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Merge branch 'add_extra_fields_documentloaders' of https://github.com/logspace-ai/langflow into add_extra_fields_documentloaders

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Alexandre Henrique 2023-06-07 16:52:58 -03:00
commit 5862f19c20
86 changed files with 1915 additions and 773 deletions
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1
Makefile
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@ -43,6 +43,7 @@ install_backend:
poetry install poetry install
backend: backend:
make install_backend
poetry run uvicorn langflow.main:app --port 7860 --reload --log-level debug poetry run uvicorn langflow.main:app --port 7860 --reload --log-level debug
build_frontend: build_frontend:

164
poetry.lock generated
View file

@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand. # This file is automatically @generated by Poetry 1.4.0 and should not be changed by hand.
[[package]] [[package]]
name = "aiofiles" name = "aiofiles"
@ -148,6 +148,27 @@ files = [
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[[package]]
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httpx = "*"
requests = "*"
tokenizers = "*"
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@ -719,14 +740,14 @@ superset = ["apache-superset (>=1.4.1)"]
[[package]] [[package]]
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@ -895,23 +916,23 @@ cffi = ">=1.12"
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pep8test = ["black", "check-manifest", "mypy", "ruff"] nox = ["nox"]
sdist = ["setuptools-rust (>=0.11.4)"] pep8test = ["black", "check-sdist", "mypy", "ruff"]
sdist = ["build"]
ssh = ["bcrypt (>=3.1.5)"] ssh = ["bcrypt (>=3.1.5)"]
test = ["iso8601", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-shard (>=0.1.2)", "pytest-subtests", "pytest-xdist"] test = ["pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
test-randomorder = ["pytest-randomly"] test-randomorder = ["pytest-randomly"]
tox = ["tox"]
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{file = "faiss_cpu-1.7.4-cp39-cp39-win_amd64.whl", hash = "sha256:98459ceeeb735b9df1a5b94572106ffe0a6ce740eb7e4626715dd218657bb4dc"},
]
[[package]] [[package]]
name = "fake-useragent" name = "fake-useragent"
version = "1.1.3" version = "1.1.3"
@ -1211,14 +1265,14 @@ importlib-resources = {version = ">=5.0", markers = "python_version < \"3.10\""}
[[package]] [[package]]
name = "fastapi" name = "fastapi"
version = "0.95.2" version = "0.96.0"
description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
files = [ files = [
{file = "fastapi-0.95.2-py3-none-any.whl", hash = "sha256:d374dbc4ef2ad9b803899bd3360d34c534adc574546e25314ab72c0c4411749f"}, {file = "fastapi-0.96.0-py3-none-any.whl", hash = "sha256:b8e11fe81e81eab4e1504209917338e0b80f783878a42c2b99467e5e1019a1e9"},
{file = "fastapi-0.95.2.tar.gz", hash = "sha256:4d9d3e8c71c73f11874bcf5e33626258d143252e329a01002f767306c64fb982"}, {file = "fastapi-0.96.0.tar.gz", hash = "sha256:71232d47c2787446991c81c41c249f8a16238d52d779c0e6b43927d3773dbe3c"},
] ]
[package.dependencies] [package.dependencies]
@ -1387,14 +1441,14 @@ uritemplate = ">=3.0.1,<5"
[[package]] [[package]]
name = "google-auth" name = "google-auth"
version = "2.19.0" version = "2.19.1"
description = "Google Authentication Library" description = "Google Authentication Library"
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.6" python-versions = ">=3.6"
files = [ files = [
{file = "google-auth-2.19.0.tar.gz", hash = "sha256:f39d528077ac540793dd3c22a8706178f157642a67d874db25c640b7fead277e"}, {file = "google-auth-2.19.1.tar.gz", hash = "sha256:a9cfa88b3e16196845e64a3658eb953992129d13ac7337b064c6546f77c17183"},
{file = "google_auth-2.19.0-py2.py3-none-any.whl", hash = "sha256:be617bfaf77774008e9d177573f782e109188c8a64ae6e744285df5cea3e7df6"}, {file = "google_auth-2.19.1-py2.py3-none-any.whl", hash = "sha256:ea165e014c7cbd496558796b627c271aa8c18b4cba79dc1cc962b24c5efdfb85"},
] ]
[package.dependencies] [package.dependencies]
@ -2037,14 +2091,14 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio"
[[package]] [[package]]
name = "ipython" name = "ipython"
version = "8.13.2" version = "8.14.0"
description = "IPython: Productive Interactive Computing" description = "IPython: Productive Interactive Computing"
category = "dev" category = "dev"
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
files = [ files = [
{file = "ipython-8.13.2-py3-none-any.whl", hash = "sha256:ffca270240fbd21b06b2974e14a86494d6d29290184e788275f55e0b55914926"}, {file = "ipython-8.14.0-py3-none-any.whl", hash = "sha256:248aca623f5c99a6635bc3857677b7320b9b8039f99f070ee0d20a5ca5a8e6bf"},
{file = "ipython-8.13.2.tar.gz", hash = "sha256:7dff3fad32b97f6488e02f87b970f309d082f758d7b7fc252e3b19ee0e432dbb"}, {file = "ipython-8.14.0.tar.gz", hash = "sha256:1d197b907b6ba441b692c48cf2a3a2de280dc0ac91a3405b39349a50272ca0a1"},
] ]
[package.dependencies] [package.dependencies]
@ -2376,13 +2430,13 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
[[package]] [[package]]
name = "langchain-serve" name = "langchain-serve"
version = "0.0.40" version = "0.0.41"
description = "Langchain Serve - serve your langchain apps on Jina AI Cloud." description = "Langchain Serve - serve your langchain apps on Jina AI Cloud."
category = "main" category = "main"
optional = true optional = true
python-versions = "*" python-versions = "*"
files = [ files = [
{file = "langchain-serve-0.0.40.tar.gz", hash = "sha256:c60b173fcf0b682fbb70d34e8f485ce168e2229f55cb5c4ffbc26a5206af1c06"}, {file = "langchain-serve-0.0.41.tar.gz", hash = "sha256:fcf0d3ac9e48b5b24825ae2e1d8a383795c5744b18ef61cb74a99020a9e5d46a"},
] ]
[package.dependencies] [package.dependencies]
@ -4679,14 +4733,14 @@ idna2008 = ["idna"]
[[package]] [[package]]
name = "rich" name = "rich"
version = "13.3.5" version = "13.4.1"
description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
category = "main" category = "main"
optional = false optional = false
python-versions = ">=3.7.0" python-versions = ">=3.7.0"
files = [ files = [
{file = "rich-13.3.5-py3-none-any.whl", hash = "sha256:69cdf53799e63f38b95b9bf9c875f8c90e78dd62b2f00c13a911c7a3b9fa4704"}, {file = "rich-13.4.1-py3-none-any.whl", hash = "sha256:d204aadb50b936bf6b1a695385429d192bc1fdaf3e8b907e8e26f4c4e4b5bf75"},
{file = "rich-13.3.5.tar.gz", hash = "sha256:2d11b9b8dd03868f09b4fffadc84a6a8cda574e40dc90821bd845720ebb8e89c"}, {file = "rich-13.4.1.tar.gz", hash = "sha256:76f6b65ea7e5c5d924ba80e322231d7cb5b5981aa60bfc1e694f1bc097fe6fe1"},
] ]
[package.dependencies] [package.dependencies]
@ -5100,14 +5154,14 @@ doc = ["reno", "sphinx", "tornado (>=4.5)"]
[[package]] [[package]]
name = "textual" name = "textual"
version = "0.26.0" version = "0.27.0"
description = "Modern Text User Interface framework" description = "Modern Text User Interface framework"
category = "main" category = "main"
optional = true optional = true
python-versions = ">=3.7,<4.0" python-versions = ">=3.7,<4.0"
files = [ files = [
{file = "textual-0.26.0-py3-none-any.whl", hash = "sha256:1efd04e9f61b3e95fd1c65436d3262f99e3f86cdeb524d13045bb551eb615c02"}, {file = "textual-0.27.0-py3-none-any.whl", hash = "sha256:dc45eaf7da330686c56d6f76f59d05fd216ce6aad90fa44ee269881efc622151"},
{file = "textual-0.26.0.tar.gz", hash = "sha256:78094c83017d2836b726513abdf434cc034a0e68cc45e63b3b056c9b8b7fa673"}, {file = "textual-0.27.0.tar.gz", hash = "sha256:8bdcb09dc35a706ef939b1276ccfdec10eaaee6147b41cb7587cf33298a8dd33"},
] ]
[package.dependencies] [package.dependencies]
@ -6180,4 +6234,4 @@ deploy = ["langchain-serve"]
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = ">=3.9,<3.12" python-versions = ">=3.9,<3.12"
content-hash = "2bf357ad30f79c68751b34c991b4a73767ceb628657f4133228d4eb487d8a6fb" content-hash = "4cac7dea0c1222711ba7eed82d5716d5e361d454edb6e0299b387fbb115d2c3d"

15
pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry] [tool.poetry]
name = "langflow" name = "langflow"
version = "0.0.79" version = "0.0.80"
description = "A Python package with a built-in web application" description = "A Python package with a built-in web application"
authors = ["Logspace <contact@logspace.ai>"] authors = ["Logspace <contact@logspace.ai>"]
maintainers = [ maintainers = [
@ -22,7 +22,7 @@ langflow = "langflow.__main__:main"
[tool.poetry.dependencies] [tool.poetry.dependencies]
python = ">=3.9,<3.12" python = ">=3.9,<3.12"
fastapi = "^0.95.0" fastapi = "^0.96.0"
uvicorn = "^0.20.0" uvicorn = "^0.20.0"
beautifulsoup4 = "^4.11.2" beautifulsoup4 = "^4.11.2"
google-search-results = "^2.4.1" google-search-results = "^2.4.1"
@ -57,6 +57,8 @@ jina = "3.15.2"
sentence-transformers = "^2.2.2" sentence-transformers = "^2.2.2"
ctransformers = "^0.2.2" ctransformers = "^0.2.2"
cohere = "^4.6.0" cohere = "^4.6.0"
faiss-cpu = "^1.7.4"
anthropic = "^0.2.9"
[tool.poetry.group.dev.dependencies] [tool.poetry.group.dev.dependencies]
@ -76,6 +78,15 @@ types-pillow = "^9.5.0.2"
[tool.poetry.extras] [tool.poetry.extras]
deploy = ["langchain-serve"] deploy = ["langchain-serve"]
[tool.pytest.ini_options]
minversion = "6.0"
addopts = "-ra"
testpaths = ["tests", "integration"]
console_output_style = "progress"
filterwarnings = ["ignore::DeprecationWarning"]
log_cli = true
[tool.ruff] [tool.ruff]
line-length = 120 line-length = 120

2
src/backend/langflow/__init__.py
View file

@ -1,4 +1,4 @@
from langflow.cache import cache_manager from langflow.cache import cache_manager
from langflow.interface.loading import load_flow_from_json from langflow.processing.process import load_flow_from_json
__all__ = ["load_flow_from_json", "cache_manager"] __all__ = ["load_flow_from_json", "cache_manager"]

3
src/backend/langflow/api/__init__.py
View file

@ -0,0 +1,3 @@
from langflow.api.router import router
__all__ = ["router"]

8
src/backend/langflow/api/router.py Normal file
View file

@ -0,0 +1,8 @@
# Router for base api
from fastapi import APIRouter
from langflow.api.v1 import chat_router, endpoints_router, validate_router
router = APIRouter(prefix="/api/v1", tags=["api"])
router.include_router(chat_router)
router.include_router(endpoints_router)
router.include_router(validate_router)

5
src/backend/langflow/api/v1/__init__.py Normal file
View file

@ -0,0 +1,5 @@
from langflow.api.v1.endpoints import router as endpoints_router
from langflow.api.v1.validate import router as validate_router
from langflow.api.v1.chat import router as chat_router
__all__ = ["chat_router", "endpoints_router", "validate_router"]

2
src/backend/langflow/api/base.py → src/backend/langflow/api/v1/base.py
View file

@ -1,6 +1,6 @@
from pydantic import BaseModel, validator from pydantic import BaseModel, validator
from langflow.graph.utils import extract_input_variables_from_prompt from langflow.interface.utils import extract_input_variables_from_prompt
class CacheResponse(BaseModel): class CacheResponse(BaseModel):

2
src/backend/langflow/api/callback.py → src/backend/langflow/api/v1/callback.py
View file

@ -3,7 +3,7 @@ from typing import Any
from langchain.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler from langchain.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler
from langflow.api.schemas import ChatResponse from langflow.api.v1.schemas import ChatResponse
# https://github.com/hwchase17/chat-langchain/blob/master/callback.py # https://github.com/hwchase17/chat-langchain/blob/master/callback.py

2
src/backend/langflow/api/chat.py → src/backend/langflow/api/v1/chat.py
View file

@ -6,7 +6,7 @@ from fastapi import (
status, status,
) )
from langflow.api.chat_manager import ChatManager from langflow.chat.manager import ChatManager
from langflow.utils.logger import logger from langflow.utils.logger import logger
router = APIRouter() router = APIRouter()

11
src/backend/langflow/api/endpoints.py → src/backend/langflow/api/v1/endpoints.py
View file

@ -3,13 +3,13 @@ from importlib.metadata import version
from fastapi import APIRouter, HTTPException from fastapi import APIRouter, HTTPException
from langflow.api.schemas import ( from langflow.api.v1.schemas import (
ExportedFlow, ExportedFlow,
GraphData, GraphData,
PredictRequest, PredictRequest,
PredictResponse, PredictResponse,
) )
from langflow.interface.run import process_graph_cached
from langflow.interface.types import build_langchain_types_dict from langflow.interface.types import build_langchain_types_dict
# build router # build router
@ -25,6 +25,8 @@ def get_all():
@router.post("/predict", response_model=PredictResponse) @router.post("/predict", response_model=PredictResponse)
async def get_load(predict_request: PredictRequest): async def get_load(predict_request: PredictRequest):
try: try:
from langflow.processing.process import process_graph_cached
exported_flow: ExportedFlow = predict_request.exported_flow exported_flow: ExportedFlow = predict_request.exported_flow
graph_data: GraphData = exported_flow.data graph_data: GraphData = exported_flow.data
data = graph_data.dict() data = graph_data.dict()
@ -40,8 +42,3 @@ async def get_load(predict_request: PredictRequest):
@router.get("/version") @router.get("/version")
def get_version(): def get_version():
return {"version": version("langflow")} return {"version": version("langflow")}
@router.get("/health")
def get_health():
return {"status": "OK"}

0
src/backend/langflow/api/schemas.py → src/backend/langflow/api/v1/schemas.py
View file

10
src/backend/langflow/api/validate.py → src/backend/langflow/api/v1/validate.py
View file

@ -2,15 +2,15 @@ import json
from fastapi import APIRouter, HTTPException from fastapi import APIRouter, HTTPException
from langflow.api.base import ( from langflow.api.v1.base import (
Code, Code,
CodeValidationResponse, CodeValidationResponse,
Prompt, Prompt,
PromptValidationResponse, PromptValidationResponse,
validate_prompt, validate_prompt,
) )
from langflow.graph.node.types import VectorStoreNode from langflow.graph.vertex.types import VectorStoreVertex
from langflow.interface.run import build_graph from langflow.graph import Graph
from langflow.utils.logger import logger from langflow.utils.logger import logger
from langflow.utils.validate import validate_code from langflow.utils.validate import validate_code
@ -44,12 +44,12 @@ def post_validate_prompt(prompt: Prompt):
def post_validate_node(node_id: str, data: dict): def post_validate_node(node_id: str, data: dict):
try: try:
# build graph # build graph
graph = build_graph(data) graph = Graph.from_payload(data)
# validate node # validate node
node = graph.get_node(node_id) node = graph.get_node(node_id)
if node is None: if node is None:
raise ValueError(f"Node {node_id} not found") raise ValueError(f"Node {node_id} not found")
if not isinstance(node, VectorStoreNode): if not isinstance(node, VectorStoreVertex):
node.build() node.build()
return json.dumps({"valid": True, "params": str(node._built_object_repr())}) return json.dumps({"valid": True, "params": str(node._built_object_repr())})
except Exception as e: except Exception as e:

0
src/backend/langflow/graph/node/__init__.py → src/backend/langflow/chat/__init__.py
View file

49
src/backend/langflow/api/chat_manager.py → src/backend/langflow/chat/manager.py
View file

@ -1,21 +1,18 @@
import asyncio
import json
from collections import defaultdict from collections import defaultdict
from typing import Dict, List
from fastapi import WebSocket, status from fastapi import WebSocket, status
from langflow.api.v1.schemas import ChatMessage, ChatResponse, FileResponse
from langflow.api.schemas import ChatMessage, ChatResponse, FileResponse
from langflow.cache import cache_manager from langflow.cache import cache_manager
from langflow.cache.manager import Subject from langflow.cache.manager import Subject
from langflow.interface.run import ( from langflow.chat.utils import process_graph
get_result_and_steps, from langflow.interface.utils import pil_to_base64
load_or_build_langchain_object,
)
from langflow.interface.utils import pil_to_base64, try_setting_streaming_options
from langflow.utils.logger import logger from langflow.utils.logger import logger
import asyncio
import json
from typing import Dict, List
class ChatHistory(Subject): class ChatHistory(Subject):
def __init__(self): def __init__(self):
super().__init__() super().__init__()
@ -191,33 +188,3 @@ class ChatManager:
except Exception as e: except Exception as e:
logger.exception(e) logger.exception(e)
self.disconnect(client_id) self.disconnect(client_id)
async def process_graph(
graph_data: Dict,
is_first_message: bool,
chat_message: ChatMessage,
websocket: WebSocket,
):
langchain_object = load_or_build_langchain_object(graph_data, is_first_message)
langchain_object = try_setting_streaming_options(langchain_object, websocket)
logger.debug("Loaded langchain object")
if langchain_object is None:
# Raise user facing error
raise ValueError(
"There was an error loading the langchain_object. Please, check all the nodes and try again."
)
# Generate result and thought
try:
logger.debug("Generating result and thought")
result, intermediate_steps = await get_result_and_steps(
langchain_object, chat_message.message or "", websocket=websocket
)
logger.debug("Generated result and intermediate_steps")
return result, intermediate_steps
except Exception as e:
# Log stack trace
logger.exception(e)
raise e

41
src/backend/langflow/chat/utils.py Normal file
View file

@ -0,0 +1,41 @@
from fastapi import WebSocket
from langflow.api.v1.schemas import ChatMessage
from langflow.processing.process import (
load_or_build_langchain_object,
)
from langflow.processing.base import get_result_and_steps
from langflow.interface.utils import try_setting_streaming_options
from langflow.utils.logger import logger
from typing import Dict
async def process_graph(
graph_data: Dict,
is_first_message: bool,
chat_message: ChatMessage,
websocket: WebSocket,
):
langchain_object = load_or_build_langchain_object(graph_data, is_first_message)
langchain_object = try_setting_streaming_options(langchain_object, websocket)
logger.debug("Loaded langchain object")
if langchain_object is None:
# Raise user facing error
raise ValueError(
"There was an error loading the langchain_object. Please, check all the nodes and try again."
)
# Generate result and thought
try:
logger.debug("Generating result and thought")
result, intermediate_steps = await get_result_and_steps(
langchain_object, chat_message.message or "", websocket=websocket
)
logger.debug("Generated result and intermediate_steps")
return result, intermediate_steps
except Exception as e:
# Log stack trace
logger.exception(e)
raise e

7
src/backend/langflow/config.yaml
View file

@ -51,10 +51,13 @@ embeddings:
llms: llms:
- OpenAI - OpenAI
# - AzureOpenAI # - AzureOpenAI
# - AzureChatOpenAI
- ChatOpenAI - ChatOpenAI
- LlamaCpp - LlamaCpp
- CTransformers - CTransformers
- Cohere - Cohere
- Anthropic
- ChatAnthropic
memories: memories:
- ConversationBufferMemory - ConversationBufferMemory
- ConversationSummaryMemory - ConversationSummaryMemory
@ -73,13 +76,14 @@ toolkits:
- JsonToolkit - JsonToolkit
- VectorStoreInfo - VectorStoreInfo
- VectorStoreRouterToolkit - VectorStoreRouterToolkit
- VectorStoreToolkit
tools: tools:
- Search - Search
- PAL-MATH - PAL-MATH
- Calculator - Calculator
- Serper Search - Serper Search
- Tool - Tool
- PythonFunction - PythonFunctionTool
- JsonSpec - JsonSpec
- News API - News API
- TMDB API - TMDB API
@ -118,6 +122,7 @@ vectorstores:
- Chroma - Chroma
- Qdrant - Qdrant
- Weaviate - Weaviate
- FAISS
wrappers: wrappers:
- RequestsWrapper - RequestsWrapper
# - ChatPromptTemplate # - ChatPromptTemplate

