Fix State Service not loading when using load_flow_from_json (#1661)
* Refactor test_loading.py to improve code readability and maintainability * Refactor code in test_template.py, __main__.py, and utils.py to improve code readability and maintainability * Fix logger.configure() to disable logging when disable flag is True * Refactor validate_icon function to use emoji library for emoji validation in model.py * Refactor import statements in base.py files to improve code organization and maintainability * Refactor state_manager.py to handle error when getting state service and use InMemoryStateService as fallback * Refactor load_flow_from_json function in load.py to configure logs and load services * Add test_run_flow_from_json_object function to test_loading.py * Refactor langflow.processing.process.py and langflow.schema.graph.py * Set all streaming to false in run_flow_from_json function * Refactor import statements in base.py files to improve code organization and maintainability * Refactor arun function in base.py to handle event loop and async execution * Add docstring to run_flow_from_json * Refactor import statements in base.py files to use logger in langflow interface * Refactor build method in ChatOutput and TextInput classes to use build_with_record * Refactor import statements in base.py files to improve code organization and maintainability * Refactor import statements in PythonREPLTool.py for improved code organization and maintainability * Refactor build method in TextOutput class to include optional record_template parameter * Refactor build method in ChatComponent class to include build_no_record method * Refactor input_value parameter in TextInput build method to use Text type * Refactor import statements in FlowTool.py for improved code organization and maintainability * Bump langflow-base version to 0.0.25 and add asyncer dependency * Refactor code in multiple files for improved organization and maintainability * Refactor import statements in multiple files for improved code organization and maintainability
This commit is contained in:
Gabriel Luiz Freitas Almeida
GitHub
parent
98d9190eee
commit
b0308336c2
55 changed files with 3856 additions and 4439 deletions
223
poetry.lock
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223
poetry.lock
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@ -167,13 +167,13 @@ files = [
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[[package]]
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name = "anthropic"
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version = "0.23.1"
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version = "0.25.0"
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description = "The official Python library for the anthropic API"
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@ -305,6 +305,20 @@ files = [
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[[package]]
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@ -455,17 +469,17 @@ files = [
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s3transfer = ">=0.10.0,<0.11.0"
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@ -474,13 +488,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
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[[package]]
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name = "botocore"
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[package.dependencies]
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@ -923,17 +937,6 @@ files = [
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name = "chroma-hnswlib"
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@ -2004,13 +2007,13 @@ zstandard = ["zstandard"]
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[[package]]
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[package.extras]
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@ -3654,13 +3657,13 @@ adal = ["adal (>=1.0.2)"]
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[[package]]
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name = "langchain"
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[package.dependencies]
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@ -3668,8 +3671,8 @@ aiohttp = ">=3.8.3,<4.0.0"
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async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
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dataclasses-json = ">=0.5.7,<0.7"
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jsonpatch = ">=1.33,<2.0"
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langchain-community = ">=0.0.30,<0.1"
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langchain-community = ">=0.0.32,<0.1"
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langsmith = ">=0.1.17,<0.2.0"
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numpy = ">=1,<2"
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[[package]]
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name = "langchain-anthropic"
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description = "An integration package connecting AnthropicMessages and LangChain"
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[package.dependencies]
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defusedxml = ">=0.7.1,<0.8.0"
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langchain-core = ">=0.1.41,<0.2.0"
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[[package]]
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name = "langchain-astradb"
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[[package]]
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name = "langchain-community"
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|
||||
extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cloudpickle (>=2.0.0)", "cohere (>=4,<5)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "elasticsearch (>=8.12.0,<9.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "friendli-client (>=1.2.4,<2.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hdbcli (>=2.19.21,<3.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "httpx (>=0.24.1,<0.25.0)", "httpx-sse (>=0.4.0,<0.5.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "nvidia-riva-client (>=2.14.0,<3.0.0)", "oci (>=2.119.1,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "premai (>=0.3.25,<0.4.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pyjwt (>=2.8.0,<3.0.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "tidb-vector (>=0.0.3,<1.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "tree-sitter (>=0.20.2,<0.21.0)", "tree-sitter-languages (>=1.8.0,<2.0.0)", "upstash-redis (>=0.15.0,<0.16.0)", "vdms (>=0.0.20,<0.0.21)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "0.1.40"
|
||||
version = "0.1.41"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_core-0.1.40-py3-none-any.whl", hash = "sha256:618dbb7ab44d8b263b91e384db1ff07d0db256ae5bdafa0123a115b6a75a13f1"},
|
||||
{file = "langchain_core-0.1.40.tar.gz", hash = "sha256:34c06fc0e6d3534b738c63f85403446b4be71161665b7e091f9bb19c914ec100"},
|
||||
{file = "langchain_core-0.1.41-py3-none-any.whl", hash = "sha256:92d3da5ca0d5fb1606b3ab42bfd455c7b386fe4c38f6c0d44ba6014abf46147d"},
|
||||
{file = "langchain_core-0.1.41.tar.gz", hash = "sha256:4002304883b251af8cb781f01c59f56aeee58be42c965dbbdeca0a3bfb8f96af"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -3790,18 +3793,18 @@ extended-testing = ["jinja2 (>=3,<4)"]
|
|||
|
||||
[[package]]
|
||||
name = "langchain-experimental"
|
||||
version = "0.0.56"
|
||||
version = "0.0.57"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_experimental-0.0.56-py3-none-any.whl", hash = "sha256:91fd7a723b0ef3193a63726745523efdd5dd7134116d838c312cfdbf4b354298"},
|
||||
{file = "langchain_experimental-0.0.56.tar.gz", hash = "sha256:ebb1c34815739d3af50c9b709c57b91d0357d567ad2042acb724853c6ba1d735"},
|
||||
{file = "langchain_experimental-0.0.57-py3-none-any.whl", hash = "sha256:96479a2d45a35722cf2fe49655639e91d3fff5ccaba498cda32b088d5b184325"},
|
||||
{file = "langchain_experimental-0.0.57.tar.gz", hash = "sha256:d1fb452aa1f04f32f0e08b83b083f35552f4ece1077c5bdcf86327f56f1758b5"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
langchain = ">=0.1.14,<0.2.0"
|
||||
langchain-core = ">=0.1.37,<0.2.0"
|
||||
langchain = ">=0.1.15,<0.2.0"
|
||||
langchain-core = ">=0.1.41,<0.2.0"
|
||||
|
||||
[package.extras]
|
||||
extended-testing = ["faker (>=19.3.1,<20.0.0)", "jinja2 (>=3,<4)", "pandas (>=2.0.1,<3.0.0)", "presidio-analyzer (>=2.2.352,<3.0.0)", "presidio-anonymizer (>=2.2.352,<3.0.0)", "sentence-transformers (>=2,<3)", "tabulate (>=0.9.0,<0.10.0)", "vowpal-wabbit-next (==0.6.0)"]
|
||||
|
|
@ -3826,17 +3829,17 @@ images = ["pillow (>=10.1.0,<11.0.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "langchain-openai"
|
||||
version = "0.1.1"
|
||||
version = "0.1.2"
|
||||
description = "An integration package connecting OpenAI and LangChain"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_openai-0.1.1-py3-none-any.whl", hash = "sha256:5cf4df5d2550af673337eafedaeec014ba52f9a25aeb8451206ca254bed01e5c"},
|
||||
{file = "langchain_openai-0.1.1.tar.gz", hash = "sha256:d10e9a9fc4c8ea99ca98f23808ce44c7dcdd65354ac07ad10afe874ecf3401ca"},
|
||||
{file = "langchain_openai-0.1.2-py3-none-any.whl", hash = "sha256:45fab91803df22c6d5fce7c010df404569898372df5ae8cd03af50bef774d2ec"},
|
||||
{file = "langchain_openai-0.1.2.tar.gz", hash = "sha256:cd391e61bd93ab72ae24d8e1f250257d6acff6d9e455e623363b8c171533050a"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
langchain-core = ">=0.1.33,<0.2.0"
|
||||
langchain-core = ">=0.1.41,<0.2.0"
|
||||
openai = ">=1.10.0,<2.0.0"
|
||||
tiktoken = ">=0.5.2,<1"
|
||||
|
||||
|
|
@ -3873,7 +3876,7 @@ six = "*"
|
|||
|
||||
[[package]]
|
||||
name = "langflow-base"
|
||||
version = "0.0.24"
|
||||
version = "0.0.25"
|
||||
description = "A Python package with a built-in web application"
|
||||
optional = false
|
||||
python-versions = ">=3.10,<3.12"
|
||||
|
|
@ -3882,6 +3885,7 @@ develop = true
|
|||
|
||||
[package.dependencies]
|
||||
alembic = "^1.13.0"
|
||||
asyncer = "^0.0.5"
|
||||
bcrypt = "4.0.1"
|
||||
cachetools = "^5.3.1"
|
||||
cryptography = "^42.0.5"
|
||||
|
|
@ -3926,18 +3930,17 @@ url = "src/backend/base"
|
|||
|
||||
[[package]]
|
||||
name = "langfuse"
|
||||
version = "2.22.0"
|
||||
version = "2.23.1"
|
||||
description = "A client library for accessing langfuse"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langfuse-2.22.0-py3-none-any.whl", hash = "sha256:9e244e3f8e81c391009b41f51cf8eb8bcd29281a93e90e8b861b231f99a8abe2"},
|
||||
{file = "langfuse-2.22.0.tar.gz", hash = "sha256:e0ed2ced0f8216e88a84331476a21b6ac5e627b340c2b01676d61fb27c368bb4"},
|
||||
{file = "langfuse-2.23.1-py3-none-any.whl", hash = "sha256:d5e2feadc988c0d784b9a89e17e35dea5d90337a58db692a528bd1e084fe01fa"},
|
||||
{file = "langfuse-2.23.1.tar.gz", hash = "sha256:9c2cb4e2610f99095bc8c9db96b0472c1c8fa9b7d28c23419705640b17f460c0"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
backoff = ">=2.2.1,<3.0.0"
|
||||
chevron = ">=0.14.0,<0.15.0"
|
||||
httpx = ">=0.15.4,<1.0"
|
||||
packaging = ">=23.2,<24.0"
|
||||
pydantic = ">=1.10.7,<3.0"
|
||||
|
|
@ -3950,13 +3953,13 @@ openai = ["openai (>=0.27.8)"]
|
|||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.1.40"
|
||||
version = "0.1.43"
|
||||
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langsmith-0.1.40-py3-none-any.whl", hash = "sha256:aa47d0f5a1eabd5c05ac6ce2cd3e28ccfc554d366e856a27b7c3c17c443881cb"},
|
||||
{file = "langsmith-0.1.40.tar.gz", hash = "sha256:50fdf313741cf94e978de06025fd180b56acf1d1a4549b0fd5453ef23d5461ef"},
|
||||
{file = "langsmith-0.1.43-py3-none-any.whl", hash = "sha256:c0a3658f10cbefaa2f53d15db519592982b59d99f24e018dc73aca6092b4158d"},
|
||||
{file = "langsmith-0.1.43.tar.gz", hash = "sha256:983c5a35bf191bb23d93e453c9fc6ea7cda998b1ca96f94680a1446092caf347"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -3983,13 +3986,13 @@ regex = ["regex"]
