fix: Add max_token param in ModelInput #11464
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WalkthroughThe changes add a new Changes
Sequence Diagram(s)sequenceDiagram
participant User as User/UI
participant Component as LanguageModelComponent
participant BuildModel as build_model()
participant GetLLM as get_llm()
participant Metadata as Provider Metadata
participant Provider as Provider API<br/>(OpenAI/Google/etc)
User->>Component: Set max_tokens input
Component->>BuildModel: Call build_model()
BuildModel->>GetLLM: Call get_llm(model, ..., max_tokens=value)
GetLLM->>Metadata: Lookup max_tokens_field_name<br/>for provider
Metadata-->>GetLLM: Return field name<br/>(e.g., "max_tokens"<br/>or "max_output_tokens")
GetLLM->>Provider: Call with provider-specific<br/>field name and value
Provider-->>GetLLM: Return configured model
GetLLM-->>BuildModel: Return LanguageModel
BuildModel-->>Component: Complete model setup
Component-->>User: Ready for inference
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes Important Pre-merge checks failedPlease resolve all errors before merging. Addressing warnings is optional. ❌ Failed checks (1 error, 3 warnings)
✅ Passed checks (3 passed)
✨ Finishing touches🧪 Generate unit tests (beta)
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #11464 +/- ##
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- Coverage 34.84% 33.21% -1.63%
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Files 1420 1420
Lines 68188 68188
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- Misses 43202 44313 +1111
Partials 1224 1224
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Actionable comments posted: 7
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⚠️ Outside diff range comments (5)
src/backend/base/langflow/initial_setup/starter_projects/Custom Component Generator.json (1)
2549-2558: Exposemax_tokensin the starter project’s node template.The
codestring now definesmax_tokens(Line 2699), but the LanguageModelComponent schema here still omits amax_tokenstemplate entry andfield_orderdoesn’t include it (Line 2549-2558, Line 2624-2890). Importing this starter project will hide the new parameter. Please add the template field and include it infield_order(or regenerate the starter project asset from the updated component definitions).🔧 Suggested update to surface `max_tokens` in the UI ordering
"field_order": [ "model", "api_key", "base_url_ibm_watsonx", "project_id", "ollama_base_url", "input_value", "system_message", "stream", - "temperature" + "temperature", + "max_tokens" ],Also applies to: 2624-2890
src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json (1)
3360-3716: Addmax_tokensto the serialized template/field order so the starter project exposes it.Line 3525 adds the IntInput in the embedded component code, but Line 3375 (field_order) and Line 3686+ (template) still omit it. That means this starter project likely loads without the new field, so users can’t configure
max_tokens.🛠️ Suggested update to keep the starter project template in sync
@@ - "field_order": [ - "model", - "api_key", - "base_url_ibm_watsonx", - "project_id", - "ollama_base_url", - "input_value", - "system_message", - "stream", - "temperature" - ], + "field_order": [ + "model", + "api_key", + "base_url_ibm_watsonx", + "project_id", + "ollama_base_url", + "input_value", + "system_message", + "stream", + "temperature", + "max_tokens" + ], @@ "temperature": { "_input_type": "SliderInput", "advanced": true, "display_name": "Temperature", "dynamic": false, "info": "Controls randomness in responses", "max_label": "", "max_label_icon": "", "min_label": "", "min_label_icon": "", "name": "temperature", "override_skip": false, "placeholder": "", "range_spec": { "max": 1, "min": 0, "step": 0.01, "step_type": "float" }, "required": false, "show": true, "slider_buttons": false, "slider_buttons_options": [], "slider_input": false, "title_case": false, "tool_mode": false, "track_in_telemetry": false, "type": "slider", "value": 0.1 - } + }, + "max_tokens": { + "_input_type": "IntInput", + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "Maximum number of tokens to generate. Field name varies by provider.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "tool_mode": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }src/backend/tests/unit/components/models_and_agents/test_language_model_component.py (1)
172-203: Fix provider label inconsistency: "Google" should be "Google Generative AI" on lines 260 and 385.Lines 260 and 385 in the same test file use
"provider": "Google", which is inconsistent with line 176 ("Google Generative AI") and with the canonical provider string used throughout the codebase (test_unified_models.py, test_models_api.py, test_models_enabled_providers.py, test_embedding_model_component.py, and starter projects all use"Google Generative AI"). Update lines 260 and 385 to use the same provider label for consistency.src/lfx/src/lfx/base/models/unified_models.py (2)