2
src/backend/langflow/custom/customs.py
View file

@ -4,7 +4,7 @@ from langflow.template import frontend_node
CUSTOM_NODES = { CUSTOM_NODES = {
"prompts": {"ZeroShotPrompt": frontend_node.prompts.ZeroShotPromptNode()}, "prompts": {"ZeroShotPrompt": frontend_node.prompts.ZeroShotPromptNode()},
"tools": { "tools": {
"PythonFunction": frontend_node.tools.PythonFunctionNode(), "PythonFunctionTool": frontend_node.tools.PythonFunctionToolNode(),
"Tool": frontend_node.tools.ToolNode(), "Tool": frontend_node.tools.ToolNode(),
}, },
"agents": { "agents": {

54
src/backend/langflow/graph/__init__.py
View file

@ -1,35 +1,35 @@
from langflow.graph.edge.base import Edge from langflow.graph.edge.base import Edge
from langflow.graph.graph.base import Graph from langflow.graph.graph.base import Graph
from langflow.graph.node.base import Node from langflow.graph.vertex.base import Vertex
from langflow.graph.node.types import ( from langflow.graph.vertex.types import (
AgentNode, AgentVertex,
ChainNode, ChainVertex,
DocumentLoaderNode, DocumentLoaderVertex,
EmbeddingNode, EmbeddingVertex,
LLMNode, LLMVertex,
MemoryNode, MemoryVertex,
PromptNode, PromptVertex,
TextSplitterNode, TextSplitterVertex,
ToolNode, ToolVertex,
ToolkitNode, ToolkitVertex,
VectorStoreNode, VectorStoreVertex,
WrapperNode, WrapperVertex,
) )
__all__ = [ __all__ = [
"Graph", "Graph",
"Node", "Vertex",
"Edge", "Edge",
"AgentNode", "AgentVertex",
"ChainNode", "ChainVertex",
"DocumentLoaderNode", "DocumentLoaderVertex",
"EmbeddingNode", "EmbeddingVertex",
"LLMNode", "LLMVertex",
"MemoryNode", "MemoryVertex",
"PromptNode", "PromptVertex",
"TextSplitterNode", "TextSplitterVertex",
"ToolNode", "ToolVertex",
"ToolkitNode", "ToolkitVertex",
"VectorStoreNode", "VectorStoreVertex",
"WrapperNode", "WrapperVertex",
] ]

10
src/backend/langflow/graph/edge/base.py
View file

@ -2,13 +2,13 @@ from langflow.utils.logger import logger
from typing import TYPE_CHECKING from typing import TYPE_CHECKING
if TYPE_CHECKING: if TYPE_CHECKING:
from langflow.graph.node.base import Node from langflow.graph.vertex.base import Vertex
class Edge: class Edge:
def __init__(self, source: "Node", target: "Node"): def __init__(self, source: "Vertex", target: "Vertex"):
self.source: "Node" = source self.source: "Vertex" = source
self.target: "Node" = target self.target: "Vertex" = target
self.validate_edge() self.validate_edge()
def validate_edge(self) -> None: def validate_edge(self) -> None:
@ -41,7 +41,7 @@ class Edge:
logger.debug(self.target_reqs) logger.debug(self.target_reqs)
if no_matched_type: if no_matched_type:
raise ValueError( raise ValueError(
f"Edge between {self.source.node_type} and {self.target.node_type} " f"Edge between {self.source.vertex_type} and {self.target.vertex_type} "
f"has no matched type" f"has no matched type"
) )

77
src/backend/langflow/graph/graph/base.py
View file

@ -1,12 +1,12 @@
from typing import Dict, List, Type, Union from typing import Dict, List, Type, Union
from langflow.graph.edge.base import Edge from langflow.graph.edge.base import Edge
from langflow.graph.graph.constants import NODE_TYPE_MAP from langflow.graph.graph.constants import VERTEX_TYPE_MAP
from langflow.graph.node.base import Node from langflow.graph.vertex.base import Vertex
from langflow.graph.node.types import ( from langflow.graph.vertex.types import (
FileToolNode, FileToolVertex,
LLMNode, LLMVertex,
ToolkitNode, ToolkitVertex,
) )
from langflow.interface.tools.constants import FILE_TOOLS from langflow.interface.tools.constants import FILE_TOOLS
from langflow.utils import payload from langflow.utils import payload
@ -24,9 +24,30 @@ class Graph:
self._edges = edges self._edges = edges
self._build_graph() self._build_graph()
@classmethod
@classmethod
def from_payload(cls, payload: Dict) -> "Graph":
"""
Creates a graph from a payload.
Args:
payload (Dict): The payload to create the graph from.
Returns:
Graph: The created graph.
"""
if "data" in payload:
payload = payload["data"]
try:
nodes = payload["nodes"]
edges = payload["edges"]
return cls(nodes, edges)
except KeyError as exc:
raise ValueError("Invalid payload") from exc
def _build_graph(self) -> None: def _build_graph(self) -> None:
"""Builds the graph from the nodes and edges.""" """Builds the graph from the nodes and edges."""
self.nodes = self._build_nodes() self.nodes = self._build_vertices()
self.edges = self._build_edges() self.edges = self._build_edges()
for edge in self.edges: for edge in self.edges:
edge.source.add_edge(edge) edge.source.add_edge(edge)
@ -43,12 +64,12 @@ class Graph:
llm_node = None llm_node = None
for node in self.nodes: for node in self.nodes:
node._build_params() node._build_params()
if isinstance(node, LLMNode): if isinstance(node, LLMVertex):
llm_node = node llm_node = node
if llm_node: if llm_node:
for node in self.nodes: for node in self.nodes:
if isinstance(node, ToolkitNode): if isinstance(node, ToolkitVertex):
node.params["llm"] = llm_node node.params["llm"] = llm_node
def _remove_invalid_nodes(self) -> None: def _remove_invalid_nodes(self) -> None:
@ -60,23 +81,23 @@ class Graph:
or (len(self.nodes) == 1 and len(self.edges) == 0) or (len(self.nodes) == 1 and len(self.edges) == 0)
] ]
def _validate_node(self, node: Node) -> bool: def _validate_node(self, node: Vertex) -> bool:
"""Validates a node.""" """Validates a node."""
# All nodes that do not have edges are invalid # All nodes that do not have edges are invalid
return len(node.edges) > 0 return len(node.edges) > 0
def get_node(self, node_id: str) -> Union[None, Node]: def get_node(self, node_id: str) -> Union[None, Vertex]:
"""Returns a node by id.""" """Returns a node by id."""
return next((node for node in self.nodes if node.id == node_id), None) return next((node for node in self.nodes if node.id == node_id), None)
def get_nodes_with_target(self, node: Node) -> List[Node]: def get_nodes_with_target(self, node: Vertex) -> List[Vertex]:
"""Returns the nodes connected to a node.""" """Returns the nodes connected to a node."""
connected_nodes: List[Node] = [ connected_nodes: List[Vertex] = [
edge.source for edge in self.edges if edge.target == node edge.source for edge in self.edges if edge.target == node
] ]
return connected_nodes return connected_nodes
def build(self) -> List[Node]: def build(self) -> List[Vertex]:
"""Builds the graph.""" """Builds the graph."""
# Get root node # Get root node
root_node = payload.get_root_node(self) root_node = payload.get_root_node(self)
@ -84,9 +105,9 @@ class Graph:
raise ValueError("No root node found") raise ValueError("No root node found")
return root_node.build() return root_node.build()
def get_node_neighbors(self, node: Node) -> Dict[Node, int]: def get_node_neighbors(self, node: Vertex) -> Dict[Vertex, int]:
"""Returns the neighbors of a node.""" """Returns the neighbors of a node."""
neighbors: Dict[Node, int] = {} neighbors: Dict[Vertex, int] = {}
for edge in self.edges: for edge in self.edges:
if edge.source == node: if edge.source == node:
neighbor = edge.target neighbor = edge.target
@ -117,28 +138,30 @@ class Graph:
edges.append(Edge(source, target)) edges.append(Edge(source, target))
return edges return edges
def _get_node_class(self, node_type: str, node_lc_type: str) -> Type[Node]: def _get_vertex_class(self, node_type: str, node_lc_type: str) -> Type[Vertex]:
"""Returns the node class based on the node type.""" """Returns the node class based on the node type."""
if node_type in FILE_TOOLS: if node_type in FILE_TOOLS:
return FileToolNode return FileToolVertex
if node_type in NODE_TYPE_MAP: if node_type in VERTEX_TYPE_MAP:
return NODE_TYPE_MAP[node_type] return VERTEX_TYPE_MAP[node_type]
return NODE_TYPE_MAP[node_lc_type] if node_lc_type in NODE_TYPE_MAP else Node return (
VERTEX_TYPE_MAP[node_lc_type] if node_lc_type in VERTEX_TYPE_MAP else Vertex
)
def _build_nodes(self) -> List[Node]: def _build_vertices(self) -> List[Vertex]:
"""Builds the nodes of the graph.""" """Builds the vertices of the graph."""
nodes: List[Node] = [] nodes: List[Vertex] = []
for node in self._nodes: for node in self._nodes:
node_data = node["data"] node_data = node["data"]
node_type: str = node_data["type"] # type: ignore node_type: str = node_data["type"] # type: ignore
node_lc_type: str = node_data["node"]["template"]["_type"] # type: ignore node_lc_type: str = node_data["node"]["template"]["_type"] # type: ignore
NodeClass = self._get_node_class(node_type, node_lc_type) VertexClass = self._get_vertex_class(node_type, node_lc_type)
nodes.append(NodeClass(node)) nodes.append(VertexClass(node))
return nodes return nodes
def get_children_by_node_type(self, node: Node, node_type: str) -> List[Node]: def get_children_by_node_type(self, node: Vertex, node_type: str) -> List[Vertex]:
"""Returns the children of a node based on the node type.""" """Returns the children of a node based on the node type."""
children = [] children = []
node_types = [node.data["type"]] node_types = [node.data["type"]]

54
src/backend/langflow/graph/graph/constants.py
View file

@ -1,17 +1,17 @@
from langflow.graph.node.base import Node from langflow.graph.vertex.base import Vertex
from langflow.graph.node.types import ( from langflow.graph.vertex.types import (
AgentNode, AgentVertex,
ChainNode, ChainVertex,
DocumentLoaderNode, DocumentLoaderVertex,
EmbeddingNode, EmbeddingVertex,
LLMNode, LLMVertex,
MemoryNode, MemoryVertex,
PromptNode, PromptVertex,
TextSplitterNode, TextSplitterVertex,
ToolNode, ToolVertex,
ToolkitNode, ToolkitVertex,
VectorStoreNode, VectorStoreVertex,
WrapperNode, WrapperVertex,
) )
from langflow.interface.agents.base import agent_creator from langflow.interface.agents.base import agent_creator
from langflow.interface.chains.base import chain_creator from langflow.interface.chains.base import chain_creator
@ -33,17 +33,17 @@ from typing import Dict, Type
DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any", "prompt"] DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any", "prompt"]
NODE_TYPE_MAP: Dict[str, Type[Node]] = { VERTEX_TYPE_MAP: Dict[str, Type[Vertex]] = {
**{t: PromptNode for t in prompt_creator.to_list()}, **{t: PromptVertex for t in prompt_creator.to_list()},
**{t: AgentNode for t in agent_creator.to_list()}, **{t: AgentVertex for t in agent_creator.to_list()},
**{t: ChainNode for t in chain_creator.to_list()}, **{t: ChainVertex for t in chain_creator.to_list()},
**{t: ToolNode for t in tool_creator.to_list()}, **{t: ToolVertex for t in tool_creator.to_list()},
**{t: ToolkitNode for t in toolkits_creator.to_list()}, **{t: ToolkitVertex for t in toolkits_creator.to_list()},
**{t: WrapperNode for t in wrapper_creator.to_list()}, **{t: WrapperVertex for t in wrapper_creator.to_list()},
**{t: LLMNode for t in llm_creator.to_list()}, **{t: LLMVertex for t in llm_creator.to_list()},
**{t: MemoryNode for t in memory_creator.to_list()}, **{t: MemoryVertex for t in memory_creator.to_list()},
**{t: EmbeddingNode for t in embedding_creator.to_list()}, **{t: EmbeddingVertex for t in embedding_creator.to_list()},
**{t: VectorStoreNode for t in vectorstore_creator.to_list()}, **{t: VectorStoreVertex for t in vectorstore_creator.to_list()},
**{t: DocumentLoaderNode for t in documentloader_creator.to_list()}, **{t: DocumentLoaderVertex for t in documentloader_creator.to_list()},
**{t: TextSplitterNode for t in textsplitter_creator.to_list()}, **{t: TextSplitterVertex for t in textsplitter_creator.to_list()},
} }

0
src/backend/langflow/graph/graph/utils.py Normal file
View file

16
src/backend/langflow/graph/utils.py
View file

@ -1,4 +1,6 @@
import re from typing import Any, Union
from langflow.interface.utils import extract_input_variables_from_prompt
def validate_prompt(prompt: str): def validate_prompt(prompt: str):
@ -14,6 +16,12 @@ def fix_prompt(prompt: str):
return prompt + " {input}" return prompt + " {input}"
def extract_input_variables_from_prompt(prompt: str) -> list[str]: def flatten_list(list_of_lists: list[Union[list, Any]]) -> list:
"""Extract input variables from prompt.""" """Flatten list of lists."""
return re.findall(r"{(.*?)}", prompt) new_list = []
for item in list_of_lists:
if isinstance(item, list):
new_list.extend(item)
else:
new_list.append(item)
return new_list

0
src/backend/langflow/graph/vertex/__init__.py Normal file
View file

32
src/backend/langflow/graph/node/base.py → src/backend/langflow/graph/vertex/base.py
View file

@ -1,5 +1,5 @@
from langflow.cache import base as cache_utils from langflow.cache import base as cache_utils
from langflow.graph.node.constants import DIRECT_TYPES from langflow.graph.vertex.constants import DIRECT_TYPES
from langflow.interface import loading from langflow.interface import loading
from langflow.interface.listing import ALL_TYPES_DICT from langflow.interface.listing import ALL_TYPES_DICT
from langflow.utils.logger import logger from langflow.utils.logger import logger
@ -17,7 +17,7 @@ if TYPE_CHECKING:
from langflow.graph.edge.base import Edge from langflow.graph.edge.base import Edge
class Node: class Vertex:
def __init__(self, data: Dict, base_type: Optional[str] = None) -> None: def __init__(self, data: Dict, base_type: Optional[str] = None) -> None:
self.id: str = data["id"] self.id: str = data["id"]
self._data = data self._data = data
@ -48,12 +48,12 @@ class Node:
] ]
template_dict = self.data["node"]["template"] template_dict = self.data["node"]["template"]
self.node_type = ( self.vertex_type = (
self.data["type"] if "Tool" not in self.output else template_dict["_type"] self.data["type"] if "Tool" not in self.output else template_dict["_type"]
) )
if self.base_type is None: if self.base_type is None:
for base_type, value in ALL_TYPES_DICT.items(): for base_type, value in ALL_TYPES_DICT.items():
if self.node_type in value: if self.vertex_type in value:
self.base_type = base_type self.base_type = base_type
break break
@ -113,7 +113,7 @@ class Node:
if value["required"] and not edges: if value["required"] and not edges:
# If a required parameter is not found, raise an error # If a required parameter is not found, raise an error
raise ValueError( raise ValueError(
f"Required input {key} for module {self.node_type} not found" f"Required input {key} for module {self.vertex_type} not found"
) )
elif value["list"]: elif value["list"]:
# If this is a list parameter, append all sources to a list # If this is a list parameter, append all sources to a list
@ -128,7 +128,7 @@ class Node:
# so we need to check if value has value # so we need to check if value has value
new_value = value.get("value") new_value = value.get("value")
if new_value is None: if new_value is None:
warnings.warn(f"Value for {key} in {self.node_type} is None. ") warnings.warn(f"Value for {key} in {self.vertex_type} is None. ")
if value.get("type") == "int": if value.get("type") == "int":
with contextlib.suppress(TypeError, ValueError): with contextlib.suppress(TypeError, ValueError):
new_value = int(new_value) # type: ignore new_value = int(new_value) # type: ignore
@ -148,12 +148,12 @@ class Node:
# and continue # and continue
# Another aspect is that the node_type is the class that we need to import # Another aspect is that the node_type is the class that we need to import
# and instantiate with these built params # and instantiate with these built params
logger.debug(f"Building {self.node_type}") logger.debug(f"Building {self.vertex_type}")
# Build each node in the params dict # Build each node in the params dict
for key, value in self.params.copy().items(): for key, value in self.params.copy().items():
# Check if Node or list of Nodes and not self # Check if Node or list of Nodes and not self
# to avoid recursion # to avoid recursion
if isinstance(value, Node): if isinstance(value, Vertex):
if value == self: if value == self:
del self.params[key] del self.params[key]
continue continue
@ -174,10 +174,16 @@ class Node:
# turn result which is a function into a coroutine # turn result which is a function into a coroutine
# so that it can be awaited # so that it can be awaited
self.params["coroutine"] = sync_to_async(result) self.params["coroutine"] = sync_to_async(result)
if isinstance(result, list):
# If the result is a list, then we need to extend the list
# with the result but first check if the key exists
# if it doesn't, then we need to create a new list
if isinstance(self.params[key], list):
self.params[key].extend(result)
self.params[key] = result self.params[key] = result
elif isinstance(value, list) and all( elif isinstance(value, list) and all(
isinstance(node, Node) for node in value isinstance(node, Vertex) for node in value
): ):
self.params[key] = [] self.params[key] = []
for node in value: for node in value:
@ -193,17 +199,17 @@ class Node:
try: try:
self._built_object = loading.instantiate_class( self._built_object = loading.instantiate_class(
node_type=self.node_type, node_type=self.vertex_type,
base_type=self.base_type, base_type=self.base_type,
params=self.params, params=self.params,
) )
except Exception as exc: except Exception as exc:
raise ValueError( raise ValueError(
f"Error building node {self.node_type}: {str(exc)}" f"Error building node {self.vertex_type}: {str(exc)}"
) from exc ) from exc
if self._built_object is None: if self._built_object is None:
raise ValueError(f"Node type {self.node_type} not found") raise ValueError(f"Node type {self.vertex_type} not found")
self._built = True self._built = True
@ -220,7 +226,7 @@ class Node:
return f"Node(id={self.id}, data={self.data})" return f"Node(id={self.id}, data={self.data})"
def __eq__(self, __o: object) -> bool: def __eq__(self, __o: object) -> bool:
return self.id == __o.id if isinstance(__o, Node) else False return self.id == __o.id if isinstance(__o, Vertex) else False
def __hash__(self) -> int: def __hash__(self) -> int:
return id(self) return id(self)

0
src/backend/langflow/graph/node/constants.py → src/backend/langflow/graph/vertex/constants.py
View file

248
src/backend/langflow/graph/node/types.py → src/backend/langflow/graph/vertex/types.py
View file

