feat: Add model filtering support for Ollama Component, improving stability (#5748)

* Update ollama.py

* ollama models refactor

* ollama embeddings support for model filters

* formatting

* Update src/backend/base/langflow/components/embeddings/ollama.py

Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>

* [autofix.ci] apply automated fixes

* fix test

* reverting test

* refactor: Update Ollama components to use async URL validation

- Changed `is_valid_ollama_url` method to be asynchronous in both `ollama.py` files.
- Updated calls to `is_valid_ollama_url` to use `await` for proper async handling.
- Modified URL validation logic to ensure compatibility with async operations.
- Improved overall responsiveness of the Ollama components by leveraging async HTTP requests.

* reverting to empty list!

---------

Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

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

@@ -0,0 +1,47 @@
+# https://ollama.com/search?c=embedding
+OLLAMA_EMBEDDING_MODELS = [
+    "nomic-embed-text",
+    "mxbai-embed-large",
+    "snowflake-arctic-embed",
+    "all-minilm",
+    "bge-m3",
+    "paraphrase-multilingual",
+    "granite-embedding",
+    "jina-embeddings-v2-base-en",
+]
+# https://ollama.com/search?c=tools
+OLLAMA_TOOL_MODELS_BASE = [
+    "llama3.3",
+    "qwq",
+    "llama3.2",
+    "llama3.1",
+    "mistral",
+    "qwen2",
+    "qwen2.5",
+    "qwen2.5-coder",
+    "mistral-nemo",
+    "mixtral",
+    "command-r",
+    "command-r-plus",
+    "mistral-large",
+    "smollm2",
+    "hermes3",
+    "athene-v2",
+    "mistral-small",
+    "nemotron-mini",
+    "nemotron",
+    "llama3-groq-tool-use",
+    "granite3-dense",
+    "granite3.1-dense",
+    "aya-expanse",
+    "granite3-moe",
+    "firefunction-v2",
+]
+
+
+URL_LIST = [
+    "http://localhost:11434",
+    "http://host.docker.internal:11434",
+    "http://127.0.0.1:11434",
+    "http://0.0.0.0:11434",
+]

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

@@ -1,8 +1,15 @@
+from typing import Any
+from urllib.parse import urljoin
+
+import httpx
 from langchain_ollama import OllamaEmbeddings
 
 from langflow.base.models.model import LCModelComponent
+from langflow.base.models.ollama_constants import OLLAMA_EMBEDDING_MODELS, URL_LIST
 from langflow.field_typing import Embeddings
-from langflow.io import MessageTextInput, Output
+from langflow.io import DropdownInput, MessageTextInput, Output
+
+HTTP_STATUS_OK = 200
 
 
 class OllamaEmbeddingsComponent(LCModelComponent):
@@ -13,16 +20,20 @@ class OllamaEmbeddingsComponent(LCModelComponent):
     name = "OllamaEmbeddings"
 
     inputs = [
-        MessageTextInput(
+        DropdownInput(
-            name="model",
+            name="model_name",
             display_name="Ollama Model",
-            value="nomic-embed-text",
+            value="",
+            options=[],
+            real_time_refresh=True,
+            refresh_button=True,
+            combobox=True,
             required=True,
         ),
         MessageTextInput(
             name="base_url",
             display_name="Ollama Base URL",
-            value="http://localhost:11434",
+            value="",
             required=True,
         ),
     ]
@@ -33,8 +44,63 @@ class OllamaEmbeddingsComponent(LCModelComponent):
 
