feat: Add LM Studio Model and Embeddings Component

src/backend/base/langflow/components/embeddings/LMStudioEmbeddings.py

@@ -0,0 +1,86 @@
+from typing import Any
+from urllib.parse import urljoin
+
+import httpx
+
+from langflow.base.embeddings.model import LCEmbeddingsModel
+from langflow.field_typing import Embeddings
+from langflow.inputs.inputs import DropdownInput, SecretStrInput
+from langflow.io import FloatInput, MessageTextInput
+
+
+class LMStudioEmbeddingsComponent(LCEmbeddingsModel):
+    display_name: str = "LM Studio Embeddings"
+    description: str = "Generate embeddings using LM Studio."
+    icon = "LMStudio"
+
+    def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):
+        if field_name == "model":
+            base_url_dict = build_config.get("base_url", {})
+            base_url_load_from_db = base_url_dict.get("load_from_db", False)
+            base_url_value = base_url_dict.get("value")
+            if base_url_load_from_db:
+                base_url_value = self.variables(base_url_value)
+            elif not base_url_value:
+                base_url_value = "http://localhost:1234/v1"
+            build_config["model"]["options"] = self.get_model(base_url_value)
+
+        return build_config
+
+    def get_model(self, base_url_value: str) -> list[str]:
+        try:
+            url = urljoin(base_url_value, "/v1/models")
+            with httpx.Client() as client:
+                response = client.get(url)
+                response.raise_for_status()
+                data = response.json()
+
+                return [model["id"] for model in data.get("data", [])]
+        except Exception as e:
+            msg = "Could not retrieve models. Please, make sure the LM Studio server is running."
+            raise ValueError(msg) from e
+
+    inputs = [
+        DropdownInput(
+            name="model",
+            display_name="Model",
+            advanced=False,
+            refresh_button=True,
+        ),
+        MessageTextInput(
+            name="base_url",
+            display_name="LM Studio Base URL",
+            refresh_button=True,
+            value="http://localhost:1234/v1",
+        ),
+        SecretStrInput(
+            name="api_key",
+            display_name="LM Studio API Key",
+            advanced=True,
+            value="LMSTUDIO_API_KEY",
+        ),
+        FloatInput(
+            name="temperature",
+            display_name="Model Temperature",
+            value=0.1,
+            advanced=True,
+        ),
+    ]
+
+    def build_embeddings(self) -> Embeddings:
+        try:
+            from langchain_nvidia_ai_endpoints import NVIDIAEmbeddings
+        except ImportError as e:
+            msg = "Please install langchain-nvidia-ai-endpoints to use LM Studio Embeddings."
+            raise ImportError(msg) from e
+        try:
+            output = NVIDIAEmbeddings(
+                model=self.model,
+                base_url=self.base_url,
+                temperature=self.temperature,
+                nvidia_api_key=self.api_key,
+            )  # type: ignore
+        except Exception as e:
+            msg = f"Could not connect to LM Studio API. Error: {e}"
+            raise ValueError(msg) from e
+        return output