@ -1,22 +1,23 @@
from typing import Any, Dict, List, Optional, Union from typing import Any, Dict, List, Optional, Union
from langflow.graph.node.base import Node from langflow.graph.vertex.base import Vertex
from langflow.graph.utils import extract_input_variables_from_prompt from langflow.graph.utils import flatten_list
from langflow.interface.utils import extract_input_variables_from_prompt
class AgentNode(Node): class AgentVertex(Vertex):
def __init__(self, data: Dict): def __init__(self, data: Dict):
super().__init__(data, base_type="agents") super().__init__(data, base_type="agents")
self.tools: List[ToolNode] = [] self.tools: List[Union[ToolkitVertex, ToolVertex]] = []
self.chains: List[ChainNode] = [] self.chains: List[ChainVertex] = []
def _set_tools_and_chains(self) -> None: def _set_tools_and_chains(self) -> None:
for edge in self.edges: for edge in self.edges:
source_node = edge.source source_node = edge.source
if isinstance(source_node, ToolNode): if isinstance(source_node, (ToolVertex, ToolkitVertex)):
self.tools.append(source_node) self.tools.append(source_node)
elif isinstance(source_node, ChainNode): elif isinstance(source_node, ChainVertex):
self.chains.append(source_node) self.chains.append(source_node)
def build(self, force: bool = False) -> Any: def build(self, force: bool = False) -> Any:
@ -32,25 +33,130 @@ class AgentNode(Node):
self._build() self._build()
#! Cannot deepcopy VectorStore, VectorStoreRouter, or SQL agents
if self.node_type in ["VectorStoreAgent", "VectorStoreRouterAgent", "SQLAgent"]:
return self._built_object
return self._built_object return self._built_object
class ToolNode(Node): class ToolVertex(Vertex):
def __init__(self, data: Dict): def __init__(self, data: Dict):
super().__init__(data, base_type="tools") super().__init__(data, base_type="tools")
class PromptNode(Node): class LLMVertex(Vertex):
built_node_type = None
class_built_object = None
def __init__(self, data: Dict):
super().__init__(data, base_type="llms")
def build(self, force: bool = False) -> Any:
# LLM is different because some models might take up too much memory
# or time to load. So we only load them when we need them.ß
if self.vertex_type == self.built_node_type:
return self.class_built_object
if not self._built or force:
self._build()
self.built_node_type = self.vertex_type
self.class_built_object = self._built_object
# Avoid deepcopying the LLM
# that are loaded from a file
return self._built_object
class ToolkitVertex(Vertex):
def __init__(self, data: Dict):
super().__init__(data, base_type="toolkits")
class FileToolVertex(ToolVertex):
def __init__(self, data: Dict):
super().__init__(data)
class WrapperVertex(Vertex):
def __init__(self, data: Dict):
super().__init__(data, base_type="wrappers")
def build(self, force: bool = False) -> Any:
if not self._built or force:
if "headers" in self.params:
self.params["headers"] = eval(self.params["headers"])
self._build()
return self._built_object
class DocumentLoaderVertex(Vertex):
def __init__(self, data: Dict):
super().__init__(data, base_type="documentloaders")
def _built_object_repr(self):
# This built_object is a list of documents. Maybe we should
# show how many documents are in the list?
if self._built_object:
return f"""{self.vertex_type}({len(self._built_object)} documents)
Documents: {self._built_object[:3]}..."""
return f"{self.vertex_type}()"
class EmbeddingVertex(Vertex):
def __init__(self, data: Dict):
super().__init__(data, base_type="embeddings")
class VectorStoreVertex(Vertex):
def __init__(self, data: Dict):
super().__init__(data, base_type="vectorstores")
def _built_object_repr(self):
return "Vector stores can take time to build. It will build on the first query."
class MemoryVertex(Vertex):
def __init__(self, data: Dict):
super().__init__(data, base_type="memory")
class TextSplitterVertex(Vertex):
def __init__(self, data: Dict):
super().__init__(data, base_type="textsplitters")
def _built_object_repr(self):
# This built_object is a list of documents. Maybe we should
# show how many documents are in the list?
if self._built_object:
return f"""{self.vertex_type}({len(self._built_object)} documents)
\nDocuments: {self._built_object[:3]}..."""
return f"{self.vertex_type}()"
class ChainVertex(Vertex):
def __init__(self, data: Dict):
super().__init__(data, base_type="chains")
def build(
self,
force: bool = False,
tools: Optional[List[Union[ToolkitVertex, ToolVertex]]] = None,
) -> Any:
if not self._built or force:
# Check if the chain requires a PromptVertex
for key, value in self.params.items():
if isinstance(value, PromptVertex):
# Build the PromptVertex, passing the tools if available
self.params[key] = value.build(tools=tools, force=force)
self._build()
return self._built_object
class PromptVertex(Vertex):
def __init__(self, data: Dict): def __init__(self, data: Dict):
super().__init__(data, base_type="prompts") super().__init__(data, base_type="prompts")
def build( def build(
self, self,
force: bool = False, force: bool = False,
tools: Optional[Union[List[Node], List[ToolNode]]] = None, tools: Optional[List[Union[ToolkitVertex, ToolVertex]]] = None,
) -> Any: ) -> Any:
if not self._built or force: if not self._built or force:
if ( if (
@ -59,12 +165,16 @@ class PromptNode(Node):
): ):
self.params["input_variables"] = [] self.params["input_variables"] = []
# Check if it is a ZeroShotPrompt and needs a tool # Check if it is a ZeroShotPrompt and needs a tool
if "ShotPrompt" in self.node_type: if "ShotPrompt" in self.vertex_type:
tools = ( tools = (
[tool_node.build() for tool_node in tools] [tool_node.build() for tool_node in tools]
if tools is not None if tools is not None
else [] else []
) )
# flatten the list of tools if it is a list of lists
# first check if it is a list
if tools and isinstance(tools, list) and isinstance(tools[0], list):
tools = flatten_list(tools)
self.params["tools"] = tools self.params["tools"] = tools
prompt_params = [ prompt_params = [
key key
@ -81,113 +191,3 @@ class PromptNode(Node):
self._build() self._build()
return self._built_object return self._built_object
class ChainNode(Node):
def __init__(self, data: Dict):
super().__init__(data, base_type="chains")
def build(
self,
force: bool = False,
tools: Optional[Union[List[Node], List[ToolNode]]] = None,
) -> Any:
if not self._built or force:
# Check if the chain requires a PromptNode
for key, value in self.params.items():
if isinstance(value, PromptNode):
# Build the PromptNode, passing the tools if available
self.params[key] = value.build(tools=tools, force=force)
self._build()
#! Cannot deepcopy SQLDatabaseChain
if self.node_type in ["SQLDatabaseChain"]:
return self._built_object
return self._built_object
class LLMNode(Node):
built_node_type = None
class_built_object = None
def __init__(self, data: Dict):
super().__init__(data, base_type="llms")
def build(self, force: bool = False) -> Any:
# LLM is different because some models might take up too much memory
# or time to load. So we only load them when we need them.ß
if self.node_type == self.built_node_type:
return self.class_built_object
if not self._built or force:
self._build()
self.built_node_type = self.node_type
self.class_built_object = self._built_object
# Avoid deepcopying the LLM
# that are loaded from a file
return self._built_object
class ToolkitNode(Node):
def __init__(self, data: Dict):
super().__init__(data, base_type="toolkits")
class FileToolNode(ToolNode):
def __init__(self, data: Dict):
super().__init__(data)
class WrapperNode(Node):
def __init__(self, data: Dict):
super().__init__(data, base_type="wrappers")
def build(self, force: bool = False) -> Any:
if not self._built or force:
if "headers" in self.params:
self.params["headers"] = eval(self.params["headers"])
self._build()
return self._built_object
class DocumentLoaderNode(Node):
def __init__(self, data: Dict):
super().__init__(data, base_type="documentloaders")
def _built_object_repr(self):
# This built_object is a list of documents. Maybe we should
# show how many documents are in the list?
if self._built_object:
return f"""{self.node_type}({len(self._built_object)} documents)
Documents: {self._built_object[:3]}..."""
return f"{self.node_type}()"
class EmbeddingNode(Node):
def __init__(self, data: Dict):
super().__init__(data, base_type="embeddings")
class VectorStoreNode(Node):
def __init__(self, data: Dict):
super().__init__(data, base_type="vectorstores")
def _built_object_repr(self):
return "Vector stores can take time to build. It will build on the first query."
class MemoryNode(Node):
def __init__(self, data: Dict):
super().__init__(data, base_type="memory")
class TextSplitterNode(Node):
def __init__(self, data: Dict):
super().__init__(data, base_type="textsplitters")
def _built_object_repr(self):
# This built_object is a list of documents. Maybe we should
# show how many documents are in the list?
if self._built_object:
return f"""{self.node_type}({len(self._built_object)} documents)\nDocuments: {self._built_object[:3]}..."""
return f"{self.node_type}()"

2
src/backend/langflow/interface/agents/custom.py
View file

@ -69,7 +69,7 @@ class JsonAgent(CustomAgentExecutor):
@classmethod @classmethod
def from_toolkit_and_llm(cls, toolkit: JsonToolkit, llm: BaseLanguageModel): def from_toolkit_and_llm(cls, toolkit: JsonToolkit, llm: BaseLanguageModel):
tools = toolkit.get_tools() tools = toolkit if isinstance(toolkit, list) else toolkit.get_tools()
tool_names = {tool.name for tool in tools} tool_names = {tool.name for tool in tools}
prompt = ZeroShotAgent.create_prompt( prompt = ZeroShotAgent.create_prompt(
tools, tools,

2
src/backend/langflow/interface/chains/custom.py
View file

@ -5,7 +5,7 @@ from langchain.memory.buffer import ConversationBufferMemory
from langchain.schema import BaseMemory from langchain.schema import BaseMemory
from pydantic import Field, root_validator from pydantic import Field, root_validator
from langflow.graph.utils import extract_input_variables_from_prompt from langflow.interface.utils import extract_input_variables_from_prompt
DEFAULT_SUFFIX = """" DEFAULT_SUFFIX = """"
Current conversation: Current conversation:

5
src/backend/langflow/interface/custom_lists.py
View file

@ -11,12 +11,15 @@ from langchain import (
text_splitter, text_splitter,
) )
from langchain.agents import agent_toolkits from langchain.agents import agent_toolkits
from langchain.chat_models import ChatOpenAI from langchain.chat_models import AzureChatOpenAI, ChatOpenAI
from langchain.chat_models import ChatAnthropic
from langflow.interface.importing.utils import import_class from langflow.interface.importing.utils import import_class
## LLMs ## LLMs
llm_type_to_cls_dict = llms.type_to_cls_dict llm_type_to_cls_dict = llms.type_to_cls_dict
llm_type_to_cls_dict["anthropic-chat"] = ChatAnthropic # type: ignore
llm_type_to_cls_dict["azure-chat"] = AzureChatOpenAI # type: ignore
llm_type_to_cls_dict["openai-chat"] = ChatOpenAI # type: ignore llm_type_to_cls_dict["openai-chat"] = ChatOpenAI # type: ignore
## Chains ## Chains

8
src/backend/langflow/interface/importing/utils.py
View file

@ -9,6 +9,7 @@ from langchain.base_language import BaseLanguageModel
from langchain.chains.base import Chain from langchain.chains.base import Chain
from langchain.chat_models.base import BaseChatModel from langchain.chat_models.base import BaseChatModel
from langchain.tools import BaseTool from langchain.tools import BaseTool
from langflow.utils import validate
def import_module(module_path: str) -> Any: def import_module(module_path: str) -> Any:
@ -147,3 +148,10 @@ def import_utility(utility: str) -> Any:
if utility == "SQLDatabase": if utility == "SQLDatabase":
return import_class(f"langchain.sql_database.{utility}") return import_class(f"langchain.sql_database.{utility}")
return import_class(f"langchain.utilities.{utility}") return import_class(f"langchain.utilities.{utility}")
def get_function(code):
"""Get the function"""
function_name = validate.extract_function_name(code)
return validate.create_function(code, function_name)

52
src/backend/langflow/interface/loading.py
View file

@ -12,7 +12,6 @@ from langchain.agents.load_tools import (
_LLM_TOOLS, _LLM_TOOLS,
) )
from langchain.agents.loading import load_agent_from_config from langchain.agents.loading import load_agent_from_config
from langflow.graph import Graph
from langchain.agents.tools import Tool from langchain.agents.tools import Tool
from langchain.base_language import BaseLanguageModel from langchain.base_language import BaseLanguageModel
from langchain.callbacks.base import BaseCallbackManager from langchain.callbacks.base import BaseCallbackManager
@ -21,12 +20,11 @@ from langchain.llms.loading import load_llm_from_config
from pydantic import ValidationError from pydantic import ValidationError
from langflow.interface.agents.custom import CUSTOM_AGENTS from langflow.interface.agents.custom import CUSTOM_AGENTS
from langflow.interface.importing.utils import import_by_type from langflow.interface.importing.utils import get_function, import_by_type
from langflow.interface.run import fix_memory_inputs
from langflow.interface.toolkits.base import toolkits_creator from langflow.interface.toolkits.base import toolkits_creator
from langflow.interface.types import get_type_list from langflow.interface.types import get_type_list
from langflow.interface.utils import load_file_into_dict from langflow.interface.utils import load_file_into_dict
from langflow.utils import util, validate from langflow.utils import util
def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any: def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
@ -100,11 +98,9 @@ def instantiate_tool(node_type, class_object, params):
if node_type == "JsonSpec": if node_type == "JsonSpec":
params["dict_"] = load_file_into_dict(params.pop("path")) params["dict_"] = load_file_into_dict(params.pop("path"))
return class_object(**params) return class_object(**params)
elif node_type == "PythonFunction": elif node_type == "PythonFunctionTool":
function_string = params["code"] params["func"] = get_function(params.get("code"))
if isinstance(function_string, str): return class_object(**params)
return validate.eval_function(function_string)
raise ValueError("Function should be a string")
elif node_type.lower() == "tool": elif node_type.lower() == "tool":
return class_object(**params) return class_object(**params)
return class_object(**params) return class_object(**params)
@ -112,8 +108,11 @@ def instantiate_tool(node_type, class_object, params):
def instantiate_toolkit(node_type, class_object, params): def instantiate_toolkit(node_type, class_object, params):
loaded_toolkit = class_object(**params) loaded_toolkit = class_object(**params)
if toolkits_creator.has_create_function(node_type): # Commenting this out for now to use toolkits as normal tools
return load_toolkits_executor(node_type, loaded_toolkit, params) # if toolkits_creator.has_create_function(node_type):
# return load_toolkits_executor(node_type, loaded_toolkit, params)
if isinstance(loaded_toolkit, BaseToolkit):
return loaded_toolkit.get_tools()
return loaded_toolkit return loaded_toolkit
@ -162,37 +161,6 @@ def instantiate_utility(node_type, class_object, params):
return class_object(**params) return class_object(**params)
def load_flow_from_json(path: str, build=True):
"""Load flow from json file"""
# This is done to avoid circular imports
with open(path, "r", encoding="utf-8") as f:
flow_graph = json.load(f)
data_graph = flow_graph["data"]
nodes = data_graph["nodes"]
# Substitute ZeroShotPrompt with PromptTemplate
# nodes = replace_zero_shot_prompt_with_prompt_template(nodes)
# Add input variables
# nodes = payload.extract_input_variables(nodes)
# Nodes, edges and root node
edges = data_graph["edges"]
graph = Graph(nodes, edges)
if build:
langchain_object = graph.build()
if hasattr(langchain_object, "verbose"):
langchain_object.verbose = True
if hasattr(langchain_object, "return_intermediate_steps"):
# https://github.com/hwchase17/langchain/issues/2068
# Deactivating until we have a frontend solution
# to display intermediate steps
langchain_object.return_intermediate_steps = False
fix_memory_inputs(langchain_object)
return langchain_object
return graph
def replace_zero_shot_prompt_with_prompt_template(nodes): def replace_zero_shot_prompt_with_prompt_template(nodes):
"""Replace ZeroShotPrompt with PromptTemplate""" """Replace ZeroShotPrompt with PromptTemplate"""
for node in nodes: for node in nodes:

2
src/backend/langflow/interface/prompts/custom.py
View file

@ -3,7 +3,7 @@ from typing import Dict, List, Optional, Type
from langchain.prompts import PromptTemplate from langchain.prompts import PromptTemplate
from pydantic import root_validator from pydantic import root_validator
from langflow.graph.utils import extract_input_variables_from_prompt from langflow.interface.utils import extract_input_variables_from_prompt
# Steps to create a BaseCustomPrompt: # Steps to create a BaseCustomPrompt:
# 1. Create a prompt template that endes with: # 1. Create a prompt template that endes with:

191
src/backend/langflow/interface/run.py
View file

@ -1,10 +1,3 @@
import contextlib
import io
from typing import Any, Dict, List, Tuple
from langchain.schema import AgentAction
from langflow.api.callback import AsyncStreamingLLMCallbackHandler, StreamingLLMCallbackHandler # type: ignore
from langflow.cache.base import compute_dict_hash, load_cache, memoize_dict from langflow.cache.base import compute_dict_hash, load_cache, memoize_dict
from langflow.graph import Graph from langflow.graph import Graph
from langflow.utils.logger import logger from langflow.utils.logger import logger
@ -24,15 +17,6 @@ def load_langchain_object(data_graph, is_first_message=False):
return computed_hash, langchain_object return computed_hash, langchain_object
def load_or_build_langchain_object(data_graph, is_first_message=False):
"""
Load langchain object from cache if it exists, otherwise build it.
"""
if is_first_message:
build_langchain_object_with_caching.clear_cache()
return build_langchain_object_with_caching(data_graph)
@memoize_dict(maxsize=10) @memoize_dict(maxsize=10)
def build_langchain_object_with_caching(data_graph): def build_langchain_object_with_caching(data_graph):
""" """
@ -40,16 +24,10 @@ def build_langchain_object_with_caching(data_graph):
""" """
logger.debug("Building langchain object") logger.debug("Building langchain object")
graph = build_graph(data_graph) graph = Graph.from_payload(data_graph)
return graph.build() return graph.build()
def build_graph(data_graph):
nodes = data_graph["nodes"]
edges = data_graph["edges"]
return Graph(nodes, edges)
def build_langchain_object(data_graph): def build_langchain_object(data_graph):
""" """
Build langchain object from data_graph. Build langchain object from data_graph.
@ -66,29 +44,6 @@ def build_langchain_object(data_graph):
return graph.build() return graph.build()
def process_graph_cached(data_graph: Dict[str, Any], message: str):
"""
Process graph by extracting input variables and replacing ZeroShotPrompt
with PromptTemplate,then run the graph and return the result and thought.
"""
# Load langchain object
is_first_message = len(data_graph.get("chatHistory", [])) == 0
langchain_object = load_or_build_langchain_object(data_graph, is_first_message)
logger.debug("Loaded langchain object")
if langchain_object is None:
# Raise user facing error
raise ValueError(
"There was an error loading the langchain_object. Please, check all the nodes and try again."
)
# Generate result and thought
logger.debug("Generating result and thought")
result, thought = get_result_and_thought(langchain_object, message)
logger.debug("Generated result and thought")
return {"result": str(result), "thought": thought.strip()}
def get_memory_key(langchain_object): def get_memory_key(langchain_object):
""" """
Given a LangChain object, this function retrieves the current memory key from the object's memory attribute. Given a LangChain object, this function retrieves the current memory key from the object's memory attribute.
@ -124,147 +79,3 @@ def update_memory_keys(langchain_object, possible_new_mem_key):
langchain_object.memory.input_key = input_key langchain_object.memory.input_key = input_key
langchain_object.memory.output_key = output_key langchain_object.memory.output_key = output_key
langchain_object.memory.memory_key = possible_new_mem_key langchain_object.memory.memory_key = possible_new_mem_key
def fix_memory_inputs(langchain_object):
"""
Given a LangChain object, this function checks if it has a memory attribute and if that memory key exists in the
object's input variables. If so, it does nothing. Otherwise, it gets a possible new memory key using the
get_memory_key function and updates the memory keys using the update_memory_keys function.
"""
if hasattr(langchain_object, "memory") and langchain_object.memory is not None:
try:
if langchain_object.memory.memory_key in langchain_object.input_variables:
return
except AttributeError:
input_variables = (
langchain_object.prompt.input_variables
if hasattr(langchain_object, "prompt")
else langchain_object.input_keys
)
if langchain_object.memory.memory_key in input_variables:
return
possible_new_mem_key = get_memory_key(langchain_object)
if possible_new_mem_key is not None:
update_memory_keys(langchain_object, possible_new_mem_key)
async def get_result_and_steps(langchain_object, message: str, **kwargs):
"""Get result and thought from extracted json"""
try:
if hasattr(langchain_object, "verbose"):
langchain_object.verbose = True
chat_input = None
memory_key = ""
if hasattr(langchain_object, "memory") and langchain_object.memory is not None:
memory_key = langchain_object.memory.memory_key
if hasattr(langchain_object, "input_keys"):
for key in langchain_object.input_keys:
if key not in [memory_key, "chat_history"]:
chat_input = {key: message}
else:
chat_input = message # type: ignore
if hasattr(langchain_object, "return_intermediate_steps"):
# https://github.com/hwchase17/langchain/issues/2068
# Deactivating until we have a frontend solution
# to display intermediate steps
langchain_object.return_intermediate_steps = True
fix_memory_inputs(langchain_object)
try:
async_callbacks = [AsyncStreamingLLMCallbackHandler(**kwargs)]
output = await langchain_object.acall(chat_input, callbacks=async_callbacks)
except Exception as exc:
# make the error message more informative
logger.debug(f"Error: {str(exc)}")
sync_callbacks = [StreamingLLMCallbackHandler(**kwargs)]
output = langchain_object(chat_input, callbacks=sync_callbacks)
intermediate_steps = (
output.get("intermediate_steps", []) if isinstance(output, dict) else []
)
result = (
output.get(langchain_object.output_keys[0])
if isinstance(output, dict)
else output
)
thought = format_actions(intermediate_steps) if intermediate_steps else ""
except Exception as exc:
raise ValueError(f"Error: {str(exc)}") from exc
return result, thought
def get_result_and_thought(langchain_object, message: str):
"""Get result and thought from extracted json"""
try:
if hasattr(langchain_object, "verbose"):
langchain_object.verbose = True
chat_input = None
memory_key = ""
if hasattr(langchain_object, "memory") and langchain_object.memory is not None:
memory_key = langchain_object.memory.memory_key
if hasattr(langchain_object, "input_keys"):
for key in langchain_object.input_keys:
if key not in [memory_key, "chat_history"]:
chat_input = {key: message}
else:
chat_input = message # type: ignore
if hasattr(langchain_object, "return_intermediate_steps"):
# https://github.com/hwchase17/langchain/issues/2068
# Deactivating until we have a frontend solution
# to display intermediate steps
langchain_object.return_intermediate_steps = False
fix_memory_inputs(langchain_object)
with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
try:
# if hasattr(langchain_object, "acall"):
# output = await langchain_object.acall(chat_input)
# else:
output = langchain_object(chat_input)
except ValueError as exc:
# make the error message more informative
logger.debug(f"Error: {str(exc)}")
output = langchain_object.run(chat_input)
intermediate_steps = (
output.get("intermediate_steps", []) if isinstance(output, dict) else []
)
result = (
output.get(langchain_object.output_keys[0])
if isinstance(output, dict)
else output
)
if intermediate_steps:
thought = format_actions(intermediate_steps)
else:
thought = output_buffer.getvalue()
except Exception as exc:
raise ValueError(f"Error: {str(exc)}") from exc
return result, thought
def format_actions(actions: List[Tuple[AgentAction, str]]) -> str:
"""Format a list of (AgentAction, answer) tuples into a string."""
output = []
for action, answer in actions:
log = action.log
tool = action.tool
tool_input = action.tool_input
output.append(f"Log: {log}")
if "Action" not in log and "Action Input" not in log:
output.append(f"Tool: {tool}")
output.append(f"Tool Input: {tool_input}")
output.append(f"Answer: {answer}")
output.append("") # Add a blank line
return "\n".join(output)

