Update environment variable settings and dependencies (#1667)
* Update environment variable settings in constants.py * Bump langflow-base version to 0.0.25 and add asyncer dependency * Update Pinecone, Qdrant, MongoDBAtlasVector, and SupabaseVectorStore components
This commit is contained in:
Gabriel Luiz Freitas Almeida
GitHub
parent
e2bdef8a5f
commit
accf3980ba
9 changed files with 42 additions and 39 deletions
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@ -1,6 +1,6 @@
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[tool.poetry]
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name = "langflow"
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version = "1.0.0a12"
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version = "1.0.0a13"
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description = "A Python package with a built-in web application"
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authors = ["Logspace <contact@logspace.ai>"]
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maintainers = [
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@ -3,6 +3,7 @@ from typing import List, Optional
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from langflow.components.vectorstores.base.model import LCVectorStoreComponent
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from langflow.components.vectorstores.Pinecone import PineconeComponent
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from langflow.field_typing import Embeddings, Text
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from langflow.field_typing.constants import NestedDict
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from langflow.schema import Record
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@ -32,7 +33,6 @@ class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
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"default": "",
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"required": True,
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},
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"search_kwargs": {"display_name": "Search Kwargs", "default": "{}"},
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"pool_threads": {
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"display_name": "Pool Threads",
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"default": 1,
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@ -57,6 +57,7 @@ class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
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pinecone_api_key: Optional[str] = None,
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namespace: Optional[str] = "default",
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search_type: str = "similarity",
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search_kwargs: Optional[NestedDict] = None,
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) -> List[Record]: # type: ignore[override]
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vector_store = super().build(
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embedding=embedding,
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@ -72,5 +73,9 @@ class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
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raise ValueError("Failed to load the Pinecone index.")
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return self.search_with_vector_store(
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vector_store=vector_store, input_value=input_value, search_type=search_type, k=number_of_results
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vector_store=vector_store,
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input_value=input_value,
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search_type=search_type,
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k=number_of_results,
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**search_kwargs,
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)
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@ -94,5 +94,9 @@ class QdrantSearchComponent(QdrantComponent, LCVectorStoreComponent):
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raise ValueError("Failed to load the Qdrant index.")
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return self.search_with_vector_store(
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vector_store=vector_store, input_value=input_value, search_type=search_type, k=number_of_results
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vector_store=vector_store,
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input_value=input_value,
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search_type=search_type,
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k=number_of_results,
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**search_kwargs,
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)
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@ -19,7 +19,6 @@ class MongoDBAtlasComponent(CustomComponent):
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"db_name": {"display_name": "Database Name"},
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"index_name": {"display_name": "Index Name"},
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"mongodb_atlas_cluster_uri": {"display_name": "MongoDB Atlas Cluster URI"},
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"search_kwargs": {"display_name": "Search Kwargs", "advanced": True},
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}
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def build(
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@ -30,9 +29,7 @@ class MongoDBAtlasComponent(CustomComponent):
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db_name: str = "",
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index_name: str = "",
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mongodb_atlas_cluster_uri: str = "",
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search_kwargs: Optional[NestedDict] = None,
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) -> MongoDBAtlasVectorSearch:
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search_kwargs = search_kwargs or {}
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try:
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from pymongo import MongoClient
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except ImportError:
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@ -56,7 +53,6 @@ class MongoDBAtlasComponent(CustomComponent):
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db_name=db_name,
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index_name=index_name,
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mongodb_atlas_cluster_uri=mongodb_atlas_cluster_uri,
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search_kwargs=search_kwargs,
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)
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else:
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vector_store = MongoDBAtlasVectorSearch(
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@ -33,7 +33,6 @@ class PineconeComponent(CustomComponent):
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"default": "",
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"required": True,
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},
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"search_kwargs": {"display_name": "Search Kwargs", "default": "{}"},
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"pool_threads": {
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"display_name": "Pool Threads",
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"default": 1,
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@ -37,7 +37,6 @@ class QdrantComponent(CustomComponent):
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"port": {"display_name": "Port", "advanced": True},
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"prefer_grpc": {"display_name": "Prefer gRPC", "advanced": True},
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"prefix": {"display_name": "Prefix", "advanced": True},
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"search_kwargs": {"display_name": "Search Kwargs", "advanced": True},
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"timeout": {"display_name": "Timeout", "advanced": True},
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"url": {"display_name": "URL", "advanced": True},
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}
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@ -59,7 +58,6 @@ class QdrantComponent(CustomComponent):
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port: Optional[int] = 6333,
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prefer_grpc: bool = False,
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prefix: Optional[str] = None,
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search_kwargs: Optional[NestedDict] = None,
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timeout: Optional[int] = None,
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url: Optional[str] = None,
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) -> Union[VectorStore, Qdrant, BaseRetriever]:
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@ -111,7 +109,6 @@ class QdrantComponent(CustomComponent):
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port=port,
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prefer_grpc=prefer_grpc,
