[Feature] OpenAI Function Calling (#1224)

tests/llm/test_anthrophic.py

@@ -24,7 +24,7 @@ def test_get_llm_model_answer(anthropic_llm):
 
 
 def test_get_answer(anthropic_llm):
-    with patch("langchain.chat_models.ChatAnthropic") as mock_chat:
+    with patch("langchain_community.chat_models.ChatAnthropic") as mock_chat:
         mock_chat_instance = mock_chat.return_value
         mock_chat_instance.return_value = MagicMock(content="Test Response")
 
@@ -53,7 +53,7 @@ def test_get_messages(anthropic_llm):
 
 
 def test_get_answer_max_tokens_is_provided(anthropic_llm, caplog):
-    with patch("langchain.chat_models.ChatAnthropic") as mock_chat:
+    with patch("langchain_community.chat_models.ChatAnthropic") as mock_chat:
         mock_chat_instance = mock_chat.return_value
         mock_chat_instance.return_value = MagicMock(content="Test Response")
 

tests/llm/test_azure_openai.py

@@ -28,7 +28,7 @@ def test_get_llm_model_answer(azure_openai_llm):
 
 
 def test_get_answer(azure_openai_llm):
-    with patch("langchain.chat_models.AzureChatOpenAI") as mock_chat:
+    with patch("langchain_community.chat_models.AzureChatOpenAI") as mock_chat:
         mock_chat_instance = mock_chat.return_value
         mock_chat_instance.return_value = MagicMock(content="Test Response")
 
@@ -60,7 +60,7 @@ def test_get_messages(azure_openai_llm):
 
 
 def test_get_answer_top_p_is_provided(azure_openai_llm, caplog):
-    with patch("langchain.chat_models.AzureChatOpenAI") as mock_chat:
+    with patch("langchain_community.chat_models.AzureChatOpenAI") as mock_chat:
         mock_chat_instance = mock_chat.return_value
         mock_chat_instance.return_value = MagicMock(content="Test Response")
 

tests/llm/test_gpt4all.py

@@ -1,5 +1,5 @@
 import pytest
-from langchain.llms.gpt4all import GPT4All as LangchainGPT4All
+from langchain_community.llms.gpt4all import GPT4All as LangchainGPT4All
 
 from embedchain.config import BaseLlmConfig
 from embedchain.llm.gpt4all import GPT4ALLLlm

tests/llm/test_openai.py

@@ -74,3 +74,32 @@ def test_get_llm_model_answer_without_system_prompt(config, mocker):
         model_kwargs={"top_p": config.top_p},
         api_key=os.environ["OPENAI_API_KEY"],
     )
+
+
+@pytest.mark.parametrize(
+    "mock_return, expected",
+    [
+        ([{"test": "test"}], '{"test": "test"}'),
+        ([], "Input could not be mapped to the function!"),
+    ],
+)
+def test_get_llm_model_answer_with_tools(config, mocker, mock_return, expected):
+    mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
+    mocked_convert_to_openai_tool = mocker.patch("langchain_core.utils.function_calling.convert_to_openai_tool")
+    mocked_json_output_tools_parser = mocker.patch("langchain.output_parsers.openai_tools.JsonOutputToolsParser")
+    mocked_openai_chat.return_value.bind.return_value.pipe.return_value.invoke.return_value = mock_return
+
+    llm = OpenAILlm(config, tools={"test": "test"})
+    answer = llm.get_llm_model_answer("Test query")
+
+    mocked_openai_chat.assert_called_once_with(
+        model=config.model,
+        temperature=config.temperature,
+        max_tokens=config.max_tokens,
+        model_kwargs={"top_p": config.top_p},
+        api_key=os.environ["OPENAI_API_KEY"],
+    )
+    mocked_convert_to_openai_tool.assert_called_once_with({"test": "test"})
+    mocked_json_output_tools_parser.assert_called_once()
+
+    assert answer == expected

tests/llm/test_vertex_ai.py

@@ -22,7 +22,7 @@ def test_get_llm_model_answer(vertexai_llm):
 
 
 def test_get_answer_with_warning(vertexai_llm, caplog):
-    with patch("langchain.chat_models.ChatVertexAI") as mock_chat:
+    with patch("langchain_community.chat_models.ChatVertexAI") as mock_chat:
         mock_chat_instance = mock_chat.return_value
         mock_chat_instance.return_value = MagicMock(content="Test Response")
 
@@ -39,7 +39,7 @@ def test_get_answer_with_warning(vertexai_llm, caplog):
 
 
 def test_get_answer_no_warning(vertexai_llm, caplog):
-    with patch("langchain.chat_models.ChatVertexAI") as mock_chat:
+    with patch("langchain_community.chat_models.ChatVertexAI") as mock_chat:
         mock_chat_instance = mock_chat.return_value
         mock_chat_instance.return_value = MagicMock(content="Test Response")