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Ibis Prevedello 2023-04-10 10:20:56 -03:00
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2
CONTRIBUTING.md
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@ -1,6 +1,6 @@
# Contributing to LangFlow
Hello there! I appreciate your interest in contributing to LangFlow.
Hello there! We appreciate your interest in contributing to LangFlow.
As an open-source project in a rapidly developing field, we are extremely open
to contributions, whether it be in the form of a new feature, improved infra, or better documentation.

2
README.md
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@ -49,7 +49,7 @@ flow("Hey, have you heard of LangFlow?")
## 👋 Contributing
We welcome contributions from developers of all levels to our open-source project on GitHub. If you'd like to contribute, please check our contributing guidelines and help make LangFlow more accessible.
We welcome contributions from developers of all levels to our open-source project on GitHub. If you'd like to contribute, please check our [contributing guidelines](./CONTRIBUTING.md) and help make LangFlow more accessible.
[![Star History Chart](https://api.star-history.com/svg?repos=logspace-ai/langflow&type=Timeline)](https://star-history.com/#logspace-ai/langflow&Date)

2
dev.Dockerfile
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@ -3,7 +3,7 @@ FROM python:3.10-slim
WORKDIR /app
# Install Poetry
RUN apt-get update && apt-get install gcc curl build-essential -y
RUN apt-get update && apt-get install gcc g++ curl build-essential -y
RUN curl -sSL https://install.python-poetry.org | python3 -
# # Add Poetry to PATH
ENV PATH="${PATH}:/root/.local/bin"

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poetry.lock generated
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@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
[[package]]
name = "aiohttp"
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[[package]]
@ -4313,4 +4326,4 @@ cffi = ["cffi (>=1.11)"]
[metadata]
lock-version = "2.0"
python-versions = "^3.9"
content-hash = "70e86f7d3b5caed792e37ccf9e11ed95008e5078dd8830e4f8b96cc1d35c7b60"
content-hash = "e591f76a5e2d3b4ff7fe6642ed440d7aa002b7c65777db018928a58a219e9212"

3
pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry]
name = "langflow"
version = "0.0.54"
version = "0.0.55"
description = "A Python package with a built-in web application"
authors = ["Logspace <contact@logspace.ai>"]
maintainers = [
@ -37,6 +37,7 @@ pandas = "^1.5.3"
chromadb = "^0.3.21"
huggingface-hub = "^0.13.3"
rich = "^13.3.3"
llama-cpp-python = "0.1.23"
[tool.poetry.group.dev.dependencies]
black = "^23.1.0"

1
src/backend/langflow/config.yaml
View file

@ -29,6 +29,7 @@ llms:
# - AzureOpenAI
- ChatOpenAI
- HuggingFaceHub
- LlamaCpp
tools:
- Search

9
src/backend/langflow/graph/base.py
View file

@ -4,6 +4,7 @@
# - Build each inner agent first, then build the outer agent
import types
import warnings
from copy import deepcopy
from typing import Any, Dict, List, Optional
@ -119,7 +120,13 @@ class Node:
params[key] = edges[0].source
elif value["required"] or value.get("value"):
params[key] = value["value"]
# If value does not have value this still passes
# but then gives a keyError
# so we need to check if value has value
new_value = value.get("value")
if new_value is None:
warnings.warn(f"Value for {key} in {self.node_type} is None. ")
params[key] = new_value
# Add _type to params
self.params = params

2
src/backend/langflow/graph/constants.py
View file

@ -1 +1 @@
DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any"]
DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any", "prompt"]

6
src/backend/langflow/graph/nodes.py
View file

@ -54,7 +54,10 @@ class PromptNode(Node):
tools: Optional[Union[List[Node], List[ToolNode]]] = None,
) -> Any:
if not self._built or force:
if "input_variables" not in self.params:
if (
"input_variables" not in self.params
or self.params["input_variables"] is None
):
self.params["input_variables"] = []
# Check if it is a ZeroShotPrompt and needs a tool
if "ShotPrompt" in self.node_type:
@ -74,7 +77,6 @@ class PromptNode(Node):
for param in prompt_params:
prompt_text = self.params[param]
variables = extract_input_variables_from_prompt(prompt_text)
self.params["input_variables"].extend(variables)
self.params["input_variables"] = list(set(self.params["input_variables"]))