|
|||
|
||||
[[package]]
|
||||
name = "litellm"
|
||||
version = "1.34.36"
|
||||
version = "1.34.39"
|
||||
description = "Library to easily interface with LLM API providers"
|
||||
optional = false
|
||||
python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
|
||||
files = [
|
||||
{file = "litellm-1.34.36-py3-none-any.whl", hash = "sha256:e5baa7f4540dd2923472f60d3ffb4f76bb48f5288a7fb26efed2010b57b0d8ad"},
|
||||
{file = "litellm-1.34.36.tar.gz", hash = "sha256:03e59c30ae21b9c1df4064dc20b015233c3d86a07bb4832c40dd73021778f3c8"},
|
||||
{file = "litellm-1.34.39-py3-none-any.whl", hash = "sha256:347b7c5ac8a105eb0dccfd4429af1bef550d839cd4f76c36640ade93a267f92a"},
|
||||
{file = "litellm-1.34.39.tar.gz", hash = "sha256:887ef607a0103bd06535f1fc52ac223cfe80a6223e7a2c165e902761db432e84"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4009,12 +4012,12 @@ proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "
|
|||
|
||||
[[package]]
|
||||
name = "llama-cpp-python"
|
||||
version = "0.2.60"
|
||||
version = "0.2.61"
|
||||
description = "Python bindings for the llama.cpp library"
|
||||
optional = true
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "llama_cpp_python-0.2.60.tar.gz", hash = "sha256:0cb98955ae6a14dacb9418d9793e4fe1a5575be3b01a55c1d49d48c79c3b19c3"},
|
||||
{file = "llama_cpp_python-0.2.61.tar.gz", hash = "sha256:2d554259a66040f5daae7f3cf7e43b44971dc49f10225a9ba196eb2a49778bd4"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4026,24 +4029,24 @@ typing-extensions = ">=4.5.0"
|
|||
[package.extras]
|
||||
all = ["llama_cpp_python[dev,server,test]"]
|
||||
dev = ["black (>=23.3.0)", "httpx (>=0.24.1)", "mkdocs (>=1.4.3)", "mkdocs-material (>=9.1.18)", "mkdocstrings[python] (>=0.22.0)", "pytest (>=7.4.0)", "twine (>=4.0.2)"]
|
||||
server = ["fastapi (>=0.100.0)", "pydantic-settings (>=2.0.1)", "sse-starlette (>=1.6.1)", "starlette-context (>=0.3.6,<0.4)", "uvicorn (>=0.22.0)"]
|
||||
server = ["PyYAML (>=5.1)", "fastapi (>=0.100.0)", "pydantic-settings (>=2.0.1)", "sse-starlette (>=1.6.1)", "starlette-context (>=0.3.6,<0.4)", "uvicorn (>=0.22.0)"]
|
||||
test = ["httpx (>=0.24.1)", "pytest (>=7.4.0)", "scipy (>=1.10)"]
|
||||
|
||||
[[package]]
|
||||
name = "llama-index"
|
||||
version = "0.10.27"
|
||||
version = "0.10.28"
|
||||
description = "Interface between LLMs and your data"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "llama_index-0.10.27-py3-none-any.whl", hash = "sha256:e4813786c8240504ac8c394bb36a1755c6de7518a2bcbfc9e54ec78724f0af0b"},
|
||||
{file = "llama_index-0.10.27.tar.gz", hash = "sha256:ef7862df50ceb1cd9f43b7e4b476121dd1a230075d2a8fdc84c92b03239602c7"},
|
||||
{file = "llama_index-0.10.28-py3-none-any.whl", hash = "sha256:2fe2857af6c2d9cefdd978931ebd09f78265a57df2d9d094d0c78869dd0715b8"},
|
||||
{file = "llama_index-0.10.28.tar.gz", hash = "sha256:2ecf9d6da489cc3f99b1adaea50b1549efa55e04cd050f332da784a87c2db846"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
llama-index-agent-openai = ">=0.1.4,<0.3.0"
|
||||
llama-index-cli = ">=0.1.2,<0.2.0"
|
||||
llama-index-core = ">=0.10.27,<0.11.0"
|
||||
llama-index-core = ">=0.10.28,<0.11.0"
|
||||
llama-index-embeddings-openai = ">=0.1.5,<0.2.0"
|
||||
llama-index-indices-managed-llama-cloud = ">=0.1.2,<0.2.0"
|
||||
llama-index-legacy = ">=0.9.48,<0.10.0"
|
||||
|
|
@ -4088,13 +4091,13 @@ llama-index-llms-openai = ">=0.1.1,<0.2.0"
|
|||
|
||||
[[package]]
|
||||
name = "llama-index-core"
|
||||
version = "0.10.27"
|
||||
version = "0.10.28"
|
||||
description = "Interface between LLMs and your data"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "llama_index_core-0.10.27-py3-none-any.whl", hash = "sha256:805b20a16a417180a32a31956710637af75e22cd0849fec2729447d182197d39"},
|
||||
{file = "llama_index_core-0.10.27.tar.gz", hash = "sha256:01881a1943cb7b37f9f8147212d4a55caeef2d68ec498a0a1b864f79cf9d2be4"},
|
||||
{file = "llama_index_core-0.10.28-py3-none-any.whl", hash = "sha256:73e2ec86ea42a0efdc73dcfe46e03ba39ab7725699dcd791464c160d24a02cb1"},
|
||||
{file = "llama_index_core-0.10.28.tar.gz", hash = "sha256:b454640396daa2678b638299e2a5e2539fa3548afd280d45d224fd3b303c20f4"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4200,13 +4203,13 @@ query-tools = ["guidance (>=0.0.64,<0.0.65)", "jsonpath-ng (>=1.6.0,<2.0.0)", "l
|
|||
|
||||
[[package]]
|
||||
name = "llama-index-llms-openai"
|
||||
version = "0.1.14"
|
||||
version = "0.1.15"
|
||||
description = "llama-index llms openai integration"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "llama_index_llms_openai-0.1.14-py3-none-any.whl", hash = "sha256:13cec467962a6ccb9e63451c7febe8e9c2ed536bd6b1058239c2b4fd86776060"},
|
||||
{file = "llama_index_llms_openai-0.1.14.tar.gz", hash = "sha256:7eba66882ae84fa42b188941234b84267c48e449ef214f511756dcad3f9f0b62"},
|
||||
{file = "llama_index_llms_openai-0.1.15-py3-none-any.whl", hash = "sha256:401ba9db1549e4287b73749dee57b11db1e0ffa814bb1464475aea1ff84442c7"},
|
||||
{file = "llama_index_llms_openai-0.1.15.tar.gz", hash = "sha256:6bdbf307b1d43a9a7c2a52f72ba7db61cb96d904f99e7ea5d889dd7818f10814"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4214,13 +4217,13 @@ llama-index-core = ">=0.10.24,<0.11.0"
|
|||
|
||||
[[package]]
|
||||
name = "llama-index-multi-modal-llms-openai"
|
||||
version = "0.1.4"
|
||||
version = "0.1.5"
|
||||
description = "llama-index multi-modal-llms openai integration"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "llama_index_multi_modal_llms_openai-0.1.4-py3-none-any.whl", hash = "sha256:03b887d110551d5d5b99b9fd110824e6311f2e31f4d5e67dafd2ee66da32818d"},
|
||||
{file = "llama_index_multi_modal_llms_openai-0.1.4.tar.gz", hash = "sha256:6a5d6584c33a9d1b06cf5c874c63af2603fc93b660bde481a8c547e876c6e2c3"},
|
||||
{file = "llama_index_multi_modal_llms_openai-0.1.5-py3-none-any.whl", hash = "sha256:bb332580e7e4b5f2f87488b3649d2ceb53ee82c848e59694578a982c3982ce0b"},
|
||||
{file = "llama_index_multi_modal_llms_openai-0.1.5.tar.gz", hash = "sha256:9a237f4f886d1e20c27e9493e80b3e1f8753859481ff1b58fe25b7aa39b198a2"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4261,13 +4264,13 @@ llama-index-program-openai = ">=0.1.1,<0.2.0"
|
|||
|
||||
[[package]]
|
||||
name = "llama-index-readers-file"
|
||||
version = "0.1.15"
|
||||
version = "0.1.16"
|
||||
description = "llama-index readers file integration"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "llama_index_readers_file-0.1.15-py3-none-any.whl", hash = "sha256:f0d26a46d4c40334729d4506d9fbdbed8f5e187e36e22159fb48b28d67c7f240"},
|
||||
{file = "llama_index_readers_file-0.1.15.tar.gz", hash = "sha256:98087d983a1f2d26961805217f13d24b0f23cbbe8e32d2327ae86b1ee668d3b2"},
|
||||
{file = "llama_index_readers_file-0.1.16-py3-none-any.whl", hash = "sha256:1a3f3bc1f09c6894318a5392edc43b118fabc2f2820f446c51cad73676662f73"},
|
||||
{file = "llama_index_readers_file-0.1.16.tar.gz", hash = "sha256:7f25b8fddaf1a91bac06c66727b913b48e26ef68714fcd5197051b3f710f4cfa"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -6599,13 +6602,13 @@ pyasn1 = ">=0.4.6,<0.7.0"
|
|||
|
||||
[[package]]
|
||||
name = "pyautogen"
|
||||
version = "0.2.22"
|
||||
version = "0.2.23"
|
||||
description = "Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework"
|
||||
optional = false
|
||||
python-versions = "<3.13,>=3.8"
|
||||
files = [
|
||||
{file = "pyautogen-0.2.22-py3-none-any.whl", hash = "sha256:022d451ea286914024c5fb0e83f5c6622df925ce02a4e10f410389e9f003cbcc"},
|
||||
{file = "pyautogen-0.2.22.tar.gz", hash = "sha256:8d25ae881779d95c13f477a42c448e91f1038c080c5bf6b905ccc1559f7ac535"},
|
||||
{file = "pyautogen-0.2.23-py3-none-any.whl", hash = "sha256:f4e2d57f60561fd34e3d9ebf31db5005ab147bb356eeaf829a1fdbbf74400f29"},
|
||||
{file = "pyautogen-0.2.23.tar.gz", hash = "sha256:88859cca22ba6718a755abb23ed0edd93ceebb9d70b822e921940c23116e5e46"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -8171,37 +8174,37 @@ torch = ["safetensors[numpy]", "torch (>=1.10)"]
|
|||
|
||||
[[package]]
|
||||
name = "scikit-learn"
|
||||
version = "1.4.1.post1"
|
||||
version = "1.4.2"
|
||||
description = "A set of python modules for machine learning and data mining"
|
||||
optional = true
|
||||
python-versions = ">=3.9"
|
||||
files = [
|
||||
{file = "scikit-learn-1.4.1.post1.tar.gz", hash = "sha256:93d3d496ff1965470f9977d05e5ec3376fb1e63b10e4fda5e39d23c2d8969a30"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c540aaf44729ab5cd4bd5e394f2b375e65ceaea9cdd8c195788e70433d91bbc5"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:4310bff71aa98b45b46cd26fa641309deb73a5d1c0461d181587ad4f30ea3c36"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9f43dd527dabff5521af2786a2f8de5ba381e182ec7292663508901cf6ceaf6e"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c02e27d65b0c7dc32f2c5eb601aaf5530b7a02bfbe92438188624524878336f2"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp310-cp310-win_amd64.whl", hash = "sha256:629e09f772ad42f657ca60a1a52342eef786218dd20cf1369a3b8d085e55ef8f"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6145dfd9605b0b50ae72cdf72b61a2acd87501369a763b0d73d004710ebb76b5"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:1afed6951bc9d2053c6ee9a518a466cbc9b07c6a3f9d43bfe734192b6125d508"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ce03506ccf5f96b7e9030fea7eb148999b254c44c10182ac55857bc9b5d4815f"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4ba516fcdc73d60e7f48cbb0bccb9acbdb21807de3651531208aac73c758e3ab"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp311-cp311-win_amd64.whl", hash = "sha256:78cd27b4669513b50db4f683ef41ea35b5dddc797bd2bbd990d49897fd1c8a46"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:a1e289f33f613cefe6707dead50db31930530dc386b6ccff176c786335a7b01c"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:0df87de9ce1c0140f2818beef310fb2e2afdc1e66fc9ad587965577f17733649"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:712c1c69c45b58ef21635360b3d0a680ff7d83ac95b6f9b82cf9294070cda710"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1754b0c2409d6ed5a3380512d0adcf182a01363c669033a2b55cca429ed86a81"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp312-cp312-win_amd64.whl", hash = "sha256:1d491ef66e37f4e812db7e6c8286520c2c3fc61b34bf5e59b67b4ce528de93af"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:aa0029b78ef59af22cfbd833e8ace8526e4df90212db7ceccbea582ebb5d6794"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:14e4c88436ac96bf69eb6d746ac76a574c314a23c6961b7d344b38877f20fee1"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d7cd3a77c32879311f2aa93466d3c288c955ef71d191503cf0677c3340ae8ae0"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2a3ee19211ded1a52ee37b0a7b373a8bfc66f95353af058a210b692bd4cda0dd"},
|
||||
{file = "scikit_learn-1.4.1.post1-cp39-cp39-win_amd64.whl", hash = "sha256:234b6bda70fdcae9e4abbbe028582ce99c280458665a155eed0b820599377d25"},
|
||||
{file = "scikit-learn-1.4.2.tar.gz", hash = "sha256:daa1c471d95bad080c6e44b4946c9390a4842adc3082572c20e4f8884e39e959"},
|
||||
{file = "scikit_learn-1.4.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:8539a41b3d6d1af82eb629f9c57f37428ff1481c1e34dddb3b9d7af8ede67ac5"},
|
||||
{file = "scikit_learn-1.4.2-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:68b8404841f944a4a1459b07198fa2edd41a82f189b44f3e1d55c104dbc2e40c"},
|
||||
{file = "scikit_learn-1.4.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:81bf5d8bbe87643103334032dd82f7419bc8c8d02a763643a6b9a5c7288c5054"},
|
||||
{file = "scikit_learn-1.4.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:36f0ea5d0f693cb247a073d21a4123bdf4172e470e6d163c12b74cbb1536cf38"},
|
||||
{file = "scikit_learn-1.4.2-cp310-cp310-win_amd64.whl", hash = "sha256:87440e2e188c87db80ea4023440923dccbd56fbc2d557b18ced00fef79da0727"},
|
||||
{file = "scikit_learn-1.4.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:45dee87ac5309bb82e3ea633955030df9bbcb8d2cdb30383c6cd483691c546cc"},
