diff --git a/llm-agents/run.ipynb b/llm-agents/run.ipynb index 94f6d8a2..c994a774 100644 --- a/llm-agents/run.ipynb +++ b/llm-agents/run.ipynb @@ -199,9 +199,18 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1;35mNote: NumExpr detected 16 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\u001b[0m\n", + "\u001b[1;35mNumExpr defaulting to 8 threads.\u001b[0m\n" + ] + } + ], "source": [ "from typing import List\n", "from typing_extensions import Annotated\n", @@ -209,12 +218,11 @@ "from zenml import step, log_artifact_metadata\n", "\n", "\n", - "@step(enable_cache=True)\n", + "@step\n", "def url_scraper(\n", - " docs_url: str = \"\",\n", - " repo_url: str = \"\",\n", - " release_notes_url: str = \"\",\n", - " website_url: str = \"\",\n", + " docs_url: str = \"https://docs.zenml.io\",\n", + " repo_url: str = \"https://github.com/zenml-io/zenml\",\n", + " website_url: str = \"https://zenml.io\",\n", ") -> Annotated[List[str], \"urls\"]:\n", " \"\"\"Generates a list of relevant URLs to scrape.\n", "\n", @@ -227,18 +235,19 @@ " Returns:\n", " List of URLs to scrape.\n", " \"\"\"\n", + " \n", + " # We comment this out to make this pipeline faster\n", " # examples_readme_urls = get_nested_readme_urls(repo_url)\n", " # docs_urls = get_all_pages(docs_url)\n", " # website_urls = get_all_pages(website_url)\n", - " # return docs_urls + website_urls + [release_notes_url]\n", + " # all_urls = docs_urls + website_urls + examples_readme_urls\n", " all_urls = [website_url]\n", " log_artifact_metadata(\n", - " artifact_name=\"urls\",\n", " metadata={\n", " \"count\": len(all_urls),\n", - " }\n", + " },\n", " )\n", - " return all_urls" + " return all_urls\n" ] }, { @@ -254,15 +263,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ + "from typing import List\n", + "\n", "from langchain.docstore.document import Document\n", "from langchain.document_loaders import UnstructuredURLLoader\n", + "from zenml import step\n", "\n", "\n", - "@step(enable_cache=True)\n", + "@step\n", "def web_url_loader(urls: List[str]) -> List[Document]:\n", " \"\"\"Loads documents from a list of URLs.\n", "\n", @@ -275,7 +287,7 @@ " loader = UnstructuredURLLoader(\n", " urls=urls,\n", " )\n", - " return loader.load()" + " return loader.load()\n" ] }, { @@ -291,20 +303,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ + "from typing_extensions import Annotated\n", + "from typing import List\n", + "\n", + "from langchain.docstore.document import Document\n", "from langchain.embeddings import OpenAIEmbeddings\n", "from langchain.text_splitter import (\n", " CharacterTextSplitter,\n", ")\n", "from langchain.schema.vectorstore import VectorStore\n", "from langchain.vectorstores.faiss import FAISS\n", + "from zenml import step, log_artifact_metadata\n", "\n", "\n", - "@step(enable_cache=True)\n", - "def index_generator(documents: List[Document]) -> Annotated[VectorStore, \"vector_store\"]:\n", + "@step\n", + "def index_generator(\n", + " documents: List[Document],\n", + ") -> Annotated[VectorStore, \"vector_store\"]:\n", " embeddings = OpenAIEmbeddings()\n", "\n", " text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n", @@ -315,10 +334,10 @@ " metadata={\n", " \"embedding_type\": \"OpenAIEmbeddings\",\n", " \"vector_store_type\": \"FAISS\",\n", - " }\n", + " },\n", " )\n", "\n", - " return FAISS.from_documents(compiled_texts, embeddings)" + " return FAISS.from_documents(compiled_texts, embeddings)\n" ] }, { @@ -335,22 +354,12 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "%reload_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ - "import logging\n", - "from typing import Dict, cast\n", + "from typing import Dict\n", + "from typing_extensions import Annotated\n", "\n", "from agent.agent_executor_materializer import AgentExecutorMaterializer\n", "from agent.prompt import PREFIX, SUFFIX\n", @@ -359,18 +368,22 @@ "from langchain.schema.vectorstore import VectorStore\n", "from langchain.tools.vectorstore.tool import VectorStoreQATool\n", "from langchain.agents import AgentExecutor\n", + "from pydantic import BaseModel\n", + "from zenml import step, ArtifactConfig, log_artifact_metadata\n", "from steps.agent_creator import AgentParameters\n", - "from zenml import step, ArtifactConfig\n", "\n", "\n", "PIPELINE_NAME = \"zenml_agent_creation_pipeline\"\n", "# Choose what character to use for your agent's answers\n", "CHARACTER = \"technical assistant\"\n", "\n", - "@step(output_materializers=AgentExecutorMaterializer, enable_cache=False)\n", + "\n", + "@step(output_materializers=AgentExecutorMaterializer)\n", "def agent_creator(\n", - " vector_store: VectorStore, config: AgentParameters\n", - ") -> Annotated[AgentExecutor, ArtifactConfig(name=\"agent\", is_model_artifact=True)]:\n", + " vector_store: VectorStore, config: AgentParameters = AgentParameters()\n", + ") -> Annotated[\n", + " AgentExecutor, ArtifactConfig(name=\"agent\", is_model_artifact=True)\n", + "]:\n", " \"\"\"Create an agent from a vector store.\n", "\n", " Args:\n", @@ -417,10 +430,10 @@ " \"temperature\": config.llm[\"temperature\"],\n", " \"model_name\": config.llm[\"model_name\"],\n", " },\n", - " }\n", + " },\n", " )\n", "\n", - " return agent_executor" + " return agent_executor\n" ] }, { @@ -449,7 +462,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -458,19 +471,13 @@ "MODEL_NAME = \"zenml_agent\"\n", "\n", "@pipeline(name=PIPELINE_NAME,\n", - " enable_cache=True,\n", " model=Model(\n", " name=MODEL_NAME,\n", " license=\"Apache\",\n", " description=\"ZenML Agent with a vector store tool.\",\n", " tags=[\"llm\", \"agent\", \"rag\"]\n", " ))\n", - "def zenml_agent_creation_pipeline(\n", - " docs_url: str = \"\",\n", - " repo_url: str = \"\",\n", - " release_notes_url: str = \"\",\n", - " website_url: str = \"\",\n", - ") -> None:\n", + "def zenml_agent_creation_pipeline():\n", " \"\"\"Generate index for ZenML.\n", "\n", " Args:\n", @@ -479,10 +486,10 @@ " release_notes_url: URL to the release notes.\n", " website_url: URL to the website.\n", " \"\"\"\n", - " urls = url_scraper(docs_url, repo_url, release_notes_url, website_url)\n", + " urls = url_scraper()\n", " documents = web_url_loader(urls)\n", " vector_store = index_generator(documents)\n", - " agent = agent_creator(vector_store=vector_store)\n" + " _ = agent_creator(vector_store=vector_store)\n" ] }, { @@ -496,7 +503,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -507,11 +514,82 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1;35mInitiating a new run for the pipeline: \u001b[0m\u001b[1;36mzenml_agent_creation_pipeline\u001b[1;35m.\u001b[0m\n", + "\u001b[1;35mRegistered new version: \u001b[0m\u001b[1;36m(version 23)\u001b[1;35m.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[1;35mNew model version \u001b[0m\u001b[1;36m4\u001b[1;35m was created.\u001b[0m\n", + "\u001b[1;35mExecuting a new run.\u001b[0m\n", + "\u001b[1;35mUsing user: \u001b[0m\u001b[1;36mjayesh.ext@zenml.io\u001b[1;35m\u001b[0m\n", + "\u001b[1;35mUsing stack: \u001b[0m\u001b[1;36mdefault\u001b[1;35m\u001b[0m\n", + "\u001b[1;35m artifact_store: \u001b[0m\u001b[1;36mdefault\u001b[1;35m\u001b[0m\n", + "\u001b[1;35m orchestrator: \u001b[0m\u001b[1;36mdefault\u001b[1;35m\u001b[0m\n", + "\u001b[1;35mStep \u001b[0m\u001b[1;36murl_scraper\u001b[1;35m has started.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[1;35mStep \u001b[0m\u001b[1;36murl_scraper\u001b[1;35m has finished in \u001b[0m\u001b[1;36m17.803s\u001b[1;35m.\u001b[0m\n", + "\u001b[1;35mStep \u001b[0m\u001b[1;36mweb_url_loader\u001b[1;35m has started.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[1;35mReading document from string ...\u001b[0m\n", + "\u001b[1;35mReading document ...\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[1;35mImplicitly linking artifact \u001b[0m\u001b[1;36moutput\u001b[1;35m to model \u001b[0m\u001b[1;36mzenml_agent\u001b[1;35m version \u001b[0m\u001b[1;36m4\u001b[1;35m.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[1;35mStep \u001b[0m\u001b[1;36mweb_url_loader\u001b[1;35m has finished in \u001b[0m\u001b[1;36m20.253s\u001b[1;35m.\u001b[0m\n", + "\u001b[1;35mStep \u001b[0m\u001b[1;36mindex_generator\u001b[1;35m has started.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[1;35mLoading faiss with AVX2 support.\u001b[0m\n", + "\u001b[1;35mSuccessfully loaded faiss with AVX2 support.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[1;35mStep \u001b[0m\u001b[1;36mindex_generator\u001b[1;35m has finished in \u001b[0m\u001b[1;36m19.652s\u001b[1;35m.\u001b[0m\n", + "\u001b[1;35mStep \u001b[0m\u001b[1;36magent_creator\u001b[1;35m has started.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[33mProvided model configuration does not match existing model \u001b[0m\u001b[1;36mzenml_agent\u001b[33m with the following changes: {'license': {'config': 'Apache', 'db': 'Apache 2.0'}}. If you want to update the model configuration, please use the \u001b[0m\u001b[1;36mzenml model update\u001b[33m command.\u001b[0m\n", + "\u001b[1;35mStep \u001b[0m\u001b[1;36magent_creator\u001b[1;35m has finished in \u001b[0m\u001b[1;36m19.672s\u001b[1;35m.\u001b[0m\n", + "\u001b[1;35mPipeline run has finished in \u001b[0m\u001b[1;36m1m27s\u001b[1;35m.\u001b[0m\n", + "\u001b[1;35mDashboard URL: https://1cf18d95-zenml.cloudinfra.zenml.io/workspaces/default/pipelines/75b11423-6af5-421d-98a8-ac39f4183c19/runs/84d0350e-b5bb-489b-a66b-9d342ee4a20d/dag\u001b[0m\n" + ] + }, + { + "data": { + "text/plain": [ + "PipelineRunResponse(id=UUID('84d0350e-b5bb-489b-a66b-9d342ee4a20d'), permission_denied=False, body=PipelineRunResponseBody(created=datetime.datetime(2024, 1, 25, 14, 10, 27), updated=datetime.datetime(2024, 1, 25, 14, 10, 27), user=UserResponse(id=UUID('8b4899df-2396-4226-9780-0c75e7e1bf75'), permission_denied=False, body=UserResponseBody(created=datetime.datetime(2023, 11, 10, 10, 9, 15), updated=datetime.datetime(2024, 1, 25, 11, 25, 59), active=True, activation_token=None, full_name='Jayesh Sharma', email_opted_in=True, is_service_account=False), metadata=None, name='jayesh.ext@zenml.io'), status=, stack=StackResponse(id=UUID('a4cd4161-6ee5-411c-8adf-559ac084ceb5'), permission_denied=False, body=StackResponseBody(created=datetime.datetime(2023, 11, 30, 9, 39, 29), updated=datetime.datetime(2023, 11, 30, 9, 39, 29), user=None), metadata=None, name='default'), pipeline=PipelineResponse(id=UUID('75b11423-6af5-421d-98a8-ac39f4183c19'), permission_denied=False, body=PipelineResponseBody(created=datetime.datetime(2024, 1, 25, 14, 10, 24), updated=datetime.datetime(2024, 1, 25, 14, 10, 24), user=UserResponse(id=UUID('8b4899df-2396-4226-9780-0c75e7e1bf75'), permission_denied=False, body=UserResponseBody(created=datetime.datetime(2023, 11, 10, 10, 9, 15), updated=datetime.datetime(2024, 1, 25, 11, 25, 59), active=True, activation_token=None, full_name='Jayesh Sharma', email_opted_in=True, is_service_account=False), metadata=None, name='jayesh.ext@zenml.io'), status=[], version='23'), metadata=None, name='zenml_agent_creation_pipeline'), build=None, schedule=None, code_reference=None), metadata=PipelineRunResponseMetadata(workspace=WorkspaceResponse(id=UUID('f3a544f2-afb5-4672-934a-7a465c66201c'), permission_denied=False, body=WorkspaceResponseBody(created=datetime.datetime(2023, 10, 23, 15, 34, 47), updated=datetime.datetime(2023, 10, 23, 15, 34, 47)), metadata=None, name='default'), run_metadata={}, steps={}, config=PipelineConfiguration(enable_cache=None, enable_artifact_metadata=None, enable_artifact_visualization=None, enable_step_logs=None, settings={}, extra={}, failure_hook_source=None, success_hook_source=None, model=Model(name='zenml_agent', license='Apache', description='ZenML Agent with a vector store tool.', audience=None, use_cases=None, limitations=None, trade_offs=None, ethics=None, tags=['llm', 'agent', 'rag'], version='4', save_models_to_registry=True, suppress_class_validation_warnings=True, was_created_in_this_run=True), parameters=None, name='zenml_agent_creation_pipeline'), start_time=datetime.datetime(2024, 1, 25, 14, 10, 25), end_time=None, client_environment={'environment': 'notebook', 'os': 'linux', 'linux_distro': 'ubuntu', 'linux_distro_like': 'debian', 'linux_distro_version': '20.04', 'python_version': '3.9.5'}, orchestrator_environment={}, orchestrator_run_id=None), name='zenml_agent_creation_pipeline-2024_01_25-14_10_25_121924')" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "version = \"0.54.1\"\n", + "version = \"0.55.0\"\n", "docs_url = f\"https://docs.zenml.io/v/{version}/\"\n", "website_url = \"https://zenml.io\"\n", "repo_url = f\"https://github.com/zenml-io/zenml/tree/{version}/examples\"\n", @@ -520,10 +598,6 @@ ")\n", "\n", "zenml_agent_creation_pipeline(\n", - " website_url=website_url,\n", - " docs_url=docs_url,\n", - " repo_url=repo_url,\n", - " release_notes_url=release_notes_url,\n", ")" ] }, @@ -708,7 +782,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.5" } }, "nbformat": 4,