7
src/backend/langflow/interface/chains/base.py
View file

@ -1,9 +1,10 @@
from typing import Dict, List, Optional
from typing import Dict, List, Optional, Type
from langflow.custom.customs import get_custom_nodes
from langflow.interface.base import LangChainTypeCreator
from langflow.interface.custom_lists import chain_type_to_cls_dict
from langflow.settings import settings
from langflow.template.nodes import ChainFrontendNode
from langflow.utils.util import build_template_from_class
# Assuming necessary imports for Field, Template, and FrontendNode classes
@ -12,6 +13,10 @@ from langflow.utils.util import build_template_from_class
class ChainCreator(LangChainTypeCreator):
type_name: str = "chains"
@property
def frontend_node_class(self) -> Type[ChainFrontendNode]:
return ChainFrontendNode
@property
def type_to_loader_dict(self) -> Dict:
if self.type_dict is None:

7
src/backend/langflow/interface/llms/base.py
View file

@ -1,14 +1,19 @@
from typing import Dict, List, Optional
from typing import Dict, List, Optional, Type
from langflow.interface.base import LangChainTypeCreator
from langflow.interface.custom_lists import llm_type_to_cls_dict
from langflow.settings import settings
from langflow.template.nodes import LLMFrontendNode
from langflow.utils.util import build_template_from_class
class LLMCreator(LangChainTypeCreator):
type_name: str = "llms"
@property
def frontend_node_class(self) -> Type[LLMFrontendNode]:
return LLMFrontendNode
@property
def type_to_loader_dict(self) -> Dict:
if self.type_dict is None:

28
src/backend/langflow/interface/tools/base.py
View file

@ -73,9 +73,14 @@ class ToolCreator(LangChainTypeCreator):
base_classes = ["Tool"]
all_tools = {}
for tool in self.type_to_loader_dict.keys():
if tool_params := get_tool_params(get_tool_by_name(tool)):
tool_fcn = get_tool_by_name(tool)
if tool_params := get_tool_params(tool_fcn):
tool_name = tool_params.get("name") or str(tool)
all_tools[tool_name] = {"type": tool, "params": tool_params}
all_tools[tool_name] = {
"type": tool,
"params": tool_params,
"fcn": tool_fcn,
}
# Raise error if name is not in tools
if name not in all_tools.keys():
@ -83,15 +88,21 @@ class ToolCreator(LangChainTypeCreator):
tool_type: str = all_tools[name]["type"] # type: ignore
if tool_type in _BASE_TOOLS:
if all_tools[tool_type]["fcn"] in _BASE_TOOLS.values():
params = []
elif tool_type in _LLM_TOOLS:
elif all_tools[tool_type]["fcn"] in _LLM_TOOLS.values():
params = ["llm"]
elif tool_type in _EXTRA_LLM_TOOLS:
_, extra_keys = _EXTRA_LLM_TOOLS[tool_type]
elif all_tools[tool_type]["fcn"] in [
val[0] for val in _EXTRA_LLM_TOOLS.values()
]:
n_dict = {val[0]: val[1] for val in _EXTRA_LLM_TOOLS.values()}
extra_keys = n_dict[all_tools[tool_type]["fcn"]]
params = ["llm"] + extra_keys
elif tool_type in _EXTRA_OPTIONAL_TOOLS:
_, extra_keys = _EXTRA_OPTIONAL_TOOLS[tool_type]
elif all_tools[tool_type]["fcn"] in [
val[0] for val in _EXTRA_OPTIONAL_TOOLS.values()
]:
n_dict = {val[0]: val[1] for val in _EXTRA_OPTIONAL_TOOLS.values()} # type: ignore
extra_keys = n_dict[all_tools[tool_type]["fcn"]]
params = extra_keys
elif tool_type == "Tool":
params = ["name", "description", "func"]
@ -104,7 +115,6 @@ class ToolCreator(LangChainTypeCreator):
elif tool_type in FILE_TOOLS:
params = all_tools[name]["params"] # type: ignore
base_classes += [name]
else:
params = []

