Merge branch 'python_custom_node_component' of personal:logspace-ai/langflow into python_custom_node_component

src/backend/langflow/api/extract_info_from_class.py

@@ -71,10 +71,14 @@ class ClassCodeExtractor:
              self.function_entrypoint_name), None
         )
 
-        funtion_args = build_function.get("arguments", None)
-        return_type = build_function.get("return_type", None)
+        if build_function:
+            function_args = build_function.get("arguments", None)
+            return_type = build_function.get("return_type", None)
+        else:
+            function_args = None
+            return_type = None
 
-        return funtion_args, return_type
+        return function_args, return_type
 
 
 def is_valid_class_template(code: dict):

src/backend/langflow/config.yaml

@@ -95,6 +95,7 @@ tools:
   - Calculator
   - Serper Search
   - Tool
+  - CustomComponent
   - PythonFunctionTool
   - PythonFunction
   - JsonSpec

src/backend/langflow/custom/customs.py

@@ -8,6 +8,7 @@ CUSTOM_NODES = {
     "tools": {
         "PythonFunctionTool": frontend_node.tools.PythonFunctionToolNode(),
         "PythonFunction": frontend_node.tools.PythonFunctionNode(),
+        "CustomComponent": frontend_node.tools.CustomComponentNode(),
         "Tool": frontend_node.tools.ToolNode(),
     },
     "agents": {

src/backend/langflow/interface/initialize/loading.py

@@ -131,7 +131,7 @@ def instantiate_tool(node_type, class_object, params):
     if node_type == "JsonSpec":
         params["dict_"] = load_file_into_dict(params.pop("path"))
         return class_object(**params)
-    elif node_type == "PythonFunctionTool":
+    elif node_type in ["PythonFunctionTool", "CustomComponent"]:
         params["func"] = get_function(params.get("code"))
         return class_object(**params)
     # For backward compatibility
@@ -243,7 +243,8 @@ def replace_zero_shot_prompt_with_prompt_template(nodes):
                 if tool["type"] != "chatOutputNode"
                 and "Tool" in tool["data"]["node"]["base_classes"]
             ]
-            node["data"] = build_prompt_template(prompt=node["data"], tools=tools)
+            node["data"] = build_prompt_template(
+                prompt=node["data"], tools=tools)
             break
     return nodes
 
@@ -260,7 +261,8 @@ def load_agent_executor(agent_class: type[agent_module.Agent], params, **kwargs)
     tool_names = [tool.name for tool in allowed_tools]
     # Agent class requires an output_parser but Agent classes
     # have a default output_parser.
-    agent = agent_class(allowed_tools=tool_names, llm_chain=llm_chain)  # type: ignore
+    agent = agent_class(allowed_tools=tool_names,
+                        llm_chain=llm_chain)  # type: ignore
     return AgentExecutor.from_agent_and_tools(
         agent=agent,
         tools=allowed_tools,

src/backend/langflow/interface/tools/constants.py

@@ -9,16 +9,22 @@ from langchain.agents.load_tools import (
 from langchain.tools.json.tool import JsonSpec
 
 from langflow.interface.importing.utils import import_class
-from langflow.interface.tools.custom import PythonFunctionTool, PythonFunction
+from langflow.interface.tools.custom import (
+    PythonFunctionTool,
+    PythonFunction,
+    CustomComponent
+)
 
 FILE_TOOLS = {"JsonSpec": JsonSpec}
 CUSTOM_TOOLS = {
     "Tool": Tool,
+    "CustomComponent": CustomComponent,
     "PythonFunctionTool": PythonFunctionTool,
     "PythonFunction": PythonFunction,
 }
 
-OTHER_TOOLS = {tool: import_class(f"langchain.tools.{tool}") for tool in tools.__all__}
+OTHER_TOOLS = {tool: import_class(f"langchain.tools.{tool}")
+               for tool in tools.__all__}
 
 ALL_TOOLS_NAMES = {
     **_BASE_TOOLS,

src/backend/langflow/interface/tools/custom.py

@@ -52,3 +52,9 @@ class PythonFunction(Function):
     """Python function"""
 
     code: str
+
+
+class CustomComponent(Function):
+    """Python function"""
+
+    code: str

src/backend/langflow/interface/types.py

@@ -12,6 +12,9 @@ from langflow.interface.utilities.base import utility_creator
 from langflow.interface.vector_store.base import vectorstore_creator
 from langflow.interface.wrappers.base import wrapper_creator
 
+from langflow.template.field.base import TemplateField
+from langflow.template.frontend_node.tools import CustomComponentNode
+
 
 def get_type_list():
     """Get a list of all langchain types"""
@@ -54,6 +57,7 @@ def build_langchain_types_dict():  # sourcery skip: dict-assign-update-to-union
     return all_types
 
 
+# TODO: Move to correct place
 def find_class_type(class_name, classes_dict):
     return next(
         (
@@ -65,10 +69,23 @@ def find_class_type(class_name, classes_dict):
     )
 
 
-def build_langchain_template_custom_component(raw_code, function_args, function_return_type):
-    type_list = get_type_list()
-    type_and_class = find_class_type("Tool", type_list)
+# TODO: Move to correct place
+def add_new_custom_field(template, field_name: str, field_type: str):
+    new_field = TemplateField(
+        name=field_name,
+        field_type=field_type,
+        show=True,
+        advanced=False
+    )
+    template.get('template')[field_name] = new_field.to_dict()
+    template.get('custom_fields').append(field_name)
 
