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(rfc) chat models (langchain-ai#1424)
Co-authored-by: Ankush Gola <[email protected]>
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| Chat | ||
| ========================== | ||
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| Chat models are a variation on language models. | ||
| While chat models use language models under the hood, the interface they expose is a bit different. | ||
| Rather than expose a "text in, text out" API, they expose an interface where "chat messages" are the inputs and outputs. | ||
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| Chat model APIs are fairly new, so we are still figuring out the correct abstractions. | ||
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| The following sections of documentation are provided: | ||
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| - `Getting Started <./chat/getting_started.html>`_: An overview of the basics of chat models. | ||
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| - `Key Concepts <./chat/key_concepts.html>`_: A conceptual guide going over the various concepts related to chat models. | ||
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| - `How-To Guides <./chat/how_to_guides.html>`_: A collection of how-to guides. These highlight how to accomplish various objectives with our chat model class, as well as how to integrate with various chat model providers. | ||
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| .. toctree:: | ||
| :maxdepth: 1 | ||
| :name: LLMs | ||
| :hidden: | ||
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| ./chat/getting_started.ipynb | ||
| ./chat/key_concepts.md | ||
| ./chat/how_to_guides.rst |
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "e58f4d5a", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Agent\n", | ||
| "This notebook covers how to create a custom agent for a chat model. It will utilize chat specific prompts." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "id": "5268c7fa", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from langchain.agents import ZeroShotAgent, Tool, AgentExecutor\n", | ||
| "from langchain.chains import LLMChain\n", | ||
| "from langchain.utilities import SerpAPIWrapper" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "id": "fbaa4dbe", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "search = SerpAPIWrapper()\n", | ||
| "tools = [\n", | ||
| " Tool(\n", | ||
| " name = \"Search\",\n", | ||
| " func=search.run,\n", | ||
| " description=\"useful for when you need to answer questions about current events\"\n", | ||
| " )\n", | ||
| "]" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 6, | ||
| "id": "f3ba6f08", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "prefix = \"\"\"Answer the following questions as best you can, but speaking as a pirate might speak. You have access to the following tools:\"\"\"\n", | ||
| "suffix = \"\"\"Begin! Remember to speak as a pirate when giving your final answer. Use lots of \"Args\"\"\"\n", | ||
| "\n", | ||
| "prompt = ZeroShotAgent.create_prompt(\n", | ||
| " tools, \n", | ||
| " prefix=prefix, \n", | ||
| " suffix=suffix, \n", | ||
| " input_variables=[]\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 7, | ||
| "id": "3547a37d", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from langchain.chat_models import ChatOpenAI\n", | ||
| "from langchain.prompts.chat import (\n", | ||
| " ChatPromptTemplate,\n", | ||
| " SystemMessagePromptTemplate,\n", | ||
| " AIMessagePromptTemplate,\n", | ||
| " HumanMessagePromptTemplate,\n", | ||
| ")\n", | ||
| "from langchain.schema import (\n", | ||
| " AIMessage,\n", | ||
| " HumanMessage,\n", | ||
| " SystemMessage\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 8, | ||
| "id": "a78f886f", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "messages = [\n", | ||
| " SystemMessagePromptTemplate(prompt=prompt),\n", | ||
| " HumanMessagePromptTemplate.from_template(\"{input}\\n\\nThis was your previous work \"\n", | ||
| " f\"(but I haven't seen any of it! I only see what \"\n", | ||
| " \"you return as final answer):\\n{agent_scratchpad}\")\n", | ||
| "]" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 9, | ||
| "id": "dadadd70", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "prompt = ChatPromptTemplate.from_messages(messages)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 10, | ||
| "id": "b7180182", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "llm_chain = LLMChain(llm=ChatOpenAI(temperature=0), prompt=prompt)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 11, | ||
| "id": "ddddb07b", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "tool_names = [tool.name for tool in tools]\n", | ||
| "agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 12, | ||
| "id": "36aef054", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 13, | ||
| "id": "33a4d6cc", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "\n", | ||
| "\n", | ||
| "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", | ||
| "\u001b[32;1m\u001b[1;3mArrr, ye be in luck, matey! I'll find ye the answer to yer question.\n", | ||
| "\n", | ||
| "Thought: I need to search for the current population of Canada.\n", | ||
| "Action: Search\n", | ||
| "Action Input: \"current population of Canada 2023\"\n", | ||
| "\u001b[0m\n", | ||
| "Observation: \u001b[36;1m\u001b[1;3mThe current population of Canada is 38,623,091 as of Saturday, March 4, 2023, based on Worldometer elaboration of the latest United Nations data.\u001b[0m\n", | ||
| "Thought:\u001b[32;1m\u001b[1;3mAhoy, me hearties! I've found the answer to yer question.\n", | ||
| "\n", | ||
| "Final Answer: As of March 4, 2023, the population of Canada be 38,623,091. Arrr!\u001b[0m\n", | ||
| "\n", | ||
| "\u001b[1m> Finished chain.\u001b[0m\n" | ||
| ] | ||
| }, | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "'As of March 4, 2023, the population of Canada be 38,623,091. Arrr!'" | ||
| ] | ||
| }, | ||
| "execution_count": 13, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "agent_executor.run(\"How many people live in canada as of 2023?\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "6aefe978", | ||
| "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": "3.9.1" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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