15
src/backend/langflow/interface/toolkits/base.py
View file

@ -42,24 +42,27 @@ class ToolkitCreator(LangChainTypeCreator):
def get_signature(self, name: str) -> Optional[Dict]: def get_signature(self, name: str) -> Optional[Dict]:
try: try:
return build_template_from_class(name, self.type_to_loader_dict) template = build_template_from_class(name, self.type_to_loader_dict)
# add Tool to base_classes
if "toolkit" in name.lower() and template:
template["base_classes"].append("Tool")
return template
except ValueError as exc: except ValueError as exc:
raise ValueError("Prompt not found") from exc raise ValueError("Toolkit not found") from exc
except AttributeError as exc: except AttributeError as exc:
logger.error(f"Prompt {name} not loaded: {exc}") logger.error(f"Toolkit {name} not loaded: {exc}")
return None return None
def to_list(self) -> List[str]: def to_list(self) -> List[str]:
return list(self.type_to_loader_dict.keys()) return list(self.type_to_loader_dict.keys())
def get_create_function(self, name: str) -> Callable: def get_create_function(self, name: str) -> Callable:
if loader_name := self.create_functions.get(name, None): if loader_name := self.create_functions.get(name):
# import loader
return import_module( return import_module(
f"from langchain.agents.agent_toolkits import {loader_name[0]}" f"from langchain.agents.agent_toolkits import {loader_name[0]}"
) )
else: else:
raise ValueError("Loader not found") raise ValueError("Toolkit not found")
def has_create_function(self, name: str) -> bool: def has_create_function(self, name: str) -> bool:
# check if the function list is not empty # check if the function list is not empty

3
src/backend/langflow/interface/tools/base.py
View file

@ -71,7 +71,8 @@ class ToolCreator(LangChainTypeCreator):
for tool, tool_fcn in ALL_TOOLS_NAMES.items(): for tool, tool_fcn in ALL_TOOLS_NAMES.items():
tool_params = get_tool_params(tool_fcn) tool_params = get_tool_params(tool_fcn)
tool_name = tool_params.get("name", tool)
tool_name = tool_params.get("name") or tool
if tool_name in settings.tools or settings.dev: if tool_name in settings.tools or settings.dev:
if tool_name == "JsonSpec": if tool_name == "JsonSpec":

4
src/backend/langflow/interface/tools/constants.py
View file

@ -9,10 +9,10 @@ from langchain.agents.load_tools import (
from langchain.tools.json.tool import JsonSpec from langchain.tools.json.tool import JsonSpec
from langflow.interface.importing.utils import import_class from langflow.interface.importing.utils import import_class
from langflow.interface.tools.custom import PythonFunction from langflow.interface.tools.custom import PythonFunctionTool
FILE_TOOLS = {"JsonSpec": JsonSpec} FILE_TOOLS = {"JsonSpec": JsonSpec}
CUSTOM_TOOLS = {"Tool": Tool, "PythonFunction": PythonFunction} CUSTOM_TOOLS = {"Tool": Tool, "PythonFunctionTool": PythonFunctionTool}
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__}

22
src/backend/langflow/interface/tools/custom.py
View file

@ -1,13 +1,14 @@
from typing import Callable, Optional from typing import Optional
from langflow.interface.importing.utils import get_function
from pydantic import BaseModel, validator from pydantic import BaseModel, validator
from langflow.utils import validate from langflow.utils import validate
from langchain.agents.tools import Tool
class Function(BaseModel): class Function(BaseModel):
code: str code: str
function: Optional[Callable] = None
imports: Optional[str] = None imports: Optional[str] = None
# Eval code and store the function # Eval code and store the function
@ -24,14 +25,17 @@ class Function(BaseModel):
return v return v
def get_function(self):
"""Get the function"""
function_name = validate.extract_function_name(self.code)
return validate.create_function(self.code, function_name) class PythonFunctionTool(Function, Tool):
class PythonFunction(Function):
"""Python function""" """Python function"""
name: str = "Custom Tool"
description: str
code: str code: str
def ___init__(self, name: str, description: str, code: str):
self.name = name
self.description = description
self.code = code
self.func = get_function(self.code)
super().__init__(name=name, description=description, func=self.func)

6
src/backend/langflow/interface/utils.py
View file

@ -2,6 +2,7 @@ import base64
import json import json
import os import os
from io import BytesIO from io import BytesIO
import re
import yaml import yaml
from langchain.base_language import BaseLanguageModel from langchain.base_language import BaseLanguageModel
@ -48,3 +49,8 @@ def try_setting_streaming_options(langchain_object, websocket):
llm.streaming = True llm.streaming = True
return langchain_object return langchain_object
def extract_input_variables_from_prompt(prompt: str) -> list[str]:
"""Extract input variables from prompt."""
return re.findall(r"{(.*?)}", prompt)

12
src/backend/langflow/main.py
View file

@ -1,9 +1,7 @@
from fastapi import FastAPI from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware from fastapi.middleware.cors import CORSMiddleware
from langflow.api.chat import router as chat_router from langflow.api import router
from langflow.api.endpoints import router as endpoints_router
from langflow.api.validate import router as validate_router
def create_app(): def create_app():
@ -14,6 +12,10 @@ def create_app():
"*", "*",
] ]
@app.get("/health")
def get_health():
return {"status": "OK"}
app.add_middleware( app.add_middleware(
CORSMiddleware, CORSMiddleware,
allow_origins=origins, allow_origins=origins,
@ -22,9 +24,7 @@ def create_app():
allow_headers=["*"], allow_headers=["*"],
) )
app.include_router(endpoints_router) app.include_router(router)
app.include_router(validate_router)
app.include_router(chat_router)
return app return app

0
src/backend/langflow/processing/__init__.py Normal file
View file

55
src/backend/langflow/processing/base.py Normal file
View file

@ -0,0 +1,55 @@
from langflow.api.v1.callback import (
AsyncStreamingLLMCallbackHandler,
StreamingLLMCallbackHandler,
)
from langflow.processing.process import fix_memory_inputs, format_actions
from langflow.utils.logger import logger
async def get_result_and_steps(langchain_object, message: str, **kwargs):
"""Get result and thought from extracted json"""
try:
if hasattr(langchain_object, "verbose"):
langchain_object.verbose = True
chat_input = None
memory_key = ""
if hasattr(langchain_object, "memory") and langchain_object.memory is not None:
memory_key = langchain_object.memory.memory_key
if hasattr(langchain_object, "input_keys"):
for key in langchain_object.input_keys:
if key not in [memory_key, "chat_history"]:
chat_input = {key: message}
else:
chat_input = message # type: ignore
if hasattr(langchain_object, "return_intermediate_steps"):
# https://github.com/hwchase17/langchain/issues/2068
# Deactivating until we have a frontend solution
# to display intermediate steps
langchain_object.return_intermediate_steps = True
fix_memory_inputs(langchain_object)
try:
async_callbacks = [AsyncStreamingLLMCallbackHandler(**kwargs)]
output = await langchain_object.acall(chat_input, callbacks=async_callbacks)
except Exception as exc:
# make the error message more informative
logger.debug(f"Error: {str(exc)}")
sync_callbacks = [StreamingLLMCallbackHandler(**kwargs)]
output = langchain_object(chat_input, callbacks=sync_callbacks)
intermediate_steps = (
output.get("intermediate_steps", []) if isinstance(output, dict) else []
)
result = (
output.get(langchain_object.output_keys[0])
if isinstance(output, dict)
else output
)
thought = format_actions(intermediate_steps) if intermediate_steps else ""
except Exception as exc:
raise ValueError(f"Error: {str(exc)}") from exc
return result, thought

172
src/backend/langflow/processing/process.py Normal file
View file

@ -0,0 +1,172 @@
import contextlib
import io
from langchain.schema import AgentAction
import json
from langflow.interface.run import (
build_langchain_object_with_caching,
get_memory_key,
update_memory_keys,
)
from langflow.utils.logger import logger
from langflow.graph import Graph
from typing import Any, Dict, List, Tuple
def fix_memory_inputs(langchain_object):
"""
Given a LangChain object, this function checks if it has a memory attribute and if that memory key exists in the
object's input variables. If so, it does nothing. Otherwise, it gets a possible new memory key using the
get_memory_key function and updates the memory keys using the update_memory_keys function.
"""
if hasattr(langchain_object, "memory") and langchain_object.memory is not None:
try:
if langchain_object.memory.memory_key in langchain_object.input_variables:
return
except AttributeError:
input_variables = (
langchain_object.prompt.input_variables
if hasattr(langchain_object, "prompt")
else langchain_object.input_keys
)
if langchain_object.memory.memory_key in input_variables:
return
possible_new_mem_key = get_memory_key(langchain_object)
if possible_new_mem_key is not None:
update_memory_keys(langchain_object, possible_new_mem_key)
def format_actions(actions: List[Tuple[AgentAction, str]]) -> str:
"""Format a list of (AgentAction, answer) tuples into a string."""
output = []
for action, answer in actions:
log = action.log
tool = action.tool
tool_input = action.tool_input
output.append(f"Log: {log}")
if "Action" not in log and "Action Input" not in log:
output.append(f"Tool: {tool}")
output.append(f"Tool Input: {tool_input}")
output.append(f"Answer: {answer}")
output.append("") # Add a blank line
return "\n".join(output)
def get_result_and_thought(langchain_object, message: str):
"""Get result and thought from extracted json"""
try:
if hasattr(langchain_object, "verbose"):
langchain_object.verbose = True
chat_input = None
memory_key = ""
if hasattr(langchain_object, "memory") and langchain_object.memory is not None:
memory_key = langchain_object.memory.memory_key
if hasattr(langchain_object, "input_keys"):
for key in langchain_object.input_keys:
if key not in [memory_key, "chat_history"]:
chat_input = {key: message}
else:
chat_input = message # type: ignore
if hasattr(langchain_object, "return_intermediate_steps"):
# https://github.com/hwchase17/langchain/issues/2068
# Deactivating until we have a frontend solution
# to display intermediate steps
langchain_object.return_intermediate_steps = False
fix_memory_inputs(langchain_object)
with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
try:
# if hasattr(langchain_object, "acall"):
# output = await langchain_object.acall(chat_input)
# else:
output = langchain_object(chat_input)
except ValueError as exc:
# make the error message more informative
logger.debug(f"Error: {str(exc)}")
output = langchain_object.run(chat_input)
intermediate_steps = (
output.get("intermediate_steps", []) if isinstance(output, dict) else []
)
result = (
output.get(langchain_object.output_keys[0])
if isinstance(output, dict)
else output
)
if intermediate_steps:
thought = format_actions(intermediate_steps)
else:
thought = output_buffer.getvalue()
except Exception as exc:
raise ValueError(f"Error: {str(exc)}") from exc
return result, thought
def load_or_build_langchain_object(data_graph, is_first_message=False):
"""
Load langchain object from cache if it exists, otherwise build it.
"""
if is_first_message:
build_langchain_object_with_caching.clear_cache()
return build_langchain_object_with_caching(data_graph)
def process_graph_cached(data_graph: Dict[str, Any], message: str):
"""
Process graph by extracting input variables and replacing ZeroShotPrompt
with PromptTemplate,then run the graph and return the result and thought.
"""
# Load langchain object
is_first_message = len(data_graph.get("chatHistory", [])) == 0
langchain_object = load_or_build_langchain_object(data_graph, is_first_message)
logger.debug("Loaded langchain object")
if langchain_object is None:
# Raise user facing error
raise ValueError(
"There was an error loading the langchain_object. Please, check all the nodes and try again."
)
# Generate result and thought
logger.debug("Generating result and thought")
result, thought = get_result_and_thought(langchain_object, message)
logger.debug("Generated result and thought")
return {"result": str(result), "thought": thought.strip()}
def load_flow_from_json(path: str, build=True):
"""Load flow from json file"""
# This is done to avoid circular imports
with open(path, "r", encoding="utf-8") as f:
flow_graph = json.load(f)
data_graph = flow_graph["data"]
nodes = data_graph["nodes"]
# Substitute ZeroShotPrompt with PromptTemplate
# nodes = replace_zero_shot_prompt_with_prompt_template(nodes)
# Add input variables
# nodes = payload.extract_input_variables(nodes)
# Nodes, edges and root node
edges = data_graph["edges"]
graph = Graph(nodes, edges)
if build:
langchain_object = graph.build()
if hasattr(langchain_object, "verbose"):
langchain_object.verbose = True
if hasattr(langchain_object, "return_intermediate_steps"):
# https://github.com/hwchase17/langchain/issues/2068
# Deactivating until we have a frontend solution
# to display intermediate steps
langchain_object.return_intermediate_steps = False
fix_memory_inputs(langchain_object)
return langchain_object
return graph

4
src/backend/langflow/template/frontend_node/agents.py
View file

@ -146,7 +146,7 @@ class CSVAgentNode(FrontendNode):
), ),
], ],
) )
description: str = """Construct a json agent from a CSV and tools.""" description: str = """Construct a CSV agent from a CSV and tools."""
base_classes: list[str] = ["AgentExecutor"] base_classes: list[str] = ["AgentExecutor"]
def to_dict(self): def to_dict(self):
@ -194,7 +194,7 @@ class InitializeAgentNode(FrontendNode):
), ),
], ],
) )
description: str = """Construct a json agent from an LLM and tools.""" description: str = """Construct a zero shot agent from an LLM and tools."""
base_classes: list[str] = ["AgentExecutor", "function"] base_classes: list[str] = ["AgentExecutor", "function"]
def to_dict(self): def to_dict(self):

30
src/backend/langflow/template/frontend_node/base.py
View file

@ -117,14 +117,30 @@ class FrontendNode(BaseModel):
) -> None: ) -> None:
"""Handles specific field values for certain fields.""" """Handles specific field values for certain fields."""
if key == "headers": if key == "headers":
field.value = """{'Authorization': field.value = """{'Authorization': 'Bearer <token>'}"""
'Bearer <token>'}""" FrontendNode._handle_model_specific_field_values(field, key, name)
if name == "OpenAI" and key == "model_name": FrontendNode._handle_api_key_specific_field_values(field, key, name)
field.options = constants.OPENAI_MODELS
field.is_list = True @staticmethod
elif name == "ChatOpenAI" and key == "model_name": def _handle_model_specific_field_values(
field.options = constants.CHAT_OPENAI_MODELS field: TemplateField, key: str, name: Optional[str] = None
) -> None:
"""Handles specific field values related to models."""
model_dict = {
"OpenAI": constants.OPENAI_MODELS,
"ChatOpenAI": constants.CHAT_OPENAI_MODELS,
"Anthropic": constants.ANTHROPIC_MODELS,
"ChatAnthropic": constants.ANTHROPIC_MODELS,
}
if name in model_dict and key == "model_name":
field.options = model_dict[name]
field.is_list = True field.is_list = True
@staticmethod
def _handle_api_key_specific_field_values(
field: TemplateField, key: str, name: Optional[str] = None
) -> None:
"""Handles specific field values related to API keys."""
if "api_key" in key and "OpenAI" in str(name): if "api_key" in key and "OpenAI" in str(name):
field.display_name = "OpenAI API Key" field.display_name = "OpenAI API Key"
field.required = False field.required = False

22
src/backend/langflow/template/frontend_node/llms.py
View file

@ -12,6 +12,18 @@ class LLMFrontendNode(FrontendNode):
field.name.title().replace("Openai", "OpenAI").replace("_", " ") field.name.title().replace("Openai", "OpenAI").replace("_", " ")
).replace("Api", "API") ).replace("Api", "API")
@staticmethod
def format_azure_field(field: TemplateField):
if field.name == "model_name":
field.show = False # Azure uses deployment_name instead of model_name.
if field.name == "openai_api_type":
field.show = False
field.password = False
field.value = "azure"
if field.name == "openai_api_version":
field.password = False
field.value = "2023-03-15-preview"
@staticmethod @staticmethod
def format_field(field: TemplateField, name: Optional[str] = None) -> None: def format_field(field: TemplateField, name: Optional[str] = None) -> None:
display_names_dict = { display_names_dict = {
@ -43,8 +55,16 @@ class LLMFrontendNode(FrontendNode):
field.field_type = "code" field.field_type = "code"
field.advanced = True field.advanced = True
field.show = True field.show = True
elif field.name in ["model_name", "temperature", "model_file", "model_type"]: elif field.name in [
"model_name",
"temperature",
"model_file",
"model_type",
"deployment_name",
]:
field.advanced = False field.advanced = False
field.show = True field.show = True
LLMFrontendNode.format_openai_field(field) LLMFrontendNode.format_openai_field(field)
if "azure" in name.lower():
LLMFrontendNode.format_azure_field(field)

32
src/backend/langflow/template/frontend_node/tools.py
View file

@ -59,11 +59,33 @@ class ToolNode(FrontendNode):
return super().to_dict() return super().to_dict()
class PythonFunctionNode(FrontendNode): class PythonFunctionToolNode(FrontendNode):
name: str = "PythonFunction" name: str = "PythonFunctionTool"
template: Template = Template( template: Template = Template(
type_name="python_function", type_name="PythonFunctionTool",
fields=[ fields=[
TemplateField(
field_type="str",
required=True,
placeholder="",
is_list=False,
show=True,
multiline=False,
value="",
name="name",
advanced=False,
),
TemplateField(
field_type="str",
required=True,
placeholder="",
is_list=False,
show=True,
multiline=False,
value="",
name="description",
advanced=False,
),
TemplateField( TemplateField(
field_type="code", field_type="code",
required=True, required=True,
@ -73,11 +95,11 @@ class PythonFunctionNode(FrontendNode):
value=DEFAULT_PYTHON_FUNCTION, value=DEFAULT_PYTHON_FUNCTION,
name="code", name="code",
advanced=False, advanced=False,
) ),
], ],
) )
description: str = "Python function to be executed." description: str = "Python function to be executed."
base_classes: list[str] = ["function"] base_classes: list[str] = ["Tool"]
def to_dict(self): def to_dict(self):
return super().to_dict() return super().to_dict()

14
src/backend/langflow/utils/constants.py
View file

@ -7,6 +7,20 @@ OPENAI_MODELS = [
] ]
CHAT_OPENAI_MODELS = ["gpt-3.5-turbo", "gpt-4", "gpt-4-32k"] CHAT_OPENAI_MODELS = ["gpt-3.5-turbo", "gpt-4", "gpt-4-32k"]
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.
# 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.
]
DEFAULT_PYTHON_FUNCTION = """ DEFAULT_PYTHON_FUNCTION = """
def python_function(text: str) -> str: def python_function(text: str) -> str:

4
src/backend/langflow/utils/util.py
View file

@ -302,7 +302,9 @@ def format_dict(d, name: Optional[str] = None):
elif name == "ChatOpenAI" and key == "model_name": elif name == "ChatOpenAI" and key == "model_name":
value["options"] = constants.CHAT_OPENAI_MODELS value["options"] = constants.CHAT_OPENAI_MODELS
value["list"] = True value["list"] = True
elif (name == "Anthropic" or name == "ChatAnthropic") and key == "model_name":
value["options"] = constants.ANTHROPIC_MODELS
value["list"] = True
return d return d