917-995:max_tokens_field_nameisn’t present in options metadata used by the UI.Line 991 looks only at
metadata.get("max_tokens_field_name"), butget_language_model_optionsdoesn’t inject that field into each option’s metadata. For models selected via the UI, this will fall back to"max_tokens"and ignore provider-specific names. Consider adding a fallback to provider metadata (or adding the field when building options) so the mapping is honored.🔧 Suggested fix (fallback to provider metadata)
- if max_tokens is not None: - max_tokens_param = metadata.get("max_tokens_field_name", "max_tokens") - kwargs[max_tokens_param] = max_tokens + if max_tokens is not None: + provider_meta = model_provider_metadata.get(provider, {}) + max_tokens_param = ( + metadata.get("max_tokens_field_name") + or provider_meta.get("max_tokens_field_name", "max_tokens") + ) + kwargs[max_tokens_param] = max_tokens
63-92: Fix incorrect max_tokens field names for Ollama and IBM WatsonX.The current field name mappings contain critical errors that will cause runtime failures:
- Ollama (line 85): should be
"num_predict", not"max_tokens"(LangChain ChatOllama reference)- IBM WatsonX (line 91): should be
"max_completion_tokens", not"max_tokens"(ChatWatsonx chat models usemax_completion_tokensparameter)The other providers are correct (OpenAI and Anthropic use
max_tokens; Google Generative AI usesmax_output_tokens). Passing unsupported kwargs will cause model instantiation to fail.
🤖 Fix all issues with AI agents
In `@src/backend/base/langflow/initial_setup/starter_projects/Blog` Writer.json:
- Line 1571: The template is missing the serialized IntInput for max_tokens and
its entry in field_order, so the UI won't show the max_tokens input; update the
serialized template for LanguageModelComponent to include the IntInput
definition corresponding to the IntInput(name="max_tokens", display_name="Max
Tokens", ...) and add "max_tokens" to the component's field_order array (e.g.,
place it after "temperature") so build_model and update_build_config can find
and use getattr(self, "max_tokens", None) correctly.
In `@src/backend/base/langflow/initial_setup/starter_projects/Instagram`
Copywriter.json:
- Line 2747: The starter project JSON adds a max_tokens input to the
LanguageModelComponent but the node template's field_order and template inputs
don't include "max_tokens", so the UI won't show it; update the JSON templates
for both LanguageModelComponent nodes to include "max_tokens" in their
field_order arrays and add a corresponding input entry in each node's template
inputs (matching the Multiline/IntInput definition used in
LanguageModelComponent) so the stored template and runtime component stay in
sync.
In `@src/backend/base/langflow/initial_setup/starter_projects/Meeting`
Summary.json:
- Line 3209: The LanguageModelComponent now exposes a max_tokens input but the
serialized node templates are missing it; update the template and field_order
for both LanguageModelComponent-cPCaH and LanguageModelComponent-mMKmF to
include "max_tokens" so the control appears in the UI. Locate the serialized
nodes for LanguageModelComponent (ids LanguageModelComponent-cPCaH and
LanguageModelComponent-mMKmF) and add "max_tokens" to their template dict (with
corresponding default/value entry) and insert "max_tokens" into the field_order
array in the appropriate position consistent with other inputs (e.g., alongside
temperature/stream). Ensure the field name matches exactly "max_tokens" so
build_model/getattr(getter) picks it up.
In `@src/backend/base/langflow/initial_setup/starter_projects/Memory`
Chatbot.json:
- Line 1449: The template JSON is missing the max_tokens input metadata even
though LanguageModelComponent defines an IntInput named "max_tokens" and
build_model() passes it to get_llm(); add a corresponding "max_tokens" field to
the template's inputs section next to "temperature" including the same
properties (name "max_tokens", display_name "Max Tokens", info, advanced true)
so the UI exposes it and aligns with LanguageModelComponent and get_llm usage.
In `@src/backend/base/langflow/initial_setup/starter_projects/Research`
Agent.json:
- Line 2255: The node template is missing a max_tokens input and therefore the
LanguageModelComponent's new max_tokens setting isn't configurable; add a new
IntInput definition named "max_tokens" (matching the
LanguageModelComponent.inputs entry) to each LanguageModelComponent node
template and insert "max_tokens" into the node's field_order array (ensure
placement matches other advanced fields like temperature/stream), updating both
LanguageModelComponent node entries so saved flows render and persist the
max_tokens value.
