fix: update import paths for input components in multiple starter pro…

…ject JSON files

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

@@ -981,7 +981,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from typing import Any\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import (\n    OPENAI_MODEL_NAMES,\n    OPENAI_REASONING_MODEL_NAMES,\n)\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\nfrom langflow.logging import logger\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 + OPENAI_REASONING_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n            real_time_refresh=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            show=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        parameters = {\n            \"api_key\": SecretStr(self.api_key).get_secret_value() if self.api_key else None,\n            \"model_name\": self.model_name,\n            \"max_tokens\": self.max_tokens or None,\n            \"model_kwargs\": self.model_kwargs or {},\n            \"base_url\": self.openai_api_base or \"https://api.openai.com/v1\",\n            \"max_retries\": self.max_retries,\n            \"timeout\": self.timeout,\n        }\n\n        logger.info(f\"Model name: {self.model_name}\")\n        if self.model_name not in OPENAI_REASONING_MODEL_NAMES:\n            parameters[\"temperature\"] = self.temperature if self.temperature is not None else 0.1\n            parameters[\"seed\"] = self.seed\n\n        output = ChatOpenAI(**parameters)\n        if self.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\n    def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None) -> dict:\n        if field_name in {\"base_url\", \"model_name\", \"api_key\"} and field_value in OPENAI_REASONING_MODEL_NAMES:\n            build_config[\"temperature\"][\"show\"] = False\n            build_config[\"seed\"][\"show\"] = False\n        if field_name in {\"base_url\", \"model_name\", \"api_key\"} and field_value in OPENAI_MODEL_NAMES:\n            build_config[\"temperature\"][\"show\"] = True\n            build_config[\"seed\"][\"show\"] = True\n        return build_config\n"
+                "value": "from typing import Any\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import (\n    OPENAI_MODEL_NAMES,\n    OPENAI_REASONING_MODEL_NAMES,\n)\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.inputs.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput\nfrom langflow.logging import logger\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 + OPENAI_REASONING_MODEL_NAMES,\n            value=OPENAI_MODEL_NAMES[1],\n            combobox=True,\n            real_time_refresh=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            show=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        parameters = {\n            \"api_key\": SecretStr(self.api_key).get_secret_value() if self.api_key else None,\n            \"model_name\": self.model_name,\n            \"max_tokens\": self.max_tokens or None,\n            \"model_kwargs\": self.model_kwargs or {},\n            \"base_url\": self.openai_api_base or \"https://api.openai.com/v1\",\n            \"max_retries\": self.max_retries,\n            \"timeout\": self.timeout,\n        }\n\n        logger.info(f\"Model name: {self.model_name}\")\n        if self.model_name not in OPENAI_REASONING_MODEL_NAMES:\n            parameters[\"temperature\"] = self.temperature if self.temperature is not None else 0.1\n            parameters[\"seed\"] = self.seed\n\n        output = ChatOpenAI(**parameters)\n        if self.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\n    def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None) -> dict:\n        if field_name in {\"base_url\", \"model_name\", \"api_key\"} and field_value in OPENAI_REASONING_MODEL_NAMES:\n            build_config[\"temperature\"][\"show\"] = False\n            build_config[\"seed\"][\"show\"] = False\n        if field_name in {\"base_url\", \"model_name\", \"api_key\"} and field_value in OPENAI_MODEL_NAMES:\n            build_config[\"temperature\"][\"show\"] = True\n            build_config[\"seed\"][\"show\"] = True\n        return build_config\n"
               },
               "input_value": {
                 "_input_type": "MessageInput",