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from typing import Any import requests from langchain_anthropic import ChatAnthropic from langchain_ibm import ChatWatsonx from langchain_ollama import ChatOllama from langchain_openai import ChatOpenAI from pydantic.v1 import SecretStr from lfx.base.models.anthropic_constants import ANTHROPIC_MODELS from lfx.base.models.google_generative_ai_constants import GOOGLE_GENERATIVE_AI_MODELS from lfx.base.models.google_generative_ai_model import ChatGoogleGenerativeAIFixed from lfx.base.models.model import LCModelComponent from lfx.base.models.model_utils import get_ollama_models, is_valid_ollama_url from lfx.base.models.openai_constants import OPENAI_CHAT_MODEL_NAMES, OPENAI_REASONING_MODEL_NAMES from lfx.field_typing import LanguageModel from lfx.field_typing.range_spec import RangeSpec from lfx.inputs.inputs import BoolInput, MessageTextInput, StrInput from lfx.io import DropdownInput, MessageInput, MultilineInput, SecretStrInput, SliderInput from lfx.log.logger import logger from lfx.schema.dotdict import dotdict from lfx.utils.util import transform_localhost_url # IBM watsonx.ai constants IBM_WATSONX_DEFAULT_MODELS = ["ibm/granite-3-2b-instruct", "ibm/granite-3-8b-instruct", "ibm/granite-13b-instruct-v2"] IBM_WATSONX_URLS = [ "https://us-south.ml.cloud.ibm.com", "https://eu-de.ml.cloud.ibm.com", "https://eu-gb.ml.cloud.ibm.com", "https://au-syd.ml.cloud.ibm.com", "https://jp-tok.ml.cloud.ibm.com", "https://ca-tor.ml.cloud.ibm.com", ] # Ollama API constants HTTP_STATUS_OK = 200 JSON_MODELS_KEY = "models" JSON_NAME_KEY = "name" JSON_CAPABILITIES_KEY = "capabilities" DESIRED_CAPABILITY = "completion" DEFAULT_OLLAMA_URL = "http://localhost:11434" class LanguageModelComponent(LCModelComponent): display_name = "Language Model" description = "Runs a language model given a specified provider." documentation: str = "https://docs.langflow.org/components-models" icon = "brain-circuit" category = "models" priority = 0 # Set priority to 0 to make it appear first @staticmethod def fetch_ibm_models(base_url: str) -> list[str]: """Fetch available models from the watsonx.ai API.""" try: endpoint = f"{base_url}/ml/v1/foundation_model_specs" params = {"version": "2024-09-16", "filters": "function_text_chat,!lifecycle_withdrawn"} response = requests.get(endpoint, params=params, timeout=10) response.raise_for_status() data = response.json() models = [model["model_id"] for model in data.get("resources", [])] return sorted(models) except Exception: # noqa: BLE001 logger.exception("Error fetching IBM watsonx models. Using default models.") return IBM_WATSONX_DEFAULT_MODELS inputs = [ DropdownInput( name="provider", display_name="Model Provider", options=["OpenAI", "Anthropic", "Google", "IBM watsonx.ai", "Ollama", "OpenAI Compatible"], value="OpenAI", info="Select the model provider", real_time_refresh=True, options_metadata=[ {"icon": "OpenAI"}, {"icon": "Anthropic"}, {"icon": "GoogleGenerativeAI"}, {"icon": "WatsonxAI"}, {"icon": "Ollama"}, {"icon": "OpenAI"}, ], ), DropdownInput( name="model_name", display_name="Model Name", options=OPENAI_CHAT_MODEL_NAMES + OPENAI_REASONING_MODEL_NAMES, value=OPENAI_CHAT_MODEL_NAMES[0], info="Select the model to use", real_time_refresh=True, refresh_button=True, ), SecretStrInput( name="api_key", display_name="OpenAI API Key", info="Model Provider API key", required=False, show=True, real_time_refresh=True, ), DropdownInput( name="base_url_ibm_watsonx", display_name="watsonx API Endpoint", info="The base URL of the API (IBM watsonx.ai only)", options=IBM_WATSONX_URLS, value=IBM_WATSONX_URLS[0], show=False, real_time_refresh=True, ), StrInput( name="base_url", display_name="API Base URL", value="https://api.openai.com/v1", show=False, required=False, ), StrInput( name="project_id", display_name="watsonx Project ID", info="The project ID associated with the foundation model (IBM watsonx.ai only)", show=False, required=False, ), MessageTextInput( name="ollama_base_url", display_name="Ollama API URL", info=f"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}", value=DEFAULT_OLLAMA_URL, show=False, real_time_refresh=True, load_from_db=True, ), MessageInput( name="input_value", display_name="Input", info="The input text to send to the model", ), MultilineInput( name="system_message", display_name="System Message", info="A system message that helps set the behavior of the assistant", advanced=False, ), BoolInput( name="stream", display_name="Stream", info="Whether to stream the response", value=False, advanced=True, ), SliderInput( name="temperature", display_name="Temperature", value=0.1, info="Controls randomness in responses", range_spec=RangeSpec(min=0, max=1, step=0.01), advanced=True, ), ] def build_model(self) -> LanguageModel: provider = self.provider model_name = self.model_name temperature = self.temperature stream = self.stream if provider == "OpenAI": if not self.api_key: msg = "OpenAI API key is required when using OpenAI provider" raise ValueError(msg) if model_name in OPENAI_REASONING_MODEL_NAMES: # reasoning models do not support temperature (yet) temperature = None return ChatOpenAI( model_name=model_name, temperature=temperature, streaming=stream, openai_api_key=self.api_key, ) if provider == "Anthropic": if not self.api_key: msg = "Anthropic API key is required when using Anthropic provider" raise ValueError(msg) return ChatAnthropic( model=model_name, temperature=temperature, streaming=stream, anthropic_api_key=self.api_key, ) if provider == "Google": if not self.api_key: msg = "Google API key is required when using Google provider" raise ValueError(msg) return ChatGoogleGenerativeAIFixed( model=model_name, temperature=temperature, streaming=stream, google_api_key=self.api_key, ) if provider == "IBM watsonx.ai": if not self.api_key: msg = "IBM API key is required when using IBM watsonx.ai provider" raise ValueError(msg) if not self.base_url_ibm_watsonx: msg = "IBM watsonx API Endpoint is required when using IBM watsonx.ai provider" raise ValueError(msg) if not self.project_id: msg = "IBM watsonx Project ID is required when using IBM watsonx.ai provider" raise ValueError(msg) return ChatWatsonx( apikey=SecretStr(self.api_key).get_secret_value(), url=self.base_url_ibm_watsonx, project_id=self.project_id, model_id=model_name, params={ "temperature": temperature, }, streaming=stream, ) if provider == "Ollama": if not self.ollama_base_url: msg = "Ollama API URL is required when using Ollama provider" raise ValueError(msg) if not model_name: msg = "Model name is required when using Ollama provider" raise ValueError(msg) transformed_base_url = transform_localhost_url(self.ollama_base_url) # Check if URL contains /v1 suffix (OpenAI-compatible mode) if transformed_base_url and transformed_base_url.rstrip("/").endswith("/v1"): # Strip /v1 suffix and log warning transformed_base_url = transformed_base_url.rstrip("/").removesuffix("/v1") logger.warning( "Detected '/v1' suffix in base URL. The Ollama component uses the native Ollama API, " "not the OpenAI-compatible API. The '/v1' suffix has been automatically removed. " "If you want to use the OpenAI-compatible API, please use the OpenAI component instead. " "Learn more at https://docs.ollama.com/openai#openai-compatibility" ) return ChatOllama( base_url=transformed_base_url, model=model_name, temperature=temperature, ) if provider == "OpenAI Compatible": return ChatOpenAI( model_name=model_name, temperature=temperature, streaming=stream, openai_api_key=self.api_key or "dummy", openai_api_base=self.base_url, ) msg = f"Unknown provider: {provider}" raise ValueError(msg) async def update_build_config( self, build_config: dotdict, field_value: Any, field_name: str | None = None ) -> dotdict: if field_name == "provider": if field_value == "OpenAI": build_config["model_name"]["options"] = OPENAI_CHAT_MODEL_NAMES + OPENAI_REASONING_MODEL_NAMES build_config["model_name"]["value"] = OPENAI_CHAT_MODEL_NAMES[0] build_config["api_key"]["display_name"] = "OpenAI API Key" build_config["api_key"]["show"] = True build_config["base_url"]["show"] = False build_config["base_url_ibm_watsonx"]["show"] = False build_config["project_id"]["show"] = False build_config["ollama_base_url"]["show"] = False elif field_value == "Anthropic": build_config["model_name"]["options"] = ANTHROPIC_MODELS build_config["model_name"]["value"] = ANTHROPIC_MODELS[0] build_config["api_key"]["display_name"] = "Anthropic API Key" build_config["api_key"]["show"] = True build_config["base_url"]["show"] = False build_config["base_url_ibm_watsonx"]["show"] = False build_config["project_id"]["show"] = False build_config["ollama_base_url"]["show"] = False elif field_value == "Google": build_config["model_name"]["options"] = GOOGLE_GENERATIVE_AI_MODELS build_config["model_name"]["value"] = GOOGLE_GENERATIVE_AI_MODELS[0] build_config["api_key"]["display_name"] = "Google API Key" build_config["api_key"]["show"] = True build_config["base_url"]["show"] = False build_config["base_url_ibm_watsonx"]["show"] = False build_config["project_id"]["show"] = False build_config["ollama_base_url"]["show"] = False elif field_value == "IBM watsonx.ai": build_config["model_name"]["options"] = IBM_WATSONX_DEFAULT_MODELS build_config["model_name"]["value"] = IBM_WATSONX_DEFAULT_MODELS[0] build_config["api_key"]["display_name"] = "IBM API Key" build_config["api_key"]["show"] = True build_config["base_url"]["show"] = False build_config["base_url_ibm_watsonx"]["show"] = True build_config["project_id"]["show"] = True build_config["ollama_base_url"]["show"] = False elif field_value == "Ollama": # Fetch Ollama models from the API build_config["api_key"]["show"] = False build_config["base_url"]["show"] = False build_config["base_url_ibm_watsonx"]["show"] = False