add unit-tests back by mocking build_client

libs/community/langchain_community/chat_models/outlines.py

@@ -199,17 +199,6 @@ class ChatOutlines(BaseChatModel):
     @model_validator(mode="after")
     def validate_environment(self) -> "ChatOutlines":
         """Validate that outlines is installed and create a model instance."""
-        try:
-            import outlines.models as models
-        except ImportError:
-            raise ImportError(
-                "Could not import the Outlines library. "
-                "Please install it with `pip install outlines`."
-            )
-
-        model: str = self.model
-        backend: str = self.backend
-
         num_constraints = sum(
             [
                 bool(self.regex),
@@ -223,6 +212,16 @@ def validate_environment(self) -> "ChatOutlines":
                 "Either none or exactly one of regex, type_constraints, "
                 "json_schema, or grammar can be provided."
             )
+        return self.build_client()
+
+    def build_client(self) -> "ChatOutlines":
+        try:
+            import outlines.models as models
+        except ImportError:
+            raise ImportError(
+                "Could not import the Outlines library. "
+                "Please install it with `pip install outlines`."
+            )
 
         def check_packages_installed(
             packages: List[Union[str, Tuple[str, str]]],
@@ -240,38 +239,40 @@ def check_packages_installed(
                     f"    pip install {' '.join(missing_packages)}"
                 )
 
-        if backend == "llamacpp":
+        if self.backend == "llamacpp":
             check_packages_installed([("llama-cpp-python", "llama_cpp")])
-            if ".gguf" in model:
-                creator, repo_name, file_name = model.split("/", 2)
+            if ".gguf" in self.model:
+                creator, repo_name, file_name = self.model.split("/", 2)
                 repo_id = f"{creator}/{repo_name}"
             else:
                 raise ValueError("GGUF file_name must be provided for llama.cpp.")
             self.client = models.llamacpp(repo_id, file_name, **self.model_kwargs)
-        elif backend == "transformers":
+        elif self.backend == "transformers":
             check_packages_installed(["transformers", "torch", "datasets"])
-            self.client = models.transformers(model_name=model, **self.model_kwargs)
-        elif backend == "transformers_vision":
+            self.client = models.transformers(
+                model_name=self.model, **self.model_kwargs
+            )
+        elif self.backend == "transformers_vision":
             if hasattr(models, "transformers_vision"):
                 from transformers import LlavaNextForConditionalGeneration
 
                 self.client = models.transformers_vision(
-                    model,
+                    self.model,
                     model_class=LlavaNextForConditionalGeneration,
                     **self.model_kwargs,
                 )
             else:
                 raise ValueError("transformers_vision backend is not supported")
-        elif backend == "vllm":
+        elif self.backend == "vllm":
             if platform.system() == "Darwin":
                 raise ValueError("vLLM backend is not supported on macOS.")
             check_packages_installed(["vllm"])
-            self.client = models.vllm(model, **self.model_kwargs)
-        elif backend == "mlxlm":
+            self.client = models.vllm(self.model, **self.model_kwargs)
+        elif self.backend == "mlxlm":
             check_packages_installed(["mlx"])
-            self.client = models.mlxlm(model, **self.model_kwargs)
+            self.client = models.mlxlm(self.model, **self.model_kwargs)
         else:
-            raise ValueError(f"Unsupported backend: {backend}")
+            raise ValueError(f"Unsupported backend: {self.backend}")
         return self
 
     @property

libs/community/langchain_community/llms/outlines.py

@@ -142,17 +142,6 @@ class Outlines(LLM):
     @model_validator(mode="after")
     def validate_environment(self) -> "Outlines":
         """Validate that outlines is installed and create a model instance."""
-        try:
-            import outlines.models as models
-        except ImportError:
-            raise ImportError(
-                "Could not import the Outlines library. "
-                "Please install it with `pip install outlines`."
-            )
-
-        model: str = self.model
-        backend: str = self.backend
-
         num_constraints = sum(
             [
                 bool(self.regex),
@@ -166,6 +155,16 @@ def validate_environment(self) -> "Outlines":
                 "Either none or exactly one of regex, type_constraints, "
                 "json_schema, or grammar can be provided."
             )
+        return self.build_client()
+
+    def build_client(self) -> "Outlines":
+        try:
+            import outlines.models as models
+        except ImportError:
+            raise ImportError(
+                "Could not import the Outlines library. "
+                "Please install it with `pip install outlines`."
+            )
 
         def check_packages_installed(
             packages: List[Union[str, Tuple[str, str]]],
@@ -183,18 +182,18 @@ def check_packages_installed(
                     f"    pip install {' '.join(missing_packages)}"
                 )
 