In `@src/backend/base/langflow/initial_setup/starter_projects/Research`
Translation Loop.json:
- Line 1091: The template JSON is missing the max_tokens field metadata even
though LanguageModelComponent defines an IntInput named "max_tokens"; add a
corresponding entry for max_tokens into the template's fields array and include
"max_tokens" in the template's field_order (place it near "temperature") so the
IntInput appears in the UI; update the template metadata to mirror the IntInput
properties (name="max_tokens", display_name, info, advanced flag if applicable)
to match the component's definition.
In `@src/backend/base/langflow/initial_setup/starter_projects/SEO` Keyword
Generator.json:
- Line 1102: The template metadata is missing the "max_tokens" field in its
field_order so the IntInput named max_tokens (declared in LanguageModelComponent
and used in build_model()) doesn't show in the UI; update the component/template
metadata's field_order array to include "max_tokens" immediately after
"temperature" so the field appears and respects the intended ordering.
🧹 Nitpick comments (3)
src/lfx/src/lfx/components/models_and_agents/language_model.py (1)
92-107: Add validation formax_tokensto enforce positive integer requirement across all providers.
Currently, any integer including negatives and zero can be passed through. All major LLM providers (OpenAI, Anthropic, Google Gemini, IBM watsonx) requiremax_tokensto be a positive integer (≥ 1). Add early validation to fail fast and improve UX rather than letting provider-side errors occur.♻️ Proposed refactor
- def build_model(self) -> LanguageModel: - return get_llm( + def build_model(self) -> LanguageModel: + max_tokens = getattr(self, "max_tokens", None) + if max_tokens is not None and max_tokens < 1: + raise ValueError("max_tokens must be a positive integer.") + return get_llm( model=self.model, user_id=self.user_id, api_key=self.api_key, temperature=self.temperature, stream=self.stream, - max_tokens=getattr(self, "max_tokens", None), + max_tokens=max_tokens, watsonx_url=getattr(self, "base_url_ibm_watsonx", None), watsonx_project_id=getattr(self, "project_id", None), ollama_base_url=getattr(self, "ollama_base_url", None), )src/backend/base/langflow/initial_setup/starter_projects/Text Sentiment Analysis.json (1)
1508-1517: Optional: Consider addingmax_tokenstofield_orderfor consistency.The
field_orderarray doesn't include the newmax_tokensfield, while other advanced inputs liketemperatureandstreamare listed. Sincemax_tokensis marked asadvanced=True, it will still appear correctly in the advanced section, so this is purely a consistency suggestion.src/lfx/src/lfx/_assets/component_index.json (1)
89759-89762: Normalizemax_tokensbefore callingget_llm.
The default config leaves the value blank, so a defensive cast avoids passing empty strings or non‑positive values downstream.♻️ Proposed fix
def build_model(self) -> LanguageModel: - return get_llm( + max_tokens = getattr(self, "max_tokens", None) + if not isinstance(max_tokens, int) or max_tokens <= 0: + max_tokens = None + return get_llm( model=self.model, user_id=self.user_id, api_key=self.api_key, temperature=self.temperature, stream=self.stream, - max_tokens=getattr(self, "max_tokens", None), + max_tokens=max_tokens, watsonx_url=getattr(self, "base_url_ibm_watsonx", None), watsonx_project_id=getattr(self, "project_id", None), ollama_base_url=getattr(self, "ollama_base_url", None), )
| "title_case": false, | ||
| "type": "code", | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import IntInput, MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n info=\"Maximum number of tokens to generate. Field name varies by provider.\",\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n max_tokens=getattr(self, \"max_tokens\", None),\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" |
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#!/bin/bash
python - <<'PY'
import json
from pathlib import Path
path = Path("src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json")
data = json.loads(path.read_text())
for node in data["data"]["nodes"]:
if str(node.get("id","")).startswith("LanguageModelComponent-"):
tmpl = node["data"]["node"]["template"]
print("node id:", node["id"])
print("has max_tokens key:", "max_tokens" in tmpl)
print("field_order:", node["data"]["node"].get("field_order", []))
if "max_tokens" in tmpl:
print("max_tokens config:", json.dumps(tmpl["max_tokens"], indent=2))
PYRepository: langflow-ai/langflow
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Add max_tokens field to the template and include it in field_order.