src/backend/base/langflow/components/models/LMStudioModel.py

@@ -0,0 +1,169 @@
+import operator
+from functools import reduce
+from typing import Any
+from urllib.parse import urljoin
+
+import httpx
+from langchain_openai import ChatOpenAI
+from pydantic.v1 import SecretStr
+
+from langflow.base.models.model import LCModelComponent
+from langflow.field_typing import LanguageModel
+from langflow.field_typing.range_spec import RangeSpec
+from langflow.inputs import (
+    BoolInput,
+    DictInput,
+    DropdownInput,
+    FloatInput,
+    IntInput,
+    SecretStrInput,
+    StrInput,
+)
+from langflow.inputs.inputs import HandleInput
+
+
+class LMStudioModelComponent(LCModelComponent):
+    display_name = "LM Studio"
+    description = "Generate text using LM Studio Local LLMs."
+    icon = "LMStudio"
+    name = "LMStudioModel"
+
+    def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):
+        if field_name == "model_name":
+            base_url_dict = build_config.get("base_url", {})
+            base_url_load_from_db = base_url_dict.get("load_from_db", False)
+            base_url_value = base_url_dict.get("value")
+            if base_url_load_from_db:
+                base_url_value = self.variables(base_url_value)
+            elif not base_url_value:
+                base_url_value = "http://localhost:1234/v1"
+            build_config["model_name"]["options"] = self.get_model(base_url_value)
+
+        return build_config
+
+    def get_model(self, base_url_value: str) -> list[str]:
+        try:
+            url = urljoin(base_url_value, "/v1/models")
+            with httpx.Client() as client:
+                response = client.get(url)
+                response.raise_for_status()
+                data = response.json()
+
+                return [model["id"] for model in data.get("data", [])]
+        except Exception as e:
+            msg = "Could not retrieve models. Please, make sure the LM Studio server is running."
+            raise ValueError(msg) from e
+
+    inputs = [
+        *LCModelComponent._base_inputs,
+        IntInput(
+            name="max_tokens",
+            display_name="Max Tokens",
+            advanced=True,
+            info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
+            range_spec=RangeSpec(min=0, max=128000),
+        ),
+        DictInput(name="model_kwargs", display_name="Model Kwargs", advanced=True),
+        BoolInput(
+            name="json_mode",
+            display_name="JSON Mode",
+            advanced=True,
+            info="If True, it will output JSON regardless of passing a schema.",
+        ),
+        DictInput(
+            name="output_schema",
+            is_list=True,
+            display_name="Schema",
+            advanced=True,
+            info="The schema for the Output of the model. "
+            "You must pass the word JSON in the prompt. "
+            "If left blank, JSON mode will be disabled.",
+        ),
+        DropdownInput(
+            name="model_name",
+            display_name="Model Name",
+            advanced=False,
+            refresh_button=True,
+        ),
+        StrInput(
+            name="base_url",
+            display_name="Base URL",
+            advanced=False,
+            info="Endpoint of the LM Studio API. Defaults to 'http://localhost:1234/v1' if not specified.",
+            value="http://localhost:1234/v1",
+        ),
+        SecretStrInput(
+            name="api_key",
+            display_name="LM Studio API Key",
+            info="The LM Studio API Key to use for LM Studio.",
+            advanced=True,
+            value="LMSTUDIO_API_KEY",
+        ),
+        FloatInput(name="temperature", display_name="Temperature", value=0.1),
+        IntInput(
+            name="seed",
+            display_name="Seed",
+            info="The seed controls the reproducibility of the job.",
+            advanced=True,
+            value=1,
+        ),
+        HandleInput(
+            name="output_parser",
+            display_name="Output Parser",
+            info="The parser to use to parse the output of the model",
+            advanced=True,
+            input_types=["OutputParser"],
+        ),
+    ]
+
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
+        # self.output_schema is a list of dictionaries
+        # let's convert it to a dictionary
+        output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})
+        lmstudio_api_key = self.api_key
+        temperature = self.temperature
+        model_name: str = self.model_name
+        max_tokens = self.max_tokens
+        model_kwargs = self.model_kwargs or {}
+        base_url = self.base_url or "http://localhost:1234/v1"
+        json_mode = bool(output_schema_dict) or self.json_mode
+        seed = self.seed
+
+        api_key = SecretStr(lmstudio_api_key) if lmstudio_api_key else None
+        output = ChatOpenAI(
+            max_tokens=max_tokens or None,
+            model_kwargs=model_kwargs,
+            model=model_name,
+            base_url=base_url,
+            api_key=api_key,
+            temperature=temperature if temperature is not None else 0.1,
+            seed=seed,
+        )
+        if json_mode:
+            if output_schema_dict:
+                output = output.with_structured_output(schema=output_schema_dict, method="json_mode")  # type: ignore
+            else:
+                output = output.bind(response_format={"type": "json_object"})  # type: ignore
+
+        return output  # type: ignore
+
+    def _get_exception_message(self, e: Exception):
+        """
+        Get a message from an LM Studio exception.
+
+        Args:
+            exception (Exception): The exception to get the message from.
+
+        Returns:
+            str: The message from the exception.
+        """
+
+        try:
+            from openai import BadRequestError
+        except ImportError:
+            return None
+        if isinstance(e, BadRequestError):
+            message = e.body.get("message")  # type: ignore
+            if message:
+                return message
+        return None

src/frontend/src/icons/LMStudio/LMStudioIcon.jsx

@@ -0,0 +1,137 @@
+const SvgLMStudio = (props) => (
+  <svg
+    xmlns="http://www.w3.org/2000/svg"
+    width="2em"
+    height="2em"
+    viewBox="0 0 271.68 271.44"
+  >
+    <path
+      fill="#4b28be"
+      fillRule="evenodd"
+      stroke="#4b28be"
+      strokeLinecap="square"
+      strokeLinejoin="bevel"
+      strokeWidth="0.372"
+      d="M0 0H236.16V200.16H0z"
+      transform="translate(16.8 33.6)"
+    ></path>
+    <path
+      fill="#4b28be"
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+      fill="#585170"
+      stroke="#000"
+      strokeLinecap="square"
+      strokeLinejoin="bevel"
+      strokeOpacity="0"
+      strokeWidth="0"
+      d="M165.447 195.543c.513-.51 1.528-.706 2.27-1.126 7.12-4.03 7.847-12.683 1.912-18.34-1.145-1.091-2.462-2.003-3.788-3.095 1.158-.245 2.406-.528 3.651-.516 9.575.096 19.15.232 28.725.392 6.214.104 11.274 4.982 11.478 10.993.204 5.994-4.542 11.473-10.76 11.686-8.963.309-17.941.168-26.913.19-2.127.006-4.254-.1-6.575-.184z"
+    ></path>
+    <path
+      fill="#554e6e"
+      stroke="#000"
+      strokeLinecap="square"
+      strokeLinejoin="bevel"
+      strokeOpacity="0"
+      strokeWidth="0"
+      d="M199.894 226.142c.953-.887 2.079-1.702 3.164-2.569 5.843-4.668 5.685-13.162-.323-17.66-.585-.878-4.018-2.084-5.245-2.328 1.27-.34 5.356-.306 6.716-.295 9.105.07 18.208.227 27.312.383 4.682.08 8.447 1.853 10.526 6.248 1.886 3.985 1.454 7.922-.902 11.587-2.033 3.16-5.248 4.682-8.802 4.744-10.567.185-21.138.065-31.708.058-.195 0-.39-.078-.738-.168z"
+    ></path>
+  </svg>
+);
+export default SvgLMStudio;