467
src/frontend/package-lock.json generated
View file

@ -13,6 +13,7 @@
"@headlessui/react": "^1.7.10", "@headlessui/react": "^1.7.10",
"@heroicons/react": "^2.0.15", "@heroicons/react": "^2.0.15",
"@mui/material": "^5.11.9", "@mui/material": "^5.11.9",
"@radix-ui/react-tooltip": "^1.0.6",
"@tabler/icons-react": "^2.18.0", "@tabler/icons-react": "^2.18.0",
"@tailwindcss/forms": "^0.5.3", "@tailwindcss/forms": "^0.5.3",
"@tailwindcss/line-clamp": "^0.4.4", "@tailwindcss/line-clamp": "^0.4.4",
@ -20,7 +21,10 @@
"ansi-to-html": "^0.7.2", "ansi-to-html": "^0.7.2",
"axios": "^1.3.2", "axios": "^1.3.2",
"base64-js": "^1.5.1", "base64-js": "^1.5.1",
"class-variance-authority": "^0.6.0",
"clsx": "^1.2.1",
"lodash": "^4.17.21", "lodash": "^4.17.21",
"lucide-react": "^0.233.0",
"react": "^18.2.0", "react": "^18.2.0",
"react-ace": "^10.1.0", "react-ace": "^10.1.0",
"react-cookie": "^4.1.1", "react-cookie": "^4.1.1",
@ -37,6 +41,8 @@
"rehype-mathjax": "^4.0.2", "rehype-mathjax": "^4.0.2",
"remark-gfm": "^3.0.1", "remark-gfm": "^3.0.1",
"remark-math": "^5.1.1", "remark-math": "^5.1.1",
"tailwind-merge": "^1.13.0",
"tailwindcss-animate": "^1.0.5",
"uuid": "^9.0.0", "uuid": "^9.0.0",
"vite-plugin-svgr": "^3.2.0", "vite-plugin-svgr": "^3.2.0",
"web-vitals": "^2.1.4" "web-vitals": "^2.1.4"
@ -911,6 +917,18 @@
"@floating-ui/core": "^1.2.6" "@floating-ui/core": "^1.2.6"
} }
}, },
"node_modules/@floating-ui/react-dom": {
"version": "2.0.0",
"resolved": "https://registry.npmjs.org/@floating-ui/react-dom/-/react-dom-2.0.0.tgz",
"integrity": "sha512-Ke0oU3SeuABC2C4OFu2mSAwHIP5WUiV98O9YWoHV4Q5aT6E9k06DV0Khi5uYspR8xmmBk08t8ZDcz3TR3ARkEg==",
"dependencies": {
"@floating-ui/dom": "^1.2.7"
},
"peerDependencies": {
"react": ">=16.8.0",
"react-dom": ">=16.8.0"
}
},
"node_modules/@headlessui/react": { "node_modules/@headlessui/react": {
"version": "1.7.10", "version": "1.7.10",
"resolved": "https://registry.npmjs.org/@headlessui/react/-/react-1.7.10.tgz", "resolved": "https://registry.npmjs.org/@headlessui/react/-/react-1.7.10.tgz",
@ -1274,6 +1292,407 @@
"url": "https://opencollective.com/popperjs" "url": "https://opencollective.com/popperjs"
} }
}, },
"node_modules/@radix-ui/primitive": {
"version": "1.0.1",
"resolved": "https://registry.npmjs.org/@radix-ui/primitive/-/primitive-1.0.1.tgz",
"integrity": "sha512-yQ8oGX2GVsEYMWGxcovu1uGWPCxV5BFfeeYxqPmuAzUyLT9qmaMXSAhXpb0WrspIeqYzdJpkh2vHModJPgRIaw==",
"dependencies": {
"@babel/runtime": "^7.13.10"
}
},
"node_modules/@radix-ui/react-arrow": {
"version": "1.0.3",
"resolved": "https://registry.npmjs.org/@radix-ui/react-arrow/-/react-arrow-1.0.3.tgz",
"integrity": "sha512-wSP+pHsB/jQRaL6voubsQ/ZlrGBHHrOjmBnr19hxYgtS0WvAFwZhK2WP/YY5yF9uKECCEEDGxuLxq1NBK51wFA==",
"dependencies": {
"@babel/runtime": "^7.13.10",
"@radix-ui/react-primitive": "1.0.3"
},
"peerDependencies": {
"@types/react": "*",
"@types/react-dom": "*",
"react": "^16.8 || ^17.0 || ^18.0",
"react-dom": "^16.8 || ^17.0 || ^18.0"
},
"peerDependenciesMeta": {
"@types/react": {
"optional": true
},
"@types/react-dom": {
"optional": true
}
}
},
"node_modules/@radix-ui/react-compose-refs": {
"version": "1.0.1",
"resolved": "https://registry.npmjs.org/@radix-ui/react-compose-refs/-/react-compose-refs-1.0.1.tgz",
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"react": "^16.8 || ^17.0 || ^18.0"
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},
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},
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"@types/react-dom": "*",
"react": "^16.8 || ^17.0 || ^18.0",
"react-dom": "^16.8 || ^17.0 || ^18.0"
},
"peerDependenciesMeta": {
"@types/react": {
"optional": true
},
"@types/react-dom": {
"optional": true
}
}
},
"node_modules/@radix-ui/rect": {
"version": "1.0.1",
"resolved": "https://registry.npmjs.org/@radix-ui/rect/-/rect-1.0.1.tgz",
"integrity": "sha512-fyrgCaedtvMg9NK3en0pnOYJdtfwxUcNolezkNPUsoX57X8oQk+NkqcvzHXD2uKNij6GXmWU9NDru2IWjrO4BQ==",
"dependencies": {
"@babel/runtime": "^7.13.10"
}
},
"node_modules/@reactflow/background": { "node_modules/@reactflow/background": {
"version": "11.1.7", "version": "11.1.7",
"resolved": "https://registry.npmjs.org/@reactflow/background/-/background-11.1.7.tgz", "resolved": "https://registry.npmjs.org/@reactflow/background/-/background-11.1.7.tgz",
@ -2422,7 +2841,7 @@
"version": "18.2.4", "version": "18.2.4",
"resolved": "https://registry.npmjs.org/@types/react-dom/-/react-dom-18.2.4.tgz", "resolved": "https://registry.npmjs.org/@types/react-dom/-/react-dom-18.2.4.tgz",
"integrity": "sha512-G2mHoTMTL4yoydITgOGwWdWMVd8sNgyEP85xVmMKAPUBwQWm9wBPQUmvbeF4V3WBY1P7mmL4BkjQ0SqUpf1snw==", "integrity": "sha512-G2mHoTMTL4yoydITgOGwWdWMVd8sNgyEP85xVmMKAPUBwQWm9wBPQUmvbeF4V3WBY1P7mmL4BkjQ0SqUpf1snw==",
"dev": true, "devOptional": true,
"dependencies": { "dependencies": {
"@types/react": "*" "@types/react": "*"
} }
@ -2947,6 +3366,25 @@
"node": ">= 6" "node": ">= 6"
} }
}, },
"node_modules/class-variance-authority": {
"version": "0.6.0",
"resolved": "https://registry.npmjs.org/class-variance-authority/-/class-variance-authority-0.6.0.tgz",
"integrity": "sha512-qdRDgfjx3GRb9fpwpSvn+YaidnT7IUJNe4wt5/SWwM+PmUwJUhQRk/8zAyNro0PmVfmen2635UboTjIBXXxy5A==",
"dependencies": {
"clsx": "1.2.1"
},
"funding": {
"url": "https://joebell.co.uk"
},
"peerDependencies": {
"typescript": ">= 4.5.5 < 6"
},
"peerDependenciesMeta": {
"typescript": {
"optional": true
}
}
},
"node_modules/classcat": { "node_modules/classcat": {
"version": "5.0.4", "version": "5.0.4",
"resolved": "https://registry.npmjs.org/classcat/-/classcat-5.0.4.tgz", "resolved": "https://registry.npmjs.org/classcat/-/classcat-5.0.4.tgz",
@ -4728,6 +5166,14 @@
"yallist": "^3.0.2" "yallist": "^3.0.2"
} }
}, },
"node_modules/lucide-react": {
"version": "0.233.0",
"resolved": "https://registry.npmjs.org/lucide-react/-/lucide-react-0.233.0.tgz",
"integrity": "sha512-r0jMHF0vPDq2wBbZ0B3rtIcBjDyWDKpHu+vAjD2OHn2WLUr3HN5IHovtO0EMgQXuSI7YrMZbjsEZWC2uBHr8nQ==",
"peerDependencies": {
"react": "^16.5.1 || ^17.0.0 || ^18.0.0"
}
},
"node_modules/lz-string": { "node_modules/lz-string": {
"version": "1.4.4", "version": "1.4.4",
"resolved": "https://registry.npmjs.org/lz-string/-/lz-string-1.4.4.tgz", "resolved": "https://registry.npmjs.org/lz-string/-/lz-string-1.4.4.tgz",
@ -7001,6 +7447,15 @@
"resolved": "https://registry.npmjs.org/symbol-tree/-/symbol-tree-3.2.4.tgz", "resolved": "https://registry.npmjs.org/symbol-tree/-/symbol-tree-3.2.4.tgz",
"integrity": "sha512-9QNk5KwDF+Bvz+PyObkmSYjI5ksVUYtjW7AU22r2NKcfLJcXp96hkDWU3+XndOsUb+AQ9QhfzfCT2O+CNWT5Tw==" "integrity": "sha512-9QNk5KwDF+Bvz+PyObkmSYjI5ksVUYtjW7AU22r2NKcfLJcXp96hkDWU3+XndOsUb+AQ9QhfzfCT2O+CNWT5Tw=="
}, },
"node_modules/tailwind-merge": {
"version": "1.13.0",
"resolved": "https://registry.npmjs.org/tailwind-merge/-/tailwind-merge-1.13.0.tgz",
"integrity": "sha512-mUTmDbcU+IhOvJ0c42eLQ/nRkvolTqfpVaVQRSxfJAv9TabS6Y2zW/1wKpKLdKzyL3Gh8j6NTLl6MWNmvOM6kA==",
"funding": {
"type": "github",
"url": "https://github.com/sponsors/dcastil"
}
},
"node_modules/tailwindcss": { "node_modules/tailwindcss": {
"version": "3.3.2", "version": "3.3.2",
"resolved": "https://registry.npmjs.org/tailwindcss/-/tailwindcss-3.3.2.tgz", "resolved": "https://registry.npmjs.org/tailwindcss/-/tailwindcss-3.3.2.tgz",
@ -7038,6 +7493,14 @@
"node": ">=14.0.0" "node": ">=14.0.0"
} }
}, },
"node_modules/tailwindcss-animate": {
"version": "1.0.5",
"resolved": "https://registry.npmjs.org/tailwindcss-animate/-/tailwindcss-animate-1.0.5.tgz",
"integrity": "sha512-UU3qrOJ4lFQABY+MVADmBm+0KW3xZyhMdRvejwtXqYOL7YjHYxmuREFAZdmVG5LPe5E9CAst846SLC4j5I3dcw==",
"peerDependencies": {
"tailwindcss": ">=3.0.0 || insiders"
}
},
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"resolved": "https://registry.npmjs.org/terser/-/terser-5.16.3.tgz", "resolved": "https://registry.npmjs.org/terser/-/terser-5.16.3.tgz",
@ -7156,7 +7619,7 @@
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"resolved": "https://registry.npmjs.org/typescript/-/typescript-5.0.4.tgz", "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.0.4.tgz",
"integrity": "sha512-cW9T5W9xY37cc+jfEnaUvX91foxtHkza3Nw3wkoF4sSlKn0MONdkdEndig/qPBWXNkmplh3NzayQzCiHM4/hqw==", "integrity": "sha512-cW9T5W9xY37cc+jfEnaUvX91foxtHkza3Nw3wkoF4sSlKn0MONdkdEndig/qPBWXNkmplh3NzayQzCiHM4/hqw==",
"dev": true, "devOptional": true,
"bin": { "bin": {
"tsc": "bin/tsc", "tsc": "bin/tsc",
"tsserver": "bin/tsserver" "tsserver": "bin/tsserver"

6
src/frontend/package.json
View file

@ -8,6 +8,7 @@
"@headlessui/react": "^1.7.10", "@headlessui/react": "^1.7.10",
"@heroicons/react": "^2.0.15", "@heroicons/react": "^2.0.15",
"@mui/material": "^5.11.9", "@mui/material": "^5.11.9",
"@radix-ui/react-tooltip": "^1.0.6",
"@tabler/icons-react": "^2.18.0", "@tabler/icons-react": "^2.18.0",
"@tailwindcss/forms": "^0.5.3", "@tailwindcss/forms": "^0.5.3",
"@tailwindcss/line-clamp": "^0.4.4", "@tailwindcss/line-clamp": "^0.4.4",
@ -15,7 +16,10 @@
"ansi-to-html": "^0.7.2", "ansi-to-html": "^0.7.2",
"axios": "^1.3.2", "axios": "^1.3.2",
"base64-js": "^1.5.1", "base64-js": "^1.5.1",
"class-variance-authority": "^0.6.0",
"clsx": "^1.2.1",
"lodash": "^4.17.21", "lodash": "^4.17.21",
"lucide-react": "^0.233.0",
"react": "^18.2.0", "react": "^18.2.0",
"react-ace": "^10.1.0", "react-ace": "^10.1.0",
"react-cookie": "^4.1.1", "react-cookie": "^4.1.1",
@ -32,6 +36,8 @@
"rehype-mathjax": "^4.0.2", "rehype-mathjax": "^4.0.2",
"remark-gfm": "^3.0.1", "remark-gfm": "^3.0.1",
"remark-math": "^5.1.1", "remark-math": "^5.1.1",
"tailwind-merge": "^1.13.0",
"tailwindcss-animate": "^1.0.5",
"uuid": "^9.0.0", "uuid": "^9.0.0",
"vite-plugin-svgr": "^3.2.0", "vite-plugin-svgr": "^3.2.0",
"web-vitals": "^2.1.4" "web-vitals": "^2.1.4"

62
src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx
View file

@ -1,6 +1,11 @@
import { Handle, Position, useUpdateNodeInternals } from "reactflow"; import { Handle, Position, useUpdateNodeInternals } from "reactflow";
import Tooltip from "../../../../components/TooltipComponent"; import Tooltip from "../../../../components/TooltipComponent";
import { classNames, isValidConnection } from "../../../../utils"; import {
classNames,
groupByFamily,
isValidConnection,
toFirstUpperCase,
} from "../../../../utils";
import { useContext, useEffect, useRef, useState } from "react"; import { useContext, useEffect, useRef, useState } from "react";
import InputComponent from "../../../../components/inputComponent"; import InputComponent from "../../../../components/inputComponent";
import ToggleComponent from "../../../../components/toggleComponent"; import ToggleComponent from "../../../../components/toggleComponent";
@ -15,6 +20,10 @@ import InputFileComponent from "../../../../components/inputFileComponent";
import { TabsContext } from "../../../../contexts/tabsContext"; import { TabsContext } from "../../../../contexts/tabsContext";
import IntComponent from "../../../../components/intComponent"; import IntComponent from "../../../../components/intComponent";
import PromptAreaComponent from "../../../../components/promptComponent"; import PromptAreaComponent from "../../../../components/promptComponent";
import { nodeNames, nodeIcons } from "../../../../utils";
import React from "react";
import { nodeColors } from "../../../../utils";
import ShadTooltip from "../../../../components/ShadTooltipComponent";
export default function ParameterComponent({ export default function ParameterComponent({
left, left,
@ -28,6 +37,7 @@ export default function ParameterComponent({
required = false, required = false,
}: ParameterComponentType) { }: ParameterComponentType) {
const ref = useRef(null); const ref = useRef(null);
const refHtml = useRef(null);
const updateNodeInternals = useUpdateNodeInternals(); const updateNodeInternals = useUpdateNodeInternals();
const [position, setPosition] = useState(0); const [position, setPosition] = useState(0);
useEffect(() => { useEffect(() => {
@ -48,6 +58,48 @@ export default function ParameterComponent({
let disabled = let disabled =
reactFlowInstance?.getEdges().some((e) => e.targetHandle === id) ?? false; reactFlowInstance?.getEdges().some((e) => e.targetHandle === id) ?? false;
const { save } = useContext(TabsContext); const { save } = useContext(TabsContext);
const [myData, setMyData] = useState(useContext(typesContext).data);
useEffect(() => {
const groupedObj = groupByFamily(myData, tooltipTitle);
refHtml.current = groupedObj.map((item, i) => (
<span
key={item}
className={classNames(
i > 0 ? "items-center flex mt-3" : "items-center flex"
)}
>
<div
className="h-5 w-5"
style={{
color: nodeColors[item.family],
}}
>
{React.createElement(nodeIcons[item.family])}
</div>
<span className="ps-2 text-gray-950">
{nodeNames[item.family] ?? ""}{" "}
<span className={classNames(left ? "hidden" : "")}>
{" "}
-&nbsp;
{item.type.split(", ").length > 2
? item.type.split(", ").map((el, i) => (
<>
<span key={el}>
{i == item.type.split(", ").length - 1
? el
: (el += `, `)}
</span>
{i % 2 == 0 && i > 0 && <br></br>}
</>
))
: item.type}
</span>
</span>
</span>
));
}, [tooltipTitle]);
return ( return (
<div <div
@ -69,7 +121,11 @@ export default function ParameterComponent({
type === "int") ? ( type === "int") ? (
<></> <></>
) : ( ) : (
<Tooltip title={tooltipTitle + (required ? " (required)" : "")}> <ShadTooltip
delayDuration={0}
content={refHtml.current}
side={left ? "left" : "right"}
>
<Handle <Handle
type={left ? "target" : "source"} type={left ? "target" : "source"}
position={left ? Position.Left : Position.Right} position={left ? Position.Left : Position.Right}
@ -86,7 +142,7 @@ export default function ParameterComponent({
top: position, top: position,
}} }}
></Handle> ></Handle>
</Tooltip> </ShadTooltip>
)} )}
{left === true && {left === true &&

19
src/frontend/src/CustomNodes/GenericNode/index.tsx
View file

@ -28,8 +28,8 @@ import NodeModal from "../../modals/NodeModal";
import { useCallback } from "react"; import { useCallback } from "react";
import { TabsContext } from "../../contexts/tabsContext"; import { TabsContext } from "../../contexts/tabsContext";
import { debounce } from "../../utils"; import { debounce } from "../../utils";
import TooltipReact from "../../components/ReactTooltipComponent";
import Tooltip from "../../components/TooltipComponent"; import Tooltip from "../../components/TooltipComponent";
import ShadTooltip from "../../components/ShadTooltipComponent";
export default function GenericNode({ export default function GenericNode({
data, data,
selected, selected,
@ -115,14 +115,9 @@ export default function GenericNode({
}} }}
/> />
<div className="ml-2 truncate"> <div className="ml-2 truncate">
<TooltipReact <ShadTooltip delayDuration={1500} content={data.type}>
delayShow={1000}
selector={`node-selector-${data.type}`}
htmlContent={data.type}
position="top"
>
<div className="ml-2 truncate">{data.type}</div> <div className="ml-2 truncate">{data.type}</div>
</TooltipReact> </ShadTooltip>
</div> </div>
</div> </div>
<div className="flex gap-3"> <div className="flex gap-3">
@ -253,11 +248,7 @@ export default function GenericNode({
: toTitleCase(t) : toTitleCase(t)
} }
name={t} name={t}
tooltipTitle={ tooltipTitle={data.node.template[t].type}
"Type: " +
data.node.template[t].type +
(data.node.template[t].list ? " list" : "")
}
required={data.node.template[t].required} required={data.node.template[t].required}
id={data.node.template[t].type + "|" + t + "|" + data.id} id={data.node.template[t].type + "|" + t + "|" + data.id}
left={true} left={true}
@ -283,7 +274,7 @@ export default function GenericNode({
data={data} data={data}
color={nodeColors[types[data.type]] ?? nodeColors.unknown} color={nodeColors[types[data.type]] ?? nodeColors.unknown}
title={data.type} title={data.type}
tooltipTitle={`Type: ${data.node.base_classes.join(" | ")}`} tooltipTitle={`${data.node.base_classes.join("\n")}`}
id={[data.type, data.id, ...data.node.base_classes].join("|")} id={[data.type, data.id, ...data.node.base_classes].join("|")}
type={data.node.base_classes.join("|")} type={data.node.base_classes.join("|")}
left={false} left={false}