|
||||
{file = "scikit_learn-1.4.2-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:1d0b25d9c651fd050555aadd57431b53d4cf664e749069da77f3d52c5ad14b3b"},
|
||||
{file = "scikit_learn-1.4.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b0203c368058ab92efc6168a1507d388d41469c873e96ec220ca8e74079bf62e"},
|
||||
{file = "scikit_learn-1.4.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:44c62f2b124848a28fd695db5bc4da019287abf390bfce602ddc8aa1ec186aae"},
|
||||
{file = "scikit_learn-1.4.2-cp311-cp311-win_amd64.whl", hash = "sha256:5cd7b524115499b18b63f0c96f4224eb885564937a0b3477531b2b63ce331904"},
|
||||
{file = "scikit_learn-1.4.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:90378e1747949f90c8f385898fff35d73193dfcaec3dd75d6b542f90c4e89755"},
|
||||
{file = "scikit_learn-1.4.2-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:ff4effe5a1d4e8fed260a83a163f7dbf4f6087b54528d8880bab1d1377bd78be"},
|
||||
{file = "scikit_learn-1.4.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:671e2f0c3f2c15409dae4f282a3a619601fa824d2c820e5b608d9d775f91780c"},
|
||||
{file = "scikit_learn-1.4.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d36d0bc983336bbc1be22f9b686b50c964f593c8a9a913a792442af9bf4f5e68"},
|
||||
{file = "scikit_learn-1.4.2-cp312-cp312-win_amd64.whl", hash = "sha256:d762070980c17ba3e9a4a1e043ba0518ce4c55152032f1af0ca6f39b376b5928"},
|
||||
{file = "scikit_learn-1.4.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:d9993d5e78a8148b1d0fdf5b15ed92452af5581734129998c26f481c46586d68"},
|
||||
{file = "scikit_learn-1.4.2-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:426d258fddac674fdf33f3cb2d54d26f49406e2599dbf9a32b4d1696091d4256"},
|
||||
{file = "scikit_learn-1.4.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5460a1a5b043ae5ae4596b3126a4ec33ccba1b51e7ca2c5d36dac2169f62ab1d"},
|
||||
{file = "scikit_learn-1.4.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:49d64ef6cb8c093d883e5a36c4766548d974898d378e395ba41a806d0e824db8"},
|
||||
{file = "scikit_learn-1.4.2-cp39-cp39-win_amd64.whl", hash = "sha256:c97a50b05c194be9146d61fe87dbf8eac62b203d9e87a3ccc6ae9aed2dfaf361"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
joblib = ">=1.2.0"
|
||||
numpy = ">=1.19.5,<2.0"
|
||||
numpy = ">=1.19.5"
|
||||
scipy = ">=1.6.0"
|
||||
threadpoolctl = ">=2.0.0"
|
||||
|
||||
|
|
@ -9039,13 +9042,13 @@ tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
|
|||
|
||||
[[package]]
|
||||
name = "typer"
|
||||
version = "0.12.2"
|
||||
version = "0.12.3"
|
||||
description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "typer-0.12.2-py3-none-any.whl", hash = "sha256:e1accbaa7e2b2350753acec896ac30493ac573211a8d4603e88f8356217e01f7"},
|
||||
{file = "typer-0.12.2.tar.gz", hash = "sha256:977929604fde12aeada011852ad9c64370501be6ac2eac248f3161cdc9eeb7c9"},
|
||||
{file = "typer-0.12.3-py3-none-any.whl", hash = "sha256:070d7ca53f785acbccba8e7d28b08dcd88f79f1fbda035ade0aecec71ca5c914"},
|
||||
{file = "typer-0.12.3.tar.gz", hash = "sha256:49e73131481d804288ef62598d97a1ceef3058905aa536a1134f90891ba35482"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
|
|||
|
|
@ -9,6 +9,12 @@ import click
|
|||
import httpx
|
||||
import typer
|
||||
from dotenv import load_dotenv
|
||||
from langflow.main import setup_app
|
||||
from langflow.services.database.utils import session_getter
|
||||
from langflow.services.deps import get_db_service
|
||||
from langflow.services.utils import initialize_services
|
||||
from langflow.utils.logger import configure, logger
|
||||
from langflow.utils.util import update_settings
|
||||
from multiprocess import Process, cpu_count # type: ignore
|
||||
from packaging import version as pkg_version
|
||||
from rich import box
|
||||
|
|
@ -17,12 +23,6 @@ from rich.console import Console
|
|||
from rich.panel import Panel
|
||||
from rich.table import Table
|
||||
|
||||
from langflow.main import setup_app
|
||||
from langflow.services.database.utils import session_getter
|
||||
from langflow.services.deps import get_db_service, get_settings_service
|
||||
from langflow.services.utils import initialize_services, initialize_settings_service
|
||||
from langflow.utils.logger import configure, logger
|
||||
|
||||
console = Console()
|
||||
|
||||
app = typer.Typer(no_args_is_help=True)
|
||||
|
|
@ -68,36 +68,6 @@ def set_var_for_macos_issue():
|
|||
logger.debug("Set OBJC_DISABLE_INITIALIZE_FORK_SAFETY to YES to avoid error")
|
||||
|
||||
|
||||
def update_settings(
|
||||
config: str,
|
||||
cache: Optional[str] = None,
|
||||
dev: bool = False,
|
||||
remove_api_keys: bool = False,
|
||||
components_path: Optional[Path] = None,
|
||||
store: bool = True,
|
||||
):
|
||||
"""Update the settings from a config file."""
|
||||
|
||||
# Check for database_url in the environment variables
|
||||
initialize_settings_service()
|
||||
settings_service = get_settings_service()
|
||||
if config:
|
||||
logger.debug(f"Loading settings from {config}")
|
||||
settings_service.settings.update_from_yaml(config, dev=dev)
|
||||
if remove_api_keys:
|
||||
logger.debug(f"Setting remove_api_keys to {remove_api_keys}")
|
||||
settings_service.settings.update_settings(REMOVE_API_KEYS=remove_api_keys)
|
||||
if cache:
|
||||
logger.debug(f"Setting cache to {cache}")
|
||||
settings_service.settings.update_settings(CACHE=cache)
|
||||
if components_path:
|
||||
logger.debug(f"Adding component path {components_path}")
|
||||
settings_service.settings.update_settings(COMPONENTS_PATH=components_path)
|
||||
if not store:
|
||||
logger.debug("Setting store to False")
|
||||
settings_service.settings.update_settings(STORE=False)
|
||||
|
||||
|
||||
@app.command()
|
||||
def run(
|
||||
host: str = typer.Option("127.0.0.1", help="Host to bind the server to.", envvar="LANGFLOW_HOST"),
|
||||
|
|
@ -316,7 +286,7 @@ def is_prerelease(version: str) -> bool:
|
|||
return "a" in version or "b" in version or "rc" in version
|
||||
|
||||
|
||||
def fetch_latest_version(package_name: str, include_prerelease: bool) -> str:
|
||||
def fetch_latest_version(package_name: str, include_prerelease: bool) -> Optional[str]:
|
||||
response = httpx.get(f"https://pypi.org/pypi/{package_name}/json")
|
||||
versions = response.json()["releases"].keys()
|
||||
valid_versions = [v for v in versions if include_prerelease or not is_prerelease(v)]
|
||||
|
|
@ -358,7 +328,7 @@ def print_banner(host: str, port: int):
|
|||
package_name = ""
|
||||
|
||||
try:
|
||||
from langflow.version import __version__ as langflow_version
|
||||
from langflow.version import __version__ as langflow_version # type: ignore
|
||||
|
||||
is_pre_release |= is_prerelease(langflow_version) # Update pre-release status
|
||||
notice = build_version_notice(langflow_version, "langflow")
|
||||
|
|
|
|||
|
|
@ -14,7 +14,6 @@ from langflow.api.v1.schemas import (
|
|||
RunResponse,
|
||||
SimplifiedAPIRequest,
|
||||
TaskStatusResponse,
|
||||
Tweaks,
|
||||
UpdateCustomComponentRequest,
|
||||
UploadFileResponse,
|
||||
)
|
||||
|
|
@ -24,6 +23,7 @@ from langflow.interface.custom.custom_component import CustomComponent
|
|||
from langflow.interface.custom.directory_reader import DirectoryReader
|
||||
from langflow.interface.custom.utils import build_custom_component_template
|
||||
from langflow.processing.process import process_tweaks, run_graph_internal
|
||||
from langflow.schema.graph import Tweaks
|
||||
from langflow.services.auth.utils import api_key_security, get_current_active_user
|
||||
from langflow.services.cache.utils import save_uploaded_file
|
||||
from langflow.services.database.models.flow import Flow
|
||||
|
|
@ -373,7 +373,7 @@ async def create_upload_file(
|
|||
@router.get("/version")
|
||||
def get_version():
|
||||
try:
|
||||
from langflow.version import __version__
|
||||
from langflow.version import __version__ # type: ignore
|
||||
|
||||
version = __version__
|
||||
package = "Langflow"
|
||||
|
|
|
|||
|
|
@ -4,10 +4,11 @@ from pathlib import Path
|
|||
from typing import Any, Dict, List, Optional, Union
|
||||
from uuid import UUID
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, Field, RootModel, field_validator, model_serializer
|
||||
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_serializer
|
||||
|
||||
from langflow.graph.schema import RunOutputs
|
||||
from langflow.schema import dotdict
|
||||
from langflow.schema.graph import Tweaks
|
||||
from langflow.schema.schema import InputType, OutputType
|
||||
from langflow.services.database.models.api_key.model import ApiKeyRead
|
||||
from langflow.services.database.models.base import orjson_dumps
|
||||
|
|
@ -283,36 +284,6 @@ class InputValueRequest(BaseModel):
|
|||
)
|
||||
|
||||
|
||||
class Tweaks(RootModel):
|
||||
root: dict[str, Union[str, dict[str, str]]] = Field(
|
||||
description="A dictionary of tweaks to adjust the flow's execution. Allows customizing flow behavior dynamically. All tweaks are overridden by the input values.",
|
||||
)
|
||||
model_config = {
|
||||
"json_schema_extra": {
|
||||
"examples": [
|
||||
{
|
||||
"parameter_name": "value",
|
||||
"Component Name": {"parameter_name": "value"},
|
||||
"component_id": {"parameter_name": "value"},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
# This should behave like a dict
|
||||
def __getitem__(self, key):
|
||||
return self.root[key]
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
self.root[key] = value
|
||||
|
||||
def __delitem__(self, key):
|
||||
del self.root[key]
|
||||
|
||||
def items(self):
|
||||
return self.root.items()
|
||||
|
||||
|
||||
class SimplifiedAPIRequest(BaseModel):
|
||||
input_value: Optional[str] = Field(default="", description="The input value")
|
||||
input_type: Optional[InputType] = Field(default="chat", description="The input type")
|
||||
|
|
|
|||
|
|
@ -79,7 +79,7 @@ class ChatComponent(CustomComponent):
|
|||
records = add_messages([record])
|
||||
return records[0]
|
||||
|
||||
def build(
|
||||
def build_with_record(
|
||||
self,
|
||||
sender: Optional[str] = "User",
|
||||
sender_name: Optional[str] = "User",
|
||||
|
|
@ -116,3 +116,41 @@ class ChatComponent(CustomComponent):
|
|||
if session_id and isinstance(result, (Record, str)):
|
||||
self.store_message(result, session_id, sender, sender_name)
|
||||
return result
|
||||
|
||||
def build_no_record(
|
||||
self,
|
||||
sender: Optional[str] = "User",
|
||||
sender_name: Optional[str] = "User",
|
||||
input_value: Optional[str] = None,
|
||||
session_id: Optional[str] = None,
|
||||
return_record: Optional[bool] = False,
|
||||
record_template: str = "Text: {text}\nData: {data}",
|
||||
) -> Union[Text, Record]:
|
||||
input_value_record: Optional[Record] = None
|
||||
if return_record:
|
||||
if isinstance(input_value, Record):
|
||||
# Update the data of the record
|
||||
input_value.data["sender"] = sender
|
||||
input_value.data["sender_name"] = sender_name
|
||||
input_value.data["session_id"] = session_id
|
||||
else:
|
||||
input_value_record = Record(
|
||||
text=input_value,
|
||||
data={
|
||||
"sender": sender,
|
||||
"sender_name": sender_name,
|
||||
"session_id": session_id,
|
||||
},
|
||||
)
|
||||
elif isinstance(input_value, Record):
|
||||
input_value = records_to_text(template=record_template, records=input_value)
|
||||
if not input_value:
|
||||
input_value = ""
|
||||
if return_record and input_value_record:
|
||||
result: Union[Text, Record] = input_value_record
|
||||
else:
|
||||
result = input_value
|
||||
self.status = result
|
||||
if session_id and isinstance(result, (Record, str)):
|
||||
self.store_message(result, session_id, sender, sender_name)
|
||||
return result
|
||||
|
|
|
|||
|
|
@ -3,7 +3,6 @@ import json
|
|||
from typing import List, Optional
|
||||
|
||||
import httpx
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.schema import Record
|
||||
|
||||
|
|
@ -47,8 +46,8 @@ class APIRequest(CustomComponent):