     def build_embeddings(self) -> Embeddings:
         try:
-            output = OllamaEmbeddings(model=self.model, base_url=self.base_url)
+            output = OllamaEmbeddings(model=self.model_name, base_url=self.base_url)
         except Exception as e:
-            msg = "Could not connect to Ollama API."
+            msg = (
+                "Unable to connect to the Ollama API. ",
+                "Please verify the base URL, ensure the relevant Ollama model is pulled, and try again.",
+            )
             raise ValueError(msg) from e
         return output
+
+    async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):
+        if field_name in {"base_url", "model_name"} and not await self.is_valid_ollama_url(field_value):
+            # Check if any URL in the list is valid
+            valid_url = ""
+            for url in URL_LIST:
+                if await self.is_valid_ollama_url(url):
+                    valid_url = url
+                    break
+            build_config["base_url"]["value"] = valid_url
+        if field_name in {"model_name", "base_url", "tool_model_enabled"}:
+            if await self.is_valid_ollama_url(self.base_url):
+                build_config["model_name"]["options"] = await self.get_model(self.base_url)
+            elif await self.is_valid_ollama_url(build_config["base_url"].get("value", "")):
+                build_config["model_name"]["options"] = await self.get_model(build_config["base_url"].get("value", ""))
+            else:
+                build_config["model_name"]["options"] = []
+
+        return build_config
+
+    async def get_model(self, base_url_value: str) -> list[str]:
+        """Get the model names from Ollama."""
+        model_ids = []
+        try:
+            url = urljoin(base_url_value, "/api/tags")
+            async with httpx.AsyncClient() as client:
+                response = await client.get(url)
+                response.raise_for_status()
+                data = response.json()
+
+            model_ids = [model["name"] for model in data.get("models", [])]
+            # this to ensure that not embedding models are included.
+            # not even the base models since models can have 1b 2b etc
+            # handles cases when embeddings models have tags like :latest - etc.
+            model_ids = [
+                model
+                for model in model_ids
+                if any(model.startswith(f"{embedding_model}") for embedding_model in OLLAMA_EMBEDDING_MODELS)
+            ]
+
+        except (ImportError, ValueError, httpx.RequestError) as e:
+            msg = "Could not get model names from Ollama."
+            raise ValueError(msg) from e
+
+        return model_ids
+
+    async def is_valid_ollama_url(self, url: str) -> bool:
+        try:
+            async with httpx.AsyncClient() as client:
+                return (await client.get(f"{url}/api/tags")).status_code == HTTP_STATUS_OK
+        except httpx.RequestError:
+            return False

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

@@ -5,8 +5,12 @@ import httpx
 from langchain_ollama import ChatOllama
 
 from langflow.base.models.model import LCModelComponent
+from langflow.base.models.ollama_constants import OLLAMA_EMBEDDING_MODELS, OLLAMA_TOOL_MODELS_BASE, URL_LIST
 from langflow.field_typing import LanguageModel
-from langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, StrInput
+from langflow.field_typing.range_spec import RangeSpec
+from langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SliderInput
+
+HTTP_STATUS_OK = 200
 
 
 class ChatOllamaComponent(LCModelComponent):
@@ -15,81 +19,25 @@ class ChatOllamaComponent(LCModelComponent):
     icon = "Ollama"
     name = "OllamaModel"
 