The embedded LanguageModelComponent code defines an IntInput for max_tokens, but the serialized template is missing both the field definition in the template object and the max_tokens entry in field_order (which currently ends with "temperature"). Without these, the UI will not expose the max_tokens input to users.
🤖 Prompt for AI Agents
In `@src/backend/base/langflow/initial_setup/starter_projects/Blog` Writer.json at
line 1571, The template is missing the serialized IntInput for max_tokens and
its entry in field_order, so the UI won't show the max_tokens input; update the
serialized template for LanguageModelComponent to include the IntInput
definition corresponding to the IntInput(name="max_tokens", display_name="Max
Tokens", ...) and add "max_tokens" to the component's field_order array (e.g.,
place it after "temperature") so build_model and update_build_config can find
and use getattr(self, "max_tokens", None) correctly.
| "title_case": false, | ||
| "type": "code", | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import IntInput, MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n info=\"Maximum number of tokens to generate. Field name varies by provider.\",\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n max_tokens=getattr(self, \"max_tokens\", None),\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" |
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Starter project template still omits max_tokens.
Line 2747 adds the max_tokens input in the embedded component code, but the node template/field_order in this JSON doesn’t include a max_tokens field. If the starter project uses the stored template (as it does for other inputs), the UI won’t expose the new control. Please add max_tokens to field_order and the template inputs for both LanguageModelComponent nodes (or confirm templates are rehydrated on load).
🤖 Prompt for AI Agents
In `@src/backend/base/langflow/initial_setup/starter_projects/Instagram`
Copywriter.json at line 2747, The starter project JSON adds a max_tokens input
to the LanguageModelComponent but the node template's field_order and template
inputs don't include "max_tokens", so the UI won't show it; update the JSON
templates for both LanguageModelComponent nodes to include "max_tokens" in their
field_order arrays and add a corresponding input entry in each node's template
inputs (matching the Multiline/IntInput definition used in
LanguageModelComponent) so the stored template and runtime component stay in
sync.
| "title_case": false, | ||
| "type": "code", | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import IntInput, MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n info=\"Maximum number of tokens to generate. Field name varies by provider.\",\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n max_tokens=getattr(self, \"max_tokens\", None),\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" |
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🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
python - <<'PY'
import json
from pathlib import Path
path = Path("src/backend/base/langflow/initial_setup/starter_projects/Meeting Summary.json")
data = json.loads(path.read_text())
lm_nodes = [n for n in data["data"]["nodes"] if n.get("data", {}).get("type") == "LanguageModelComponent"]
for n in lm_nodes:
node = n["data"]["node"]
tmpl = node.get("template", {})
field_order = node.get("field_order", [])
print(
n["id"],
"max_tokens_in_template:", "max_tokens" in tmpl,
"max_tokens_in_field_order:", "max_tokens" in field_order,
)
PYRepository: langflow-ai/langflow
Length of output: 247
Update template and field_order to expose max_tokens for LanguageModelComponent nodes.
The embedded code at line 3209 now defines and uses max_tokens, but both LanguageModelComponent nodes (LanguageModelComponent-cPCaH and LanguageModelComponent-mMKmF) are missing max_tokens from their serialized template and field_order. This will prevent the max_tokens control from appearing in the UI. Add max_tokens to both nodes' template and field_order to match the updated code.
🤖 Prompt for AI Agents
In `@src/backend/base/langflow/initial_setup/starter_projects/Meeting`
Summary.json at line 3209, The LanguageModelComponent now exposes a max_tokens
input but the serialized node templates are missing it; update the template and
field_order for both LanguageModelComponent-cPCaH and
LanguageModelComponent-mMKmF to include "max_tokens" so the control appears in
the UI. Locate the serialized nodes for LanguageModelComponent (ids
LanguageModelComponent-cPCaH and LanguageModelComponent-mMKmF) and add
"max_tokens" to their template dict (with corresponding default/value entry) and
insert "max_tokens" into the field_order array in the appropriate position
consistent with other inputs (e.g., alongside temperature/stream). Ensure the
field name matches exactly "max_tokens" so build_model/getattr(getter) picks it
up.