|
|||
client: httpx.AsyncClient,
|
||||
method: str,
|
||||
url: str,
|
||||
headers: Optional[Record] = None,
|
||||
body: Optional[Record] = None,
|
||||
headers: Optional[dict] = None,
|
||||
body: Optional[dict] = None,
|
||||
timeout: int = 5,
|
||||
) -> Record:
|
||||
method = method.upper()
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from langchain_openai.embeddings.base import OpenAIEmbeddings
|
||||
from pydantic.v1 import SecretStr
|
||||
|
||||
from langflow.field_typing import Embeddings, NestedDict
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
|
@ -113,6 +114,10 @@ class OpenAIEmbeddingsComponent(CustomComponent):
|
|||
# This is to avoid errors with Vector Stores (e.g Chroma)
|
||||
if disallowed_special == ["all"]:
|
||||
disallowed_special = "all" # type: ignore
|
||||
if openai_api_key:
|
||||
api_key = SecretStr(openai_api_key)
|
||||
else:
|
||||
api_key = None
|
||||
|
||||
return OpenAIEmbeddings(
|
||||
tiktoken_enabled=tiktoken_enable,
|
||||
|
|
@ -128,7 +133,7 @@ class OpenAIEmbeddingsComponent(CustomComponent):
|
|||
model=model,
|
||||
model_kwargs=model_kwargs,
|
||||
base_url=openai_api_base,
|
||||
api_key=openai_api_key,
|
||||
api_key=api_key,
|
||||
openai_api_type=openai_api_type,
|
||||
api_version=openai_api_version,
|
||||
organization=openai_organization,
|
||||
|
|
|
|||
|
|
@ -1,14 +1,14 @@
|
|||
from typing import Any, List, Optional
|
||||
|
||||
from asyncer import syncify
|
||||
from langchain_core.tools import StructuredTool
|
||||
from loguru import logger
|
||||
|
||||
from langflow.custom import CustomComponent
|
||||
from langflow.field_typing import Tool
|
||||
from langflow.graph.graph.base import Graph
|
||||
from langflow.helpers.flow import build_function_and_schema
|
||||
from langflow.schema.dotdict import dotdict
|
||||
from langflow.schema.schema import Record
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class FlowToolComponent(CustomComponent):
|
||||
|
|
@ -74,6 +74,7 @@ class FlowToolComponent(CustomComponent):
|
|||
graph = Graph.from_payload(flow_record.data["data"])
|
||||
dynamic_flow_function, schema = build_function_and_schema(flow_record, graph)
|
||||
tool = StructuredTool.from_function(
|
||||
func=syncify(dynamic_flow_function, raise_sync_error=False), # type: ignore
|
||||
coroutine=dynamic_flow_function,
|
||||
name=name,
|
||||
description=description,
|
||||
|
|
|
|||
|
|
@ -61,6 +61,6 @@ class MemoryComponent(CustomComponent):
|
|||
limit=n_messages,
|
||||
order=order,
|
||||
)
|
||||
messages_str = records_to_text(template=record_template, records=messages)
|
||||
messages_str = records_to_text(template=record_template or "", records=messages)
|
||||
self.status = messages_str
|
||||
return messages_str
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
from typing import Optional
|
||||
from typing import Optional, Union
|
||||
|
||||
from langchain.text_splitter import CharacterTextSplitter, RecursiveCharacterTextSplitter
|
||||
from langchain_core.documents import Document
|
||||
|
|
@ -51,6 +51,8 @@ class SplitTextComponent(CustomComponent):
|
|||
chunk_overlap: Optional[int] = 200,
|
||||
recursive: bool = False,
|
||||
) -> list[Record]:
|
||||
if separators is None:
|
||||
separators = []
|
||||
separators = [unescape_string(x) for x in separators]
|
||||
|
||||
# Make sure chunk_size and chunk_overlap are ints
|
||||
|
|
@ -58,7 +60,7 @@ class SplitTextComponent(CustomComponent):
|
|||
chunk_size = int(chunk_size)
|
||||
if isinstance(chunk_overlap, str):
|
||||
chunk_overlap = int(chunk_overlap)
|
||||
|
||||
splitter: Optional[Union[CharacterTextSplitter, RecursiveCharacterTextSplitter]] = None
|
||||
if recursive:
|
||||
splitter = RecursiveCharacterTextSplitter(
|
||||
separators=separators,
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ class ChatInput(ChatComponent):
|
|||
session_id: Optional[str] = None,
|
||||
return_record: Optional[bool] = False,
|
||||
) -> Union[Text, Record]:
|
||||
return super().build(
|
||||
return super().build_no_record(
|
||||
sender=sender,
|
||||
sender_name=sender_name,
|
||||
input_value=input_value,
|
||||
|
|
|
|||
|
|
@ -26,7 +26,7 @@ class TextInput(TextComponent):
|
|||
|
||||
def build(
|
||||
self,
|
||||
input_value: Optional[str] = "",
|
||||
input_value: Optional[Text] = "",
|
||||
record_template: Optional[str] = "",
|
||||
) -> Text:
|
||||
return super().build(input_value=input_value, record_template=record_template)
|
||||
|
|
|
|||
|
|
@ -1,10 +1,7 @@
|
|||
from .AmazonBedrockSpecs import AmazonBedrockComponent
|
||||
from .AnthropicLLMSpecs import ChatAntropicSpecsComponent
|
||||
|
||||
from .AzureChatOpenAISpecs import AzureChatOpenAISpecsComponent
|
||||
from .BaiduQianfanChatEndpointsSpecs import QianfanChatEndpointComponent
|
||||
from .BaiduQianfanLLMEndpointsSpecs import QianfanLLMEndpointComponent
|
||||
from .ChatAnthropicSpecs import ChatAnthropicComponent
|
||||
from .ChatAnthropicSpecs import AnthropicLLM
|
||||
from .ChatLiteLLMSpecs import ChatLiteLLMComponent
|
||||
from .ChatOllamaEndpointSpecs import ChatOllamaComponent
|
||||
from .ChatOpenAISpecs import ChatOpenAIComponent
|
||||
|
|
@ -21,7 +18,7 @@ __all__ = [
|
|||
"AzureChatOpenAISpecsComponent",
|
||||
"QianfanChatEndpointComponent",
|
||||
"QianfanLLMEndpointComponent",
|
||||
"ChatAnthropicComponent",
|
||||
"AnthropicLLM",
|
||||
"ChatLiteLLMComponent",
|
||||
"ChatOllamaComponent",
|
||||
"ChatOpenAIComponent",
|
||||
|
|
|
|||
|
|
@ -2,6 +2,7 @@ from typing import Optional
|
|||
|
||||
from langchain.llms.base import BaseLanguageModel
|
||||
from langchain_openai import AzureChatOpenAI
|
||||
from pydantic.v1 import SecretStr
|
||||
|
||||
from langflow.base.constants import STREAM_INFO_TEXT
|
||||
from langflow.base.models.model import LCModelComponent
|
||||
|
|
@ -105,13 +106,17 @@ class AzureChatOpenAIComponent(LCModelComponent):
|
|||
max_tokens: Optional[int] = 1000,
|
||||
stream: bool = False,
|
||||
) -> BaseLanguageModel:
|
||||
if api_key:
|
||||
secret_api_key = SecretStr(api_key)
|
||||
else:
|
||||
secret_api_key = None
|
||||
try:
|
||||
output = AzureChatOpenAI(
|
||||
model=model,
|
||||
azure_endpoint=azure_endpoint,
|
||||
azure_deployment=azure_deployment,
|
||||
api_version=api_version,
|
||||
api_key=api_key,
|
||||
api_key=secret_api_key,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
from typing import Optional
|
||||
|
||||
from langchain_openai import ChatOpenAI
|
||||
from pydantic.v1 import SecretStr
|
||||
|
||||
from langflow.base.constants import STREAM_INFO_TEXT
|
||||
from langflow.base.models.model import LCModelComponent
|
||||
|
|
@ -94,12 +95,17 @@ class OpenAIModelComponent(LCModelComponent):
|
|||
) -> Text:
|
||||
if not openai_api_base:
|
||||
openai_api_base = "https://api.openai.com/v1"
|
||||
if openai_api_key:
|
||||
api_key = SecretStr(openai_api_key)
|
||||
else:
|
||||
api_key = None
|
||||
|
||||
output = ChatOpenAI(
|
||||
max_tokens=max_tokens,
|
||||
model_kwargs=model_kwargs,
|
||||
model=model_name,
|
||||
base_url=openai_api_base,
|
||||
api_key=openai_api_key,
|
||||
api_key=api_key,
|
||||
temperature=temperature,
|
||||
)
|
||||
|
||||
|
|
|
|||
|
|
@ -19,11 +19,11 @@ class ChatOutput(ChatComponent):
|
|||
return_record: Optional[bool] = False,
|
||||
record_template: Optional[str] = "{text}",
|
||||
) -> Union[Text, Record]:
|
||||
return super().build(
|
||||
return super().build_with_record(
|
||||
sender=sender,
|
||||
sender_name=sender_name,
|
||||
input_value=input_value,
|
||||
session_id=session_id,
|
||||
return_record=return_record,
|
||||
record_template=record_template,
|
||||
record_template=record_template or "",
|
||||
)
|
||||
|
|
|
|||
|
|
@ -24,5 +24,5 @@ class TextOutput(TextComponent):
|
|||
},
|
||||
}
|
||||
|
||||
def build(self, input_value: Optional[Text] = "", record_template: str = "") -> Text:
|
||||
def build(self, input_value: Optional[Text] = "", record_template: Optional[str] = "") -> Text:
|
||||
return super().build(input_value=input_value, record_template=record_template)
|
||||
|
|
|
|||
|
|
@ -34,8 +34,8 @@ class PythonREPLToolComponent(CustomComponent):
|
|||
global_dict = {}
|
||||
for module in globals:
|
||||
try:
|
||||
module = importlib.import_module(module)
|
||||
global_dict[module.__name__] = module
|
||||
imported_module = importlib.import_module(module)
|
||||
global_dict[imported_module.__name__] = imported_module
|
||||
except ImportError:
|
||||
print(f"Could not import module {module}")
|
||||
return global_dict
|
||||
|
|
|
|||
|
|
@ -296,18 +296,27 @@ class Graph:
|
|||
# run the async function in a sync way
|
||||
# this could be used in a FastAPI endpoint
|
||||
# so we should take care of the event loop
|
||||
loop = asyncio.get_event_loop()
|
||||
return loop.run_until_complete(
|
||||
self.arun(
|
||||
inputs=inputs,
|
||||
inputs_components=input_components,
|
||||
types=types,
|
||||
outputs=outputs,
|
||||
session_id=session_id,
|
||||
stream=stream,
|
||||
)
|
||||
coro = self.arun(
|
||||
inputs=inputs,
|
||||
inputs_components=input_components,
|
||||
types=types,
|
||||
outputs=outputs,
|
||||
session_id=session_id,
|
||||
stream=stream,
|
||||
)
|
||||
|
||||
try:
|
||||
# Attempt to get the running event loop; if none, an exception is raised
|
||||
loop = asyncio.get_running_loop()
|
||||
if loop.is_closed():
|
||||
raise RuntimeError("The running event loop is closed.")
|
||||
except RuntimeError:
|
||||
# If there's no running event loop or it's closed, use asyncio.run
|
||||
return asyncio.run(coro)
|
||||
|
||||
# If there's an existing, open event loop, use it to run the async function
|
||||
return loop.run_until_complete(coro)
|
||||
|
||||
async def arun(
|
||||
self,
|
||||
inputs: list[Dict[str, str]],
|
||||
|
|
|
|||
|
|
@ -1,15 +1,22 @@
|
|||
from typing import TYPE_CHECKING, Callable
|
||||
|
||||
from langflow.services.deps import get_state_service
|
||||
from loguru import logger
|
||||
|
||||
from langflow.services.deps import get_settings_service, get_state_service
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.services.state.service import StateService
|
||||
|
||||
|
||||
class GraphStateManager:
|
||||
def __init__(self):
|
||||
self.state_service: "StateService" = get_state_service()
|
||||
try:
|
||||
self.state_service: "StateService" = get_state_service()
|
||||
except Exception as e:
|
||||
logger.debug(f"Error getting state service. Defaulting to InMemoryStateService: {e}")
|
||||
from langflow.services.state.service import InMemoryStateService
|
||||
|
||||
self.state_service = InMemoryStateService(get_settings_service())
|
||||
|
||||
def append_state(self, key, new_state, run_id: str):
|
||||
self.state_service.append_state(key, new_state, run_id)
|
||||
|
|
|
|||
|
|
@ -1,11 +1,10 @@
|
|||
from typing import TYPE_CHECKING, Any, Callable, Coroutine, List, Optional, Tuple, Type, Union, cast
|
||||
|
||||
from pydantic.v1 import BaseModel, Field, create_model
|
||||
from sqlmodel import select
|
||||
from typing import TYPE_CHECKING, Any, Awaitable, Callable, List, Optional, Tuple, Type, Union, cast
|
||||
|
||||
from langflow.schema.schema import INPUT_FIELD_NAME, Record
|
||||
from langflow.services.database.models.flow.model import Flow
|
||||
from langflow.services.deps import session_scope
|
||||
from pydantic.v1 import BaseModel, Field, create_model
|
||||
from sqlmodel import select
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.graph.graph.base import Graph
|
||||
|
|
@ -86,7 +85,7 @@ async def run_flow(
|
|||
return await graph.arun(inputs_list, inputs_components=inputs_components, types=types)
|
||||
|
||||
|
||||
def generate_function_for_flow(inputs: List["Vertex"], flow_id: str) -> Coroutine:
|
||||
def generate_function_for_flow(inputs: List["Vertex"], flow_id: str) -> Callable[..., Awaitable[Any]]:
|
||||
"""
|
||||
Generate a dynamic flow function based on the given inputs and flow ID.