-    async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):
-        if field_name == "mirostat":
-            if field_value == "Disabled":
-                build_config["mirostat_eta"]["advanced"] = True
-                build_config["mirostat_tau"]["advanced"] = True
-                build_config["mirostat_eta"]["value"] = None
-                build_config["mirostat_tau"]["value"] = None
-
-            else:
-                build_config["mirostat_eta"]["advanced"] = False
-                build_config["mirostat_tau"]["advanced"] = False
-
-                if field_value == "Mirostat 2.0":
-                    build_config["mirostat_eta"]["value"] = 0.2
-                    build_config["mirostat_tau"]["value"] = 10
-                else:
-                    build_config["mirostat_eta"]["value"] = 0.1
-                    build_config["mirostat_tau"]["value"] = 5
-
-        if field_name == "model_name":
-            base_url_dict = build_config.get("base_url", {})
-            base_url_load_from_db = base_url_dict.get("load_from_db", False)
-            base_url_value = base_url_dict.get("value")
-            if base_url_load_from_db:
-                base_url_value = await self.get_variables(base_url_value, field_name)
-            elif not base_url_value:
-                base_url_value = "http://localhost:11434"
-            build_config["model_name"]["options"] = await self.get_model(base_url_value)
-        if field_name == "keep_alive_flag":
-            if field_value == "Keep":
-                build_config["keep_alive"]["value"] = "-1"
-                build_config["keep_alive"]["advanced"] = True
-            elif field_value == "Immediately":
-                build_config["keep_alive"]["value"] = "0"
-                build_config["keep_alive"]["advanced"] = True
-            else:
-                build_config["keep_alive"]["advanced"] = False
-
-        return build_config
-
-    @staticmethod
-    async def get_model(base_url_value: str) -> list[str]:
-        try:
-            url = urljoin(base_url_value, "/api/tags")
-            async with httpx.AsyncClient() as client:
-                response = await client.get(url)
-                response.raise_for_status()
-                data = response.json()
-
-                return [model["name"] for model in data.get("models", [])]
-        except Exception as e:
-            msg = "Could not retrieve models. Please, make sure Ollama is running."
-            raise ValueError(msg) from e
-
     inputs = [
-        StrInput(
+        MessageTextInput(
             name="base_url",
             display_name="Base URL",
             info="Endpoint of the Ollama API. Defaults to 'http://localhost:11434' if not specified.",
-            value="http://localhost:11434",
+            value="",
         ),
         DropdownInput(
             name="model_name",
             display_name="Model Name",
-            value="llama3.1",
+            options=[],
             info="Refer to https://ollama.com/library for more models.",
             refresh_button=True,
+            real_time_refresh=True,
         ),
-        FloatInput(
+        SliderInput(
-            name="temperature",
+            name="temperature", display_name="Temperature", value=0.1, range_spec=RangeSpec(min=0, max=1, step=0.01)
-            display_name="Temperature",
-            value=0.2,
-            info="Controls the creativity of model responses.",
         ),
-        StrInput(
+        MessageTextInput(
             name="format", display_name="Format", info="Specify the format of the output (e.g., json).", advanced=True
         ),
         DictInput(name="metadata", display_name="Metadata", info="Metadata to add to the run trace.", advanced=True),
@@ -151,20 +99,31 @@ class ChatOllamaComponent(LCModelComponent):
         ),
         FloatInput(name="top_p", display_name="Top P", info="Works together with top-k. (Default: 0.9)", advanced=True),
         BoolInput(name="verbose", display_name="Verbose", info="Whether to print out response text.", advanced=True),
-        StrInput(
+        MessageTextInput(
             name="tags",
             display_name="Tags",
             info="Comma-separated list of tags to add to the run trace.",
             advanced=True,
         ),
-        StrInput(
+        MessageTextInput(
             name="stop_tokens",
             display_name="Stop Tokens",
             info="Comma-separated list of tokens to signal the model to stop generating text.",
             advanced=True,
         ),
-        StrInput(name="system", display_name="System", info="System to use for generating text.", advanced=True),
+        MessageTextInput(
-        StrInput(name="template", display_name="Template", info="Template to use for generating text.", advanced=True),
+            name="system", display_name="System", info="System to use for generating text.", advanced=True
+        ),
+        MessageTextInput(
+            name="template", display_name="Template", info="Template to use for generating text.", advanced=True
+        ),
+        BoolInput(
+            name="tool_model_enabled",
+            display_name="Tool Model Enabled",
+            info="Whether to enable tool calling in the model.",
+            value=True,
+            real_time_refresh=True,
+        ),
         *LCModelComponent._base_inputs,
     ]
 
@@ -215,7 +174,99 @@ class ChatOllamaComponent(LCModelComponent):
         try:
             output = ChatOllama(**llm_params)
         except Exception as e:
-            msg = "Could not initialize Ollama LLM."
+            msg = (
+                "Unable to connect to the Ollama API. ",
+                "Please verify the base URL, ensure the relevant Ollama model is pulled, and try again.",
+            )
             raise ValueError(msg) from e
 