| "title_case": false, | ||
| "type": "code", | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import IntInput, MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n info=\"Maximum number of tokens to generate. Field name varies by provider.\",\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n max_tokens=getattr(self, \"max_tokens\", None),\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" |
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🧩 Analysis chain
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#!/bin/bash
# Check if the file exists and get its size
if [ -f "src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json" ]; then
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fiRepository: langflow-ai/langflow
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sed -n '1300,1700p' "src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json" | grep -A 20 '"max_tokens"' | head -30Repository: langflow-ai/langflow
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echo "=== Fields in template (from previous output) ==="
echo "base_url_ibm_watsonx, code, input_value, model, ollama_base_url, project_id, stream, system_message, temperature"
echo ""
echo "=== Fields defined in code string ==="
rg -o '"name":"[^"]+' "src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json" | grep -A 1 'IntInput\|StrInput\|MessageInput\|ModelInput\|SliderInput\|MultilineInput\|BoolInput\|SecretStrInput\|DropdownInput' | grep 'name' | head -20Repository: langflow-ai/langflow
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# Search for max_tokens in the entire JSON file to see if it's defined anywhere
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Add max_tokens field to the template metadata.
The Language Model code string defines max_tokens as an IntInput with advanced=True, and the build_model() method passes it to get_llm(). However, this field is not exposed in the template section of the JSON. Add the max_tokens field definition to the template alongside temperature to make it available in the UI.
🤖 Prompt for AI Agents
In `@src/backend/base/langflow/initial_setup/starter_projects/Memory` Chatbot.json
at line 1449, The template JSON is missing the max_tokens input metadata even
though LanguageModelComponent defines an IntInput named "max_tokens" and
build_model() passes it to get_llm(); add a corresponding "max_tokens" field to
the template's inputs section next to "temperature" including the same
properties (name "max_tokens", display_name "Max Tokens", info, advanced true)
so the UI exposes it and aligns with LanguageModelComponent and get_llm usage.
| "title_case": false, | ||
| "type": "code", | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import IntInput, MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n info=\"Maximum number of tokens to generate. Field name varies by provider.\",\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n max_tokens=getattr(self, \"max_tokens\", None),\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" |
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Expose max_tokens in the node template so the new input is actually configurable.
The embedded component code adds max_tokens, but this starter project’s node template doesn’t define a max_tokens field or include it in field_order for either LanguageModelComponent node. In saved flows, inputs render from the node template, so the new setting can be hidden.
Please add the max_tokens field definition and include it in field_order for both LanguageModelComponent nodes (or regenerate the starter project template).
🛠️ Example JSON edits (apply to both LanguageModelComponent nodes)
"field_order": [
"model",
"api_key",
"base_url_ibm_watsonx",
"project_id",
"ollama_base_url",
"input_value",
"system_message",
"stream",
- "temperature"
+ "temperature",
+ "max_tokens"
],
...
"temperature": {
"_input_type": "SliderInput",
...
"value": 0.1
},
+ "max_tokens": {
+ "_input_type": "IntInput",
+ "advanced": true,
+ "display_name": "Max Tokens",
+ "dynamic": false,
+ "info": "Maximum number of tokens to generate. Field name varies by provider.",
+ "list": false,
+ "list_add_label": "Add More",
+ "name": "max_tokens",
+ "placeholder": "",
+ "required": false,
+ "show": true,
+ "title_case": false,
+ "tool_mode": false,
+ "trace_as_metadata": true,
+ "type": "int",
+ "value": null
+ }Also applies to: 2632-2632
🤖 Prompt for AI Agents
In `@src/backend/base/langflow/initial_setup/starter_projects/Research` Agent.json
at line 2255, The node template is missing a max_tokens input and therefore the
LanguageModelComponent's new max_tokens setting isn't configurable; add a new
IntInput definition named "max_tokens" (matching the
LanguageModelComponent.inputs entry) to each LanguageModelComponent node
template and insert "max_tokens" into the node's field_order array (ensure
placement matches other advanced fields like temperature/stream), updating both
LanguageModelComponent node entries so saved flows render and persist the
max_tokens value.
