Community/Partners: Add support for Perplexity AI

docs/docs/integrations/chat/perplexity.ipynb

@@ -0,0 +1,229 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "a016701c",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "sidebar_label: Perplexity\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bf733a38-db84-4363-89e2-de6735c37230",
+   "metadata": {},
+   "source": [
+    "# ChatPerplexity\n",
+    "\n",
+    "This notebook covers how to get started with Perplexity chat models."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "d4a7c55d-b235-4ca4-a579-c90cc9570da9",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-01-19T11:25:00.590587Z",
+     "start_time": "2024-01-19T11:25:00.127293Z"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from langchain_community.chat_models import ChatPerplexity\n",
+    "from langchain_core.prompts import ChatPromptTemplate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97a8ce3a",
+   "metadata": {},
+   "source": [
+    "The code provided assumes that your PPLX_API_KEY is set in your environment variables. If you would like to manually specify your API key and also choose a different model, you can use the following code:\n",
+    "\n",
+    "```python\n",
+    "chat = ChatPerplexity(temperature=0, pplx_api_key=\"YOUR_API_KEY\", model=\"pplx-70b-online\")\n",
+    "```\n",
+    "\n",
+    "You can check a list of available models [here](https://docs.perplexity.ai/docs/model-cards). For reproducibility, we can set the API key dynamically by taking it as an input in this notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "d3e49d78",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from getpass import getpass\n",
+    "\n",
+    "PPLX_API_KEY = getpass()\n",
+    "os.environ[\"PPLX_API_KEY\"] = PPLX_API_KEY"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "70cf04e8-423a-4ff6-8b09-f11fb711c817",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-01-19T11:25:04.349676Z",
+     "start_time": "2024-01-19T11:25:03.964930Z"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "chat = ChatPerplexity(temperature=0, model=\"pplx-70b-online\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "8199ef8f-eb8b-4253-9ea0-6c24a013ca4c",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-01-19T11:25:07.274418Z",
+     "start_time": "2024-01-19T11:25:05.898031Z"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'The Higgs Boson is an elementary subatomic particle that plays a crucial role in the Standard Model of particle physics, which accounts for three of the four fundamental forces governing the behavior of our universe: the strong and weak nuclear forces, electromagnetism, and gravity. The Higgs Boson is important for several reasons:\\n\\n1. **Final Elementary Particle**: The Higgs Boson is the last elementary particle waiting to be discovered under the Standard Model. Its detection helps complete the Standard Model and further our understanding of the fundamental forces in the universe.\\n\\n2. **Mass Generation**: The Higgs Boson is responsible for giving mass to other particles, a process that occurs through its interaction with the Higgs field. This mass generation is essential for the formation of atoms, molecules, and the visible matter we observe in the universe.\\n\\n3. **Implications for New Physics**: While the detection of the Higgs Boson has confirmed many aspects of the Standard Model, it also opens up new possibilities for discoveries beyond the Standard Model. Further research on the Higgs Boson could reveal insights into the nature of dark matter, supersymmetry, and other exotic phenomena.\\n\\n4. **Advancements in Technology**: The search for the Higgs Boson has led to significant advancements in technology, such as the development of artificial intelligence and machine learning algorithms used in particle accelerators like the Large Hadron Collider (LHC). These advancements have not only contributed to the discovery of the Higgs Boson but also have potential applications in various other fields.\\n\\nIn summary, the Higgs Boson is important because it completes the Standard Model, plays a crucial role in mass generation, hints at new physics phenomena beyond the Standard Model, and drives advancements in technology.\\n'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "system = \"You are a helpful assistant.\"\n",
+    "human = \"{input}\"\n",
+    "prompt = ChatPromptTemplate.from_messages([(\"system\", system), (\"human\", human)])\n",
+    "\n",
+    "chain = prompt | chat\n",
+    "response = chain.invoke({\"input\": \"Why is the Higgs Boson important?\"})\n",
+    "response.content"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de6d8d5a",
+   "metadata": {},
+   "source": [
+    "You can format and structure the prompts like you would typically. In the following example, we ask the model to tell us a joke about cats."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "c5fac0e9-05a4-4fc1-a3b3-e5bbb24b971b",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-01-19T11:25:10.448733Z",
+     "start_time": "2024-01-19T11:25:08.866277Z"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Here\\'s a joke about cats:\\n\\nWhy did the cat want math lessons from a mermaid?\\n\\nBecause it couldn\\'t find its \"core purpose\" in life!\\n\\nRemember, cats are unique and fascinating creatures, and each one has its own special traits and abilities. While some may see them as mysterious or even a bit aloof, they are still beloved pets that bring joy and companionship to their owners. So, if your cat ever seeks guidance from a mermaid, just remember that they are on their own journey to self-discovery!\\n'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chat = ChatPerplexity(temperature=0, model=\"pplx-70b-online\")\n",
+    "prompt = ChatPromptTemplate.from_messages([(\"human\", \"Tell me a joke about {topic}\")])\n",
+    "chain = prompt | chat\n",
+    "response = chain.invoke({\"topic\": \"cats\"})\n",
+    "response.content"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "13d93dc4",
+   "metadata": {},
+   "source": [
+    "## `ChatPerplexity` also supports streaming functionality:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "025be980-e50d-4a68-93dc-c9c7b500ce34",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-01-19T11:25:24.438696Z",
+     "start_time": "2024-01-19T11:25:14.687480Z"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Here is a list of some famous tourist attractions in Pakistan:\n",
+      "\n",
+      "1. **Minar-e-Pakistan**: A 62-meter high minaret in Lahore that represents the history of Pakistan.\n",
+      "2. **Badshahi Mosque**: A historic mosque in Lahore with a capacity of 10,000 worshippers.\n",
+      "3. **Shalimar Gardens**: A beautiful garden in Lahore with landscaped grounds and a series of cascading pools.\n",
+      "4. **Pakistan Monument**: A national monument in Islamabad representing the four provinces and three districts of Pakistan.\n",
+      "5. **National Museum of Pakistan**: A museum in Karachi showcasing the country's cultural history.\n",
+      "6. **Faisal Mosque**: A large mosque in Islamabad that can accommodate up to 300,000 worshippers.\n",
+      "7. **Clifton Beach**: A popular beach in Karachi offering water activities and recreational facilities.\n",
+      "8. **Kartarpur Corridor**: A visa-free border crossing and religious corridor connecting Gurdwara Darbar Sahib in Pakistan to Gurudwara Sri Kartarpur Sahib in India.\n",
+      "9. **Mohenjo-daro**: An ancient Indus Valley civilization site in Sindh, Pakistan, dating back to around 2500 BCE.\n",
+      "10. **Hunza Valley**: A picturesque valley in Gilgit-Baltistan known for its stunning mountain scenery and unique culture.\n",
+      "\n",
+      "These attractions showcase the rich history, diverse culture, and natural beauty of Pakistan, making them popular destinations for both local and international tourists.\n"
+     ]
+    }
+   ],
+   "source": [
+    "chat = ChatPerplexity(temperature=0.7, model=\"pplx-70b-online\")\n",
+    "prompt = ChatPromptTemplate.from_messages(\n",
+    "    [(\"human\", \"Give me a list of famous tourist attractions in Pakistan\")]\n",
+    ")\n",
+    "chain = prompt | chat\n",
+    "for chunk in chain.stream({}):\n",
+    "    print(chunk.content, end=\"\", flush=True)"
+   ]
+  }
+ ],
+ "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": "3.9.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docs/docs/integrations/llms/perplexity.ipynb

