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 3849 additions and 4432 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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@ -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)
|
||||
|
|
|
|||
Some files were not shown because too many files have changed in this diff Show more
Loading…
Reference in a new issue