| "title_case": false, | ||
| "type": "code", | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import IntInput, MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n info=\"Maximum number of tokens to generate. Field name varies by provider.\",\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n max_tokens=getattr(self, \"max_tokens\", None),\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" |
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🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
python3 <<'PY'
import json
import pathlib
path = pathlib.Path("src/backend/base/langflow/initial_setup/starter_projects/Research Translation Loop.json")
try:
data = json.loads(path.read_text())
# Search for LanguageModelComponent node
found = False
for node in data.get("data", {}).get("nodes", []):
node_data = node.get("data", {})
node_type = node_data.get("type")
node_obj = node_data.get("node", {})
display_name = node_obj.get("display_name")
if node_type == "LanguageModelComponent" or display_name == "Language Model":
found = True
print(f"=== Found node: {display_name} (type: {node_type}) ===")
template = node_obj.get("template", {})
print(f"\nTemplate fields present: {list(template.keys())}")
print(f"\n'max_tokens' in template: {'max_tokens' in template}")
field_order = node_obj.get("field_order", [])
print(f"\nfield_order: {field_order}")
if "max_tokens" in template:
print(f"\nmax_tokens config: {json.dumps(template['max_tokens'], indent=2)}")
break
if not found:
print("LanguageModelComponent node not found. Searching for 'Language Model' by display name...")
# Try broader search
for node in data.get("data", {}).get("nodes", []):
if "Language Model" in str(node):
print("Found node containing 'Language Model':", node.get("data", {}).get("node", {}).get("display_name"))
except Exception as e:
print(f"Error: {e}")
PYRepository: langflow-ai/langflow
Length of output: 559
Add max_tokens to the template metadata.
The LanguageModelComponent code defines max_tokens as an IntInput, but it's missing from the JSON template metadata. The template fields do not include max_tokens, and it's absent from field_order as well. This will prevent the field from appearing in the UI. Add the max_tokens field configuration to the template alongside temperature.
🤖 Prompt for AI Agents
In `@src/backend/base/langflow/initial_setup/starter_projects/Research`
Translation Loop.json at line 1091, The template JSON is missing the max_tokens
field metadata even though LanguageModelComponent defines an IntInput named
"max_tokens"; add a corresponding entry for max_tokens into the template's
fields array and include "max_tokens" in the template's field_order (place it
near "temperature") so the IntInput appears in the UI; update the template
metadata to mirror the IntInput properties (name="max_tokens", display_name,
info, advanced flag if applicable) to match the component's definition.
| "title_case": false, | ||
| "type": "code", | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" | ||
| "value": "from lfx.base.models.model import LCModelComponent\nfrom lfx.base.models.unified_models import (\n get_language_model_options,\n get_llm,\n update_model_options_in_build_config,\n)\nfrom lfx.base.models.watsonx_constants import IBM_WATSONX_URLS\nfrom lfx.field_typing import LanguageModel\nfrom lfx.field_typing.range_spec import RangeSpec\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, StrInput\nfrom lfx.io import IntInput, MessageInput, ModelInput, MultilineInput, SecretStrInput, SliderInput\n\nDEFAULT_OLLAMA_URL = \"http://localhost:11434\"\n\n\nclass LanguageModelComponent(LCModelComponent):\n display_name = \"Language Model\"\n description = \"Runs a language model given a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-models\"\n icon = \"brain-circuit\"\n category = \"models\"\n priority = 0 # Set priority to 0 to make it appear first\n\n inputs = [\n ModelInput(\n name=\"model\",\n display_name=\"Language Model\",\n info=\"Select your model provider\",\n real_time_refresh=True,\n required=True,\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"API Key\",\n info=\"Model Provider API key\",\n required=False,\n show=True,\n real_time_refresh=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"base_url_ibm_watsonx\",\n display_name=\"watsonx API Endpoint\",\n info=\"The base URL of the API (IBM watsonx.ai only)\",\n options=IBM_WATSONX_URLS,\n value=IBM_WATSONX_URLS[0],\n show=False,\n real_time_refresh=True,\n ),\n StrInput(\n name=\"project_id\",\n display_name=\"watsonx Project ID\",\n info=\"The project ID associated with the foundation model (IBM watsonx.ai only)\",\n show=False,\n required=False,\n ),\n MessageInput(\n name=\"ollama_base_url\",\n