Fixed components: added load from db and removed Flow encapsulation
This commit is contained in:
Lucas Oliveira
parent
0eb0bd7e9e
commit
65bf20a1e4
6 changed files with 2120 additions and 2011 deletions
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@ -1,171 +1,142 @@
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"node": {
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"template": {
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"_type": "Component",
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"base_url": {
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"load_from_db": false,
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"list": false,
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"list_add_label": "Add More",
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"required": true,
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"placeholder": "",
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"show": true,
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"name": "base_url",
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"value": "http://host.docker.internal:11434",
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"display_name": "Ollama Base URL",
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"advanced": false,
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"Message"
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"value": "from typing import Any\nfrom urllib.parse import urljoin\n\nimport httpx\nfrom langchain_ollama import OllamaEmbeddings\n\nfrom lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.ollama_constants import OLLAMA_EMBEDDING_MODELS, URL_LIST\nfrom lfx.field_typing import Embeddings\nfrom lfx.io import DropdownInput, MessageTextInput, Output\n\nHTTP_STATUS_OK = 200\n\n\nclass OllamaEmbeddingsComponent(LCModelComponent):\n display_name: str = \"Ollama Embeddings\"\n description: str = \"Generate embeddings using Ollama models.\"\n documentation = \"https://python.langchain.com/docs/integrations/text_embedding/ollama\"\n icon = \"Ollama\"\n name = \"OllamaEmbeddings\"\n\n inputs = [\n DropdownInput(\n name=\"model_name\",\n display_name=\"Ollama Model\",\n value=\"\",\n options=[],\n real_time_refresh=True,\n refresh_button=True,\n combobox=True,\n required=True,\n ),\n MessageTextInput(\n name=\"base_url\",\n display_name=\"Ollama Base URL\",\n value=\"\",\n required=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Embeddings\", name=\"embeddings\", method=\"build_embeddings\"),\n ]\n\n def build_embeddings(self) -> Embeddings:\n try:\n output = OllamaEmbeddings(model=self.model_name, base_url=self.base_url)\n except Exception as e:\n msg = (\n \"Unable to connect to the Ollama API. \",\n \"Please verify the base URL, ensure the relevant Ollama model is pulled, and try again.\",\n )\n raise ValueError(msg) from e\n return output\n\n async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):\n if field_name in {\"base_url\", \"model_name\"} and not await self.is_valid_ollama_url(field_value):\n # Check if any URL in the list is valid\n valid_url = \"\"\n for url in URL_LIST:\n if await self.is_valid_ollama_url(url):\n valid_url = url\n break\n build_config[\"base_url\"][\"value\"] = valid_url\n if field_name in {\"model_name\", \"base_url\", \"tool_model_enabled\"}:\n if await self.is_valid_ollama_url(self.base_url):\n build_config[\"model_name\"][\"options\"] = await self.get_model(self.base_url)\n elif await self.is_valid_ollama_url(build_config[\"base_url\"].get(\"value\", \"\")):\n build_config[\"model_name\"][\"options\"] = await self.get_model(build_config[\"base_url\"].get(\"value\", \"\"))\n else:\n build_config[\"model_name\"][\"options\"] = []\n\n return build_config\n\n async def get_model(self, base_url_value: str) -> list[str]:\n \"\"\"Get the model names from Ollama.\"\"\"\n model_ids = []\n try:\n url = urljoin(base_url_value, \"/api/tags\")\n async with httpx.AsyncClient() as client:\n response = await client.get(url)\n response.raise_for_status()\n data = response.json()\n\n model_ids = [model[\"name\"] for model in data.get(\"models\", [])]\n # this to ensure that not embedding models are included.\n # not even the base models since models can have 1b 2b etc\n # handles cases when embeddings models have tags like :latest - etc.\n model_ids = [\n model\n for model in model_ids\n if any(model.startswith(f\"{embedding_model}\") for embedding_model in OLLAMA_EMBEDDING_MODELS)\n ]\n\n except (ImportError, ValueError, httpx.RequestError) as e:\n msg = \"Could not get model names from Ollama.\"\n raise ValueError(msg) from e\n\n return model_ids\n\n async def is_valid_ollama_url(self, url: str) -> bool:\n try:\n async with httpx.AsyncClient() as client:\n return (await client.get(f\"{url}/api/tags\")).status_code == HTTP_STATUS_OK\n except httpx.RequestError:\n return False\n",
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"name": "code",
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"dynamic": true,
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"info": "",
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"load_from_db": false,
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"title_case": false
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},
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"model_name": {
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"tool_mode": false,
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"trace_as_metadata": true,
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"options": [
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"nomic-embed-text:latest",
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"all-minilm:latest"
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],
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"options_metadata": [],
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"combobox": true,
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"dialog_inputs": {},
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"toggle": false,
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"required": true,
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"placeholder": "",
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"show": true,
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"name": "model_name",
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"value": "",
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"display_name": "Ollama Model",
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"advanced": false,
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"dynamic": false,
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"info": "",
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"real_time_refresh": true,
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"refresh_button": true,
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"title_case": false,
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"external_options": {},
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"type": "str",
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"_input_type": "DropdownInput"
