feat: change params for models (#6992)

* feat: change advanced params for models

* [autofix.ci] apply automated fixes

* [autofix.ci] apply automated fixes (attempt 2/3)

* fix: ruff erros

* remove Redundant component

* refactor: streamline freeze-path test by removing redundant slider interactions and updating model selection

- Removed unnecessary wait for the default slider display value.
- Updated model selection to use 'gpt-4o-mini-0-option' for varied output in tests.

* [autofix.ci] apply automated fixes

* test: update slider component test to reflect new parameter values and structure

- Modified the test to replace a multiline string with updated values for the slider component.
- Ensured that the new code differs from the original to validate changes.
- Adjusted the test to fill the textarea with the new code after modification.

* ✅ (intComponent.spec.ts): update test assertions to match expected behavior for IntComponent regarding checkbox states

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Edwin Jose <edwin.jose@datastax.com>
Co-authored-by: italojohnny <italojohnnydosanjos@gmail.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>
Co-authored-by: cristhianzl <cristhian.lousa@gmail.com>

src/backend/base/langflow/base/models/model.py

@@ -33,7 +33,7 @@ class LCModelComponent(Component):
             info="System message to pass to the model.",
             advanced=False,
         ),
-        BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=False),
+        BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
     ]
 
     outputs = [

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

@@ -48,6 +48,7 @@ class AnthropicModelComponent(LCModelComponent):
             value=0.1,
             info="Run inference with this temperature. Must by in the closed interval [0.0, 1.0].",
             range_spec=RangeSpec(min=0, max=1, step=0.01),
+            advanced=True,
         ),
         MessageTextInput(
             name="base_url",

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

@@ -56,6 +56,7 @@ class AzureChatOpenAIComponent(LCModelComponent):
             value=0.7,
             range_spec=RangeSpec(min=0, max=2, step=0.01),
             info="Controls randomness. Lower values are more deterministic, higher values are more creative.",
+            advanced=True,
         ),
         IntInput(
             name="max_tokens",

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

@@ -30,6 +30,7 @@ class CohereComponent(LCModelComponent):
             value=0.75,
             range_spec=RangeSpec(min=0, max=2, step=0.01),
             info="Controls randomness. Lower values are more deterministic, higher values are more creative.",
+            advanced=True,
         ),
     ]
 

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

@@ -64,6 +64,7 @@ class DeepSeekModelComponent(LCModelComponent):
             info="Controls randomness in responses",
             value=1.0,
             range_spec=RangeSpec(min=0, max=2, step=0.01),
+            advanced=True,
         ),
         IntInput(
             name="seed",

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

@@ -6,7 +6,7 @@ from langflow.base.models.groq_constants import GROQ_MODELS
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
 from langflow.field_typing.range_spec import RangeSpec
-from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput, SliderInput
+from langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, SecretStrInput, SliderInput
 
 
 class GroqModel(LCModelComponent):
@@ -34,18 +34,13 @@ class GroqModel(LCModelComponent):
             info="The maximum number of tokens to generate.",
             advanced=True,
         ),
-        FloatInput(
-            name="temperature",
-            display_name="Temperature",
-            info="Run inference with this temperature. Must by in the closed interval [0.0, 1.0].",
-            value=0.1,
-        ),
         SliderInput(
             name="temperature",
             display_name="Temperature",
             value=0.1,
             info="Run inference with this temperature. Must by in the closed interval [0.0, 1.0].",
             range_spec=RangeSpec(min=0, max=1, step=0.01),
+            advanced=True,
         ),
         IntInput(
             name="n",

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

@@ -75,7 +75,12 @@ class LMStudioModelComponent(LCModelComponent):
             advanced=True,
             value="LMSTUDIO_API_KEY",
         ),
-        FloatInput(name="temperature", display_name="Temperature", value=0.1),
+        FloatInput(
+            name="temperature",
+            display_name="Temperature",
+            value=0.1,
+            advanced=True,
+        ),
         IntInput(
             name="seed",
             display_name="Seed",

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

@@ -52,8 +52,8 @@ class MistralAIModelComponent(LCModelComponent):
         FloatInput(
             name="temperature",
             display_name="Temperature",
-            advanced=False,
-            value=0.5,
+            value=0.1,
+            advanced=True,
         ),
         IntInput(
             name="max_retries",