38
src/backend/langflow/template/nodes.py
View file

@ -345,3 +345,41 @@ class MemoryFrontendNode(FrontendNode):
field.field_type = "int"
field.value = 10
field.display_name = "Memory Size"
class ChainFrontendNode(FrontendNode):
@staticmethod
def format_field(field: TemplateField, name: Optional[str] = None) -> None:
FrontendNode.format_field(field, name)
if "key" in field.name:
field.password = False
field.show = False
class LLMFrontendNode(FrontendNode):
@staticmethod
def format_field(field: TemplateField, name: Optional[str] = None) -> None:
display_names_dict = {
"huggingfacehub_api_token": "HuggingFace Hub API Token",
}
FrontendNode.format_field(field, name)
SHOW_FIELDS = ["repo_id", "task", "model_kwargs"]
if field.name in SHOW_FIELDS:
field.show = True
if "api" in field.name and ("key" in field.name or "token" in field.name):
field.password = True
field.show = True
field.required = True
if field.name == "task":
field.required = True
field.show = True
field.is_list = True
field.options = ["text-generation", "text2text-generation"]
if display_name := display_names_dict.get(field.name):
field.display_name = display_name
if field.name == "model_kwargs":
field.field_type = "code"

30
tests/test_graph.py
View file

@ -1,4 +1,5 @@
import json
from typing import Type, Union
import pytest
from langchain.agents import AgentExecutor
@ -14,6 +15,8 @@ from langflow.graph.nodes import (
WrapperNode,
)
from langflow.utils.payload import build_json, get_root_node
from langflow.interface.run import get_result_and_thought_using_graph
from langchain.llms.fake import FakeListLLM
# Test cases for the graph module
@ -53,7 +56,7 @@ def openapi_graph():
return get_graph("openapi")
def get_node_by_type(graph, node_type):
def get_node_by_type(graph, node_type: Type[Node]) -> Union[Node, None]:
"""Get a node by type"""
return next((node for node in graph.nodes if isinstance(node, node_type)), None)
@ -418,3 +421,28 @@ def test_wrapper_node_build(openapi_graph):
built_object = wrapper_node.build()
assert built_object is not None
# Add any further assertions specific to the WrapperNode's build() method
def test_get_result_and_thought(basic_graph):
"""Test the get_result_and_thought method"""
responses = [
"Final Answer: I am a response",
]
message = "Hello"
# Find the node that is an LLMNode and change the
# _built_object to a FakeListLLM
llm_node = get_node_by_type(basic_graph, LLMNode)
assert llm_node is not None
llm_node._built_object = FakeListLLM(responses=responses)
llm_node._built = True
langchain_object = basic_graph.build()
# assert all nodes are built
assert all(node._built for node in basic_graph.nodes)
# now build again and check if FakeListLLM was used
# Get the result and thought
result, thought = get_result_and_thought_using_graph(langchain_object, message)
# The result should be a str
assert isinstance(result, str)
# The thought should be a Thought
assert isinstance(thought, str)

18
tests/test_llms_template.py
View file

@ -53,7 +53,7 @@ def test_hugging_face_hub(client: TestClient):
assert template["repo_id"] == {
"required": False,
"placeholder": "",
"show": False,
"show": True,
"multiline": False,
"value": "gpt2",
"password": False,
@ -62,19 +62,20 @@ def test_hugging_face_hub(client: TestClient):
"list": False,
}
assert template["task"] == {
"required": False,
"required": True,
"placeholder": "",
"show": False,
"show": True,
"multiline": False,
"password": False,
"options": ["text-generation", "text2text-generation"],
"name": "task",
"type": "str",
"list": False,
"list": True,
}
assert template["model_kwargs"] == {
"required": False,
"placeholder": "",
"show": False,
"show": True,
"multiline": False,
"password": False,
"name": "model_kwargs",
@ -82,12 +83,13 @@ def test_hugging_face_hub(client: TestClient):
"list": False,
}
assert template["huggingfacehub_api_token"] == {
"required": False,
"required": True,
"placeholder": "",
"show": True,
"multiline": False,
"password": True,
"name": "huggingfacehub_api_token",
"display_name": "HuggingFace Hub API Token",
"type": "str",
"list": False,
}
@ -231,7 +233,7 @@ def test_openai(client: TestClient):
assert template["model_kwargs"] == {
"required": False,
"placeholder": "",
"show": False,
"show": True,
"multiline": False,
"password": False,
"name": "model_kwargs",
@ -361,7 +363,7 @@ def test_chat_open_ai(client: TestClient):
assert template["model_kwargs"] == {
"required": False,
"placeholder": "",
"show": False,
"show": True,
"multiline": False,
"password": False,
"name": "model_kwargs",