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}
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},
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"description": "Generate embeddings using Ollama models.",
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"icon": "Ollama",
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"base_classes": [
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"Embeddings"
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],
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"display_name": "Ollama Embeddings",
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"documentation": "https://python.langchain.com/docs/integrations/text_embedding/ollama",
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"minimized": false,
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"custom_fields": {},
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"output_types": [],
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"pinned": false,
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"conditional_paths": [],
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"frozen": false,
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"outputs": [
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{
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"types": [
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"Embeddings"
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],
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"selected": "Embeddings",
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"name": "embeddings",
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"display_name": "Embeddings",
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"method": "build_embeddings",
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"value": "__UNDEFINED__",
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"cache": true,
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"required_inputs": null,
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"allows_loop": false,
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"group_outputs": false,
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"options": null,
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"tool_mode": true
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}
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],
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"field_order": [
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"model_name",
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"base_url"
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],
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"beta": false,
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"legacy": false,
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"edited": false,
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"metadata": {
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"keywords": [
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"model",
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"llm",
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"language model",
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"large language model"
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],
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"module": "lfx.components.ollama.ollama_embeddings.OllamaEmbeddingsComponent",
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"code_hash": "c41821735548",
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"dependencies": {
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"total_dependencies": 3,
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"dependencies": [
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{
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"name": "httpx",
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"version": "0.28.1"
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},
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{
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"name": "langchain_ollama",
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"version": "0.2.1"
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},
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{
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"name": "lfx",
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"version": null
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}
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]
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}
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},
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"tool_mode": false,
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"last_updated": "2025-09-29T18:40:10.242Z",
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"official": false
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},
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"showNode": true,
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"type": "OllamaEmbeddings",
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"id": "OllamaEmbeddings-vnNn8"
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"node": {
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"template": {
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"_type": "Component",
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"base_url": {
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"load_from_db": true,
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"list": false,
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"list_add_label": "Add More",
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"required": true,
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"placeholder": "",
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"show": true,
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"name": "base_url",
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"value": "OLLAMA_BASE_URL",
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"display_name": "Ollama Base URL",
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"advanced": false,
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"input_types": ["Message"],
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"dynamic": false,
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"info": "",
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"title_case": false,
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"type": "str",
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"_input_type": "MessageTextInput"
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},
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"id": "OllamaEmbeddings-vnNn8",
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"position": {
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"x": 0,
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"y": 0
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"code": {
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"type": "code",
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"required": true,