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

@@ -60,6 +60,7 @@ class NVIDIAModelComponent(LCModelComponent):
             value=0.1,
             info="Run inference with this temperature. Must by in the closed interval [0.0, 1.0].",
             range_spec=RangeSpec(min=0, max=1, step=0.01),
+            advanced=True,
         ),
         IntInput(
             name="seed",

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

@@ -35,7 +35,11 @@ class ChatOllamaComponent(LCModelComponent):
             real_time_refresh=True,
         ),
         SliderInput(
-            name="temperature", display_name="Temperature", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)
+            name="temperature",
+            display_name="Temperature",
+            value=0.1,
+            range_spec=RangeSpec(min=0, max=1, step=0.01),
+            advanced=True,
         ),
         MessageTextInput(
             name="format", display_name="Format", info="Specify the format of the output (e.g., json).", advanced=True

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

@@ -60,7 +60,11 @@ class OpenAIModelComponent(LCModelComponent):
             required=True,
         ),
         SliderInput(
-            name="temperature", display_name="Temperature", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)
+            name="temperature",
+            display_name="Temperature",
+            value=0.1,
+            range_spec=RangeSpec(min=0, max=1, step=0.01),
+            advanced=True,
         ),
         IntInput(
             name="seed",

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

@@ -67,6 +67,7 @@ class OpenRouterComponent(LCModelComponent):
             value=0.7,
             range_spec=RangeSpec(min=0, max=2, step=0.01),
             info="Controls randomness. Lower values are more deterministic, higher values are more creative.",
+            advanced=True,
         ),
         IntInput(
             name="max_tokens",

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

@@ -56,7 +56,11 @@ class SambaNovaComponent(LCModelComponent):
             info="Model top_p",
         ),
         SliderInput(
-            name="temperature", display_name="Temperature", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)
+            name="temperature",
+            display_name="Temperature",
+            value=0.1,
+            range_spec=RangeSpec(min=0, max=2, step=0.01),
+            advanced=True,
         ),
     ]
 

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

@@ -64,7 +64,11 @@ class XAIModelComponent(LCModelComponent):
             required=True,
         ),
         SliderInput(
-            name="temperature", display_name="Temperature", value=0.1, range_spec=RangeSpec(min=0, max=2, step=0.01)
+            name="temperature",
+            display_name="Temperature",
+            value=0.1,
+            range_spec=RangeSpec(min=0, max=2, step=0.01),
+            advanced=True,
         ),
         IntInput(
             name="seed",

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json

@@ -1354,7 +1354,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1524,7 +1524,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1566,7 +1566,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",
@@ -1736,7 +1736,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1906,7 +1906,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1948,7 +1948,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",
@@ -2118,7 +2118,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -2288,7 +2288,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -2330,7 +2330,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json

@@ -974,7 +974,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1144,7 +1144,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1186,7 +1186,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json

@@ -1079,7 +1079,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1249,7 +1249,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1291,7 +1291,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json

@@ -1508,7 +1508,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1678,7 +1678,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1720,7 +1720,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Financial Report Parser.json

@@ -226,7 +226,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -396,7 +396,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -438,7 +438,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Graph Vector Store RAG.json

@@ -1804,7 +1804,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1960,7 +1960,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1998,7 +1998,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json

@@ -1438,7 +1438,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1608,7 +1608,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1650,7 +1650,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json

@@ -2716,7 +2716,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -2886,7 +2886,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -2928,7 +2928,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",
@@ -3098,7 +3098,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -3268,7 +3268,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -3310,7 +3310,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Market Research.json

@@ -2424,7 +2424,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -2594,7 +2594,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -2636,7 +2636,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Meeting Summary.json

@@ -705,7 +705,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -875,7 +875,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -917,7 +917,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",
@@ -1839,7 +1839,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -2009,7 +2009,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -2051,7 +2051,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json

@@ -1295,7 +1295,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1465,7 +1465,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1507,7 +1507,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json

@@ -2295,7 +2295,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -2465,7 +2465,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -2507,7 +2507,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",
@@ -2677,7 +2677,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -2847,7 +2847,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -2889,7 +2889,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json

