ktem/ktem_tests/test_qa.py

@@ -7,7 +7,7 @@ from index import ReaderIndexingPipeline
 from openai.resources.embeddings import Embeddings
 from openai.types.chat.chat_completion import ChatCompletion
 
-from kotaemon.llms import LCAzureChatOpenAI
+from kotaemon.llms import AzureChatOpenAI
 
 with open(Path(__file__).parent / "resources" / "embedding_openai.json") as f:
     openai_embedding = json.load(f)
@@ -61,12 +61,11 @@ def test_ingest_pipeline(patch, mock_openai_embedding, tmp_path):
     assert len(results) == 1
 
     # create llm
-    llm = LCAzureChatOpenAI(
-        openai_api_base="https://test.openai.azure.com/",
-        openai_api_key="some-key",
-        openai_api_version="2023-03-15-preview",
-        deployment_name="gpt35turbo",
-        temperature=0,
+    llm = AzureChatOpenAI(
+        api_key="dummy",
+        api_version="2024-05-01-preview",
+        azure_deployment="gpt-4o",
+        azure_endpoint="https://test.openai.azure.com/",
     )
     qa_pipeline = indexing_pipeline.to_qa_pipeline(llm=llm, openai_api_key="some-key")
     response = qa_pipeline("Summarize this document.")