more ignore deps

llama-index-core/llama_index/core/agent/runner/base.py

@@ -253,16 +253,18 @@ def from_llm(
             )
 
         try:
-            from llama_index.llms.openai import OpenAI
-            from llama_index.llms.openai.utils import is_function_calling_model
+            from llama_index.llms.openai import OpenAI  # pants: no-infer-dep
+            from llama_index.llms.openai.utils import (
+                is_function_calling_model,
+            )  # pants: no-infer-dep
         except ImportError:
             raise ImportError(
                 "`llama-index-llms-openai` package not found. Please "
                 "install by running `pip install llama-index-llms-openai`."
             )
 
         if isinstance(llm, OpenAI) and is_function_calling_model(llm.model):
-            from llama_index.agent.openai import OpenAIAgent
+            from llama_index.agent.openai import OpenAIAgent  # pants: no-infer-dep
 
             return OpenAIAgent.from_tools(
                 tools=tools,

llama-index-core/llama_index/core/command_line/command_line.py

@@ -99,7 +99,7 @@ def default_rag_cli() -> RagCLI:
 
         from llama_index.vector_stores.chroma import (
             ChromaVectorStore,
-        )
+        )  # pants: no-infer-dep
     except ImportError:
         ChromaVectorStore = None
 

llama-index-core/llama_index/core/ingestion/api_utils.py

@@ -30,7 +30,7 @@
 
 def default_transformations() -> List[TransformComponent]:
     """Default transformations."""
-    from llama_index.embeddings.openai import OpenAIEmbedding
+    from llama_index.embeddings.openai import OpenAIEmbedding  # pants: no-infer-dep
 
     return [
         SentenceSplitter(),

llama-index-core/llama_index/core/ingestion/transformations.py

@@ -255,7 +255,7 @@ def build_configured_transformation(
 
     # Embeddings
     try:
-        from llama_index.embeddings.openai import OpenAIEmbedding
+        from llama_index.embeddings.openai import OpenAIEmbedding  # pants: no-infer-dep
 
         enum_members.append(
             (

llama-index-core/llama_index/core/program/utils.py

@@ -70,7 +70,9 @@ def get_program_for_llm(
                 **kwargs,
             )
     elif pydantic_program_mode == PydanticProgramMode.OPENAI:
-        from llama_index.core.program.openai_program import OpenAIPydanticProgram
+        from llama_index.program.openai import (
+            OpenAIPydanticProgram,
+        )  # pants: no-infer-dep
 
         return OpenAIPydanticProgram.from_defaults(
             output_cls=output_cls,

llama-index-core/llama_index/core/prompts/base.py

@@ -451,7 +451,7 @@ def partial_format(self, **kwargs: Any) -> "BasePromptTemplate":
 
     def format(self, llm: Optional[BaseLLM] = None, **kwargs: Any) -> str:
         """Format the prompt into a string."""
-        from llama_index.llms.langchain import LangChainLLM
+        from llama_index.llms.langchain import LangChainLLM  # pants: no-infer-dep
 
         if llm is not None:
             # if llamaindex LLM is provided, and we require a langchain LLM,
@@ -474,8 +474,10 @@ def format_messages(
         self, llm: Optional[BaseLLM] = None, **kwargs: Any
     ) -> List[ChatMessage]:
         """Format the prompt into a list of chat messages."""
-        from llama_index.llms.langchain import LangChainLLM
-        from llama_index.llms.langchain.utils import from_lc_messages
+        from llama_index.llms.langchain import LangChainLLM  # pants: no-infer-dep
+        from llama_index.llms.langchain.utils import (
+            from_lc_messages,
+        )  # pants: no-infer-dep
 
         if llm is not None:
             # if llamaindex LLM is provided, and we require a langchain LLM,
@@ -497,7 +499,7 @@ def format_messages(
         return from_lc_messages(lc_messages)
 
     def get_template(self, llm: Optional[BaseLLM] = None) -> str:
-        from llama_index.llms.langchain import LangChainLLM
+        from llama_index.llms.langchain import LangChainLLM  # pants: no-infer-dep
 
         if llm is not None:
             # if llamaindex LLM is provided, and we require a langchain LLM,

llama-index-core/tests/embeddings/todo_hf_test_utils.py

@@ -0,0 +1,56 @@
+from typing import Any, Dict
+
+# pants: no-infer-dep
+from llama_index.core.embeddings.mock_embed_model import MockEmbedding
+from llama_index.core.embeddings.utils import resolve_embed_model
+from llama_index.embeddings.huggingface import (
+    HuggingFaceEmbedding,
+)  # pants: no-infer-dep
+from llama_index.embeddings.openai import OpenAIEmbedding  # pants: no-infer-dep
+from pytest import MonkeyPatch
+
+
+def mock_hf_embeddings(self: Any, *args: Any, **kwargs: Dict[str, Any]) -> Any:
+    """Mock HuggingFaceEmbeddings."""
+    super(HuggingFaceEmbedding, self).__init__(
+        model_name="fake",
+        tokenizer_name="fake",
+        model="fake",
+        tokenizer="fake",
+    )
+    return
+
+
+def mock_openai_embeddings(self: Any, *args: Any, **kwargs: Dict[str, Any]) -> Any:
+    """Mock OpenAIEmbedding."""
+    super(OpenAIEmbedding, self).__init__(
+        api_key="fake", api_base="fake", api_version="fake"
+    )
+    return
+
+
+def test_resolve_embed_model(monkeypatch: MonkeyPatch) -> None:
+    monkeypatch.setattr(
+        "llama_index.embeddings.huggingface.HuggingFaceEmbedding.__init__",
+        mock_hf_embeddings,
+    )
+    monkeypatch.setattr(
+        "llama_index.embeddings.openai.OpenAIEmbedding.__init__",
+        mock_openai_embeddings,
+    )
+
+    # Test None
+    embed_model = resolve_embed_model(None)
+    assert isinstance(embed_model, MockEmbedding)
+
+    # Test str
+    embed_model = resolve_embed_model("local")
+    assert isinstance(embed_model, HuggingFaceEmbedding)
+
+    # Test LCEmbeddings
+    embed_model = resolve_embed_model(HuggingFaceEmbedding())
+    assert isinstance(embed_model, HuggingFaceEmbedding)
+
+    # Test BaseEmbedding
+    embed_model = resolve_embed_model(OpenAIEmbedding())
+    assert isinstance(embed_model, OpenAIEmbedding)