@@ -960,7 +960,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -1130,7 +1130,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1172,7 +1172,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json

@@ -1896,7 +1896,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -2066,7 +2066,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -2108,7 +2108,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json

@@ -3019,7 +3019,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -3189,7 +3189,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -3231,7 +3231,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/backend/base/langflow/initial_setup/starter_projects/Youtube Analysis.json

@@ -815,7 +815,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\", display_name=\"Temperature\", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
+                "value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import OPENAI_MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\n\n\nclass OpenAIModelComponent(LCModelComponent):\n    display_name = \"OpenAI\"\n    description = \"Generates text using OpenAI LLMs.\"\n    icon = \"OpenAI\"\n    name = \"OpenAIModel\"\n\n    inputs = [\n        *LCModelComponent._base_inputs,\n        IntInput(\n            name=\"max_tokens\",\n            display_name=\"Max Tokens\",\n            advanced=True,\n            info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n            range_spec=RangeSpec(min=0, max=128000),\n        ),\n        DictInput(\n            name=\"model_kwargs\",\n            display_name=\"Model Kwargs\",\n            advanced=True,\n            info=\"Additional keyword arguments to pass to the model.\",\n        ),\n        BoolInput(\n            name=\"json_mode\",\n            display_name=\"JSON Mode\",\n            advanced=True,\n            info=\"If True, it will output JSON regardless of passing a schema.\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            advanced=False,\n            options=OPENAI_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n        ),\n        StrInput(\n            name=\"openai_api_base\",\n            display_name=\"OpenAI API Base\",\n            advanced=True,\n            info=\"The base URL of the OpenAI API. \"\n            \"Defaults to https://api.openai.com/v1. \"\n            \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n        ),\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"OpenAI API Key\",\n            info=\"The OpenAI API Key to use for the OpenAI model.\",\n            advanced=False,\n            value=\"OPENAI_API_KEY\",\n            required=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        IntInput(\n            name=\"seed\",\n            display_name=\"Seed\",\n            info=\"The seed controls the reproducibility of the job.\",\n            advanced=True,\n            value=1,\n        ),\n        IntInput(\n            name=\"max_retries\",\n            display_name=\"Max Retries\",\n            info=\"The maximum number of retries to make when generating.\",\n            advanced=True,\n            value=5,\n        ),\n        IntInput(\n            name=\"timeout\",\n            display_name=\"Timeout\",\n            info=\"The timeout for requests to OpenAI completion API.\",\n            advanced=True,\n            value=700,\n        ),\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        openai_api_key = self.api_key\n        temperature = self.temperature\n        model_name: str = self.model_name\n        max_tokens = self.max_tokens\n        model_kwargs = self.model_kwargs or {}\n        openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n        json_mode = self.json_mode\n        seed = self.seed\n        max_retries = self.max_retries\n        timeout = self.timeout\n\n        api_key = SecretStr(openai_api_key).get_secret_value() if openai_api_key else None\n        output = ChatOpenAI(\n            max_tokens=max_tokens or None,\n            model_kwargs=model_kwargs,\n            model=model_name,\n            base_url=openai_api_base,\n            api_key=api_key,\n            temperature=temperature if temperature is not None else 0.1,\n            seed=seed,\n            max_retries=max_retries,\n            request_timeout=timeout,\n        )\n        if json_mode:\n            output = output.bind(response_format={\"type\": \"json_object\"})\n\n        return output\n\n    def _get_exception_message(self, e: Exception):\n        \"\"\"Get a message from an OpenAI exception.\n\n        Args:\n            e (Exception): The exception to get the message from.\n\n        Returns:\n            str: The message from the exception.\n        \"\"\"\n        try:\n            from openai import BadRequestError\n        except ImportError:\n            return None\n        if isinstance(e, BadRequestError):\n            message = e.body.get(\"message\")\n            if message:\n                return message\n        return None\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",
@@ -985,7 +985,7 @@
               },
               "stream": {
                 "_input_type": "BoolInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Stream",
                 "dynamic": false,
                 "info": "Stream the response from the model. Streaming works only in Chat.",
@@ -1027,7 +1027,7 @@
               },
               "temperature": {
                 "_input_type": "SliderInput",
-                "advanced": false,
+                "advanced": true,
                 "display_name": "Temperature",
                 "dynamic": false,
                 "info": "",

src/frontend/tests/core/features/freeze-path.spec.ts

@@ -35,14 +35,7 @@ test(
     await page.getByTestId("dropdown_str_model_name").click();
     await page.getByTestId("gpt-4o-1-option").click();
 