4
src/frontend/src/components/ReactTooltipComponent/index.tsx
View file

@ -37,13 +37,15 @@ const TooltipReact: FC<TooltipProps> = ({
id={selector} id={selector}
content={content} content={content}
className={classNames( className={classNames(
"!bg-white !text-xs !font-normal !text-gray-700 !shadow-md !opacity-100 z-20", "!bg-white !text-xs !font-normal !text-gray-700 !shadow-md !opacity-100 z-[9999]",
className className
)} )}
place={position} place={position}
clickable={clickable} clickable={clickable}
isOpen={disabled ? false : undefined} isOpen={disabled ? false : undefined}
delayShow={delayShow} delayShow={delayShow}
positionStrategy="absolute"
float={true}
> >
{htmlContent && htmlContent} {htmlContent && htmlContent}
</ReactTooltip> </ReactTooltip>

25
src/frontend/src/components/ShadTooltipComponent/index.tsx Normal file
View file

@ -0,0 +1,25 @@
import {
Tooltip,
TooltipContent,
TooltipProvider,
TooltipTrigger,
} from "../ui/tooltip";
const ShadTooltip = (props) => {
return (
<TooltipProvider>
<Tooltip delayDuration={props.delayDuration}>
<TooltipTrigger asChild>{props.children}</TooltipTrigger>
<TooltipContent
side={props.side}
avoidCollisions={false}
sticky="always"
>
{props.content}
</TooltipContent>
</Tooltip>
</TooltipProvider>
);
};
export default ShadTooltip;

4
src/frontend/src/components/dropdownComponent/index.tsx
View file

@ -25,7 +25,9 @@ export default function Dropdown({
<> <>
<div className="relative mt-1 w-full"> <div className="relative mt-1 w-full">
<Listbox.Button className="relative w-full cursor-default rounded-md border border-gray-300 bg-white dark:bg-gray-900 py-2 pl-3 pr-10 text-left shadow-sm focus:border-indigo-500 focus:outline-none focus:ring-1 focus:ring-indigo-500 sm:text-sm"> <Listbox.Button className="relative w-full cursor-default rounded-md border border-gray-300 bg-white dark:bg-gray-900 py-2 pl-3 pr-10 text-left shadow-sm focus:border-indigo-500 focus:outline-none focus:ring-1 focus:ring-indigo-500 sm:text-sm">
<span className="block truncate w-full">{internalValue}</span> <span className="block truncate w-full dark:text-gray-300">
{internalValue}
</span>
<span className="pointer-events-none absolute inset-y-0 right-0 flex items-center pr-2"> <span className="pointer-events-none absolute inset-y-0 right-0 flex items-center pr-2">
<ChevronUpDownIcon <ChevronUpDownIcon
className="h-5 w-5 text-gray-400" className="h-5 w-5 text-gray-400"

29
src/frontend/src/components/ui/tooltip.tsx Normal file
View file

@ -0,0 +1,29 @@
"use client";
import * as React from "react";
import * as TooltipPrimitive from "@radix-ui/react-tooltip";
import { cn } from "../../utils";
const TooltipProvider = TooltipPrimitive.Provider;
const Tooltip = TooltipPrimitive.Root;
const TooltipTrigger = TooltipPrimitive.Trigger;
const TooltipContent = React.forwardRef<
React.ElementRef<typeof TooltipPrimitive.Content>,
React.ComponentPropsWithoutRef<typeof TooltipPrimitive.Content>
>(({ className, sideOffset = 4, ...props }, ref) => (
<TooltipPrimitive.Content
ref={ref}
sideOffset={sideOffset}
className={cn(
"z-50 overflow-hidden rounded-md border bg-popover px-3 py-1.5 text-sm text-popover-foreground shadow-md animate-in fade-in-50 data-[side=bottom]:slide-in-from-top-1 data-[side=left]:slide-in-from-right-1 data-[side=right]:slide-in-from-left-1 data-[side=top]:slide-in-from-bottom-1",
className
)}
{...props}
/>
));
TooltipContent.displayName = TooltipPrimitive.Content.displayName;
export { Tooltip, TooltipTrigger, TooltipContent, TooltipProvider };

5
src/frontend/src/contexts/darkContext.tsx
View file

@ -13,13 +13,16 @@ const initialValue = {
export const darkContext = createContext<darkContextType>(initialValue); export const darkContext = createContext<darkContextType>(initialValue);
export function DarkProvider({ children }) { export function DarkProvider({ children }) {
const [dark, setDark] = useState(false); const [dark, setDark] = useState(
JSON.parse(window.localStorage.getItem("isDark")) ?? false
);
useEffect(() => { useEffect(() => {
if (dark) { if (dark) {
document.getElementById("body").classList.add("dark"); document.getElementById("body").classList.add("dark");
} else { } else {
document.getElementById("body").classList.remove("dark"); document.getElementById("body").classList.remove("dark");
} }
window.localStorage.setItem("isDark", dark.toString());
}, [dark]); }, [dark]);
return ( return (
<darkContext.Provider <darkContext.Provider

38
src/frontend/src/contexts/tabsContext.tsx
View file

@ -47,7 +47,7 @@ export const TabsContext = createContext<TabsContextType>(
); );
export function TabsProvider({ children }: { children: ReactNode }) { export function TabsProvider({ children }: { children: ReactNode }) {
const { setNoticeData } = useContext(alertContext); const { setErrorData, setNoticeData } = useContext(alertContext);
const [tabIndex, setTabIndex] = useState(0); const [tabIndex, setTabIndex] = useState(0);
const [flows, setFlows] = useState<Array<FlowType>>([]); const [flows, setFlows] = useState<Array<FlowType>>([]);
const [id, setId] = useState(uuidv4()); const [id, setId] = useState(uuidv4());
@ -95,25 +95,25 @@ export function TabsProvider({ children }: { children: ReactNode }) {
edge.style = { stroke: "#555555" }; edge.style = { stroke: "#555555" };
}); });
flow.data.nodes.forEach((node) => { flow.data.nodes.forEach((node) => {
if (Object.keys(templates[node.data.type]["template"]).length > 0) { const template = templates[node.data.type];
node.data.node.base_classes = if (!template) {
templates[node.data.type]["base_classes"]; setErrorData({ title: `Unknown node type: ${node.data.type}` });
return;
}
if (Object.keys(template["template"]).length > 0) {
node.data.node.base_classes = template["base_classes"];
flow.data.edges.forEach((edge) => { flow.data.edges.forEach((edge) => {
if (edge.source === node.id) { if (edge.source === node.id) {
edge.sourceHandle = edge.sourceHandle edge.sourceHandle = edge.sourceHandle
.split("|") .split("|")
.slice(0, 2) .slice(0, 2)
.concat(templates[node.data.type]["base_classes"]) .concat(template["base_classes"])
.join("|"); .join("|");
} }
}); });
node.data.node.description = node.data.node.description = template["description"];
templates[node.data.type]["description"];
node.data.node.template = updateTemplate( node.data.node.template = updateTemplate(
templates[node.data.type][ template["template"] as unknown as APITemplateType,
"template"
] as unknown as APITemplateType,
node.data.node.template as APITemplateType node.data.node.template as APITemplateType
); );
} }
@ -316,21 +316,25 @@ export function TabsProvider({ children }: { children: ReactNode }) {
edge.animated = edge.targetHandle.split("|")[0] === "Text"; edge.animated = edge.targetHandle.split("|")[0] === "Text";
}); });
data.nodes.forEach((node) => { data.nodes.forEach((node) => {
if (Object.keys(templates[node.data.type]["template"]).length > 0) { const template = templates[node.data.type];
node.data.node.base_classes = if (!template) {
templates[node.data.type]["base_classes"]; setErrorData({ title: `Unknown node type: ${node.data.type}` });
return;
}
if (Object.keys(template["template"]).length > 0) {
node.data.node.base_classes = template["base_classes"];
flow.data.edges.forEach((edge) => { flow.data.edges.forEach((edge) => {
if (edge.source === node.id) { if (edge.source === node.id) {
edge.sourceHandle = edge.sourceHandle edge.sourceHandle = edge.sourceHandle
.split("|") .split("|")
.slice(0, 2) .slice(0, 2)
.concat(templates[node.data.type]["base_classes"]) .concat(template["base_classes"])
.join("|"); .join("|");
} }
}); });
node.data.node.description = templates[node.data.type]["description"]; node.data.node.description = template["description"];
node.data.node.template = updateTemplate( node.data.node.template = updateTemplate(
templates[node.data.type]["template"] as unknown as APITemplateType, template["template"] as unknown as APITemplateType,
node.data.node.template as APITemplateType node.data.node.template as APITemplateType
); );
} }

4
src/frontend/src/controllers/API/index.ts
View file

@ -14,13 +14,13 @@ export async function sendAll(data: sendAllProps) {
export async function checkCode( export async function checkCode(
code: string code: string
): Promise<AxiosResponse<errorsTypeAPI>> { ): Promise<AxiosResponse<errorsTypeAPI>> {
return await axios.post("/validate/code", { code }); return await axios.post("api/v1/validate/code", { code });
} }
export async function checkPrompt( export async function checkPrompt(
template: string template: string
): Promise<AxiosResponse<PromptTypeAPI>> { ): Promise<AxiosResponse<PromptTypeAPI>> {
return await axios.post("/validate/prompt", { template }); return await axios.post("api/v1/validate/prompt", { template });
} }
export async function getExamples(): Promise<FlowType[]> { export async function getExamples(): Promise<FlowType[]> {

9
src/frontend/src/icons/Anthropic/anthropic.svg Normal file
View file

@ -0,0 +1,9 @@
<?xml version="1.0" encoding="utf-8"?>
<svg version="1.1" xmlns="http://www.w3.org/2000/svg" viewBox="-170.333 113.047 600 67.4" width="600" height="67.4">
<defs>
<style type="text/css">
.st0{fill:#1F1F1E;}
</style>
</defs>
<path class="st0" d="M -23.533 126.747 L -1.633 126.747 L -1.633 179.347 L 12.367 179.347 L 12.367 126.747 L 34.267 126.747 L 34.267 114.147 L -23.533 114.147 L -23.533 126.747 Z M -48.133 159.747 L -77.433 114.147 L -93.233 114.147 L -93.233 179.247 L -79.733 179.247 L -79.733 133.647 L -50.433 179.347 L -34.633 179.347 L -34.633 114.247 L -48.133 114.247 L -48.133 159.747 Z M 90.067 140.147 L 59.367 140.147 L 59.367 114.147 L 45.367 114.147 L 45.367 179.247 L 59.367 179.247 L 59.367 152.647 L 90.067 152.647 L 90.067 179.247 L 104.067 179.247 L 104.067 114.147 L 90.067 114.147 L 90.067 140.147 Z M -144.333 114.147 L -170.333 179.247 L -155.833 179.247 L -150.533 165.547 L -123.333 165.547 L -118.033 179.247 L -103.533 179.247 L -129.533 114.147 L -144.333 114.147 Z M -145.833 153.547 L -136.933 130.647 L -128.033 153.547 L -145.833 153.547 Z M 219.667 113.047 C 200.867 113.047 187.567 127.047 187.567 146.847 C 187.567 166.447 200.867 180.447 219.667 180.447 C 238.367 180.447 251.567 166.447 251.567 146.847 C 251.567 127.047 238.367 113.047 219.667 113.047 Z M 219.667 167.447 C 208.667 167.447 201.967 159.647 201.967 146.847 C 201.967 133.947 208.667 126.047 219.667 126.047 C 230.567 126.047 237.167 133.847 237.167 146.847 C 237.167 159.547 230.567 167.447 219.667 167.447 Z M 414.767 157.447 C 412.367 163.747 407.467 167.447 400.867 167.447 C 389.867 167.447 383.167 159.647 383.167 146.847 C 383.167 133.947 389.867 126.047 400.867 126.047 C 407.467 126.047 412.267 129.647 414.767 136.047 L 429.567 136.047 C 425.967 122.047 415.067 113.047 400.867 113.047 C 382.067 113.047 368.767 127.047 368.767 146.847 C 368.767 166.447 382.067 180.447 400.867 180.447 C 415.067 180.447 425.967 171.347 429.667 157.447 L 414.767 157.447 Z M 325.867 114.147 L 351.867 179.247 L 366.067 179.247 L 340.067 114.147 L 325.867 114.147 Z M 296.367 114.147 L 264.567 114.147 L 264.567 179.247 L 278.567 179.247 L 278.567 155.647 L 296.467 155.647 C 311.267 155.647 320.267 147.847 320.267 134.847 C 320.267 121.947 311.167 114.147 296.367 114.147 Z M 295.767 143.147 L 278.567 143.147 L 278.567 126.747 L 295.767 126.747 C 302.667 126.747 306.267 129.547 306.267 134.947 C 306.267 140.347 302.667 143.147 295.767 143.147 Z M 176.867 134.047 C 176.867 121.747 167.867 114.247 153.067 114.247 L 121.267 114.247 L 121.267 179.347 L 135.267 179.347 L 135.267 153.847 L 150.767 153.847 L 164.767 179.347 L 180.167 179.347 L 164.667 151.947 C 172.367 148.847 176.867 142.647 176.867 134.047 Z M 135.167 126.747 L 152.367 126.747 C 159.267 126.747 162.867 129.247 162.867 134.047 C 162.867 138.747 159.267 141.347 152.367 141.347 L 135.167 141.347 L 135.167 126.747 Z"></path>
</svg>
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11
src/frontend/src/icons/Anthropic/anthropic_box.svg Normal file
View file

@ -0,0 +1,11 @@
<?xml version="1.0" encoding="utf-8"?>
<svg version="1.1" xmlns="http://www.w3.org/2000/svg" viewBox="-126.9 247.9 207.161 212.728" width="207.161" height="212.728">
<defs>
<style type="text/css">
.st0{fill:#1F1F1E;}
</style>
</defs>
<path class="st0" d="M 19.9 260.5 L 41.8 260.5 L 41.8 313.1 L 55.8 313.1 L 55.8 260.5 L 77.7 260.5 L 77.7 247.9 L 19.9 247.9 L 19.9 260.5 Z M -4.7 293.5 L -34 247.9 L -49.8 247.9 L -49.8 313 L -36.3 313 L -36.3 267.4 L -7 313.1 L 8.8 313.1 L 8.8 248 L -4.7 248 L -4.7 293.5 Z M -100.9 247.9 L -126.9 313 L -112.4 313 L -107.1 299.3 L -79.9 299.3 L -74.6 313 L -60.1 313 L -86.1 247.9 L -100.9 247.9 Z M -102.4 287.3 L -93.5 264.4 L -84.6 287.3 L -102.4 287.3 Z"></path>
<path class="st0" d="M 38.246 437.628 C 35.846 443.928 30.946 447.628 24.346 447.628 C 13.346 447.628 6.646 439.828 6.646 427.028 C 6.646 414.128 13.346 406.228 24.346 406.228 C 30.946 406.228 35.746 409.828 38.246 416.228 L 53.046 416.228 C 49.446 402.228 38.546 393.228 24.346 393.228 C 5.546 393.228 -7.754 407.228 -7.754 427.028 C -7.754 446.628 5.546 460.628 24.346 460.628 C 38.546 460.628 49.446 451.528 53.146 437.628 L 38.246 437.628 Z M -50.654 394.328 L -24.654 459.428 L -10.454 459.428 L -36.454 394.328 L -50.654 394.328 Z M -80.154 394.328 L -111.954 394.328 L -111.954 459.428 L -97.954 459.428 L -97.954 435.828 L -80.054 435.828 C -65.254 435.828 -56.254 428.028 -56.254 415.028 C -56.254 402.128 -65.354 394.328 -80.154 394.328 Z M -80.754 423.328 L -97.954 423.328 L -97.954 406.928 L -80.754 406.928 C -73.854 406.928 -70.254 409.728 -70.254 415.128 C -70.254 420.528 -73.854 423.328 -80.754 423.328 Z"></path>
<path class="st0" d="M -81.239 347.704 L -111.939 347.704 L -111.939 321.704 L -125.939 321.704 L -125.939 386.804 L -111.939 386.804 L -111.939 360.204 L -81.239 360.204 L -81.239 386.804 L -67.239 386.804 L -67.239 321.704 L -81.239 321.704 L -81.239 347.704 Z M 48.361 320.604 C 29.561 320.604 16.261 334.604 16.261 354.404 C 16.261 374.004 29.561 388.004 48.361 388.004 C 67.061 388.004 80.261 374.004 80.261 354.404 C 80.261 334.604 67.061 320.604 48.361 320.604 Z M 48.361 375.004 C 37.361 375.004 30.661 367.204 30.661 354.404 C 30.661 341.504 37.361 333.604 48.361 333.604 C 59.261 333.604 65.861 341.404 65.861 354.404 C 65.861 367.104 59.261 375.004 48.361 375.004 Z M 5.561 341.604 C 5.561 329.304 -3.439 321.804 -18.239 321.804 L -50.039 321.804 L -50.039 386.904 L -36.039 386.904 L -36.039 361.404 L -20.539 361.404 L -6.539 386.904 L 8.861 386.904 L -6.639 359.504 C 1.061 356.404 5.561 350.204 5.561 341.604 Z M -36.139 334.304 L -18.939 334.304 C -12.039 334.304 -8.439 336.804 -8.439 341.604 C -8.439 346.304 -12.039 348.904 -18.939 348.904 L -36.139 348.904 L -36.139 334.304 Z"></path>
</svg>
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9
src/frontend/src/icons/Anthropic/index.tsx Normal file
View file

@ -0,0 +1,9 @@
import React, { forwardRef } from "react";
import { ReactComponent as AnthropicSVG } from "./anthropic_box.svg";
export const AnthropicIcon = forwardRef<
SVGSVGElement,
React.PropsWithChildren<{}>
>((props, ref) => {
return <AnthropicSVG ref={ref} {...props} />;
});

86
src/frontend/src/index.css
View file

@ -2,22 +2,88 @@
@tailwind components; @tailwind components;
@tailwind utilities; @tailwind utilities;
@layer base {
:root {
--background: 0 0% 100%;
--foreground: 222.2 47.4% 11.2%;
--muted: 210 40% 96.1%;
--muted-foreground: 215.4 16.3% 46.9%;
--popover: 0 0% 100%;
--popover-foreground: 222.2 47.4% 11.2%;
--card: 0 0% 100%;
--card-foreground: 222.2 47.4% 11.2%;
--border: 214.3 31.8% 91.4%;
--input: 214.3 31.8% 91.4%;
--primary: 222.2 47.4% 11.2%;
--primary-foreground: 210 40% 98%;
--secondary: 210 40% 96.1%;
--secondary-foreground: 222.2 47.4% 11.2%;
--accent: 210 40% 96.1%;
--accent-foreground: 222.2 47.4% 11.2%;
--destructive: 0 100% 50%;
--destructive-foreground: 210 40% 98%;
--ring: 215 20.2% 65.1%;
--radius: 0.5rem;
}
.dark {
-background: 224 71% 4%;
-foreground: 213 31% 91%;
-muted: 223 47% 11%;
-muted-foreground: 215.4 16.3% 56.9%;
-popover: 224 71% 4%;
-popover-foreground: 215 20.2% 65.1%;
-card: 224 71% 4%;
-card-foreground: 213 31% 91%;
-border: 216 34% 17%;
-input: 216 34% 17%;
-primary: 210 40% 98%;
-primary-foreground: 222.2 47.4% 1.2%;
-secondary: 222.2 47.4% 11.2%;
-secondary-foreground: 210 40% 98%;
-accent: 216 34% 17%;
-accent-foreground: 210 40% 98%;
-destructive: 0 63% 31%;
-destructive-foreground: 210 40% 98%;
-ring: 216 34% 17%;
-radius: 0.5rem;
}
}
@layer base {
* {
@apply border-border;
}
body {
@apply bg-background text-foreground;
font-feature-settings: "rlig" 1, "calt" 1;
}
}
@layer base {
* {
@apply border-border;
}
body {
@apply bg-background text-foreground;
font-feature-settings: "rlig" 1, "calt" 1;
}
}
body { body {
margin: 0; margin: 0;
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", "Roboto", "Oxygen", font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", "Roboto", "Oxygen",
"Ubuntu", "Cantarell", "Fira Sans", "Droid Sans", "Helvetica Neue", "Ubuntu", "Cantarell", "Fira Sans", "Droid Sans", "Helvetica Neue",
sans-serif; sans-serif;
-webkit-font-smoothing: antialiased; -webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale; -moz-osx-font-smoothing: grayscale;
} }
code { code {
font-family: source-code-pro, Menlo, Monaco, Consolas, "Courier New", font-family: source-code-pro, Menlo, Monaco, Consolas, "Courier New",
monospace; monospace;
} }
/* The style below sets the cursor property of the element with the class .react-flow__pane to the default cursor.
The cursor: default; property value restores the browser's default cursor style for the targeted element. By applying this style, the element will no longer have a custom cursor appearance such as "grab" or any other custom cursor defined elsewhere in the application. Instead, it will revert to the default cursor style determined by the browser, typically an arrow-shaped cursor. */
.react-flow__pane { .react-flow__pane {
cursor: default; cursor: default;
} }