|
||||
|
||||
|
|
@ -145,7 +144,9 @@ async def flow_function({func_args}):
|
|||
return local_scope["flow_function"]
|
||||
|
||||
|
||||
def build_function_and_schema(flow_record: Record, graph: "Graph") -> Tuple[Callable, Type[BaseModel]]:
|
||||
def build_function_and_schema(
|
||||
flow_record: Record, graph: "Graph"
|
||||
) -> Tuple[Callable[..., Awaitable[Any]], Type[BaseModel]]:
|
||||
"""
|
||||
Builds a dynamic function and schema for a given flow.
|
||||
|
||||
|
|
|
|||
|
|
@ -1,888 +0,0 @@
|
|||
{
|
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"id": "c091a57f-43a7-4a5e-b352-035ae8d8379c",
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"nodes": [
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{
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"id": "Prompt-uxBqP",
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"type": "genericNode",
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"position": {
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"y": -107.07318910019967
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"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from langchain_core.prompts import PromptTemplate\n\nfrom langflow.field_typing import Prompt, TemplateField, Text\nfrom langflow.interface.custom.custom_component import CustomComponent\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n def build_config(self):\n return {\n \"template\": TemplateField(display_name=\"Template\"),\n \"code\": TemplateField(advanced=True),\n }\n\n def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Text:\n from langflow.base.prompts.utils import dict_values_to_string\n\n prompt_template = PromptTemplate.from_template(Text(template))\n kwargs = dict_values_to_string(kwargs)\n kwargs = {k: \"\\n\".join(v) if isinstance(v, list) else v for k, v in kwargs.items()}\n try:\n formated_prompt = prompt_template.format(**kwargs)\n except Exception as exc:\n raise ValueError(f\"Error formatting prompt: {exc}\") from exc\n self.status = f'Prompt:\\n\"{formated_prompt}\"'\n return formated_prompt\n",
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"type": "prompt",
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"required": false,
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"placeholder": "",
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"list": false,
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||||
"show": true,
|
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"multiline": false,
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"value": "Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: ",
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"file_path": "",
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"password": false,
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"load_from_db": false,
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},
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"display_name": "user_input",
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"advanced": false,
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"input_types": [
|
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"Document",
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||||
"BaseOutputParser",
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"Record",
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"Text"
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],
|
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"dynamic": false,
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"info": "",
|
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"load_from_db": false,
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"title_case": false,
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"type": "str"
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},
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"is_output": null,
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"is_composition": null,
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"base_classes": [
|
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"object",
|
||||
"str",
|
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"Text"
|
||||
],
|
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"name": "",
|
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"display_name": "Prompt",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"template": [
|
||||
"user_input"
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"Text"
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},
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"display_name": "Input",
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"value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"openai_api_key\": {\n \"display_name\": \"OpenAI API Key\",\n \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n \"advanced\": False,\n \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=openai_api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"multiline": false,
|
||||
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|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "max_tokens",
|
||||
"display_name": "Max Tokens",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"model_kwargs": {
|
||||
"type": "NestedDict",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": {},
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "model_kwargs",
|
||||
"display_name": "Model Kwargs",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
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|
||||
},
|
||||
"model_name": {
|
||||
"type": "str",
|
||||
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|
||||
"placeholder": "",
|
||||
"list": true,
|
||||
"show": true,
|
||||
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|
||||
"value": "gpt-3.5-turbo",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"gpt-4-turbo-preview",
|
||||
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|
||||
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|
||||
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|
||||
"gpt-4-vision-preview",
|
||||
"gpt-3.5-turbo-0125",
|
||||
"gpt-3.5-turbo-1106"
|
||||
],
|
||||
"name": "model_name",
|
||||
"display_name": "Model Name",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"type": "str",
|
||||
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|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
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|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
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|
||||
"name": "openai_api_base",
|
||||
"display_name": "OpenAI API Base",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"openai_api_key": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
"file_path": "",
|
||||
"password": true,
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||||
"name": "openai_api_key",
|
||||
"display_name": "OpenAI API Key",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"load_from_db": true,
|
||||
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|
||||
"input_types": [
|
||||
"Text"
|
||||
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|
||||
"value": ""
|
||||
},
|
||||
"stream": {
|
||||
"type": "bool",
|
||||
"required": false,
|
||||
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|
||||
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|
||||
"show": true,
|
||||
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|
||||
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|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "stream",
|
||||
"display_name": "Stream",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "Stream the response from the model. Streaming works only in Chat.",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"system_message": {
|
||||
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|
||||
"required": false,
|
||||
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
"info": "System message to pass to the model.",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"password": false,
|
||||
"name": "temperature",
|
||||
"display_name": "Temperature",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"rangeSpec": {
|
||||
"step_type": "float",
|
||||
"min": -1,
|
||||
"max": 1,
|
||||
"step": 0.1
|
||||
},
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Generates text using OpenAI LLMs.",
|
||||
"icon": "OpenAI",
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
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|
||||
"documentation": "",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"output_types": [
|
||||
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|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"openai_api_key",
|
||||
"temperature",
|
||||
"input_value",
|
||||
"system_message",
|
||||
"stream"
|
||||
],
|
||||
"beta": false
|
||||
},
|
||||
"id": "OpenAIModel-k39HS",
|
||||
"description": "Generates text using OpenAI LLMs.",
|
||||
"display_name": "OpenAI"
|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
"positionAbsolute": {
|
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|
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|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"id": "ChatOutput-njtka",
|
||||
"type": "genericNode",
|
||||
"position": {
|
||||
"x": 1193.250417197867,
|
||||
"y": 71.88476890163852
|
||||
},
|
||||
"data": {
|
||||
"type": "ChatOutput",
|
||||
"node": {
|
||||
"template": {
|
||||
"code": {
|
||||
"type": "code",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template,\n )\n",
|
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"type": "str",
|
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||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "input_value",
|
||||
"display_name": "Message",
|
||||
"advanced": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"record_template": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "{text}",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "record_template",
|
||||
"display_name": "Record Template",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "In case of Message being a Record, this template will be used to convert it to text.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"return_record": {
|
||||
"type": "bool",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "return_record",
|
||||
"display_name": "Return Record",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "Return the message as a record containing the sender, sender_name, and session_id.",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"sender": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": true,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "Machine",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"name": "sender",
|
||||
"display_name": "Sender Type",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"sender_name": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "AI",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "sender_name",
|
||||
"display_name": "Sender Name",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"session_id": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "session_id",
|
||||
"display_name": "Session ID",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "If provided, the message will be stored in the memory.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Display a chat message in the Interaction Panel.",
|
||||
"icon": "ChatOutput",
|
||||
"base_classes": [
|
||||
"Record",
|
||||
"Text",
|
||||
"str",
|
||||
"object"
|
||||
],
|
||||
"display_name": "Chat Output",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"sender": null,
|
||||
"sender_name": null,
|
||||
"input_value": null,
|
||||
"session_id": null,
|
||||
"return_record": null,
|
||||
"record_template": null
|
||||
},
|
||||
"output_types": [
|
||||
"Text",
|
||||
"Record"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
"beta": false
|
||||
},
|
||||
"id": "ChatOutput-njtka"
|
||||
},
|
||||
"selected": false,
|
||||
"width": 384,
|
||||
"height": 383,
|
||||
"positionAbsolute": {
|
||||
"x": 1193.250417197867,
|
||||
"y": 71.88476890163852
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"id": "ChatInput-P3fgL",
|
||||
"type": "genericNode",
|
||||
"position": {
|
||||
"x": -495.2223093083827,
|
||||
"y": -232.56998443685862
|
||||
},
|
||||
"data": {
|
||||
"type": "ChatInput",
|
||||
"node": {
|
||||
"template": {
|
||||
"code": {
|
||||
"type": "code",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Interaction Panel.\"\n icon = \"ChatInput\"\n\n def build_config(self):\n build_config = super().build_config()\n build_config[\"input_value\"] = {\n \"input_types\": [],\n \"display_name\": \"Message\",\n \"multiline\": True,\n }\n\n return build_config\n\n def build(\n self,\n sender: Optional[str] = \"User\",\n sender_name: Optional[str] = \"User\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n ) -> Union[Text, Record]:\n return super().build(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n )\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "code",
|
||||
"advanced": true,
|
||||
"dynamic": true,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"input_value": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "input_value",
|
||||
"display_name": "Message",
|
||||
"advanced": false,
|
||||
"input_types": [],
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"value": "hi"
|
||||
},
|
||||
"return_record": {
|
||||
"type": "bool",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "return_record",
|
||||
"display_name": "Return Record",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "Return the message as a record containing the sender, sender_name, and session_id.",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"sender": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": true,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "User",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"name": "sender",
|
||||
"display_name": "Sender Type",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"sender_name": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "User",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "sender_name",
|
||||
"display_name": "Sender Name",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"session_id": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "session_id",
|
||||
"display_name": "Session ID",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "If provided, the message will be stored in the memory.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Get chat inputs from the Interaction Panel.",
|
||||
"icon": "ChatInput",
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Record",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"display_name": "Chat Input",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"sender": null,
|
||||
"sender_name": null,
|
||||
"input_value": null,
|
||||
"session_id": null,
|
||||
"return_record": null
|
||||
},
|
||||
"output_types": [
|
||||
"Text",
|
||||
"Record"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
"beta": false
|
||||
},
|
||||
"id": "ChatInput-P3fgL"
|
||||
},
|
||||
"selected": false,
|
||||
"width": 384,
|
||||
"height": 375,
|
||||
"positionAbsolute": {
|
||||
"x": -495.2223093083827,
|
||||
"y": -232.56998443685862
|
||||
},
|
||||
"dragging": false
|
||||
}
|
||||
],
|
||||
"edges": [
|
||||
{
|
||||
"source": "OpenAIModel-k39HS",
|
||||
"sourceHandle": "{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-k39HSœ}",
|
||||
"target": "ChatOutput-njtka",
|
||||
"targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-njtkaœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
|
||||
"data": {
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "ChatOutput-njtka",
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-k39HS"
|
||||
}
|
||||
},
|
||||
"style": {
|
||||
"stroke": "#555"
|
||||
},
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
"id": "reactflow__edge-OpenAIModel-k39HS{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-k39HSœ}-ChatOutput-njtka{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-njtkaœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
|
||||
},
|
||||
{
|
||||
"source": "Prompt-uxBqP",
|
||||
"sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-uxBqPœ}",
|
||||
"target": "OpenAIModel-k39HS",
|
||||
"targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-k39HSœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
|
||||
"data": {
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-k39HS",
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": [
|
||||
"object",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"dataType": "Prompt",
|
||||
"id": "Prompt-uxBqP"
|
||||
}
|
||||
},
|
||||
"style": {
|
||||
"stroke": "#555"
|
||||
},
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
"id": "reactflow__edge-Prompt-uxBqP{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-uxBqPœ}-OpenAIModel-k39HS{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-k39HSœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
|
||||
},
|
||||
{
|
||||
"source": "ChatInput-P3fgL",
|
||||
"sourceHandle": "{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-P3fgLœ}",
|
||||
"target": "Prompt-uxBqP",
|
||||
"targetHandle": "{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-uxBqPœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
|
||||
"data": {
|
||||
"targetHandle": {
|
||||
"fieldName": "user_input",
|
||||
"id": "Prompt-uxBqP",
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": [
|
||||
"object",
|
||||
"Record",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"dataType": "ChatInput",
|
||||
"id": "ChatInput-P3fgL"
|
||||
}
|
||||
},
|
||||
"style": {
|
||||
"stroke": "#555"
|
||||
},
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
"id": "reactflow__edge-ChatInput-P3fgL{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-P3fgLœ}-Prompt-uxBqP{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-uxBqPœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