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"placeholder": "",
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"list": false,
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"show": true,
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"multiline": true,
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"value": "from typing import Any\nfrom urllib.parse import urljoin\n\nimport httpx\nfrom langchain_ollama import OllamaEmbeddings\n\nfrom lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.ollama_constants import OLLAMA_EMBEDDING_MODELS, URL_LIST\nfrom lfx.field_typing import Embeddings\nfrom lfx.io import DropdownInput, MessageTextInput, Output\n\nHTTP_STATUS_OK = 200\n\n\nclass OllamaEmbeddingsComponent(LCModelComponent):\n display_name: str = \"Ollama Embeddings\"\n description: str = \"Generate embeddings using Ollama models.\"\n documentation = \"https://python.langchain.com/docs/integrations/text_embedding/ollama\"\n icon = \"Ollama\"\n name = \"OllamaEmbeddings\"\n\n inputs = [\n DropdownInput(\n name=\"model_name\",\n display_name=\"Ollama Model\",\n value=\"\",\n options=[],\n real_time_refresh=True,\n refresh_button=True,\n combobox=True,\n required=True,\n ),\n MessageTextInput(\n name=\"base_url\",\n display_name=\"Ollama Base URL\",\n value=\"\",\n required=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Embeddings\", name=\"embeddings\", method=\"build_embeddings\"),\n ]\n\n def build_embeddings(self) -> Embeddings:\n try:\n output = OllamaEmbeddings(model=self.model_name, base_url=self.base_url)\n except Exception as e:\n msg = (\n \"Unable to connect to the Ollama API. \",\n \"Please verify the base URL, ensure the relevant Ollama model is pulled, and try again.\",\n )\n raise ValueError(msg) from e\n return output\n\n async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):\n if field_name in {\"base_url\", \"model_name\"} and not await self.is_valid_ollama_url(field_value):\n # Check if any URL in the list is valid\n valid_url = \"\"\n for url in URL_LIST:\n if await self.is_valid_ollama_url(url):\n valid_url = url\n break\n build_config[\"base_url\"][\"value\"] = valid_url\n if field_name in {\"model_name\", \"base_url\", \"tool_model_enabled\"}:\n if await self.is_valid_ollama_url(self.base_url):\n build_config[\"model_name\"][\"options\"] = await self.get_model(self.base_url)\n elif await self.is_valid_ollama_url(build_config[\"base_url\"].get(\"value\", \"\")):\n build_config[\"model_name\"][\"options\"] = await self.get_model(build_config[\"base_url\"].get(\"value\", \"\"))\n else:\n build_config[\"model_name\"][\"options\"] = []\n\n return build_config\n\n async def get_model(self, base_url_value: str) -> list[str]:\n \"\"\"Get the model names from Ollama.\"\"\"\n model_ids = []\n try:\n url = urljoin(base_url_value, \"/api/tags\")\n async with httpx.AsyncClient() as client:\n response = await client.get(url)\n response.raise_for_status()\n data = response.json()\n\n model_ids = [model[\"name\"] for model in data.get(\"models\", [])]\n # this to ensure that not embedding models are included.\n # not even the base models since models can have 1b 2b etc\n # handles cases when embeddings models have tags like :latest - etc.\n model_ids = [\n model\n for model in model_ids\n if any(model.startswith(f\"{embedding_model}\") for embedding_model in OLLAMA_EMBEDDING_MODELS)\n ]\n\n except (ImportError, ValueError, httpx.RequestError) as e:\n msg = \"Could not get model names from Ollama.\"\n raise ValueError(msg) from e\n\n return model_ids\n\n async def is_valid_ollama_url(self, url: str) -> bool:\n try:\n async with httpx.AsyncClient() as client:\n return (await client.get(f\"{url}/api/tags\")).status_code == HTTP_STATUS_OK\n except httpx.RequestError:\n return False\n",
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"fileTypes": [],
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"file_path": "",
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"password": false,
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"name": "code",
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"advanced": true,
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"dynamic": true,
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"info": "",
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"load_from_db": false,
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"title_case": false
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},
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"type": "genericNode"
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}
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],
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"viewport": {
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"x": 1,
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"y": 1,
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"zoom": 1
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}
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"model_name": {
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"tool_mode": false,
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"trace_as_metadata": true,
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"options": ["nomic-embed-text:latest", "all-minilm:latest"],
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"options_metadata": [],
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"combobox": true,
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"dialog_inputs": {},
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"toggle": false,
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"required": true,
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"placeholder": "",
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"show": true,
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"name": "model_name",
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"value": "",
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"display_name": "Ollama Model",
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"advanced": false,
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"dynamic": false,
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"info": "",
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"real_time_refresh": true,
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"refresh_button": true,
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"title_case": false,
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"external_options": {},
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"type": "str",
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"_input_type": "DropdownInput"
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}
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},
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"description": "Generate embeddings using Ollama models.",
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"icon": "Ollama",
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"base_classes": ["Embeddings"],
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"display_name": "Ollama Embeddings",