-    await page.waitForSelector('[data-testid="default_slider_display_value"]', {
-      timeout: 1000,
-    });
-
     await page.getByTestId("fit_view").click();
-    await page
-      .getByTestId("default_slider_display_value")
-      .click({ force: true });
 
     await page.waitForSelector('[data-testid="button_run_chat output"]', {
       timeout: 1000,
@@ -68,11 +61,9 @@ test(
 
     await page.getByText("Close").last().click();
 
-    await page.waitForSelector('[data-testid="default_slider_display_value"]', {
-      timeout: 1000,
-    });
-
-    await moveSlider(page, "right", false);
+    // Change model to force different output
+    await page.getByTestId("dropdown_str_model_name").click();
+    await page.getByTestId("gpt-4o-mini-0-option").click();
 
     await page.waitForSelector('[data-testid="button_run_chat output"]', {
       timeout: 1000,

src/frontend/tests/core/unit/intComponent.spec.ts

@@ -90,7 +90,7 @@ test("IntComponent", { tag: ["@release", "@workspace"] }, async ({ page }) => {
   await page.locator('//*[@id="showtemperature"]').click();
   expect(
     await page.locator('//*[@id="showtemperature"]').isChecked(),
-  ).toBeFalsy();
+  ).toBeTruthy();
 
   await page.locator('//*[@id="showmodel_kwargs"]').click();
   expect(
@@ -110,7 +110,7 @@ test("IntComponent", { tag: ["@release", "@workspace"] }, async ({ page }) => {
   await page.locator('//*[@id="showtemperature"]').click();
   expect(
     await page.locator('//*[@id="showtemperature"]').isChecked(),
-  ).toBeTruthy();
+  ).toBeFalsy();
 
   await page.locator('//*[@id="showmodel_kwargs"]').click();
   expect(
@@ -130,7 +130,7 @@ test("IntComponent", { tag: ["@release", "@workspace"] }, async ({ page }) => {
   await page.locator('//*[@id="showtemperature"]').click();
   expect(
     await page.locator('//*[@id="showtemperature"]').isChecked(),
-  ).toBeFalsy();
+  ).toBeTruthy();
 
   await page.getByText("Close").last().click();
 

src/frontend/tests/core/unit/sliderComponent.spec.ts

@@ -35,15 +35,31 @@ test(
 
     let cleanCode = await extractAndCleanCode(page);
 
-    // Replace the import statement
-    cleanCode = cleanCode.replace(
-      'name="temperature", display_name="Temperature", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)',
-      'name="temperature", display_name="Temperature", value=0.2, range_spec=RangeSpec(min=3, max=30, step=1), min_label="test", max_label="test2", min_label_icon="pencil-ruler", max_label_icon="palette", slider_buttons=False, slider_buttons_options=[], slider_input=False,',
+    // Replace the multiline string in the code
+    const newCode = cleanCode.replace(
+      `name="temperature",
+            display_name="Temperature",
+            value=0.1,
+            range_spec=RangeSpec(min=0, max=1, step=0.01),
+            advanced=True,`,
+      `name="temperature",
+            display_name="Temperature",
+            value=0.2,
+            range_spec=RangeSpec(min=3, max=30, step=1),
+            min_label="test",
+            max_label="test2",
+            min_label_icon="pencil-ruler",
+            max_label_icon="palette",
+            slider_buttons=False,
+            slider_buttons_options=[],
+            slider_input=False,
+            advanced=False,`,
     );
-
+    // make sure codes are different
+    expect(cleanCode).not.toEqual(newCode);
     await page.locator("textarea").last().press(`ControlOrMeta+a`);
     await page.keyboard.press("Backspace");
-    await page.locator("textarea").last().fill(cleanCode);
+    await page.locator("textarea").last().fill(newCode);
     await page.locator('//*[@id="checkAndSaveBtn"]').click();
 
     await page.getByTestId("fit_view").click();