build_config["project_id"]["show"] = False build_config["ollama_base_url"]["show"] = True # Try multiple sources to get the URL (in order of preference): # 1. Instance attribute (already resolved from global/db) # 2. Build config value (may be a global variable reference) # 3. Default value ollama_url = getattr(self, "ollama_base_url", None) if not ollama_url: config_value = build_config["ollama_base_url"].get("value", DEFAULT_OLLAMA_URL) # If config_value looks like a variable name (all caps with underscores), use default is_variable_ref = ( config_value and isinstance(config_value, str) and config_value.isupper() and "_" in config_value ) if is_variable_ref: await logger.adebug( f"Config value appears to be a variable reference: {config_value}, using default" ) ollama_url = DEFAULT_OLLAMA_URL else: ollama_url = config_value await logger.adebug(f"Fetching Ollama models for provider switch. URL: {ollama_url}") if await is_valid_ollama_url(url=ollama_url): try: models = await get_ollama_models( base_url_value=ollama_url, desired_capability=DESIRED_CAPABILITY, json_models_key=JSON_MODELS_KEY, json_name_key=JSON_NAME_KEY, json_capabilities_key=JSON_CAPABILITIES_KEY, ) build_config["model_name"]["options"] = models build_config["model_name"]["value"] = models[0] if models else "" except ValueError: await logger.awarning("Failed to fetch Ollama models. Setting empty options.") build_config["model_name"]["options"] = [] build_config["model_name"]["value"] = "" else: await logger.awarning(f"Invalid Ollama URL: {ollama_url}") build_config["model_name"]["options"] = [] build_config["model_name"]["value"] = "" elif field_value == "OpenAI Compatible": build_config["model_name"]["options"] = OPENAI_CHAT_MODEL_NAMES build_config["model_name"]["value"] = OPENAI_CHAT_MODEL_NAMES[0] build_config["api_key"]["display_name"] = "API Key" build_config["api_key"]["show"] = True build_config["base_url"]["show"] = True build_config["base_url_ibm_watsonx"]["show"] = False build_config["project_id"]["show"] = False build_config["ollama_base_url"]["show"] = False elif ( field_name == "base_url_ibm_watsonx" and field_value and hasattr(self, "provider") and self.provider == "IBM watsonx.ai" ): # Fetch IBM models when base_url changes try: models = self.fetch_ibm_models(base_url=field_value) build_config["model_name"]["options"] = models build_config["model_name"]["value"] = models[0] if models else IBM_WATSONX_DEFAULT_MODELS[0] info_message = f"Updated model options: {len(models)} models found in {field_value}" logger.info(info_message) except Exception: # noqa: BLE001 logger.exception("Error updating IBM model options.") elif field_name == "ollama_base_url": # Fetch Ollama models when ollama_base_url changes # Use the field_value directly since this is triggered when the field changes logger.debug( f"Fetching Ollama models from updated URL: {build_config['ollama_base_url']} \ and value {self.ollama_base_url}", ) await logger.adebug(f"Fetching Ollama models from updated URL: {self.ollama_base_url}") if await is_valid_ollama_url(url=self.ollama_base_url): try: models = await get_ollama_models( base_url_value=self.ollama_base_url, desired_capability=DESIRED_CAPABILITY, json_models_key=JSON_MODELS_KEY, json_name_key=JSON_NAME_KEY, json_capabilities_key=JSON_CAPABILITIES_KEY, ) build_config["model_name"]["options"] = models build_config["model_name"]["value"] = models[0] if models else "" info_message = f"Updated model options: {len(models)} models found in {self.ollama_base_url}" await logger.ainfo(info_message) except ValueError: await logger.awarning("Error updating Ollama model options.") build_config["model_name"]["options"] = [] build_config["model_name"]["value"] = "" else: await logger.awarning(f"Invalid Ollama URL: {self.ollama_base_url}") build_config["model_name"]["options"] = [] build_config["model_name"]["value"] = "" elif field_name == "model_name": # Refresh Ollama models when model_name field is accessed if hasattr(self, "provider") and self.provider == "Ollama": ollama_url = getattr(self, "ollama_base_url", DEFAULT_OLLAMA_URL) if await is_valid_ollama_url(url=ollama_url): try: models = await get_ollama_models( base_url_value=ollama_url, desired_capability=DESIRED_CAPABILITY, json_models_key=JSON_MODELS_KEY, json_name_key=JSON_NAME_KEY, json_capabilities_key=JSON_CAPABILITIES_KEY, ) build_config["model_name"]["options"] = models except ValueError: await logger.awarning("Failed to refresh Ollama models.") build_config["model_name"]["options"] = [] else: build_config["model_name"]["options"] = [] # Hide system_message for o1 models - currently unsupported if field_value and field_value.startswith("o1") and hasattr(self, "provider") and self.provider == "OpenAI": if "system_message" in build_config: build_config["system_message"]["show"] = False elif "system_message" in build_config: build_config["system_message"]["show"] = True return build_config