4
src/frontend/src/modals/chatModal/index.tsx
View file

@ -182,10 +182,10 @@ export default function ChatModal({
try { try {
const urlWs = const urlWs =
process.env.NODE_ENV === "development" process.env.NODE_ENV === "development"
? `ws://localhost:7860/chat/${id.current}` ? `ws://localhost:7860/api/v1/chat/${id.current}`
: `${window.location.protocol === "https:" ? "wss" : "ws"}://${ : `${window.location.protocol === "https:" ? "wss" : "ws"}://${
window.location.host window.location.host
}/chat/${id.current}`; }api/v1/chat/${id.current}`;
const newWs = new WebSocket(urlWs); const newWs = new WebSocket(urlWs);
newWs.onopen = () => { newWs.onopen = () => {
console.log("WebSocket connection established!"); console.log("WebSocket connection established!");

5
src/frontend/src/pages/FlowPage/components/DisclosureComponent/index.tsx
View file

@ -5,6 +5,7 @@ import { DisclosureComponentType } from "../../../../types/components";
export default function DisclosureComponent({ export default function DisclosureComponent({
button: { title, Icon, buttons = [] }, button: { title, Icon, buttons = [] },
children, children,
openDisc,
}: DisclosureComponentType) { }: DisclosureComponentType) {
return ( return (
<Disclosure as="div" key={title}> <Disclosure as="div" key={title}>
@ -27,14 +28,14 @@ export default function DisclosureComponent({
<div> <div>
<ChevronRightIcon <ChevronRightIcon
className={`${ className={`${
open ? "rotate-90 transform" : "" open || openDisc ? "rotate-90 transform" : ""
} h-4 w-4 text-gray-800 dark:text-white`} } h-4 w-4 text-gray-800 dark:text-white`}
/> />
</div> </div>
</div> </div>
</Disclosure.Button> </Disclosure.Button>
</div> </div>
<Disclosure.Panel as="div" className="-mt-px"> <Disclosure.Panel as="div" className="-mt-px" static={openDisc}>
{children} {children}
</Disclosure.Panel> </Disclosure.Panel>
</> </>

17
src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx
View file

@ -9,12 +9,13 @@ import {
import { useContext, useEffect, useState, useRef } from "react"; import { useContext, useEffect, useState, useRef } from "react";
import { typesContext } from "../../../../contexts/typesContext"; import { typesContext } from "../../../../contexts/typesContext";
import { APIClassType, APIObjectType } from "../../../../types/api"; import { APIClassType, APIObjectType } from "../../../../types/api";
import TooltipReact from "../../../../components/ReactTooltipComponent";
import { MagnifyingGlassIcon } from "@heroicons/react/24/outline"; import { MagnifyingGlassIcon } from "@heroicons/react/24/outline";
import ShadTooltip from "../../../../components/ShadTooltipComponent";
export default function ExtraSidebar() { export default function ExtraSidebar() {
const { data } = useContext(typesContext); const { data } = useContext(typesContext);
const [dataFilter, setFilterData] = useState(data); const [dataFilter, setFilterData] = useState(data);
const [search, setSearch] = useState("");
function onDragStart( function onDragStart(
event: React.DragEvent<any>, event: React.DragEvent<any>,
@ -58,6 +59,7 @@ export default function ExtraSidebar() {
className="dark:text-white focus:outline-none block w-full rounded-md py-1.5 ps-3 pr-9 text-gray-900 shadow-sm ring-1 ring-inset ring-gray-300 placeholder:text-gray-400 sm:text-sm sm:leading-6 dark:ring-0 dark:bg-[#2d3747] dark:focus:outline-none" className="dark:text-white focus:outline-none block w-full rounded-md py-1.5 ps-3 pr-9 text-gray-900 shadow-sm ring-1 ring-inset ring-gray-300 placeholder:text-gray-400 sm:text-sm sm:leading-6 dark:ring-0 dark:bg-[#2d3747] dark:focus:outline-none"
onChange={(e) => { onChange={(e) => {
handleSearchInput(e.target.value); handleSearchInput(e.target.value);
setSearch(e.target.value);
}} }}
/> />
<div className="absolute inset-y-0 right-0 flex py-1.5 pr-3 items-center"> <div className="absolute inset-y-0 right-0 flex py-1.5 pr-3 items-center">
@ -71,6 +73,7 @@ export default function ExtraSidebar() {
.map((d: keyof APIObjectType, i) => .map((d: keyof APIObjectType, i) =>
Object.keys(dataFilter[d]).length > 0 ? ( Object.keys(dataFilter[d]).length > 0 ? (
<DisclosureComponent <DisclosureComponent
openDisc={search.length == 0 ? false : true}
key={i} key={i}
button={{ button={{
title: nodeNames[d] ?? nodeNames.unknown, title: nodeNames[d] ?? nodeNames.unknown,
@ -81,12 +84,10 @@ export default function ExtraSidebar() {
{Object.keys(dataFilter[d]) {Object.keys(dataFilter[d])
.sort() .sort()
.map((t: string, k) => ( .map((t: string, k) => (
<TooltipReact <ShadTooltip
selector={t} content={t}
htmlContent={t} delayDuration={1500}
position="right" side="right"
delayShow={1500}
key={k}
> >
<div key={k} data-tooltip-id={t}> <div key={k} data-tooltip-id={t}>
<div <div
@ -118,7 +119,7 @@ export default function ExtraSidebar() {
</div> </div>
</div> </div>
</div> </div>
</TooltipReact> </ShadTooltip>
))} ))}
</div> </div>
</DisclosureComponent> </DisclosureComponent>

2
src/frontend/src/pages/FlowPage/components/tabsManagerComponent/index.tsx
View file

@ -116,7 +116,7 @@ export default function TabsManagerComponent() {
</button> </button>
</div> </div>
</div> </div>
<div className="w-full h-full"> <div className="w-full h-full dark:bg-gray-800">
<ReactFlowProvider> <ReactFlowProvider>
{flows[tabIndex] ? ( {flows[tabIndex] ? (
<FlowPage flow={flows[tabIndex]}></FlowPage> <FlowPage flow={flows[tabIndex]}></FlowPage>

2
src/frontend/src/types/components/index.ts
View file

@ -3,6 +3,7 @@ import {
ReactElement, ReactElement,
ReactFragment, ReactFragment,
ReactNode, ReactNode,
SVGProps,
} from "react"; } from "react";
import { NodeDataType } from "../flow/index"; import { NodeDataType } from "../flow/index";
export type InputComponentType = { export type InputComponentType = {
@ -56,6 +57,7 @@ export type FileComponentType = {
export type DisclosureComponentType = { export type DisclosureComponentType = {
children: ReactNode; children: ReactNode;
openDisc: boolean;
button: { button: {
title: string; title: string;
Icon: ForwardRefExoticComponent<React.SVGProps<SVGSVGElement>>; Icon: ForwardRefExoticComponent<React.SVGProps<SVGSVGElement>>;

64
src/frontend/src/utils.ts
View file

@ -21,6 +21,7 @@ import { FlowType, NodeType } from "./types/flow";
import { APITemplateType, TemplateVariableType } from "./types/api"; import { APITemplateType, TemplateVariableType } from "./types/api";
import _ from "lodash"; import _ from "lodash";
import { ChromaIcon } from "./icons/ChromaIcon"; import { ChromaIcon } from "./icons/ChromaIcon";
import { AnthropicIcon } from "./icons/Anthropic";
import { AirbyteIcon } from "./icons/Airbyte"; import { AirbyteIcon } from "./icons/Airbyte";
import { AzIcon } from "./icons/AzLogo"; import { AzIcon } from "./icons/AzLogo";
import { BingIcon } from "./icons/Bing"; import { BingIcon } from "./icons/Bing";
@ -47,6 +48,12 @@ import { WolframIcon } from "./icons/Wolfram";
import { WordIcon } from "./icons/Word"; import { WordIcon } from "./icons/Word";
import { SerperIcon } from "./icons/Serper"; import { SerperIcon } from "./icons/Serper";
import { v4 as uuidv4 } from "uuid"; import { v4 as uuidv4 } from "uuid";
import { clsx, type ClassValue } from "clsx";
import { twMerge } from "tailwind-merge";
export function cn(...inputs: ClassValue[]) {
return twMerge(clsx(inputs));
}
export function classNames(...classes: Array<string>) { export function classNames(...classes: Array<string>) {
return classes.filter(Boolean).join(" "); return classes.filter(Boolean).join(" ");
@ -153,6 +160,8 @@ export const nodeIcons: {
AirbyteJSONLoader: AirbyteIcon, AirbyteJSONLoader: AirbyteIcon,
// SerpAPIWrapper: SerperIcon, // SerpAPIWrapper: SerperIcon,
// AZLyricsLoader: AzIcon, // AZLyricsLoader: AzIcon,
Anthropic: AnthropicIcon,
ChatAnthropic: AnthropicIcon,
BingSearchAPIWrapper: BingIcon, BingSearchAPIWrapper: BingIcon,
BingSearchRun: BingIcon, BingSearchRun: BingIcon,
Cohere: CohereIcon, Cohere: CohereIcon,
@ -632,3 +641,58 @@ export function updateIds(newFlow, getNodeId) {
e.targetHandle; e.targetHandle;
}); });
} }
export function groupByFamily(data, baseClasses) {
let arrOfParent: string[] = [];
let arrOfType: { family: string; type: string }[] = [];
Object.keys(data).map((d) => {
Object.keys(data[d]).map((n) => {
if (
data[d][n].base_classes.some((r) => baseClasses.split("\n").includes(r))
) {
arrOfParent.push(d);
}
});
});
let uniq = arrOfParent.filter(
(item, index) => arrOfParent.indexOf(item) === index
);
Object.keys(data).map((d) => {
Object.keys(data[d]).map((n) => {
baseClasses.split("\n").forEach((tol) => {
data[d][n].base_classes.forEach((data) => {
if (tol == data) {
arrOfType.push({
family: d,
type: data,
});
}
});
});
});
});
let groupedBy = arrOfType.filter((object, index, self) => {
const foundIndex = self.findIndex(
(o) => o.family === object.family && o.type === object.type
);
return foundIndex === index;
});
let groupedObj = groupedBy.reduce((result, item) => {
const existingGroup = result.find((group) => group.family === item.family);
if (existingGroup) {
existingGroup.type += `, ${item.type}`;
} else {
result.push({ family: item.family, type: item.type });
}
return result;
}, []);
return groupedObj;
}

83
src/frontend/tailwind.config.js
View file

@ -1,11 +1,83 @@
/** @type {import('tailwindcss').Config} */ /** @type {import('tailwindcss').Config} */
const { fontFamily } = require("tailwindcss/defaultTheme")
import plugin from "tailwindcss/plugin"; import plugin from "tailwindcss/plugin";
module.exports = { module.exports = {
content: ["./index.html", "./src/**/*.{js,ts,tsx,jsx}"], content: ["./index.html", "./src/**/*.{js,ts,tsx,jsx}"],
darkMode: "class", darkMode: "class",
important: true, important: true,
theme: { theme: {
container: {
center: true,
padding: "2rem",
screens: {
"2xl": "1400px",
},
},
extend: { extend: {
colors: {
border: "hsl(var(--border))",
input: "hsl(var(--input))",
ring: "hsl(var(--ring))",
background: "hsl(var(--background))",
foreground: "hsl(var(--foreground))",
primary: {
DEFAULT: "hsl(var(--primary))",
foreground: "hsl(var(--primary-foreground))",
},
secondary: {
DEFAULT: "hsl(var(--secondary))",
foreground: "hsl(var(--secondary-foreground))",
},
destructive: {
DEFAULT: "hsl(var(--destructive))",
foreground: "hsl(var(--destructive-foreground))",
},
muted: {
DEFAULT: "hsl(var(--muted))",
foreground: "hsl(var(--muted-foreground))",
},
accent: {
DEFAULT: "hsl(var(--accent))",
foreground: "hsl(var(--accent-foreground))",
},
popover: {
DEFAULT: "hsl(var(--popover))",
foreground: "hsl(var(--popover-foreground))",
},
card: {
DEFAULT: "hsl(var(--card))",
foreground: "hsl(var(--card-foreground))",
},
},
borderRadius: {
lg: `var(--radius)`,
md: `calc(var(--radius) - 2px)`,
sm: "calc(var(--radius) - 4px)",
},
fontFamily: {
sans: ["var(--font-sans)", ...fontFamily.sans],
},
keyframes: {
"accordion-down": {
from: { height: 0 },
to: { height: "var(--radix-accordion-content-height)" },
},
"accordion-up": {
from: { height: "var(--radix-accordion-content-height)" },
to: { height: 0 },
},
pulseGreen: {
"0%": { boxShadow: "0 0 0 0 rgba(72, 187, 120, 0.7)" },
"100%": { boxShadow: "0 0 0 10px rgba(72, 187, 120, 0)" },
},
},
animation: {
"accordion-down": "accordion-down 0.2s ease-out",
"accordion-up": "accordion-up 0.2s ease-out",
"pulse-green": "pulseGreen 1s linear",
'spin-once': 'spin 1s linear 0.7'
},
borderColor: { borderColor: {
"red-outline": "rgba(255, 0, 0, 0.8)", "red-outline": "rgba(255, 0, 0, 0.8)",
"green-outline": "rgba(72, 187, 120, 0.7)", "green-outline": "rgba(72, 187, 120, 0.7)",
@ -14,17 +86,6 @@ module.exports = {
"red-outline": "0 0 5px rgba(255, 0, 0, 0.5)", "red-outline": "0 0 5px rgba(255, 0, 0, 0.5)",
"green-outline": "0 0 5px rgba(72, 187, 120, 0.7)", "green-outline": "0 0 5px rgba(72, 187, 120, 0.7)",
}, },
animation: {
"pulse-green": "pulseGreen 1s linear",
'spin-once': 'spin 1s linear 0.7'
},
keyframes: {
pulseGreen: {
"0%": { boxShadow: "0 0 0 0 rgba(72, 187, 120, 0.7)" },
"100%": { boxShadow: "0 0 0 10px rgba(72, 187, 120, 0)" },
},
},
}, },
}, },
plugins: [ plugins: [

3
src/frontend/tsconfig.json
View file

@ -19,7 +19,8 @@
"isolatedModules": true, "isolatedModules": true,
"noEmit": true, "noEmit": true,
"jsx": "react-jsx", "jsx": "react-jsx",
"noImplicitAny": false "noImplicitAny": false,
"baseUrl": "."
}, },
"include": [ "include": [
"src" "src"

2
src/frontend/vite.config.ts
View file

@ -11,7 +11,7 @@ const apiRoutes = [
]; ];
// Use environment variable to determine the target. // Use environment variable to determine the target.
const target = process.env.VITE_PROXY_TARGET || "http://127.0.0.1:7860"; const target = process.env.VITE_PROXY_TARGET || "http://127.0.0.1:7860/api/v1";
const proxyTargets = apiRoutes.reduce((proxyObj, route) => { const proxyTargets = apiRoutes.reduce((proxyObj, route) => {
proxyObj[route] = { proxyObj[route] = {

22
tests/data/complex_example.json
View file

@ -197,7 +197,7 @@
"y": 136.29836646158452 "y": 136.29836646158452
}, },
"data": { "data": {
"type": "PythonFunction", "type": "PythonFunctionTool",
"node": { "node": {
"template": { "template": {
"code": { "code": {
@ -210,6 +210,26 @@
"type": "str", "type": "str",
"list": false "list": false
}, },
"description": {
"required": true,
"placeholder": "",
"show": true,
"multiline": true,
"value": "My description",
"name": "description",
"type": "str",
"list": false
},
"name": {
"required": true,
"placeholder": "",
"show": true,
"multiline": true,
"value": "My Tool",
"name": "name",
"type": "str",
"list": false
},
"_type": "python_function" "_type": "python_function"
}, },
"description": "Python function to be executed.", "description": "Python function to be executed.",

10
tests/test_agents_template.py
View file

@ -5,7 +5,7 @@ from langflow.settings import settings
# check that all agents are in settings.agents # check that all agents are in settings.agents
# are in json_response["agents"] # are in json_response["agents"]
def test_agents_settings(client: TestClient): def test_agents_settings(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
agents = json_response["agents"] agents = json_response["agents"]
@ -13,7 +13,7 @@ def test_agents_settings(client: TestClient):
def test_zero_shot_agent(client: TestClient): def test_zero_shot_agent(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
agents = json_response["agents"] agents = json_response["agents"]
@ -52,7 +52,7 @@ def test_zero_shot_agent(client: TestClient):
def test_json_agent(client: TestClient): def test_json_agent(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
agents = json_response["agents"] agents = json_response["agents"]
@ -87,7 +87,7 @@ def test_json_agent(client: TestClient):
def test_csv_agent(client: TestClient): def test_csv_agent(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
agents = json_response["agents"] agents = json_response["agents"]
@ -126,7 +126,7 @@ def test_csv_agent(client: TestClient):
def test_initialize_agent(client: TestClient): def test_initialize_agent(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
agents = json_response["agents"] agents = json_response["agents"]

6
tests/test_cache.py
View file

@ -1,10 +1,10 @@
import json import json
from langflow.graph import Graph
from langflow.processing.process import load_or_build_langchain_object
import pytest import pytest
from langflow.interface.run import ( from langflow.interface.run import (
build_graph,
build_langchain_object_with_caching, build_langchain_object_with_caching,
load_or_build_langchain_object,
) )
@ -62,7 +62,7 @@ def test_build_langchain_object_with_caching(basic_data_graph):
# Test build_graph # Test build_graph
def test_build_graph(basic_data_graph): def test_build_graph(basic_data_graph):
graph = build_graph(basic_data_graph) graph = Graph.from_payload(basic_data_graph)
assert graph is not None assert graph is not None
assert len(graph.nodes) == len(basic_data_graph["nodes"]) assert len(graph.nodes) == len(basic_data_graph["nodes"])
assert len(graph.edges) == len(basic_data_graph["edges"]) assert len(graph.edges) == len(basic_data_graph["edges"])

16
tests/test_chains_template.py
View file

@ -3,7 +3,7 @@ from langflow.settings import settings
def test_chains_settings(client: TestClient): def test_chains_settings(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
chains = json_response["chains"] chains = json_response["chains"]
@ -12,7 +12,7 @@ def test_chains_settings(client: TestClient):
# Test the ConversationChain object # Test the ConversationChain object
def test_conversation_chain(client: TestClient): def test_conversation_chain(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
chains = json_response["chains"] chains = json_response["chains"]
@ -94,7 +94,7 @@ def test_conversation_chain(client: TestClient):
def test_llm_chain(client: TestClient): def test_llm_chain(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
chains = json_response["chains"] chains = json_response["chains"]
@ -152,7 +152,7 @@ def test_llm_chain(client: TestClient):
def test_llm_checker_chain(client: TestClient): def test_llm_checker_chain(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
chains = json_response["chains"] chains = json_response["chains"]
@ -228,7 +228,7 @@ def test_llm_checker_chain(client: TestClient):
def test_llm_math_chain(client: TestClient): def test_llm_math_chain(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
chains = json_response["chains"] chains = json_response["chains"]
@ -306,7 +306,7 @@ def test_llm_math_chain(client: TestClient):
def test_series_character_chain(client: TestClient): def test_series_character_chain(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
chains = json_response["chains"] chains = json_response["chains"]
@ -368,7 +368,7 @@ def test_series_character_chain(client: TestClient):
def test_mid_journey_prompt_chain(client: TestClient): def test_mid_journey_prompt_chain(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
chains = json_response["chains"] chains = json_response["chains"]
@ -407,7 +407,7 @@ def test_mid_journey_prompt_chain(client: TestClient):
def test_time_travel_guide_chain(client: TestClient): def test_time_travel_guide_chain(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
chains = json_response["chains"] chains = json_response["chains"]

15
tests/test_custom_types.py
View file

@ -1,16 +1,23 @@
# Test this: # Test this:
from langflow.interface.importing.utils import get_function
import pytest import pytest
from langflow.interface.tools.custom import PythonFunction from langflow.interface.tools.custom import PythonFunctionTool
from langflow.utils import constants from langflow.utils import constants
def test_python_function(): def test_python_function():
"""Test Python function""" """Test Python function"""
func = PythonFunction(code=constants.DEFAULT_PYTHON_FUNCTION) code = constants.DEFAULT_PYTHON_FUNCTION
assert func.get_function()("text") == "text" func = get_function(code)
func = PythonFunctionTool(name="Test", description="Testing", code=code, func=func)
assert func("text") == "text"
# the tool decorator should raise an error if # the tool decorator should raise an error if
# the function is not str -> str # the function is not str -> str
# This raises ValidationError # This raises ValidationError
with pytest.raises(SyntaxError): with pytest.raises(SyntaxError):
func = PythonFunction(code=pytest.CODE_WITH_SYNTAX_ERROR) code = pytest.CODE_WITH_SYNTAX_ERROR
func = get_function(code)
func = PythonFunctionTool(
name="Test", description="Testing", code=code, func=func
)

20
tests/test_endpoints.py
View file

@ -4,7 +4,7 @@ from langflow.interface.tools.constants import CUSTOM_TOOLS
def test_get_all(client: TestClient): def test_get_all(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
# We need to test the custom nodes # We need to test the custom nodes
@ -21,7 +21,7 @@ import math
def square(x): def square(x):
return x ** 2 return x ** 2
""" """
response1 = client.post("/validate/code", json={"code": code1}) response1 = client.post("api/v1/validate/code", json={"code": code1})
assert response1.status_code == 200 assert response1.status_code == 200
assert response1.json() == {"imports": {"errors": []}, "function": {"errors": []}} assert response1.json() == {"imports": {"errors": []}, "function": {"errors": []}}
@ -32,7 +32,7 @@ import non_existent_module
def square(x): def square(x):
return x ** 2 return x ** 2
""" """
response2 = client.post("/validate/code", json={"code": code2}) response2 = client.post("api/v1/validate/code", json={"code": code2})
assert response2.status_code == 200 assert response2.status_code == 200
assert response2.json() == { assert response2.json() == {
"imports": {"errors": ["No module named 'non_existent_module'"]}, "imports": {"errors": ["No module named 'non_existent_module'"]},
@ -46,7 +46,7 @@ import math
def square(x) def square(x)
return x ** 2 return x ** 2
""" """
response3 = client.post("/validate/code", json={"code": code3}) response3 = client.post("api/v1/validate/code", json={"code": code3})
assert response3.status_code == 200 assert response3.status_code == 200
assert response3.json() == { assert response3.json() == {
"imports": {"errors": []}, "imports": {"errors": []},
@ -54,11 +54,11 @@ def square(x)
} }
# Test case with invalid JSON payload # Test case with invalid JSON payload
response4 = client.post("/validate/code", json={"invalid_key": code1}) response4 = client.post("api/v1/validate/code", json={"invalid_key": code1})
assert response4.status_code == 422 assert response4.status_code == 422
# Test case with an empty code string # Test case with an empty code string
response5 = client.post("/validate/code", json={"code": ""}) response5 = client.post("api/v1/validate/code", json={"code": ""})
assert response5.status_code == 200 assert response5.status_code == 200
assert response5.json() == {"imports": {"errors": []}, "function": {"errors": []}} assert response5.json() == {"imports": {"errors": []}, "function": {"errors": []}}
@ -69,7 +69,7 @@ import math
def square(x) def square(x)
return x ** 2 return x ** 2
""" """
response6 = client.post("/validate/code", json={"code": code6}) response6 = client.post("api/v1/validate/code", json={"code": code6})
assert response6.status_code == 200 assert response6.status_code == 200
assert response6.json() == { assert response6.json() == {
"imports": {"errors": []}, "imports": {"errors": []},
@ -95,13 +95,13 @@ INVALID_PROMPT = "This is an invalid prompt without any input variable."
def test_valid_prompt(client: TestClient): def test_valid_prompt(client: TestClient):
response = client.post("/validate/prompt", json={"template": VALID_PROMPT}) response = client.post("api/v1/validate/prompt", json={"template": VALID_PROMPT})
assert response.status_code == 200 assert response.status_code == 200
assert response.json() == {"input_variables": ["product"]} assert response.json() == {"input_variables": ["product"]}
def test_invalid_prompt(client: TestClient): def test_invalid_prompt(client: TestClient):
response = client.post("/validate/prompt", json={"template": INVALID_PROMPT}) response = client.post("api/v1/validate/prompt", json={"template": INVALID_PROMPT})
assert response.status_code == 200 assert response.status_code == 200
assert response.json() == {"input_variables": []} assert response.json() == {"input_variables": []}
@ -116,7 +116,7 @@ def test_invalid_prompt(client: TestClient):
], ],
) )
def test_various_prompts(client, prompt, expected_input_variables): def test_various_prompts(client, prompt, expected_input_variables):
response = client.post("/validate/prompt", json={"template": prompt}) response = client.post("api/v1/validate/prompt", json={"template": prompt})
assert response.status_code == 200 assert response.status_code == 200
assert response.json() == { assert response.json() == {
"input_variables": expected_input_variables, "input_variables": expected_input_variables,

63
tests/test_graph.py
View file

@ -1,22 +1,22 @@
from typing import Type, Union from typing import Type, Union
from langflow.graph.edge.base import Edge from langflow.graph.edge.base import Edge
from langflow.graph.node.base import Node from langflow.graph.vertex.base import Vertex
import pytest import pytest
from langchain.chains.base import Chain from langchain.chains.base import Chain
from langchain.llms.fake import FakeListLLM from langchain.llms.fake import FakeListLLM
from langflow.graph import Graph from langflow.graph import Graph
from langflow.graph.node.types import ( from langflow.graph.vertex.types import (
AgentNode, AgentVertex,
ChainNode, ChainVertex,
FileToolNode, FileToolVertex,
LLMNode, LLMVertex,
PromptNode, PromptVertex,
ToolkitNode, ToolkitVertex,
ToolNode, ToolVertex,
WrapperNode, WrapperVertex,
) )
from langflow.interface.run import get_result_and_thought from langflow.processing.process import get_result_and_thought
from langflow.utils.payload import get_root_node from langflow.utils.payload import get_root_node
# Test cases for the graph module # Test cases for the graph module
@ -25,7 +25,7 @@ from langflow.utils.payload import get_root_node
# BASIC_EXAMPLE_PATH, COMPLEX_EXAMPLE_PATH, OPENAPI_EXAMPLE_PATH # BASIC_EXAMPLE_PATH, COMPLEX_EXAMPLE_PATH, OPENAPI_EXAMPLE_PATH
def get_node_by_type(graph, node_type: Type[Node]) -> Union[Node, None]: def get_node_by_type(graph, node_type: Type[Vertex]) -> Union[Vertex, None]:
"""Get a node by type""" """Get a node by type"""
return next((node for node in graph.nodes if isinstance(node, node_type)), None) return next((node for node in graph.nodes if isinstance(node, node_type)), None)
@ -35,7 +35,7 @@ def test_graph_structure(basic_graph):
assert len(basic_graph.nodes) > 0 assert len(basic_graph.nodes) > 0
assert len(basic_graph.edges) > 0 assert len(basic_graph.edges) > 0
for node in basic_graph.nodes: for node in basic_graph.nodes:
assert isinstance(node, Node) assert isinstance(node, Vertex)
for edge in basic_graph.edges: for edge in basic_graph.edges:
assert isinstance(edge, Edge) assert isinstance(edge, Edge)
assert edge.source in basic_graph.nodes assert edge.source in basic_graph.nodes
@ -158,14 +158,16 @@ def test_get_node_neighbors_complex(complex_graph):
tool_neighbors = complex_graph.get_nodes_with_target(tool) tool_neighbors = complex_graph.get_nodes_with_target(tool)
assert tool_neighbors is not None assert tool_neighbors is not None
# Check if there is a PythonFunction in the tool's neighbors # Check if there is a PythonFunction in the tool's neighbors
assert any("PythonFunction" in neighbor.data["type"] for neighbor in tool_neighbors) assert any(
"PythonFunctionTool" in neighbor.data["type"] for neighbor in tool_neighbors
)
def test_get_node(basic_graph): def test_get_node(basic_graph):
"""Test getting a single node""" """Test getting a single node"""
node_id = basic_graph.nodes[0].id node_id = basic_graph.nodes[0].id
node = basic_graph.get_node(node_id) node = basic_graph.get_node(node_id)
assert isinstance(node, Node) assert isinstance(node, Vertex)
assert node.id == node_id assert node.id == node_id
@ -174,7 +176,7 @@ def test_build_nodes(basic_graph):
assert len(basic_graph.nodes) == len(basic_graph._nodes) assert len(basic_graph.nodes) == len(basic_graph._nodes)
for node in basic_graph.nodes: for node in basic_graph.nodes:
assert isinstance(node, Node) assert isinstance(node, Vertex)
def test_build_edges(basic_graph): def test_build_edges(basic_graph):
@ -182,8 +184,8 @@ def test_build_edges(basic_graph):
assert len(basic_graph.edges) == len(basic_graph._edges) assert len(basic_graph.edges) == len(basic_graph._edges)
for edge in basic_graph.edges: for edge in basic_graph.edges:
assert isinstance(edge, Edge) assert isinstance(edge, Edge)
assert isinstance(edge.source, Node) assert isinstance(edge.source, Vertex)
assert isinstance(edge.target, Node) assert isinstance(edge.target, Vertex)
def test_get_root_node(basic_graph, complex_graph): def test_get_root_node(basic_graph, complex_graph):
@ -191,13 +193,13 @@ def test_get_root_node(basic_graph, complex_graph):
assert isinstance(basic_graph, Graph) assert isinstance(basic_graph, Graph)
root = get_root_node(basic_graph) root = get_root_node(basic_graph)
assert root is not None assert root is not None
assert isinstance(root, Node) assert isinstance(root, Vertex)
assert root.data["type"] == "TimeTravelGuideChain" assert root.data["type"] == "TimeTravelGuideChain"
# For complex example, the root node is a ZeroShotAgent too # For complex example, the root node is a ZeroShotAgent too
assert isinstance(complex_graph, Graph) assert isinstance(complex_graph, Graph)
root = get_root_node(complex_graph) root = get_root_node(complex_graph)
assert root is not None assert root is not None
assert isinstance(root, Node) assert isinstance(root, Vertex)
assert root.data["type"] == "ZeroShotAgent" assert root.data["type"] == "ZeroShotAgent"
@ -239,11 +241,10 @@ def test_build_params(basic_graph):
assert "memory" in root.params assert "memory" in root.params
def test_build(basic_graph, complex_graph, openapi_graph): def test_build(basic_graph, complex_graph):
"""Test Node's build method""" """Test Node's build method"""
assert_agent_was_built(basic_graph) assert_agent_was_built(basic_graph)
assert_agent_was_built(complex_graph) assert_agent_was_built(complex_graph)
assert_agent_was_built(openapi_graph)
def assert_agent_was_built(graph): def assert_agent_was_built(graph):
@ -257,14 +258,14 @@ def assert_agent_was_built(graph):
def test_agent_node_build(complex_graph): def test_agent_node_build(complex_graph):
agent_node = get_node_by_type(complex_graph, AgentNode) agent_node = get_node_by_type(complex_graph, AgentVertex)
assert agent_node is not None assert agent_node is not None
built_object = agent_node.build() built_object = agent_node.build()
assert built_object is not None assert built_object is not None
def test_tool_node_build(complex_graph): def test_tool_node_build(complex_graph):
tool_node = get_node_by_type(complex_graph, ToolNode) tool_node = get_node_by_type(complex_graph, ToolVertex)
assert tool_node is not None assert tool_node is not None
built_object = tool_node.build() built_object = tool_node.build()
assert built_object is not None assert built_object is not None
@ -272,7 +273,7 @@ def test_tool_node_build(complex_graph):
def test_chain_node_build(complex_graph): def test_chain_node_build(complex_graph):
chain_node = get_node_by_type(complex_graph, ChainNode) chain_node = get_node_by_type(complex_graph, ChainVertex)
assert chain_node is not None assert chain_node is not None
built_object = chain_node.build() built_object = chain_node.build()
assert built_object is not None assert built_object is not None
@ -280,7 +281,7 @@ def test_chain_node_build(complex_graph):
def test_prompt_node_build(complex_graph): def test_prompt_node_build(complex_graph):
prompt_node = get_node_by_type(complex_graph, PromptNode) prompt_node = get_node_by_type(complex_graph, PromptVertex)
assert prompt_node is not None assert prompt_node is not None
built_object = prompt_node.build() built_object = prompt_node.build()
assert built_object is not None assert built_object is not None
@ -288,7 +289,7 @@ def test_prompt_node_build(complex_graph):
def test_llm_node_build(basic_graph): def test_llm_node_build(basic_graph):
llm_node = get_node_by_type(basic_graph, LLMNode) llm_node = get_node_by_type(basic_graph, LLMVertex)
assert llm_node is not None assert llm_node is not None
built_object = llm_node.build() built_object = llm_node.build()
assert built_object is not None assert built_object is not None
@ -296,7 +297,7 @@ def test_llm_node_build(basic_graph):
def test_toolkit_node_build(openapi_graph): def test_toolkit_node_build(openapi_graph):
toolkit_node = get_node_by_type(openapi_graph, ToolkitNode) toolkit_node = get_node_by_type(openapi_graph, ToolkitVertex)
assert toolkit_node is not None assert toolkit_node is not None
built_object = toolkit_node.build() built_object = toolkit_node.build()
assert built_object is not None assert built_object is not None
@ -304,7 +305,7 @@ def test_toolkit_node_build(openapi_graph):
def test_file_tool_node_build(openapi_graph): def test_file_tool_node_build(openapi_graph):
file_tool_node = get_node_by_type(openapi_graph, FileToolNode) file_tool_node = get_node_by_type(openapi_graph, FileToolVertex)
assert file_tool_node is not None assert file_tool_node is not None
built_object = file_tool_node.build() built_object = file_tool_node.build()
assert built_object is not None assert built_object is not None
@ -312,7 +313,7 @@ def test_file_tool_node_build(openapi_graph):
def test_wrapper_node_build(openapi_graph): def test_wrapper_node_build(openapi_graph):
wrapper_node = get_node_by_type(openapi_graph, WrapperNode) wrapper_node = get_node_by_type(openapi_graph, WrapperVertex)
assert wrapper_node is not None assert wrapper_node is not None
built_object = wrapper_node.build() built_object = wrapper_node.build()
assert built_object is not None assert built_object is not None
@ -327,7 +328,7 @@ def test_get_result_and_thought(basic_graph):
message = "Hello" message = "Hello"
# Find the node that is an LLMNode and change the # Find the node that is an LLMNode and change the
# _built_object to a FakeListLLM # _built_object to a FakeListLLM
llm_node = get_node_by_type(basic_graph, LLMNode) llm_node = get_node_by_type(basic_graph, LLMVertex)
assert llm_node is not None assert llm_node is not None
llm_node._built_object = FakeListLLM(responses=responses) llm_node._built_object = FakeListLLM(responses=responses)
llm_node._built = True llm_node._built = True

82
tests/test_llms_template.py
View file

@ -3,7 +3,7 @@ from langflow.settings import settings
def test_llms_settings(client: TestClient): def test_llms_settings(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
llms = json_response["llms"] llms = json_response["llms"]
@ -11,7 +11,7 @@ def test_llms_settings(client: TestClient):
# def test_hugging_face_hub(client: TestClient): # def test_hugging_face_hub(client: TestClient):
# response = client.get("/all") # response = client.get("api/v1/all")
# assert response.status_code == 200 # assert response.status_code == 200
# json_response = response.json() # json_response = response.json()
# language_models = json_response["llms"] # language_models = json_response["llms"]
@ -103,7 +103,7 @@ def test_llms_settings(client: TestClient):
def test_openai(client: TestClient): def test_openai(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
language_models = json_response["llms"] language_models = json_response["llms"]
@ -333,7 +333,7 @@ def test_openai(client: TestClient):
def test_chat_open_ai(client: TestClient): def test_chat_open_ai(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
language_models = json_response["llms"] language_models = json_response["llms"]
@ -482,3 +482,77 @@ def test_chat_open_ai(client: TestClient):
"ChatOpenAI", "ChatOpenAI",
"BaseLanguageModel", "BaseLanguageModel",
} }
def test_azure_open_ai(client: TestClient):
response = client.get("/all")
assert response.status_code == 200
json_response = response.json()
language_models = json_response["llms"]
model = language_models["AzureOpenAI"]
template = model["template"]
assert template["model_name"].show is False
assert template["deployment_name"] == {
"required": False,
"placeholder": "",
"show": True,
"multiline": False,
"value": "",
"password": False,
"name": "deployment_name",
"advanced": False,
"type": "str",
"list": False,
}
def test_azure_chat_open_ai(client: TestClient):
response = client.get("/all")
assert response.status_code == 200
json_response = response.json()
language_models = json_response["llms"]
model = language_models["AzureChatOpenAI"]
template = model["template"]
assert template["model_name"].show is False
assert template["deployment_name"] == {
"required": False,
"placeholder": "",
"show": True,
"multiline": False,
"value": "",
"password": False,
"name": "deployment_name",
"advanced": False,
"type": "str",
"list": False,
}
assert template["openai_api_type"] == {
"required": False,
"placeholder": "",
"show": False,
"multiline": False,
"value": "azure",
"password": False,
"name": "openai_api_type",
"display_name": "OpenAI API Type",
"advanced": False,
"type": "str",
"list": False,
}
assert template["openai_api_version"] == {
"required": False,
"placeholder": "",
"show": True,
"multiline": False,
"value": "2023-03-15-preview",
"password": False,
"name": "openai_api_version",
"display_name": "OpenAI API Version",
"advanced": False,
"type": "str",
"list": False,
}

2
tests/test_loading.py
View file

@ -2,7 +2,7 @@ import json
import pytest import pytest
from langchain.chains.base import Chain from langchain.chains.base import Chain
from langflow import load_flow_from_json from langflow.processing.process import load_flow_from_json
from langflow.graph import Graph from langflow.graph import Graph
from langflow.utils.payload import get_root_node from langflow.utils.payload import get_root_node

8
tests/test_prompts_template.py
View file

@ -3,7 +3,7 @@ from langflow.settings import settings
def test_prompts_settings(client: TestClient): def test_prompts_settings(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
prompts = json_response["prompts"] prompts = json_response["prompts"]
@ -11,7 +11,7 @@ def test_prompts_settings(client: TestClient):
def test_prompt_template(client: TestClient): def test_prompt_template(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
prompts = json_response["prompts"] prompts = json_response["prompts"]
@ -89,7 +89,7 @@ def test_prompt_template(client: TestClient):
def test_few_shot_prompt_template(client: TestClient): def test_few_shot_prompt_template(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
prompts = json_response["prompts"] prompts = json_response["prompts"]
@ -168,7 +168,7 @@ def test_few_shot_prompt_template(client: TestClient):
def test_zero_shot_prompt(client: TestClient): def test_zero_shot_prompt(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
prompts = json_response["prompts"] prompts = json_response["prompts"]

2
tests/test_vectorstore_template.py
View file

@ -5,7 +5,7 @@ from langflow.settings import settings
# check that all agents are in settings.agents # check that all agents are in settings.agents
# are in json_response["agents"] # are in json_response["agents"]
def test_vectorstores_settings(client: TestClient): def test_vectorstores_settings(client: TestClient):
response = client.get("/all") response = client.get("api/v1/all")
assert response.status_code == 200 assert response.status_code == 200
json_response = response.json() json_response = response.json()
vectorstores = json_response["vectorstores"] vectorstores = json_response["vectorstores"]

8
tests/test_websocket.py
View file

@ -5,17 +5,17 @@ from fastapi.testclient import TestClient
def test_websocket_connection(client: TestClient): def test_websocket_connection(client: TestClient):
with client.websocket_connect("/chat/test_client") as websocket: with client.websocket_connect("api/v1/chat/test_client") as websocket:
assert websocket.scope["client"] == ["testclient", 50000] assert websocket.scope["client"] == ["testclient", 50000]
assert websocket.scope["path"] == "/chat/test_client" assert websocket.scope["path"] == "/api/v1/chat/test_client"
def test_chat_history(client: TestClient): def test_chat_history(client: TestClient):
# Mock the process_graph function to return a specific value # Mock the process_graph function to return a specific value
with patch("langflow.api.chat_manager.process_graph") as mock_process_graph: with patch("langflow.chat.manager.process_graph") as mock_process_graph:
mock_process_graph.return_value = ("Hello, I'm a mock response!", "") mock_process_graph.return_value = ("Hello, I'm a mock response!", "")
with client.websocket_connect("/chat/test_client") as websocket: with client.websocket_connect("api/v1/chat/test_client") as websocket:
# First message should be the history # First message should be the history
history = websocket.receive_json() history = websocket.receive_json()
assert history == [] # Empty history assert history == [] # Empty history