display_name=\"Ollama API URL\",\n info=f\"Endpoint of the Ollama API (Ollama only). Defaults to {DEFAULT_OLLAMA_URL}\",\n value=DEFAULT_OLLAMA_URL,\n show=False,\n real_time_refresh=True,\n load_from_db=True,\n ),\n MessageInput(\n name=\"input_value\",\n display_name=\"Input\",\n info=\"The input text to send to the model\",\n ),\n MultilineInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"A system message that helps set the behavior of the assistant\",\n advanced=False,\n ),\n BoolInput(\n name=\"stream\",\n display_name=\"Stream\",\n info=\"Whether to stream the response\",\n value=False,\n advanced=True,\n ),\n SliderInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n value=0.1,\n info=\"Controls randomness in responses\",\n range_spec=RangeSpec(min=0, max=1, step=0.01),\n advanced=True,\n ),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n info=\"Maximum number of tokens to generate. Field name varies by provider.\",\n advanced=True,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n return get_llm(\n model=self.model,\n user_id=self.user_id,\n api_key=self.api_key,\n temperature=self.temperature,\n stream=self.stream,\n max_tokens=getattr(self, \"max_tokens\", None),\n watsonx_url=getattr(self, \"base_url_ibm_watsonx\", None),\n watsonx_project_id=getattr(self, \"project_id\", None),\n ollama_base_url=getattr(self, \"ollama_base_url\", None),\n )\n\n def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):\n \"\"\"Dynamically update build config with user-filtered model options.\"\"\"\n # Update model options\n build_config = update_model_options_in_build_config(\n component=self,\n build_config=build_config,\n cache_key_prefix=\"language_model_options\",\n get_options_func=get_language_model_options,\n field_name=field_name,\n field_value=field_value,\n )\n\n # Show/hide provider-specific fields based on selected model\n # Get current model value - from field_value if model is being changed, otherwise from build_config\n current_model_value = field_value if field_name == \"model\" else build_config.get(\"model\", {}).get(\"value\")\n if isinstance(current_model_value, list) and len(current_model_value) > 0:\n selected_model = current_model_value[0]\n provider = selected_model.get(\"provider\", \"\")\n\n # Show/hide watsonx fields\n is_watsonx = provider == \"IBM WatsonX\"\n build_config[\"base_url_ibm_watsonx\"][\"show\"] = is_watsonx\n build_config[\"project_id\"][\"show\"] = is_watsonx\n build_config[\"base_url_ibm_watsonx\"][\"required\"] = is_watsonx\n build_config[\"project_id\"][\"required\"] = is_watsonx\n\n # Show/hide Ollama fields\n is_ollama = provider == \"Ollama\"\n build_config[\"ollama_base_url\"][\"show\"] = is_ollama\n\n return build_config\n" |
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🏁 Script executed:
# First, find the exact line and surrounding context to understand the JSON structure
wc -l src/backend/base/langflow/initial_setup/starter_projects/SEO\ Keyword\ Generator.jsonRepository: langflow-ai/langflow
Length of output: 152
🏁 Script executed:
# Read the file around line 1102 to see the full context
sed -n '1090,1150p' src/backend/base/langflow/initial_setup/starter_projects/SEO\ Keyword\ Generator.jsonRepository: langflow-ai/langflow
Length of output: 7879
🏁 Script executed:
# Search for max_tokens references in the file
rg "max_tokens" src/backend/base/langflow/initial_setup/starter_projects/SEO\ Keyword\ Generator.json -nRepository: langflow-ai/langflow
Length of output: 5784
🏁 Script executed:
# Look at the LanguageModelComponent section to understand template structure
# Search for the component definition containing this code
rg -A 50 '"display_name".*"Language Model"' src/backend/base/langflow/initial_setup/starter_projects/SEO\ Keyword\ Generator.json | head -100Repository: langflow-ai/langflow
Length of output: 3486
Add max_tokens to the template's field_order array.
The Language Model component code defines max_tokens as an IntInput and uses it in the build_model() method, but it's missing from the field_order array in the template metadata. This prevents the field from appearing in the UI. Add "max_tokens" to field_order after "temperature".
🤖 Prompt for AI Agents
In `@src/backend/base/langflow/initial_setup/starter_projects/SEO` Keyword
Generator.json at line 1102, The template metadata is missing the "max_tokens"
field in its field_order so the IntInput named max_tokens (declared in
LanguageModelComponent and used in build_model()) doesn't show in the UI; update
the component/template metadata's field_order array to include "max_tokens"
immediately after "temperature" so the field appears and respects the intended
ordering.
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