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"documentation": "https://python.langchain.com/docs/integrations/text_embedding/ollama",
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"minimized": false,
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"custom_fields": {},
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"output_types": [],
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"pinned": false,
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"conditional_paths": [],
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"frozen": false,
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"outputs": [
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{
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"types": ["Embeddings"],
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"selected": "Embeddings",
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"name": "embeddings",
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"display_name": "Embeddings",
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"method": "build_embeddings",
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"value": "__UNDEFINED__",
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"cache": true,
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"required_inputs": null,
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"allows_loop": false,
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"group_outputs": false,
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"options": null,
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"tool_mode": true
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}
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],
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"field_order": ["model_name", "base_url"],
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"beta": false,
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"legacy": false,
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"edited": false,
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"metadata": {
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"keywords": [
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"model",
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"llm",
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"language model",
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"large language model"
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],
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"module": "lfx.components.ollama.ollama_embeddings.OllamaEmbeddingsComponent",
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"code_hash": "c41821735548",
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"dependencies": {
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"total_dependencies": 3,
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"dependencies": [
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{
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"name": "httpx",
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"version": "0.28.1"
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},
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{
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"name": "langchain_ollama",
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"version": "0.2.1"
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},
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{
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"name": "lfx",
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"version": null
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}
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]
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}
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},
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"tool_mode": false,
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"last_updated": "2025-09-29T18:40:10.242Z",
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"official": false
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},
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"showNode": true,
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"type": "OllamaEmbeddings",
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"id": "OllamaEmbeddings-vnNn8"
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},
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"description": "Generate embeddings using Ollama models.",
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"name": "Ollama Embeddings",
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"id": "OllamaEmbeddings-vnNn8",
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"is_component": true,
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"last_tested_version": "1.6.0"
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"position": {
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"x": 0,
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"y": 0
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},
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"type": "genericNode"
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}
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@ -1,8 +1,4 @@
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{
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"data": {
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"edges": [],
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"nodes": [
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{
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"data": {
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"node": {
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"template": {
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@ -11,14 +7,14 @@
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"load_from_db": false,
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"load_from_db": true,
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"list": false,
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"list_add_label": "Add More",
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"required": false,
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"placeholder": "",
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"show": true,
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"name": "base_url",
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"value": "",
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"value": "OLLAMA_BASE_URL",
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"display_name": "Base URL",
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"advanced": false,
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"input_types": [
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@ -605,95 +601,82 @@
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"cache": true,
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"required_inputs": null,
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"allows_loop": false,
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"group_outputs": false,