|
||||
}
|
||||
],
|
||||
"viewport": {
|
||||
"x": 260.58251815500563,
|
||||
"y": 318.2261172111936,
|
||||
"zoom": 0.43514115784696294
|
||||
}
|
||||
},
|
||||
"description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ",
|
||||
"name": "Basic Prompting (Ahoy World!)",
|
||||
"last_tested_version": "1.0.0a4",
|
||||
"is_component": false
|
||||
}
|
||||
File diff suppressed because it is too large
Load diff
|
|
@ -45,7 +45,9 @@
|
|||
"name": "template",
|
||||
"display_name": "Template",
|
||||
"advanced": false,
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
|
|
@ -136,14 +138,24 @@
|
|||
"is_input": null,
|
||||
"is_output": null,
|
||||
"is_composition": null,
|
||||
"base_classes": ["object", "Text", "str"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"name": "",
|
||||
"display_name": "Prompt",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"template": ["reference_1", "reference_2", "instructions"]
|
||||
"template": [
|
||||
"reference_1",
|
||||
"reference_2",
|
||||
"instructions"
|
||||
]
|
||||
},
|
||||
"output_types": ["Text"],
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"full_path": null,
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
|
|
@ -210,7 +222,9 @@
|
|||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"value": [
|
||||
"https://www.promptingguide.ai/techniques/prompt_chaining"
|
||||
]
|
||||
|
|
@ -219,13 +233,17 @@
|
|||
},
|
||||
"description": "Fetch content from one or more URLs.",
|
||||
"icon": "layout-template",
|
||||
"base_classes": ["Record"],
|
||||
"base_classes": [
|
||||
"Record"
|
||||
],
|
||||
"display_name": "URL",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"urls": null
|
||||
},
|
||||
"output_types": ["Record"],
|
||||
"output_types": [
|
||||
"Record"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
|
|
@ -260,7 +278,7 @@
|
|||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template,\n )\n",
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build_with_record(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template,\n )\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
|
|
@ -284,7 +302,9 @@
|
|||
"name": "input_value",
|
||||
"display_name": "Message",
|
||||
"advanced": false,
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
|
|
@ -308,7 +328,9 @@
|
|||
"info": "In case of Message being a Record, this template will be used to convert it to text.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"return_record": {
|
||||
"type": "bool",
|
||||
|
|
@ -340,7 +362,10 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"name": "sender",
|
||||
"display_name": "Sender Type",
|
||||
"advanced": true,
|
||||
|
|
@ -348,7 +373,9 @@
|
|||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"sender_name": {
|
||||
"type": "str",
|
||||
|
|
@ -368,7 +395,9 @@
|
|||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"session_id": {
|
||||
"type": "str",
|
||||
|
|
@ -387,13 +416,20 @@
|
|||
"info": "If provided, the message will be stored in the memory.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Display a chat message in the Interaction Panel.",
|
||||
"icon": "ChatOutput",
|
||||
"base_classes": ["Text", "Record", "object", "str"],
|
||||
"base_classes": [
|
||||
"Text",
|
||||
"Record",
|
||||
"object",
|
||||
"str"
|
||||
],
|
||||
"display_name": "Chat Output",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
|
|
@ -404,7 +440,10 @@
|
|||
"return_record": null,
|
||||
"record_template": null
|
||||
},
|
||||
"output_types": ["Text", "Record"],
|
||||
"output_types": [
|
||||
"Text",
|
||||
"Record"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
|
|
@ -444,7 +483,9 @@
|
|||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"code": {
|
||||
"type": "code",
|
||||
|
|
@ -529,7 +570,9 @@
|
|||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"openai_api_base": {
|
||||
"type": "str",
|
||||
|
|
@ -548,7 +591,9 @@
|
|||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"openai_api_key": {
|
||||
"type": "str",
|
||||
|
|
@ -567,7 +612,9 @@
|
|||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"value": ""
|
||||
},
|
||||
"stream": {
|
||||
|
|
@ -606,7 +653,9 @@
|
|||
"info": "System message to pass to the model.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"temperature": {
|
||||
"type": "float",
|
||||
|
|
@ -637,7 +686,11 @@
|
|||
},
|
||||
"description": "Generates text using OpenAI LLMs.",
|
||||
"icon": "OpenAI",
|
||||
"base_classes": ["str", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"display_name": "OpenAI",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
|
|
@ -651,7 +704,9 @@
|
|||
"stream": null,
|
||||
"system_message": null
|
||||
},
|
||||
"output_types": ["Text"],
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [
|
||||
|
|
@ -724,20 +779,28 @@
|
|||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"],
|
||||
"value": ["https://www.promptingguide.ai/introduction/basics"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"value": [
|
||||
"https://www.promptingguide.ai/introduction/basics"
|
||||
]
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Fetch content from one or more URLs.",
|
||||
"icon": "layout-template",
|
||||
"base_classes": ["Record"],
|
||||
"base_classes": [
|
||||
"Record"
|
||||
],
|
||||
"display_name": "URL",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"urls": null
|
||||
},
|
||||
"output_types": ["Record"],
|
||||
"output_types": [
|
||||
"Record"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
|
|
@ -797,7 +860,10 @@
|
|||
"name": "input_value",
|
||||
"display_name": "Value",
|
||||
"advanced": false,
|
||||
"input_types": ["Record", "Text"],
|
||||
"input_types": [
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"dynamic": false,
|
||||
"info": "Text or Record to be passed as input.",
|
||||
"load_from_db": false,
|
||||
|
|
@ -821,20 +887,28 @@
|
|||
"info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": ["Text"]
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Get text inputs from the Interaction Panel.",
|
||||
"icon": "type",
|
||||
"base_classes": ["object", "Text", "str"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"display_name": "Instructions",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
"record_template": null
|
||||
},
|
||||
"output_types": ["Text"],
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
|
|
@ -863,11 +937,18 @@
|
|||
"targetHandle": {
|
||||
"fieldName": "reference_2",
|
||||
"id": "Prompt-Rse03",
|
||||
"inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": ["Record"],
|
||||
"baseClasses": [
|
||||
"Record"
|
||||
],
|
||||
"dataType": "URL",
|
||||
"id": "URL-HYPkR"
|
||||
}
|
||||
|
|
@ -887,11 +968,17 @@
|
|||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "ChatOutput-JPlxl",
|
||||
"inputTypes": ["Text"],
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": ["str", "Text", "object"],
|
||||
"baseClasses": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-gi29P"
|
||||
}
|
||||
|
|
@ -911,11 +998,18 @@
|
|||
"targetHandle": {
|
||||
"fieldName": "reference_1",
|
||||
"id": "Prompt-Rse03",
|
||||
"inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": ["Record"],
|
||||
"baseClasses": [
|
||||
"Record"
|
||||
],
|
||||
"dataType": "URL",
|
||||
"id": "URL-2cX90"
|
||||
}
|
||||
|
|
@ -935,11 +1029,20 @@
|
|||
"targetHandle": {
|
||||
"fieldName": "instructions",
|
||||
"id": "Prompt-Rse03",
|
||||
"inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": ["object", "Text", "str"],
|
||||
"baseClasses": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"dataType": "TextInput",
|
||||
"id": "TextInput-og8Or"
|
||||
}
|
||||
|
|
@ -959,11 +1062,17 @@
|
|||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-gi29P",
|
||||
"inputTypes": ["Text"],
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": ["object", "Text", "str"],
|
||||
"baseClasses": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"dataType": "Prompt",
|
||||
"id": "Prompt-Rse03"
|
||||
}
|
||||
|
|
@ -986,4 +1095,4 @@
|
|||
"name": "Blog Writer",
|
||||
"last_tested_version": "1.0.0a0",
|
||||
"is_component": false
|
||||
}
|
||||
}
|
||||
File diff suppressed because it is too large
Load diff
File diff suppressed because it is too large
Load diff
|
|
@ -256,7 +256,7 @@
|
|||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template,\n )\n",
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build_with_record(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template,\n )\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
|
|
@ -452,7 +452,7 @@
|
|||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template,\n )\n",
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build_with_record(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template,\n )\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
|
|
@ -647,7 +647,7 @@
|
|||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextInput(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Interaction Panel.\"\n icon = \"type\"\n\n def build_config(self):\n return {\n \"input_value\": {\n \"display_name\": \"Value\",\n \"input_types\": [\"Record\", \"Text\"],\n \"info\": \"Text or Record to be passed as input.\",\n },\n \"record_template\": {\n \"display_name\": \"Record Template\",\n \"multiline\": True,\n \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Optional[str] = \"\",\n record_template: Optional[str] = \"\",\n ) -> Text:\n return super().build(input_value=input_value, record_template=record_template)\n",
|
||||
"value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextInput(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Interaction Panel.\"\n icon = \"type\"\n\n def build_config(self):\n return {\n \"input_value\": {\n \"display_name\": \"Value\",\n \"input_types\": [\"Record\", \"Text\"],\n \"info\": \"Text or Record to be passed as input.\",\n },\n \"record_template\": {\n \"display_name\": \"Record Template\",\n \"multiline\": True,\n \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Optional[Text] = \"\",\n record_template: Optional[str] = \"\",\n ) -> Text:\n return super().build(input_value=input_value, record_template=record_template)\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
|
|
@ -1,14 +1,14 @@
|
|||
from typing import ClassVar, Dict, List, Optional
|
||||
|
||||
from langchain.agents import types
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.agents.custom import CUSTOM_AGENTS
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.legacy_custom.customs import get_custom_nodes
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.agents import AgentFrontendNode
|
||||
from langflow.utils.util import build_template_from_class, build_template_from_method
|
||||
from langflow.utils.util import build_template_from_method
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class AgentCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -2,14 +2,14 @@ from typing import Any, ClassVar, Dict, List, Optional, Type
|
|||
|
||||
from langchain import chains
|
||||
from langchain_experimental.sql import SQLDatabaseChain
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.importing.utils import import_class
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.legacy_custom.customs import get_custom_nodes
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.chains import ChainFrontendNode
|
||||
from langflow.utils.util import build_template_from_class, build_template_from_method
|
||||
from langflow.utils.util import build_template_from_method
|
||||
from loguru import logger
|
||||
|
||||
# Assuming necessary imports for Field, Template, and FrontendNode classes
|
||||
|
||||
|
|
|
|||
|
|
@ -4,9 +4,9 @@ from loguru import logger
|
|||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.custom_lists import documentloaders_type_to_cls_dict
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.documentloaders import DocumentLoaderFrontNode
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
|
||||
class DocumentLoaderCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -4,10 +4,10 @@ from loguru import logger
|
|||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.custom_lists import embedding_type_to_cls_dict
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.base import FrontendNode
|
||||
from langflow.template.frontend_node.embeddings import EmbeddingFrontendNode
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
|
||||
class EmbeddingCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -4,9 +4,9 @@ from loguru import logger
|
|||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.custom_lists import llm_type_to_cls_dict
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.llms import LLMFrontendNode
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
|
||||
class LLMCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -1,14 +1,14 @@
|
|||
from typing import ClassVar, Dict, List, Optional, Type
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.custom_lists import memory_type_to_cls_dict
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.legacy_custom.customs import get_custom_nodes
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.base import FrontendNode
|
||||
from langflow.template.frontend_node.memories import MemoryFrontendNode
|
||||
from langflow.utils.util import build_template_from_class, build_template_from_method
|
||||
from langflow.utils.util import build_template_from_method
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class MemoryCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -1,13 +1,13 @@
|
|||
from typing import ClassVar, Dict, List, Optional, Type
|
||||
|
||||
from langchain import output_parsers
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.importing.utils import import_class
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.output_parsers import OutputParserFrontendNode
|
||||
from langflow.utils.util import build_template_from_class, build_template_from_method
|
||||
from langflow.utils.util import build_template_from_method
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class OutputParserCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -2,13 +2,12 @@ from typing import Dict, List, Optional, Type
|
|||
|
||||
from langchain import prompts
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.importing.utils import import_class
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.legacy_custom.customs import get_custom_nodes
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.prompts import PromptFrontendNode
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
|
||||
class PromptCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -1,13 +1,13 @@
|
|||
from typing import Any, ClassVar, Dict, List, Optional, Type
|
||||
|
||||
from langchain_community import retrievers
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.importing.utils import import_class
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.retrievers import RetrieverFrontendNode
|
||||
from langflow.utils.util import build_template_from_class, build_template_from_method
|
||||
from langflow.utils.util import build_template_from_method
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class RetrieverCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -4,9 +4,9 @@ from loguru import logger
|
|||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.custom_lists import textsplitter_type_to_cls_dict
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.textsplitters import TextSplittersFrontendNode
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
|
||||
class TextSplitterCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -3,11 +3,10 @@ from typing import Callable, Dict, List, Optional
|
|||
|
||||
from langchain.agents import agent_toolkits
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.importing.utils import import_class, import_module
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
|
||||
class ToolkitCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@ from langflow.template.field.base import TemplateField
|
|||
from langflow.template.template.base import Template
|
||||
from langflow.utils import util
|
||||
from langflow.utils.logger import logger
|
||||
from langflow.utils.util import build_template_from_class
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
|
||||
TOOL_INPUTS = {
|
||||
"str": TemplateField(
|
||||
|
|
|
|||
|
|
@ -2,13 +2,12 @@ from typing import Dict, List, Optional, Type
|
|||
|
||||
from langchain_community import utilities
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.interface.importing.utils import import_class
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.legacy_custom.customs import get_custom_nodes
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.utilities import UtilitiesFrontendNode
|
||||
from langflow.utils.util import build_template_from_class
|
||||
|
||||
|
||||
class UtilityCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -3,14 +3,16 @@ import json
|
|||
import os
|
||||
import re
|
||||
from io import BytesIO
|
||||
from typing import Dict
|
||||
|
||||
import yaml
|
||||
from docstring_parser import parse
|
||||
from langchain.base_language import BaseLanguageModel
|
||||
from loguru import logger
|
||||
from PIL.Image import Image
|
||||
|
||||
from langflow.services.chat.config import ChatConfig
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.utils.util import format_dict, get_base_classes, get_default_factory
|
||||
from loguru import logger
|
||||
from PIL.Image import Image
|
||||
|
||||
|
||||
def load_file_into_dict(file_path: str) -> dict:
|
||||
|
|
@ -100,7 +102,6 @@ def setup_llm_caching():
|
|||
|
||||
def set_langchain_cache(settings):
|
||||
from langchain.globals import set_llm_cache
|
||||
|
||||
from langflow.interface.importing.utils import import_class
|
||||
|
||||
if cache_type := os.getenv("LANGFLOW_LANGCHAIN_CACHE"):
|
||||
|
|
@ -114,3 +115,51 @@ def set_langchain_cache(settings):
|
|||
logger.warning(f"Could not import {cache_type}. ")
|
||||
else:
|
||||
logger.info("No LLM cache set.")