-        if backend == "llamacpp":
-            if ".gguf" in model:
-                creator, repo_name, file_name = model.split("/", 2)
+        if self.backend == "llamacpp":
+            if ".gguf" in self.model:
+                creator, repo_name, file_name = self.model.split("/", 2)
                 repo_id = f"{creator}/{repo_name}"
             else:  # todo add auto-file-selection if no file is given
                 raise ValueError("GGUF file_name must be provided for llama.cpp.")
             check_packages_installed([("llama-cpp-python", "llama_cpp")])
             self.client = models.llamacpp(repo_id, file_name, **self.model_kwargs)
-        elif backend == "transformers":
+        elif self.backend == "transformers":
             check_packages_installed(["transformers", "torch", "datasets"])
-            self.client = models.transformers(model, **self.model_kwargs)
-        elif backend == "transformers_vision":
+            self.client = models.transformers(self.model, **self.model_kwargs)
+        elif self.backend == "transformers_vision":
             check_packages_installed(
                 ["transformers", "datasets", "torchvision", "PIL", "flash_attn"]
             )
@@ -206,22 +205,20 @@ def check_packages_installed(
                     "please install the correct outlines version."
                 )
             self.client = models.transformers_vision(
-                model,
+                self.model,
                 model_class=LlavaNextForConditionalGeneration,
                 **self.model_kwargs,
             )
-        elif backend == "vllm":
+        elif self.backend == "vllm":
             if platform.system() == "Darwin":
                 raise ValueError("vLLM backend is not supported on macOS.")
             check_packages_installed(["vllm"])
-            self.client = models.vllm(model, **self.model_kwargs)
-        elif backend == "mlxlm":
+            self.client = models.vllm(self.model, **self.model_kwargs)
+        elif self.backend == "mlxlm":
             check_packages_installed(["mlx"])
-            self.client = models.mlxlm(model, **self.model_kwargs)
+            self.client = models.mlxlm(self.model, **self.model_kwargs)
         else:
-            raise ValueError(f"Unsupported backend: {backend}")
-
-        return self
+            raise ValueError(f"Unsupported backend: {self.backend}")
 
     @property
     def _llm_type(self) -> str:

libs/community/tests/unit_tests/chat_models/test_outlines.py

@@ -0,0 +1,90 @@
+import pytest
+from pydantic import BaseModel, Field
+
+from langchain_community.chat_models.outlines import ChatOutlines
+
+
+def test_chat_outlines_initialization(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+
+    chat = ChatOutlines(
+        model="microsoft/Phi-3-mini-4k-instruct",
+        max_tokens=42,
+        stop=["\n"],
+    )
+    assert chat.model == "microsoft/Phi-3-mini-4k-instruct"
+    assert chat.max_tokens == 42
+    assert chat.backend == "transformers"
+    assert chat.stop == ["\n"]
+
+
+def test_chat_outlines_backend_llamacpp(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+    chat = ChatOutlines(
+        model="TheBloke/Llama-2-7B-Chat-GGUF/llama-2-7b-chat.Q4_K_M.gguf",
+        backend="llamacpp",
+    )
+    assert chat.backend == "llamacpp"
+
+
+def test_chat_outlines_backend_vllm(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+    chat = ChatOutlines(model="microsoft/Phi-3-mini-4k-instruct", backend="vllm")
+    assert chat.backend == "vllm"
+
+
+def test_chat_outlines_backend_mlxlm(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+    chat = ChatOutlines(model="microsoft/Phi-3-mini-4k-instruct", backend="mlxlm")
+    assert chat.backend == "mlxlm"
+
+
+def test_chat_outlines_with_regex(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+    regex = r"\d{3}-\d{3}-\d{4}"
+    chat = ChatOutlines(model="microsoft/Phi-3-mini-4k-instruct", regex=regex)
+    assert chat.regex == regex
+
+
+def test_chat_outlines_with_type_constraints(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+    chat = ChatOutlines(model="microsoft/Phi-3-mini-4k-instruct", type_constraints=int)
+    assert chat.type_constraints == int  # noqa
+
+
+def test_chat_outlines_with_json_schema(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+
+    class TestSchema(BaseModel):
+        name: str = Field(description="A person's name")
+        age: int = Field(description="A person's age")
+
+    chat = ChatOutlines(
+        model="microsoft/Phi-3-mini-4k-instruct", json_schema=TestSchema
+    )
+    assert chat.json_schema == TestSchema
+
+
+def test_chat_outlines_with_grammar(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+
+    grammar = """
+?start: expression
+?expression: term (("+" | "-") term)*
+?term: factor (("*" | "/") factor)*
+?factor: NUMBER | "-" factor | "(" expression ")"
+%import common.NUMBER
+    """
+    chat = ChatOutlines(model="microsoft/Phi-3-mini-4k-instruct", grammar=grammar)
+    assert chat.grammar == grammar
+
+
+def test_raise_for_multiple_output_constraints(monkeypatch):
+    monkeypatch.setattr(ChatOutlines, "build_client", lambda self: self)
+
+    with pytest.raises(ValueError):
+        ChatOutlines(
+            model="microsoft/Phi-3-mini-4k-instruct",
+            type_constraints=int,
+            regex=r"\d{3}-\d{3}-\d{4}",
+        )

libs/community/tests/unit_tests/llms/test_outlines.py

@@ -0,0 +1,91 @@
+import pytest
+
+from langchain_community.llms.outlines import Outlines
+
+
+def test_outlines_initialization(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+
+    llm = Outlines(
+        model="microsoft/Phi-3-mini-4k-instruct",
+        max_tokens=42,
+        stop=["\n"],
+    )
+    assert llm.model == "microsoft/Phi-3-mini-4k-instruct"
+    assert llm.max_tokens == 42
+    assert llm.backend == "transformers"
+    assert llm.stop == ["\n"]
+
+
+def test_outlines_backend_llamacpp(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+    llm = Outlines(
+        model="TheBloke/Llama-2-7B-Chat-GGUF/llama-2-7b-chat.Q4_K_M.gguf",
+        backend="llamacpp",
+    )
+    assert llm.backend == "llamacpp"
+
+
+def test_outlines_backend_vllm(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+    llm = Outlines(model="microsoft/Phi-3-mini-4k-instruct", backend="vllm")
+    assert llm.backend == "vllm"
+
+
+def test_outlines_backend_mlxlm(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+    llm = Outlines(model="microsoft/Phi-3-mini-4k-instruct", backend="mlxlm")
+    assert llm.backend == "mlxlm"
+
+
+def test_outlines_with_regex(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+    regex = r"\d{3}-\d{3}-\d{4}"
+    llm = Outlines(model="microsoft/Phi-3-mini-4k-instruct", regex=regex)
+    assert llm.regex == regex
+
+
+def test_outlines_with_type_constraints(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+    llm = Outlines(model="microsoft/Phi-3-mini-4k-instruct", type_constraints=int)
+    assert llm.type_constraints == int  # noqa
+
+
+def test_outlines_with_json_schema(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+    from pydantic import BaseModel, Field
+
+    class TestSchema(BaseModel):
+        name: str = Field(description="A person's name")
+        age: int = Field(description="A person's age")
+
+    llm = Outlines(model="microsoft/Phi-3-mini-4k-instruct", json_schema=TestSchema)
+    assert llm.json_schema == TestSchema
+
+
+def test_outlines_with_grammar(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+    grammar = """
+    ?start: expression
+    ?expression: term (("+" | "-") term)*
+    ?term: factor (("*" | "/") factor)*
+    ?factor: NUMBER | "-" factor | "(" expression ")"
+    %import common.NUMBER
+    """
+    llm = Outlines(model="microsoft/Phi-3-mini-4k-instruct", grammar=grammar)
+    assert llm.grammar == grammar
+
+
+def test_raise_for_multiple_output_constraints(monkeypatch):
+    monkeypatch.setattr(Outlines, "build_client", lambda self: self)
+    with pytest.raises(ValueError):
+        Outlines(
+            model="microsoft/Phi-3-mini-4k-instruct",
+            type_constraints=int,
+            regex=r"\d{3}-\d{3}-\d{4}",
+        )
+        Outlines(
+            model="microsoft/Phi-3-mini-4k-instruct",
+            type_constraints=int,
+            regex=r"\d{3}-\d{3}-\d{4}",
+        )