+    return template
+
+# TODO: Move to correct place
+
+
+def add_code_field(template, raw_code):
     # Field with the Python code to allow update
     code_field = {
         "code": {
@@ -84,13 +101,47 @@ def build_langchain_template_custom_component(raw_code, function_args, function_
             "list": False
         }
     }
+    template.get('template')['code'] = code_field.get('code')
+
+    return template
+
+
+def build_langchain_template_custom_component(raw_code, function_args, function_return_type):
+    # type_list = get_type_list()
+    # type_and_class = find_class_type("Tool", type_list)
+    # node = get_custom_nodes(node_type: str)
+
+    # TODO: Build base template
+    template = llm_creator.to_dict()['llms']['ChatOpenAI']
+
+    template = CustomComponentNode().to_dict().get('CustomComponent')
 
     # TODO: Add extra fields
+    template = add_new_custom_field(
+        template,
+        "my_id",
+        "str"
+    )
 
-    # TODO: Build template result
-    template = chain_creator.to_dict()['chains']['ConversationChain']
+    template = add_new_custom_field(
+        template,
+        "year",
+        "int"
+    )
 
-    template.get('template')['code'] = code_field.get('code')
+    template = add_new_custom_field(
+        template,
+        "other_field",
+        "bool"
+    )
+
+    template = add_code_field(
+        template,
+        raw_code
+    )
+
+    # criar um vertex
+    # olhar loading.py
 
     return template
     # return globals()['tool_creator'].to_dict()[type_and_class['type']][type_and_class['class']]

src/backend/langflow/template/frontend_node/tools.py

@@ -1,7 +1,10 @@
 from langflow.template.field.base import TemplateField
 from langflow.template.frontend_node.base import FrontendNode
 from langflow.template.template.base import Template
-from langflow.utils.constants import DEFAULT_PYTHON_FUNCTION
+from langflow.utils.constants import (
+    DEFAULT_PYTHON_FUNCTION,
+    DEFAULT_CUSTOM_COMPONENT_CODE
+)
 
 
 class ToolNode(FrontendNode):
@@ -137,3 +140,27 @@ class PythonFunctionNode(FrontendNode):
 
     def to_dict(self):
         return super().to_dict()
+
+
+class CustomComponentNode(FrontendNode):
+    name: str = "CustomComponent"
+    template: Template = Template(
+        type_name="CustomComponent",
+        fields=[
+            TemplateField(
+                field_type="code",
+                required=True,
+                placeholder="",
+                is_list=False,
+                show=True,
+                value=DEFAULT_CUSTOM_COMPONENT_CODE,
+                name="code",
+                advanced=False,
+            )
+        ],
+    )
+    description: str = "Python Class to be executed."
+    base_classes: list[str] = []
+
+    def to_dict(self):
+        return super().to_dict()

src/backend/langflow/utils/constants.py

@@ -17,18 +17,30 @@ CHAT_OPENAI_MODELS = [
 ]
 
 ANTHROPIC_MODELS = [
-    "claude-v1",  # largest model, ideal for a wide range of more complex tasks.
-    "claude-v1-100k",  # An enhanced version of claude-v1 with a 100,000 token (roughly 75,000 word) context window.
-    "claude-instant-v1",  # A smaller model with far lower latency, sampling at roughly 40 words/sec!
-    "claude-instant-v1-100k",  # Like claude-instant-v1 with a 100,000 token context window but retains its performance.
+    # largest model, ideal for a wide range of more complex tasks.
+    "claude-v1",
+    # An enhanced version of claude-v1 with a 100,000 token (roughly 75,000 word) context window.
+    "claude-v1-100k",
+    # A smaller model with far lower latency, sampling at roughly 40 words/sec!
+    "claude-instant-v1",
+    # Like claude-instant-v1 with a 100,000 token context window but retains its performance.
+    "claude-instant-v1-100k",
+
     # Specific sub-versions of the above models:
-    "claude-v1.3",  # Vs claude-v1.2: better instruction-following, code, and non-English dialogue and writing.
-    "claude-v1.3-100k",  # An enhanced version of claude-v1.3 with a 100,000 token (roughly 75,000 word) context window.
-    "claude-v1.2",  # Vs claude-v1.1: small adv in general helpfulness, instruction following, coding, and other tasks.
-    "claude-v1.0",  # An earlier version of claude-v1.
-    "claude-instant-v1.1",  # Latest version of claude-instant-v1. Better than claude-instant-v1.0 at most tasks.
-    "claude-instant-v1.1-100k",  # Version of claude-instant-v1.1 with a 100K token context window.
-    "claude-instant-v1.0",  # An earlier version of claude-instant-v1.
+    # Vs claude-v1.2: better instruction-following, code, and non-English dialogue and writing.
+    "claude-v1.3",
+    # An enhanced version of claude-v1.3 with a 100,000 token (roughly 75,000 word) context window.
+    "claude-v1.3-100k",
+    # Vs claude-v1.1: small adv in general helpfulness, instruction following, coding, and other tasks.
+    "claude-v1.2",
+    # An earlier version of claude-v1.
+    "claude-v1.0",
+    # Latest version of claude-instant-v1. Better than claude-instant-v1.0 at most tasks.
+    "claude-instant-v1.1",
+    # Version of claude-instant-v1.1 with a 100K token context window.
+    "claude-instant-v1.1-100k",
+    # An earlier version of claude-instant-v1.
+    "claude-instant-v1.0",
 ]
 
 DEFAULT_PYTHON_FUNCTION = """
@@ -36,4 +48,12 @@ def python_function(text: str) -> str:
     \"\"\"This is a default python function that returns the input text\"\"\"
     return text
 """
+
+DEFAULT_CUSTOM_COMPONENT_CODE = """
+def custom_component(text: str) -> str:
+    \"\"\"This is a default custom component function that returns the input text\"\"\"
+    \"\"\"TODO: Add a Class template\"\"\"
+    return text
+"""
+
 DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any", "prompt"]