|
||||
|
||||
|
||||
def build_template_from_class(name: str, type_to_cls_dict: Dict, add_function: bool = False):
|
||||
classes = [item.__name__ for item in type_to_cls_dict.values()]
|
||||
|
||||
# Raise error if name is not in chains
|
||||
if name not in classes:
|
||||
raise ValueError(f"{name} not found.")
|
||||
|
||||
for _type, v in type_to_cls_dict.items():
|
||||
if v.__name__ == name:
|
||||
_class = v
|
||||
|
||||
# Get the docstring
|
||||
docs = parse(_class.__doc__)
|
||||
|
||||
variables = {"_type": _type}
|
||||
|
||||
if "__fields__" in _class.__dict__:
|
||||
for class_field_items, value in _class.__fields__.items():
|
||||
if class_field_items in ["callback_manager"]:
|
||||
continue
|
||||
variables[class_field_items] = {}
|
||||
for name_, value_ in value.__repr_args__():
|
||||
if name_ == "default_factory":
|
||||
try:
|
||||
variables[class_field_items]["default"] = get_default_factory(
|
||||
module=_class.__base__.__module__,
|
||||
function=value_,
|
||||
)
|
||||
except Exception:
|
||||
variables[class_field_items]["default"] = None
|
||||
elif name_ not in ["name"]:
|
||||
variables[class_field_items][name_] = value_
|
||||
|
||||
variables[class_field_items]["placeholder"] = (
|
||||
docs.params[class_field_items] if class_field_items in docs.params else ""
|
||||
)
|
||||
base_classes = get_base_classes(_class)
|
||||
# Adding function to base classes to allow
|
||||
# the output to be a function
|
||||
if add_function:
|
||||
base_classes.append("Callable")
|
||||
return {
|
||||
"template": format_dict(variables, name),
|
||||
"description": docs.short_description or "",
|
||||
"base_classes": base_classes,
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,10 +1,9 @@
|
|||
from typing import Dict, List, Optional
|
||||
|
||||
from langchain_community.utilities import requests
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.base import LangChainTypeCreator
|
||||
from langflow.utils.util import build_template_from_class
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class WrapperCreator(LangChainTypeCreator):
|
||||
|
|
|
|||
|
|
@ -2,21 +2,55 @@ import json
|
|||
from pathlib import Path
|
||||
from typing import List, Optional, Union
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from langflow.graph import Graph
|
||||
from langflow.graph.schema import RunOutputs
|
||||
from langflow.processing.process import process_tweaks, run_graph
|
||||
from langflow.utils.logger import configure
|
||||
from langflow.utils.util import update_settings
|
||||
|
||||
|
||||
def load_flow_from_json(flow: Union[Path, str, dict], tweaks: Optional[dict] = None) -> Graph:
|
||||
def load_flow_from_json(
|
||||
flow: Union[Path, str, dict],
|
||||
tweaks: Optional[dict] = None,
|
||||
log_level: Optional[str] = None,
|
||||
log_file: Optional[str] = None,
|
||||
env_file: Optional[str] = None,
|
||||
cache: Optional[str] = None,
|
||||
disable_logs: Optional[bool] = True,
|
||||
) -> Graph:
|
||||
"""
|
||||
Load flow from a JSON file or a JSON object.
|
||||
Load a flow graph from a JSON file or a JSON object.
|
||||
|
||||
Args:
|
||||
flow (Union[Path, str, dict]): The flow to load. It can be a file path (str or Path object)
|
||||
or a JSON object (dict).
|
||||
tweaks (Optional[dict]): Optional tweaks to apply to the loaded flow graph.
|
||||
log_level (Optional[str]): Optional log level to configure for the flow processing.
|
||||
log_file (Optional[str]): Optional log file to configure for the flow processing.
|
||||
env_file (Optional[str]): Optional .env file to override environment variables.
|
||||
cache (Optional[str]): Optional cache path to update the flow settings.
|
||||
disable_logs (Optional[bool], default=True): Optional flag to disable logs during flow processing.
|
||||
If log_level or log_file are set, disable_logs is not used.
|
||||
|
||||
Returns:
|
||||
Graph: The loaded flow graph as a Graph object.
|
||||
|
||||
Raises:
|
||||
TypeError: If the input is neither a file path (str or Path object) nor a JSON object (dict).
|
||||
|
||||
:param flow: JSON file path or JSON object
|
||||
:param tweaks: Optional tweaks to be processed
|
||||
:param build: If True, build the graph, otherwise return the graph object
|
||||
:return: Langchain object or Graph object depending on the build parameter
|
||||
"""
|
||||
# If input is a file path, load JSON from the file
|
||||
log_file_path = Path(log_file) if log_file else None
|
||||
configure(log_level=log_level, log_file=log_file_path, disable=disable_logs)
|
||||
|
||||
# override env variables with .env file
|
||||
if env_file:
|
||||
load_dotenv(env_file, override=True)
|
||||
|
||||
# Update settings with cache and components path
|
||||
update_settings(cache=cache)
|
||||
|
||||
if isinstance(flow, (str, Path)):
|
||||
with open(flow, "r", encoding="utf-8") as f:
|
||||
flow_graph = json.load(f)
|
||||
|
|
@ -41,22 +75,44 @@ def run_flow_from_json(
|
|||
input_type: str = "chat",
|
||||
output_type: str = "chat",
|
||||
output_component: Optional[str] = None,
|
||||
log_level: Optional[str] = None,
|
||||
log_file: Optional[str] = None,
|
||||
env_file: Optional[str] = None,
|
||||
cache: Optional[str] = None,
|
||||
disable_logs: Optional[bool] = True,
|
||||
) -> List[RunOutputs]:
|
||||
"""
|
||||
Runs a JSON flow by loading it from a file or dictionary and executing it with the given input value.
|
||||
Run a flow from a JSON file or dictionary.
|
||||
|
||||
Args:
|
||||
flow (Union[Path, str, dict]): The path to the JSON file, or the JSON dictionary representing the flow.
|
||||
flow (Union[Path, str, dict]): The path to the JSON file or the JSON dictionary representing the flow.
|
||||
input_value (str): The input value to be processed by the flow.
|
||||
tweaks (Optional[dict], optional): Optional tweaks to be applied to the flow. Defaults to None.
|
||||
input_type (str, optional): The type of the input value. Defaults to "chat".
|
||||
output_type (str, optional): The type of the output value. Defaults to "chat".
|
||||
output_component (Optional[str], optional): The specific output component to retrieve. Defaults to None.
|
||||
output_component (Optional[str], optional): The specific component to output. Defaults to None.
|
||||
log_level (Optional[str], optional): The log level to use. Defaults to None.
|
||||
log_file (Optional[str], optional): The log file to write logs to. Defaults to None.
|
||||
env_file (Optional[str], optional): The environment file to load. Defaults to None.
|
||||
cache (Optional[str], optional): The cache directory to use. Defaults to None.
|
||||
disable_logs (Optional[bool], optional): Whether to disable logs. Defaults to True.
|
||||
|
||||
Returns:
|
||||
None: The result of running the flow.
|
||||
List[RunOutputs]: A list of RunOutputs objects representing the results of running the flow.
|
||||
"""
|
||||
graph = load_flow_from_json(flow, tweaks)
|
||||
# Set all streaming to false
|
||||
if tweaks is None:
|
||||
tweaks = {}
|
||||
tweaks["stream"] = False
|
||||
graph = load_flow_from_json(
|
||||
flow=flow,
|
||||
tweaks=tweaks,
|
||||
log_level=log_level,
|
||||
log_file=log_file,
|
||||
env_file=env_file,
|
||||
cache=cache,
|
||||
disable_logs=disable_logs,
|
||||
)
|
||||
result = run_graph(
|
||||
graph=graph,
|
||||
input_value=input_value,
|
||||
|
|
|
|||
|
|
@ -9,11 +9,12 @@ from langflow.graph.graph.base import Graph
|
|||
from langflow.graph.schema import RunOutputs
|
||||
from langflow.graph.vertex.base import Vertex
|
||||
from langflow.interface.run import get_memory_key, update_memory_keys
|
||||
from langflow.schema.graph import InputValue, Tweaks
|
||||
from langflow.schema.schema import INPUT_FIELD_NAME
|
||||
from langflow.services.session.service import SessionService
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.api.v1.schemas import InputValueRequest, Tweaks
|
||||
from langflow.api.v1.schemas import InputValueRequest
|
||||
|
||||
|
||||
def fix_memory_inputs(langchain_object):
|
||||
|
|
@ -188,7 +189,7 @@ def run_graph(
|
|||
List[RunOutputs]: A list of RunOutputs objects representing the outputs of the graph.
|
||||
|
||||
"""
|
||||
inputs = [InputValueRequest(components=[], input_value=input_value, type=input_type)]
|
||||
inputs = [InputValue(components=[], input_value=input_value, type=input_type)]
|
||||
if output_component:
|
||||
outputs = [output_component]
|
||||
else:
|
||||
|
|
|
|||
43
src/backend/base/langflow/schema/graph.py
Normal file
43
src/backend/base/langflow/schema/graph.py
Normal file
|
|
@ -0,0 +1,43 @@
|
|||
from typing import List, Optional, Union
|
||||
|
||||
from langflow.schema.schema import InputType
|
||||
from pydantic import BaseModel, Field, RootModel
|
||||
|
||||
|
||||
class InputValue(BaseModel):
|
||||
components: Optional[List[str]] = []
|
||||
input_value: Optional[str] = None
|
||||
type: Optional[InputType] = Field(
|
||||
"any",
|
||||
description="Defines on which components the input value should be applied. 'any' applies to all input components.",
|
||||
)
|
||||
|
||||
|
||||
class Tweaks(RootModel):
|
||||
root: dict[str, Union[str, dict[str, str]]] = Field(
|
||||
description="A dictionary of tweaks to adjust the flow's execution. Allows customizing flow behavior dynamically. All tweaks are overridden by the input values.",
|
||||
)
|
||||
model_config = {
|
||||
"json_schema_extra": {
|
||||
"examples": [
|
||||
{
|
||||
"parameter_name": "value",
|
||||
"Component Name": {"parameter_name": "value"},
|
||||
"component_id": {"parameter_name": "value"},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
# This should behave like a dict
|
||||
def __getitem__(self, key):
|
||||
return self.root[key]
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
self.root[key] = value
|
||||
|
||||
def __delitem__(self, key):
|
||||
del self.root[key]
|
||||
|
||||
def items(self):
|
||||
return self.root.items()
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
import logging
|
||||
|
||||
from gunicorn import glogging
|
||||
from gunicorn import glogging # type: ignore
|
||||
from gunicorn.app.base import BaseApplication # type: ignore
|
||||
from uvicorn.workers import UvicornWorker
|
||||
|
||||
|
|
|
|||
|
|
@ -1,14 +1,15 @@
|
|||
# Path: src/backend/langflow/services/database/models/flow/model.py
|
||||
|
||||
import warnings
|
||||
from datetime import datetime
|
||||
from typing import TYPE_CHECKING, Dict, Optional
|
||||
from uuid import UUID, uuid4
|
||||
|
||||
import emoji
|
||||
from emoji import purely_emoji # type: ignore
|
||||
from pydantic import field_serializer, field_validator
|
||||
from sqlmodel import JSON, Column, Field, Relationship, SQLModel
|
||||
|
||||
from langflow.interface.custom.attributes import validate_icon
|
||||
from langflow.schema.schema import Record
|
||||
|
||||
if TYPE_CHECKING:
|
||||
|
|
@ -45,12 +46,25 @@ class FlowBase(SQLModel):
|
|||
# emoji pattern in Python
|
||||
if v is None:
|
||||
return v
|
||||
# we are going to use the emoji library to validate the emoji
|
||||
# emojis can be defined using the :emoji_name: syntax
|
||||
|
||||
emoji = validate_icon(v)
|
||||
if not v.startswith(":") and not v.endswith(":"):
|
||||
return v
|
||||
elif not v.startswith(":") or not v.endswith(":"):
|
||||
# emoji should have both starting and ending colons
|
||||
# so if one of them is missing, we will raise
|
||||
raise ValueError(f"Invalid emoji. {v} is not a valid emoji.")
|
||||
|
||||
if purely_emoji(emoji):
|
||||
emoji_value = emoji.emojize(v, variant="emoji_type")
|
||||
if v == emoji_value:
|
||||
warnings.warn(f"Invalid emoji. {v} is not a valid emoji.")