@@ -0,0 +1,143 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9597802c",
+   "metadata": {},
+   "source": [
+    "# Perplexity\n",
+    "\n",
+    "This example goes over how to use LangChain to interact with `Perplexity` [models](https://docs.perplexity.ai/docs/model-cards).\n",
+    "\n",
+    "The code provided assumes that your PPLX_API_KEY is set in your environment variables. If you would like to manually specify your API key and also choose a different model, you can use the following code:\n",
+    "\n",
+    "```python\n",
+    "llm = PerplexityLLM(model=\"pplx-70b-online\", pplx_api_key=\"YOUR_API_KEY\")\n",
+    "```\n",
+    "\n",
+    "For reproducibility, we can set the API key dynamically by taking it as an input in this notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "5472a7cd-af26-48ca-ae9b-5f6ae73c74d2",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from getpass import getpass\n",
+    "\n",
+    "PPLX_API_KEY = getpass()\n",
+    "os.environ[\"PPLX_API_KEY\"] = PPLX_API_KEY"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "6fb585dd",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from langchain.chains import LLMChain\n",
+    "from langchain.prompts import PromptTemplate\n",
+    "from langchain_community.llms.perplexity import PerplexityLLM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "035dea0f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "template = \"\"\"Question: {question}\n",
+    "\n",
+    "Answer: Let's think step by step.\"\"\"\n",
+    "\n",
+    "prompt = PromptTemplate(template=template, input_variables=[\"question\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "3f3458d9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "llm = PerplexityLLM(model=\"pplx-70b-online\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "a641dbd9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "llm_chain = LLMChain(prompt=prompt, llm=llm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "9f844993",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Justin Bieber was born on March 1, 1994. The Super Bowl that took place in the year Justin Bieber was born was Super Bowl XXVIII. The game was played on January 30, 1994, and it was between the Dallas Cowboys and the Buffalo Bills. The Dallas Cowboys won the game with a score of 30-13, and their wide receiver, Michael Irvin, was named the MVP (Most Valuable Player) of the game.\\n'"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
+    "\n",
+    "llm_chain.run(question)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.11.1 64-bit",
+   "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": "3.9.18"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "e971737741ff4ec9aff7dc6155a1060a59a8a6d52c757dbbe66bf8ee389494b1"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

libs/community/langchain_community/chat_models/__init__.py

@@ -49,6 +49,7 @@
 from langchain_community.chat_models.ollama import ChatOllama
 from langchain_community.chat_models.openai import ChatOpenAI
 from langchain_community.chat_models.pai_eas_endpoint import PaiEasChatEndpoint
+from langchain_community.chat_models.perplexity import ChatPerplexity
 from langchain_community.chat_models.promptlayer_openai import PromptLayerChatOpenAI
 from langchain_community.chat_models.sparkllm import ChatSparkLLM
 from langchain_community.chat_models.tongyi import ChatTongyi
@@ -98,5 +99,6 @@
     "GPTRouter",
     "ChatYuan2",
     "ChatZhipuAI",
+    "ChatPerplexity",
     "ChatKinetica",
 ]