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"options": null,
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"tool_mode": true
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}
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],
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"field_order": [
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"base_url",
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"model_name",
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"temperature",
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"format",
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"metadata",
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"mirostat",
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"mirostat_eta",
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"mirostat_tau",
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"num_ctx",
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"num_gpu",
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"num_thread",
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"repeat_last_n",
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"repeat_penalty",
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"tfs_z",
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"timeout",
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"top_k",
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"top_p",
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"verbose",
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"tags",
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"stop_tokens",
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"system",
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"tool_model_enabled",
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"template",
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"input_value",
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"system_message",
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"stream"
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],
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"beta": false,
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"legacy": false,
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"edited": false,
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"metadata": {
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"keywords": [
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"model",
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"llm",
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"language model",
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"large language model"
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],
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"module": "lfx.components.ollama.ollama.ChatOllamaComponent",
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"code_hash": "54de3b5da388",
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"dependencies": {
|
||||
"total_dependencies": 3,
|
||||
"dependencies": [
|
||||
{
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||||
"name": "httpx",
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||||
"version": "0.28.1"
|
||||
},
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||||
{
|
||||
"name": "langchain_ollama",
|
||||
"version": "0.2.1"
|
||||
},
|
||||
{
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||||
"name": "lfx",
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"version": null
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}
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]
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}
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"group_outputs": false,
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"options": null,
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"tool_mode": true
|
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}
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],
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||||
"field_order": [
|
||||
"base_url",
|
||||
"model_name",
|
||||
"temperature",
|
||||
"format",
|
||||
"metadata",
|
||||
"mirostat",
|
||||
"mirostat_eta",
|
||||
"mirostat_tau",
|
||||
"num_ctx",
|
||||
"num_gpu",
|
||||
"num_thread",
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||||
"repeat_last_n",
|
||||
"repeat_penalty",
|
||||
"tfs_z",
|
||||
"timeout",
|
||||
"top_k",
|
||||
"top_p",
|
||||
"verbose",
|
||||
"tags",
|
||||
"stop_tokens",
|
||||
"system",
|
||||
"tool_model_enabled",
|
||||
"template",
|
||||
"input_value",
|
||||
"system_message",
|
||||
"stream"
|
||||
],
|
||||
"beta": false,
|
||||
"legacy": false,
|
||||
"edited": false,
|
||||
"metadata": {
|
||||
"keywords": [
|
||||
"model",
|
||||
"llm",
|
||||
"language model",
|
||||
"large language model"
|
||||
],
|
||||
"module": "lfx.components.ollama.ollama.ChatOllamaComponent",
|
||||
"code_hash": "54de3b5da388",
|
||||
"dependencies": {
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"total_dependencies": 3,
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||||
"dependencies": [
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{
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"name": "httpx",
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},
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||||
"tool_mode": false,
|
||||
"last_updated": "2025-09-29T18:39:30.798Z",
|
||||
"official": false
|
||||
},
|
||||
"showNode": true,
|
||||
"type": "OllamaModel",
|
||||
"id": "OllamaModel-8Re0J",
|
||||
"selected_output": "model_output"
|
||||
},
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||||
"id": "OllamaModel-8Re0J",
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||||
"position": {
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||||
"x": 0,
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||||
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||||
},
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||||
"type": "genericNode"
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||||
}
|
||||
],
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||||
"viewport": {
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||||
"x": 1,
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||||
"y": 1,
|
||||
"zoom": 1
|
||||
}
|
||||
{
|
||||
"name": "langchain_ollama",
|
||||
"version": "0.2.1"
|
||||
},
|
||||
{
|
||||
"name": "lfx",
|
||||
"version": null
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"tool_mode": false,
|
||||
"last_updated": "2025-09-29T18:39:30.798Z",
|
||||
"official": false
|
||||
},
|
||||
"showNode": true,
|
||||
"type": "OllamaModel",
|
||||
"id": "OllamaModel-8Re0J",
|
||||
"selected_output": "model_output"
|
||||
},
|
||||
"description": "Generate text using Ollama Local LLMs.",
|
||||
"name": "Ollama",
|
||||
"id": "OllamaModel-8Re0J",
|
||||
"is_component": true,
|
||||
"last_tested_version": "1.6.0"
|
||||
"position": {
|
||||
"x": 0,
|
||||
"y": 0
|
||||
},
|
||||
"type": "genericNode"
|
||||
}
|
||||
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Loading…
Add table
Reference in a new issue