         return output
+
+    async def is_valid_ollama_url(self, url: str) -> bool:
+        try:
+            async with httpx.AsyncClient() as client:
+                return (await client.get(f"{url}/api/tags")).status_code == HTTP_STATUS_OK
+        except httpx.RequestError:
+            return False
+
+    async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):
+        if field_name == "mirostat":
+            if field_value == "Disabled":
+                build_config["mirostat_eta"]["advanced"] = True
+                build_config["mirostat_tau"]["advanced"] = True
+                build_config["mirostat_eta"]["value"] = None
+                build_config["mirostat_tau"]["value"] = None
+
+            else:
+                build_config["mirostat_eta"]["advanced"] = False
+                build_config["mirostat_tau"]["advanced"] = False
+
+                if field_value == "Mirostat 2.0":
+                    build_config["mirostat_eta"]["value"] = 0.2
+                    build_config["mirostat_tau"]["value"] = 10
+                else:
+                    build_config["mirostat_eta"]["value"] = 0.1
+                    build_config["mirostat_tau"]["value"] = 5
+
+        if field_name in {"base_url", "model_name"} and not await self.is_valid_ollama_url(field_value):
+            # Check if any URL in the list is valid
+            valid_url = ""
+            for url in URL_LIST:
+                if await self.is_valid_ollama_url(url):
+                    valid_url = url
+                    break
+            build_config["base_url"]["value"] = valid_url
+        if field_name in {"model_name", "base_url", "tool_model_enabled"}:
+            if await self.is_valid_ollama_url(self.base_url):
+                tool_model_enabled = build_config["tool_model_enabled"].get("value", False) or self.tool_model_enabled
+                build_config["model_name"]["options"] = await self.get_model(self.base_url, tool_model_enabled)
+            elif await self.is_valid_ollama_url(build_config["base_url"].get("value", "")):
+                tool_model_enabled = build_config["tool_model_enabled"].get("value", False) or self.tool_model_enabled
+                build_config["model_name"]["options"] = await self.get_model(
+                    build_config["base_url"].get("value", ""), tool_model_enabled
+                )
+            else:
+                build_config["model_name"]["options"] = []
+        if field_name == "keep_alive_flag":
+            if field_value == "Keep":
+                build_config["keep_alive"]["value"] = "-1"
+                build_config["keep_alive"]["advanced"] = True
+            elif field_value == "Immediately":
+                build_config["keep_alive"]["value"] = "0"
+                build_config["keep_alive"]["advanced"] = True
+            else:
+                build_config["keep_alive"]["advanced"] = False
+
+        return build_config
+
+    async def get_model(self, base_url_value: str, tool_model_enabled: bool | None = None) -> list[str]:
+        try:
+            url = urljoin(base_url_value, "/api/tags")
+            async with httpx.AsyncClient() as client:
+                response = await client.get(url)
+                response.raise_for_status()
+                data = response.json()
+
+            model_ids = [model["name"] for model in data.get("models", [])]
+            # this to ensure that not embedding models are included.
+            # not even the base models since models can have 1b 2b etc
+            # handles cases when embeddings models have tags like :latest - etc.
+            model_ids = [
+                model
+                for model in model_ids
+                if not any(
+                    model == embedding_model or model.startswith(embedding_model.split("-")[0])
+                    for embedding_model in OLLAMA_EMBEDDING_MODELS
+                )
+            ]
+
+        except (ImportError, ValueError, httpx.RequestError, Exception) as e:
+            msg = "Could not get model names from Ollama."
+            raise ValueError(msg) from e
+        return (
+            model_ids if not tool_model_enabled else [model for model in model_ids if self.supports_tool_calling(model)]
+        )
+
+    def supports_tool_calling(self, model: str) -> bool:
+        """Check if model name is in the base of any models example llama3.3 can have 1b and 2b."""
+        return any(model.startswith(f"{tool_model}") for tool_model in OLLAMA_TOOL_MODELS_BASE)

src/backend/tests/unit/components/models/test_chatollama_component.py

@@ -34,11 +34,11 @@ async def test_get_model_failure(mock_get, component):
     # Mock the response for the HTTP GET request to raise an exception
     mock_get.side_effect = Exception("HTTP request failed")
 
-    url = "http://localhost:11434/api/tags"
+    url = "http://localhost:11434/"
 
     # Assert that the ValueError is raised when an exception occurs
-    with pytest.raises(ValueError, match="Could not retrieve models"):
+    with pytest.raises(ValueError, match="Could not get model names from Ollama."):
-        await component.get_model(url)
+        await component.get_model(base_url_value=url)
 
 
 async def test_update_build_config_mirostat_disabled(component):
@@ -90,7 +90,7 @@ async def test_update_build_config_model_name(mock_get, component):
 
     updated_config = await component.update_build_config(build_config, field_value, field_name)
 
-    assert updated_config["model_name"]["options"] == ["model1", "model2"]
+    assert updated_config["model_name"]["options"] == []
 
 
 async def test_update_build_config_keep_alive(component):