8172e62236* Initial Restructure * Replace import langflow for import langflow_base * Fix dependencies * 🔧 chore(Makefile): refactor build process to separate base and frontend builds for better organization and maintainability * 🚀 chore(Makefile): update build_frontend command to copy frontend build to the correct directory 🔖 chore(pyproject.toml): update python and httpx dependencies versions 🔧 chore(__init__.py): update import statement for load_flow_from_json function * 🔖 chore(pyproject.toml): update package version from 0.0.6 to 0.0.8 to reflect changes in the codebase * 🚀 feat(server.ts): change port variable case from lowercase port to uppercase PORT to improve semantics 🚀 feat(server.ts): add support for process.env.PORT environment variable to be able to run app on a configurable port * 🐛 fix(server.ts): change port variable case from lowercase port to uppercase PORT to improve semantics ✨ feat(server.ts): add support for process.env.PORT environment variable to be able to run app on a configurable port 🚚 chore(pyproject.toml): update langflow-base version from 0.0.8 to 0.0.10 ✨ feat(server.ts): add new agent component LCAgentComponent to langflow_base ✨ feat(server.ts): add new model component LCModelComponent to langflow_base ✨ feat(server.ts): add new helper functions docs_to_records and records_to_text to langflow_base ✨ feat(server.ts): add new flow helper functions list_flows, load_flow, run_flow, generate_function_for_flow, get_flow_inputs, build_schema_from_inputs to langflow_base ✨ feat(server.ts): add new prompt component PromptComponent to langflow_base ✨ feat(server.ts): add new chat components ChatInput and ChatOutput to langflow_base ✨ feat(server.ts): add new model component OpenAIModelComponent to langflow_base 🚚 chore(main.py): update import path from langflow.main to langflow_base.main 🚚 chore(service.py): update import path from langflow.services.database.manager to langflow_base.services.database.manager 🚚 chore(factory.py): update import path from langflow.services to langflow_base.services 🚚 chore(service.py): update import path from langflow.services.plugins to langflow_base.services.plugins 🚚 chore(utils.py): update import path from langflow.services to langflow_base.services 🚚 chore(validate.py): update import path from langflow.field_typing to langflow_base.field_typing 🚚 chore(pyproject.toml): update langflow-base version from 0.0.8 to 0.0.10 * Update Makefile to install backend dependencies and build langflow * Add langflow main module and update __init__.py * Update langflow install process to use implicit namespace * Add langflow-base as a local dependency * Add setup_poetry target to Makefile * Update Poetry version and add poetry-monorepo-dependency-plugin * Refactor code to improve performance and readability * Update imports to custom and load * Update content-hash in poetry.lock --------- Co-authored-by: Matheus <jacquesmats@gmail.com> Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@logspace.ai>
1747 lines
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88 KiB
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1747 lines
No EOL
88 KiB
JSON
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"value": "from typing import List, Optional, Union\n\nimport chromadb # type: ignore\nfrom langchain.embeddings.base import Embeddings\nfrom langchain.schema import BaseRetriever, Document\nfrom langchain.vectorstores import Chroma\nfrom langchain.vectorstores.base import VectorStore\n\nfrom langflow.custom import CustomComponent\n\n\nclass ChromaComponent(CustomComponent):\n \"\"\"\n A custom component for implementing a Vector Store using Chroma.\n \"\"\"\n\n display_name: str = \"Chroma\"\n description: str = \"Implementation of Vector Store using Chroma\"\n documentation = \"https://python.langchain.com/docs/integrations/vectorstores/chroma\"\n beta: bool = True\n\n def build_config(self):\n \"\"\"\n Builds the configuration for the component.\n\n Returns:\n - dict: A dictionary containing the configuration options for the component.\n \"\"\"\n return {\n \"collection_name\": {\"display_name\": \"Collection Name\", \"value\": \"langflow\"},\n \"persist\": {\"display_name\": \"Persist\"},\n \"persist_directory\": {\"display_name\": \"Persist Directory\"},\n \"code\": {\"show\": False, \"display_name\": \"Code\"},\n \"documents\": {\"display_name\": \"Documents\", \"is_list\": True},\n \"embedding\": {\"display_name\": \"Embedding\"},\n \"chroma_server_cors_allow_origins\": {\n \"display_name\": \"Server CORS Allow Origins\",\n \"advanced\": True,\n },\n \"chroma_server_host\": {\"display_name\": \"Server Host\", \"advanced\": True},\n \"chroma_server_port\": {\"display_name\": \"Server Port\", \"advanced\": True},\n \"chroma_server_grpc_port\": {\n \"display_name\": \"Server gRPC Port\",\n \"advanced\": True,\n },\n \"chroma_server_ssl_enabled\": {\n \"display_name\": \"Server SSL Enabled\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n collection_name: str,\n persist: bool,\n embedding: Embeddings,\n chroma_server_ssl_enabled: bool,\n persist_directory: Optional[str] = None,\n documents: Optional[List[Document]] = None,\n chroma_server_cors_allow_origins: Optional[str] = None,\n chroma_server_host: Optional[str] = None,\n chroma_server_port: Optional[int] = None,\n chroma_server_grpc_port: Optional[int] = None,\n ) -> Union[VectorStore, BaseRetriever]:\n \"\"\"\n Builds the Vector Store or BaseRetriever object.\n\n Args:\n - collection_name (str): The name of the collection.\n - persist_directory (Optional[str]): The directory to persist the Vector Store to.\n - chroma_server_ssl_enabled (bool): Whether to enable SSL for the Chroma server.\n - persist (bool): Whether to persist the Vector Store or not.\n - embedding (Optional[Embeddings]): The embeddings to use for the Vector Store.\n - documents (Optional[Document]): The documents to use for the Vector Store.\n - chroma_server_cors_allow_origins (Optional[str]): The CORS allow origins for the Chroma server.\n - chroma_server_host (Optional[str]): The host for the Chroma server.\n - chroma_server_port (Optional[int]): The port for the Chroma server.\n - chroma_server_grpc_port (Optional[int]): The gRPC port for the Chroma server.\n\n Returns:\n - Union[VectorStore, BaseRetriever]: The Vector Store or BaseRetriever object.\n \"\"\"\n\n # Chroma settings\n chroma_settings = None\n\n if chroma_server_host is not None:\n chroma_settings = chromadb.config.Settings(\n chroma_server_cors_allow_origins=chroma_server_cors_allow_origins or None,\n chroma_server_host=chroma_server_host,\n chroma_server_port=chroma_server_port or None,\n chroma_server_grpc_port=chroma_server_grpc_port or None,\n chroma_server_ssl_enabled=chroma_server_ssl_enabled,\n )\n\n # If documents, then we need to create a Chroma instance using .from_documents\n if documents is not None and embedding is not None:\n if len(documents) == 0:\n raise ValueError(\"If documents are provided, there must be at least one document.\")\n return Chroma.from_documents(\n documents=documents, # type: ignore\n persist_directory=persist_directory if persist else None,\n collection_name=collection_name,\n embedding=embedding,\n client_settings=chroma_settings,\n )\n\n return Chroma(persist_directory=persist_directory, client_settings=chroma_settings)\n",
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{
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"value": "youtube_transcripts"
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},
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"params": {
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{
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"video_id": "krsBRQbOPQ4"
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