|
||||
icon = v
|
||||
icon = emoji_value
|
||||
|
||||
if purely_emoji(icon):
|
||||
# this is indeed an emoji
|
||||
return emoji
|
||||
return icon
|
||||
# otherwise it should be a valid lucide icon
|
||||
if v is not None and not isinstance(v, str):
|
||||
raise ValueError("Icon must be a string")
|
||||
|
|
|
|||
|
|
@ -25,7 +25,9 @@ def patching(record):
|
|||
record["extra"]["serialized"] = serialize(record)
|
||||
|
||||
|
||||
def configure(log_level: Optional[str] = None, log_file: Optional[Path] = None):
|
||||
def configure(log_level: Optional[str] = None, log_file: Optional[Path] = None, disable: Optional[bool] = False):
|
||||
if disable and log_level is None and log_file is None:
|
||||
logger.disable("langflow")
|
||||
if os.getenv("LANGFLOW_LOG_LEVEL", "").upper() in VALID_LOG_LEVELS and log_level is None:
|
||||
log_level = os.getenv("LANGFLOW_LOG_LEVEL")
|
||||
if log_level is None:
|
||||
|
|
|
|||
|
|
@ -2,13 +2,15 @@ import importlib
|
|||
import inspect
|
||||
import re
|
||||
from functools import wraps
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List, Optional, Union
|
||||
|
||||
from docstring_parser import parse
|
||||
|
||||
from langflow.schema.schema import Record
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.template.frontend_node.constants import FORCE_SHOW_FIELDS
|
||||
from langflow.utils import constants
|
||||
from langflow.utils.logger import logger
|
||||
|
||||
|
||||
def unescape_string(s: str):
|
||||
|
|
@ -66,54 +68,6 @@ def build_template_from_function(name: str, type_to_loader_dict: Dict, add_funct
|
|||
}
|
||||
|
||||
|
||||
def build_template_from_class(name: str, type_to_cls_dict: Dict, add_function: bool = False):
|
||||
classes = [item.__name__ for item in type_to_cls_dict.values()]
|
||||
|
||||
# Raise error if name is not in chains
|
||||
if name not in classes:
|
||||
raise ValueError(f"{name} not found.")
|
||||
|
||||
for _type, v in type_to_cls_dict.items():
|
||||
if v.__name__ == name:
|
||||
_class = v
|
||||
|
||||
# Get the docstring
|
||||
docs = parse(_class.__doc__)
|
||||
|
||||
variables = {"_type": _type}
|
||||
|
||||
if "__fields__" in _class.__dict__:
|
||||
for class_field_items, value in _class.__fields__.items():
|
||||
if class_field_items in ["callback_manager"]:
|
||||
continue
|
||||
variables[class_field_items] = {}
|
||||
for name_, value_ in value.__repr_args__():
|
||||
if name_ == "default_factory":
|
||||
try:
|
||||
variables[class_field_items]["default"] = get_default_factory(
|
||||
module=_class.__base__.__module__,
|
||||
function=value_,
|
||||
)
|
||||
except Exception:
|
||||
variables[class_field_items]["default"] = None
|
||||
elif name_ not in ["name"]:
|
||||
variables[class_field_items][name_] = value_
|
||||
|
||||
variables[class_field_items]["placeholder"] = (
|
||||
docs.params[class_field_items] if class_field_items in docs.params else ""
|
||||
)
|
||||
base_classes = get_base_classes(_class)
|
||||
# Adding function to base classes to allow
|
||||
# the output to be a function
|
||||
if add_function:
|
||||
base_classes.append("Callable")
|
||||
return {
|
||||
"template": format_dict(variables, name),
|
||||
"description": docs.short_description or "",
|
||||
"base_classes": base_classes,
|
||||
}
|
||||
|
||||
|
||||
def build_template_from_method(
|
||||
class_name: str,
|
||||
method_name: str,
|
||||
|
|
@ -462,3 +416,35 @@ def build_loader_repr_from_records(records: List[Record]) -> str:
|
|||
\nAvg. Record Length (characters): {int(avg_length)}
|
||||
Records: {records[:3]}..."""
|
||||
return "0 records"
|
||||
|
||||
|
||||
def update_settings(
|
||||
config: Optional[str] = None,
|
||||
cache: Optional[str] = None,
|
||||
dev: bool = False,
|
||||
remove_api_keys: bool = False,
|
||||
components_path: Optional[Path] = None,
|
||||
store: bool = True,
|
||||
):
|
||||
"""Update the settings from a config file."""
|
||||
from langflow.services.utils import initialize_settings_service
|
||||
|
||||
# Check for database_url in the environment variables
|
||||
|
||||
initialize_settings_service()
|
||||
settings_service = get_settings_service()
|
||||
if config:
|
||||
logger.debug(f"Loading settings from {config}")
|
||||
settings_service.settings.update_from_yaml(config, dev=dev)
|
||||
if remove_api_keys:
|
||||
logger.debug(f"Setting remove_api_keys to {remove_api_keys}")
|
||||
settings_service.settings.update_settings(REMOVE_API_KEYS=remove_api_keys)
|
||||
if cache:
|
||||
logger.debug(f"Setting cache to {cache}")
|
||||
settings_service.settings.update_settings(CACHE=cache)
|
||||
if components_path:
|
||||
logger.debug(f"Adding component path {components_path}")
|
||||
settings_service.settings.update_settings(COMPONENTS_PATH=components_path)
|
||||
if not store:
|
||||
logger.debug("Setting store to False")
|
||||
settings_service.settings.update_settings(STORE=False)
|
||||
|
|
|
|||
16
src/backend/base/poetry.lock
generated
16
src/backend/base/poetry.lock
generated
|
|
@ -202,6 +202,20 @@ files = [
|
|||
{file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "asyncer"
|
||||
version = "0.0.5"
|
||||
description = "Asyncer, async and await, focused on developer experience."
|
||||
optional = false
|
||||
python-versions = ">=3.8,<4.0"
|
||||
files = [
|
||||
{file = "asyncer-0.0.5-py3-none-any.whl", hash = "sha256:ba06d6de3c750763868dffacf89b18d40b667605b0241d31c2ee43f188e2ab74"},
|
||||
{file = "asyncer-0.0.5.tar.gz", hash = "sha256:2979f3e04cbedfe5cfeb79027dcf7d004fcc4430a0ca0066ae20490f218ec06e"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
anyio = ">=3.4.0,<5.0"
|
||||
|
||||
[[package]]
|
||||
name = "attrs"
|
||||
version = "23.2.0"
|
||||
|
|
@ -4444,4 +4458,4 @@ local = []
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10,<3.12"
|
||||
content-hash = "ab99a3fe4d80dff80dfa69347dcb22b85d48d33487a14e01c709b51f7b62699e"
|
||||
content-hash = "67dfc26573145c0b2b8daea7f07ae228d2a3403033a6c25b41e8e1b280b01e38"
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow-base"
|
||||
version = "0.0.24"
|
||||
version = "0.0.25"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Logspace <contact@logspace.ai>"]
|
||||
maintainers = [
|
||||
|
|
@ -60,6 +60,7 @@ pypdf = "^4.1.0"
|
|||
nest-asyncio = "^1.6.0"
|
||||
emoji = "^2.11.0"
|
||||
cryptography = "^42.0.5"
|
||||
asyncer = "^0.0.5"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
|
|
|
|||
|
|
@ -10,10 +10,6 @@ import orjson
|
|||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
from httpx import AsyncClient
|
||||
from sqlmodel import Session, SQLModel, create_engine, select
|
||||
from sqlmodel.pool import StaticPool
|
||||
from typer.testing import CliRunner
|
||||
|
||||
from langflow.graph.graph.base import Graph
|
||||
from langflow.initial_setup.setup import STARTER_FOLDER_NAME
|
||||
from langflow.services.auth.utils import get_password_hash
|
||||
|
|
@ -22,6 +18,9 @@ from langflow.services.database.models.flow.model import Flow, FlowCreate
|
|||
from langflow.services.database.models.user.model import User, UserCreate
|
||||
from langflow.services.database.utils import session_getter
|
||||
from langflow.services.deps import get_db_service
|
||||
from sqlmodel import Session, SQLModel, create_engine, select
|
||||
from sqlmodel.pool import StaticPool
|
||||
from typer.testing import CliRunner
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.services.database.service import DatabaseService
|
||||
|
|
@ -204,25 +203,28 @@ def complex_graph_with_groups():
|
|||
|
||||
|
||||
@pytest.fixture(name="client", autouse=True)
|
||||
def client_fixture(session: Session, monkeypatch):
|
||||
def client_fixture(session: Session, monkeypatch, request):
|
||||
# Set the database url to a test database
|
||||
db_dir = tempfile.mkdtemp()
|
||||
db_path = Path(db_dir) / "test.db"
|
||||
monkeypatch.setenv("LANGFLOW_DATABASE_URL", f"sqlite:///{db_path}")
|
||||
monkeypatch.setenv("LANGFLOW_AUTO_LOGIN", "false")
|
||||
if "noclient" in request.keywords:
|
||||
yield
|
||||
else:
|
||||
db_dir = tempfile.mkdtemp()
|
||||
db_path = Path(db_dir) / "test.db"
|
||||
monkeypatch.setenv("LANGFLOW_DATABASE_URL", f"sqlite:///{db_path}")
|
||||
monkeypatch.setenv("LANGFLOW_AUTO_LOGIN", "false")
|
||||
|
||||
from langflow.main import create_app
|
||||
from langflow.main import create_app
|
||||
|
||||
app = create_app()
|
||||
app = create_app()
|
||||
|
||||
# app.dependency_overrides[get_session] = get_session_override
|
||||
with TestClient(app) as client:
|
||||
yield client
|
||||
# app.dependency_overrides.clear()
|
||||
monkeypatch.undo()
|
||||
# clear the temp db
|
||||
with suppress(FileNotFoundError):
|
||||
db_path.unlink()
|
||||
# app.dependency_overrides[get_session] = get_session_override
|
||||
with TestClient(app) as client:
|
||||
yield client
|
||||
# app.dependency_overrides.clear()
|
||||
monkeypatch.undo()
|
||||
# clear the temp db
|
||||
with suppress(FileNotFoundError):
|
||||
db_path.unlink()
|
||||
|
||||
|
||||
# create a fixture for session_getter above
|
||||
|
|
|
|||
|
|
@ -1,9 +1,11 @@
|
|||
import pytest
|
||||
|
||||
from langflow.graph import Graph
|
||||
from langflow.processing.load import load_flow_from_json
|
||||
from langflow.graph.schema import RunOutputs
|
||||
from langflow.initial_setup.setup import load_starter_projects
|
||||
from langflow.processing.load import load_flow_from_json, run_flow_from_json
|
||||
|
||||
|
||||
@pytest.mark.noclient
|
||||
def test_load_flow_from_json():
|
||||
"""Test loading a flow from a json file"""
|
||||
loaded = load_flow_from_json(pytest.BASIC_EXAMPLE_PATH)
|
||||
|
|
@ -11,9 +13,30 @@ def test_load_flow_from_json():
|
|||
assert isinstance(loaded, Graph)
|
||||
|
||||
|
||||
@pytest.mark.noclient
|
||||
def test_load_flow_from_json_with_tweaks():
|
||||
"""Test loading a flow from a json file and applying tweaks"""
|
||||
tweaks = {"dndnode_82": {"model_name": "gpt-3.5-turbo-16k-0613"}}
|
||||
loaded = load_flow_from_json(pytest.BASIC_EXAMPLE_PATH, tweaks=tweaks)
|
||||
assert loaded is not None
|
||||
assert isinstance(loaded, Graph)
|
||||
|
||||
|
||||
@pytest.mark.noclient
|
||||
def test_load_flow_from_json_object():
|
||||
"""Test loading a flow from a json file and applying tweaks"""
|
||||
_, projects = zip(*load_starter_projects())
|
||||
project = projects[0]
|
||||
loaded = load_flow_from_json(project)
|
||||
assert loaded is not None
|
||||
assert isinstance(loaded, Graph)
|
||||
|
||||
|
||||
@pytest.mark.noclient
|
||||
def test_run_flow_from_json_object():
|
||||
"""Test loading a flow from a json file and applying tweaks"""
|
||||
_, projects = zip(*load_starter_projects())
|
||||
project = projects[0]
|
||||
results = run_flow_from_json(project, input_value="test")
|
||||
assert results is not None
|
||||
assert all(isinstance(result, RunOutputs) for result in results)
|
||||
|
|
|
|||
|
|
@ -2,14 +2,9 @@ import importlib
|
|||
from typing import Dict, List, Optional
|
||||
|
||||
import pytest
|
||||
from langflow.interface.utils import build_template_from_class
|
||||
from langflow.utils.constants import CHAT_OPENAI_MODELS, OPENAI_MODELS
|
||||
from langflow.utils.util import (
|
||||
build_template_from_class,
|
||||
build_template_from_function,
|
||||
format_dict,
|
||||
get_base_classes,
|
||||
get_default_factory,
|
||||
)
|
||||
from langflow.utils.util import build_template_from_function, format_dict, get_base_classes, get_default_factory
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue