upstage: init package (#20574)

Co-authored-by: Sean Cho <sean@upstage.ai>
Co-authored-by: JuHyung-Son <sonju0427@gmail.com>

docs/docs/integrations/chat/solar.ipynb

@@ -1,80 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "a9667088-04e1-4f67-8221-a0072a2d635f",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-03-06T17:04:59.273702Z",
-     "iopub.status.busy": "2024-03-06T17:04:59.272602Z",
-     "iopub.status.idle": "2024-03-06T17:05:00.129177Z",
-     "shell.execute_reply": "2024-03-06T17:05:00.124594Z",
-     "shell.execute_reply.started": "2024-03-06T17:04:59.273646Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "AIMessage(content='저는 대형 언어 모델 프로젝트를 구축하고 싶습니다.')"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import os\n",
-    "\n",
-    "os.environ[\"SOLAR_API_KEY\"] = \"SOLAR_API_KEY\"\n",
-    "\n",
-    "from langchain_community.chat_models.solar import SolarChat\n",
-    "from langchain_core.messages import HumanMessage, SystemMessage\n",
-    "\n",
-    "chat = SolarChat(max_tokens=1024)\n",
-    "\n",
-    "messages = [\n",
-    "    SystemMessage(\n",
-    "        content=\"You are a helpful assistant who translates English to Korean.\"\n",
-    "    ),\n",
-    "    HumanMessage(\n",
-    "        content=\"Translate this sentence from English to Korean. I want to build a project of large language model.\"\n",
-    "    ),\n",
-    "]\n",
-    "\n",
-    "chat.invoke(messages)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8cb792fe-2844-4969-a9e9-f4c0f97b1699",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.0"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

docs/docs/integrations/chat/upstage.ipynb

@@ -0,0 +1,157 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "910f5772b6af13c9",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "---\n",
+    "sidebar_label: Upstage\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "433f5422ad8e1efa",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "# ChatUpstage\n",
+    "\n",
+    "This notebook covers how to get started with Upstage chat models.\n",
+    "\n",
+    "## Installation\n",
+    "\n",
+    "Install `langchain-upstage` package.\n",
+    "\n",
+    "```bash\n",
+    "pip install -U langchain-upstage\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b3c5c4627fe95eae",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "## Environment Setup\n",
+    "\n",
+    "Make sure to set the following environment variables:\n",
+    "\n",
+    "- `UPSTAGE_API_KEY`: Your Upstage API key from [Upstage console](https://console.upstage.ai/).\n",
+    "\n",
+    "## Usage"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "20a0067b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ[\"UPSTAGE_API_KEY\"] = \"YOUR_API_KEY\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8a4d650d76a33494",
+   "metadata": {
+    "collapsed": false,
+    "is_executing": true
+   },
+   "outputs": [],
+   "source": [
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain_upstage import ChatUpstage\n",
+    "\n",
+    "chat = ChatUpstage()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a1679b5cafaf88b9",
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# using chat invoke\n",
+    "chat.invoke(\"Hello, how are you?\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "698a788a63b5c3e5",
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# using chat stream\n",
+    "for m in chat.stream(\"Hello, how are you?\"):\n",
+    "    print(m)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "36f8a703",
+   "metadata": {},
+   "source": [
+    "## Chaining"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "efa06617e5d4f6b2",
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# using chain\n",
+    "prompt = ChatPromptTemplate.from_messages(\n",
+    "    [\n",
+    "        (\"system\", \"You are a helpful assistant that translates English to French.\"),\n",
+    "        (\"human\", \"Translate this sentence from English to French. {english_text}.\"),\n",
+    "    ]\n",
+    ")\n",
+    "chain = prompt | chat\n",
+    "\n",
+    "chain.invoke({\"english_text\": \"Hello, how are you?\"})"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docs/docs/integrations/llms/solar.ipynb

@@ -1,30 +1,19 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Solar\n",
+    "\n",
+    "*This community integration is deprecated. You should use [`ChatUpstage`](../../chat/upstage) instead to access Solar LLM via the chat model connector.*"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "id": "2ff00e23-1a90-4a39-b220-83ebfffd96d6",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-03-06T17:10:57.375714Z",
-     "iopub.status.busy": "2024-03-06T17:10:57.375261Z",
-     "iopub.status.idle": "2024-03-06T17:11:03.473978Z",
-     "shell.execute_reply": "2024-03-06T17:11:03.472875Z",
-     "shell.execute_reply.started": "2024-03-06T17:10:57.375670Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "\"Once upon a time, in a far-off land, there was a young girl named Lily. Lily was a kind and curious girl who loved to explore the world around her. One day, while wandering through the forest, she came across a small, shimmering pond.\\n\\nAs she approached the pond, she saw a beautiful, glowing flower floating on the water's surface. Lily reached out to touch the flower, and as she did, she felt a strange tingling sensation. Suddenly, the flower began to glow even brighter, and Lily was transported to a magical world filled with talking animals and enchanted forests.\\n\\nIn this world, Lily met a wise old owl named Winston who told her that the flower she had touched was a magical one that could grant her any wish she desired. Lily was overjoyed and asked Winston to show her around the magical world.\\n\\nTogether, they explored the enchanted forests, met friendly animals, and discovered hidden treasures. Lily was having the time of her life, but she knew that she couldn't stay in this magical world forever. Eventually, she had to return home.\\n\\nAs she said goodbye to Winston and the magical world, Lily realized that she had learned an important lesson. She had discovered that sometimes, the most magical things in life are the ones that are right in front of us, if we only take the time to look.\\n\\nFrom that day on, Lily always kept her eyes open for the magic in the world around her, and she never forgot the adventure she had in the enchanted forest.\""
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import os\n",
     "\n",
@@ -37,37 +26,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "67fa1711-f08f-43fa-a3bd-75ae5bc6b988",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-03-06T17:11:11.359924Z",
-     "iopub.status.busy": "2024-03-06T17:11:11.358357Z",
-     "iopub.status.idle": "2024-03-06T17:11:16.692138Z",
-     "shell.execute_reply": "2024-03-06T17:11:16.686492Z",
-     "shell.execute_reply.started": "2024-03-06T17:11:11.359835Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/ary/dev/llm/langchain/libs/core/langchain_core/_api/deprecation.py:117: LangChainDeprecationWarning: The function `run` was deprecated in LangChain 0.1.0 and will be removed in 0.2.0. Use invoke instead.\n",
-      "  warn_deprecated(\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "'Step 1: Determine the year Justin Bieber was born.\\nJustin Bieber was born on March 1, 1994.\\n\\nStep 2: Determine the Super Bowl held in 1994.\\nSuper Bowl XXVIII was held in 1994.\\n\\nStep 3: Determine the winning team of Super Bowl XXVIII.\\nThe Dallas Cowboys won Super Bowl XXVIII in 1994.\\n\\nFinal Answer: The Dallas Cowboys won the Super Bowl in the year Justin Bieber was born (1994).'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "from langchain.chains import LLMChain\n",
     "from langchain.prompts import PromptTemplate\n",
@@ -86,35 +47,13 @@
     "\n",
     "llm_chain.run(question)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "91961983-d0d5-4901-b854-531e158c0416",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
   "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.0"
+   "name": "python"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 5
+ "nbformat_minor": 2
 }

docs/docs/integrations/platforms/index.mdx

@@ -30,6 +30,7 @@ These providers have standalone `langchain-{provider}` packages for improved ver
 - [Pinecone](/docs/integrations/providers/pinecone)
 - [Robocorp](/docs/integrations/providers/robocorp)
 - [Together AI](/docs/integrations/providers/together)
+- [Upstage](/docs/integrations/providers/upstage)
 - [Voyage AI](/docs/integrations/providers/voyageai)
 
 

docs/docs/integrations/providers/upstage.ipynb

@@ -0,0 +1,149 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Upstage\n",
+    "\n",
+    "[Upstage](https://upstage.ai) is a leading artificial intelligence (AI) company specializing in delivering above-human-grade performance LLM components. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Solar LLM\n",
+    "\n",
+    "**Solar Mini Chat** is a fast yet powerful advanced large language model focusing on English and Korean. It has been specifically fine-tuned for multi-turn chat purposes, showing enhanced performance across a wide range of natural language processing tasks, like multi-turn conversation or tasks that require an understanding of long contexts, such as RAG (Retrieval-Augmented Generation), compared to other models of a similar size. This fine-tuning equips it with the ability to handle longer conversations more effectively, making it particularly adept for interactive applications."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Installation and Setup\n",
+    "\n",
+    "Install `langchain-upstage` package:\n",
+    "\n",
+    "```bash\n",
+    "pip install -qU langchain-core langchain-upstage\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Get an [access token](https://console.upstage.ai) and set it as an environment variable (`UPSTAGE_API_KEY`)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Upstage LangChain integrations\n",
+    "\n",
+    "| API | Description | Import | Example usage |\n",
+    "| --- | --- | --- | --- |\n",
+    "| Chat | Build assistants using Solar Mini Chat | `from langchain_upstage import ChatUpstage` | [Go](../../chat/upstage) |\n",
+    "| Text Embedding | Embed strings to vectors | `from langchain_upstage import UpstageEmbeddings` | [Go](../../text_embedding/upstage) |\n",
+    "\n",
+    "See [documentations](https://developers.upstage.ai/) for more details about the features."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Quick Examples\n",
+    "\n",
+    "### Environment Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ[\"UPSTAGE_API_KEY\"] = \"YOUR_API_KEY\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "### Chat\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_upstage import ChatUpstage\n",
+    "\n",
+    "chat = ChatUpstage()\n",
+    "response = chat.invoke(\"Hello, how are you?\")\n",
+    "print(response)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n",
+    "### Text embedding\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_upstage import UpstageEmbeddings\n",
+    "\n",
+    "embeddings = UpstageEmbeddings()\n",
+    "doc_result = embeddings.embed_documents(\n",
+    "    [\"Sam is a teacher.\", \"This is another document\"]\n",
+    ")\n",
+    "print(doc_result)\n",
+    "\n",
+    "query_result = embeddings.embed_query(\"What does Sam do?\")\n",
+    "print(query_result)"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

docs/docs/integrations/text_embedding/upstage.ipynb

@@ -0,0 +1,216 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "a1915c573ecefe5e",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "---\n",
+    "sidebar_label: Upstage\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c07bf6cf93adec81",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "# UpstageEmbeddings\n",
+    "\n",
+    "This notebook covers how to get started with Upstage embedding models.\n",
+    "\n",
+    "## Installation\n",
+    "\n",
+    "Install `langchain-upstage` package.\n",
+    "\n",
+    "```bash\n",
+    "pip install -U langchain-upstage\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c2b1c8fd01d71683",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "## Environment Setup\n",
+    "\n",
+    "Make sure to set the following environment variables:\n",
+    "\n",
+    "- `UPSTAGE_API_KEY`: Your Upstage API key from [Upstage console](https://console.upstage.ai/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a50c04f9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ[\"UPSTAGE_API_KEY\"] = \"YOUR_API_KEY\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c02e30aa",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Usage\n",
+    "\n",
+    "Initialize `UpstageEmbeddings` class."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ea89ac9da2520b91",
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from langchain_upstage import UpstageEmbeddings\n",
+    "\n",
+    "embeddings = UpstageEmbeddings()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8be6eab1",
+   "metadata": {},
+   "source": [
+    "Use `embed_documents` to embed list of texts or documents. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "26aa179f7ad60cbe",
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "doc_result = embeddings.embed_documents(\n",
+    "    [\"Sam is a teacher.\", \"This is another document\"]\n",
+    ")\n",
+    "print(doc_result)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0197135c",
+   "metadata": {},
+   "source": [
+    "Use `embed_query` to embed query string."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5a80d47413c27bbc",
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "query_result = embeddings.embed_query(\"What does Sam do?\")\n",
+    "print(query_result)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d5ff58e",
+   "metadata": {},
+   "source": [
+    "Use `aembed_documents` and `aembed_query` for async operations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "af75139d0e1d9ba2",
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# async embed query\n",
+    "await embeddings.aembed_query(\"My query to look up\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17968d20c0dfb2f9",
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# async embed documents\n",
+    "await embeddings.aembed_documents(\n",
+    "    [\"This is a content of the document\", \"This is another document\"]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6429f2f8",
+   "metadata": {},
+   "source": [
+    "## Using with vector store\n",
+    "\n",
+    "You can use `UpstageEmbeddings` with vector store component. The following demonstrates a simple example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09ac41d5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_community.vectorstores import DocArrayInMemorySearch\n",
+    "\n",
+    "vectorstore = DocArrayInMemorySearch.from_texts(\n",
+    "    [\"harrison worked at kensho\", \"bears like to eat honey\"],\n",
+    "    embedding=UpstageEmbeddings(),\n",
+    ")\n",
+    "retriever = vectorstore.as_retriever()\n",
+    "docs = retriever.get_relevant_documents(\"Where did Harrison work?\")\n",
+    "print(docs)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docs/vercel.json

@@ -1185,6 +1185,14 @@
     {
       "source": "/docs/guides/evaluation/:path*(/?)",
       "destination": "/docs/guides/productionization/evaluation/:path*/"
+    },
+    {
+      "source": "/docs/integrations/text_embedding/solar(/?)",
+      "destination": "/docs/integrations/text_embedding/upstage"
+    },
+    {
+      "source": "/docs/integrations/chat/solar(/?)",
+      "destination": "/docs/integrations/chat/upstage"
     }
   ]
 }