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prefix=prefix,
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search_kwargs=search_kwargs,
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timeout=timeout,
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url=url,
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)
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@ -19,7 +19,6 @@ class SupabaseComponent(CustomComponent):
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"inputs": {"display_name": "Input", "input_types": ["Document", "Record"]},
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"embedding": {"display_name": "Embedding"},
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"query_name": {"display_name": "Query Name"},
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"search_kwargs": {"display_name": "Search Kwargs", "advanced": True},
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"supabase_service_key": {"display_name": "Supabase Service Key"},
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"supabase_url": {"display_name": "Supabase URL"},
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"table_name": {"display_name": "Table Name", "advanced": True},
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@ -30,7 +29,6 @@ class SupabaseComponent(CustomComponent):
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embedding: Embeddings,
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inputs: Optional[List[Record]] = None,
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query_name: str = "",
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search_kwargs: NestedDict = {},
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supabase_service_key: str = "",
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supabase_url: str = "",
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table_name: str = "",
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@ -46,7 +44,6 @@ class SupabaseComponent(CustomComponent):
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documents=documents,
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embedding=embedding,
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query_name=query_name,
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search_kwargs=search_kwargs,
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client=supabase,
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table_name=table_name,
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)
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@ -13,4 +13,9 @@ VARIABLES_TO_GET_FROM_ENVIRONMENT = [
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"ASTRA_DB_API_ENDPOINT",
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"COHERE_API_KEY",
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"HUGGINGFACEHUB_API_TOKEN",
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"SEARCHAPI_API_KEY",
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"SERPAPI_API_KEY",
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"VECTARA_CUSTOMER_ID",
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"VECTARA_CORPUS_ID",
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"VECTARA_API_KEY",
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]
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48
src/backend/base/poetry.lock
generated
48
src/backend/base/poetry.lock
generated
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@ -1734,13 +1734,13 @@ test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"
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[[package]]
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name = "langchain"
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version = "0.1.14"
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version = "0.1.15"
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description = "Building applications with LLMs through composability"
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optional = false
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python-versions = "<4.0,>=3.8.1"
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files = [
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{file = "langchain-0.1.14-py3-none-any.whl", hash = "sha256:94f9b5df2421faaf762d4f43b9d65c270c2f701934580d281e4c6226deef7234"},
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{file = "langchain-0.1.14.tar.gz", hash = "sha256:124c6244cf3957616b98f2df07dc2992fc40dff6ed1a62d8ee8a40f1e0260a40"},
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{file = "langchain-0.1.15-py3-none-any.whl", hash = "sha256:3ac516463ae7f80047091f04592a1eea138321710bbc266005f9de238d71acd3"},
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{file = "langchain-0.1.15.tar.gz", hash = "sha256:79d43035327fdcc5ac81a3db10f2b879f2bd5db3b268ef82bac7baf3ec32954e"},
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]
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[package.dependencies]
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@ -1748,8 +1748,8 @@ 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-core = ">=0.1.37,<0.2.0"
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langchain-community = ">=0.0.32,<0.1"
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langchain-core = ">=0.1.41,<0.2.0"
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langchain-text-splitters = ">=0.0.1,<0.1"
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langsmith = ">=0.1.17,<0.2.0"
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numpy = ">=1,<2"
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@ -1775,19 +1775,19 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
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[[package]]
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name = "langchain-community"
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version = "0.0.31"
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version = "0.0.32"
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description = "Community contributed LangChain integrations."
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optional = false
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python-versions = "<4.0,>=3.8.1"
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files = [
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{file = "langchain_community-0.0.31-py3-none-any.whl", hash = "sha256:905c01b978a1cef7fdcddd2d9241dedc9987db6f23ba1b58d974e38b1cdf2775"},
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{file = "langchain_community-0.0.31.tar.gz", hash = "sha256:9a970bc2bb59bb4c204b696d8c62c2534f6ddb31005005cc1b7d7f934e58a5fc"},
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{file = "langchain_community-0.0.32-py3-none-any.whl", hash = "sha256:406977009999952d0705de3806de2b4867e9bb8eda8ca154a59c7a8ed58da38d"},
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{file = "langchain_community-0.0.32.tar.gz", hash = "sha256:1510217d646c8380f54e9850351f6d2a0b0dd73c501b666c6f4b40baa8160b29"},
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]
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[package.dependencies]
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aiohttp = ">=3.8.3,<4.0.0"
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dataclasses-json = ">=0.5.7,<0.7"
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langchain-core = ">=0.1.37,<0.2.0"
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langchain-core = ">=0.1.41,<0.2.0"
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langsmith = ">=0.1.0,<0.2.0"
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numpy = ">=1,<2"
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PyYAML = ">=5.3"
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@ -1797,17 +1797,17 @@ tenacity = ">=8.1.0,<9.0.0"
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[package.extras]
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cli = ["typer (>=0.9.0,<0.10.0)"]
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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)", "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)", "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)", "zhipuai (>=1.0.7,<2.0.0)"]
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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)"]
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[[package]]
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name = "langchain-core"
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version = "0.1.40"
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version = "0.1.41"
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description = "Building applications with LLMs through composability"
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optional = false
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python-versions = "<4.0,>=3.8.1"
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files = [
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{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]
|
||||
|
|
@ -1823,18 +1823,18 @@ 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)"]
|
||||
|
|
@ -1858,13 +1858,13 @@ extended-testing = ["lxml (>=5.1.0,<6.0.0)"]
|
|||
|
||||
[[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]
|
||||
|
|
@ -3917,13 +3917,13 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
|
|||
|
||||
[[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]
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue