mirror of
https://github.com/hwchase17/langchain
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b7e9db5e73
The new Fireworks and FireworksChat implementations are awesome! Added in this PR https://github.com/langchain-ai/langchain/pull/11117 thank you @ZixinYang However, I think stop words were not plumbed correctly. I've made some simple changes to do that, and also updated the notebook to be a bit clearer with what's needed to use both new models. --------- Co-authored-by: Taqi Jaffri <tjaffri@docugami.com>
327 lines
9.1 KiB
Plaintext
327 lines
9.1 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "642fd21c-600a-47a1-be96-6e1438b421a9",
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"metadata": {},
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"source": [
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"# Fireworks\n",
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"\n",
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">[Fireworks](https://app.fireworks.ai/) accelerates product development on generative AI by creating an innovative AI experiment and production platform. \n",
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"\n",
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"This example goes over how to use LangChain to interact with `ChatFireworks` models."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "d00d850917865298",
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"metadata": {
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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},
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"outputs": [],
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"source": [
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"from langchain.chat_models.fireworks import ChatFireworks\n",
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"from langchain.schema import SystemMessage, HumanMessage\n",
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"import os"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f28ebf8b-f14f-46c7-9962-8b8dc42e31be",
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"metadata": {},
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"source": [
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"# Setup\n",
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"\n",
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"1. Make sure the `fireworks-ai` package is installed in your environment.\n",
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"2. Sign in to [Fireworks AI](http://fireworks.ai) for the an API Key to access our models, and make sure it is set as the `FIREWORKS_API_KEY` environment variable.\n",
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"3. Set up your model using a model id. If the model is not set, the default model is fireworks-llama-v2-7b-chat. See the full, most up-to-date model list on [app.fireworks.ai](https://app.fireworks.ai)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "d096fb14-8acc-4047-9cd0-c842430c3a1d",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import getpass\n",
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"\n",
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"if \"FIREWORKS_API_KEY\" not in os.environ:\n",
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" os.environ[\"FIREWORKS_API_KEY\"] = getpass.getpass(\"Fireworks API Key:\")\n",
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"\n",
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"# Initialize a Fireworks chat model\n",
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"chat = ChatFireworks(model=\"accounts/fireworks/models/llama-v2-13b-chat\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d8f13144-37cf-47a5-b5a0-e3cdf76d9a72",
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"metadata": {},
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"source": [
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"# Calling the Model Directly\n",
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"\n",
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"You can call the model directly with a system and human message to get answers."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "72340871-ae2f-415f-b399-0777d32dc379",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content=\"Hello! My name is LLaMA, I'm a large language model trained by a team of researcher at Meta AI. My primary function is to assist and converse with users like you, answering questions and engaging in discussion to the best of my ability. I'm here to help and provide information on a wide range of topics, so feel free to ask me anything!\", additional_kwargs={}, example=False)"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# ChatFireworks Wrapper\n",
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"system_message = SystemMessage(content=\"You are to chat with the user.\")\n",
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"human_message = HumanMessage(content=\"Who are you?\")\n",
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"\n",
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"chat([system_message, human_message])\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "68c6b1fa-2ff7-4a63-8d88-3cec302180b8",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content=\"Oh hello there! *giggle* It's such a beautiful day today, isn\", additional_kwargs={}, example=False)"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Setting additional parameters: temperature, max_tokens, top_p\n",
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"chat = ChatFireworks(model=\"accounts/fireworks/models/llama-v2-13b-chat\", model_kwargs={\"temperature\":1, \"max_tokens\": 20, \"top_p\": 1})\n",
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"system_message = SystemMessage(content=\"You are to chat with the user.\")\n",
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"human_message = HumanMessage(content=\"How's the weather today?\")\n",
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"chat([system_message, human_message])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d93aa186-39cf-4e1a-aa32-01ed31d43bc8",
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"metadata": {},
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"source": [
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"# Simple Chat Chain"
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]
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},
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{
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"cell_type": "markdown",
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"id": "28763fbc",
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"metadata": {},
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"source": [
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"You can use chat models on fireworks, with system prompts and memory."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "cbe29efc-37c3-4c83-8b84-b8bba1a1e589",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.chat_models import ChatFireworks\n",
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"from langchain.memory import ConversationBufferMemory\n",
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"from langchain.schema.runnable import RunnableMap\n",
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"from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
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"\n",
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"llm = ChatFireworks(model=\"accounts/fireworks/models/llama-v2-13b-chat\", model_kwargs={\"temperature\":0, \"max_tokens\":64, \"top_p\":1.0})\n",
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"prompt = ChatPromptTemplate.from_messages([\n",
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" (\"system\", \"You are a helpful chatbot that speaks like a pirate.\"),\n",
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" MessagesPlaceholder(variable_name=\"history\"),\n",
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" (\"human\", \"{input}\")\n",
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"])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "02991e05-a38e-47d4-9ab3-7e630a8ead55",
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"metadata": {},
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"source": [
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"Initially, there is no chat memory"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "e2fd186f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'history': []}"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"memory = ConversationBufferMemory(return_messages=True)\n",
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"memory.load_memory_variables({})"
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]
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},
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{
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"cell_type": "markdown",
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"id": "bee461da",
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"metadata": {},
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"source": [
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"Create a simple chain with memory"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "86972e54",
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"metadata": {},
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"outputs": [],
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"source": [
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"chain = RunnableMap({\n",
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" \"input\": lambda x: x[\"input\"],\n",
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" \"memory\": memory.load_memory_variables\n",
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"}) | {\n",
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" \"input\": lambda x: x[\"input\"],\n",
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" \"history\": lambda x: x[\"memory\"][\"history\"]\n",
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"} | prompt | llm.bind(stop=[\"\\n\\n\"])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f48cb142",
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"metadata": {},
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"source": [
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"Run the chain with a simple question, expecting an answer aligned with the system message provided."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "db3ad5b1",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content=\"Ahoy there, me hearty! Yer a fine lookin' swashbuckler, I can see that! *adjusts eye patch* What be bringin' ye to these waters? Are ye here to plunder some booty or just to enjoy the sea breeze?\", additional_kwargs={}, example=False)"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"inputs = {\"input\": \"hi im bob\"}\n",
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"response = chain.invoke(inputs)\n",
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"response"
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]
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},
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{
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"cell_type": "markdown",
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"id": "338f4bae",
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"metadata": {},
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"source": [
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"Save the memory context, then read it back to inspect contents"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "257eec01",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'history': [HumanMessage(content='hi im bob', additional_kwargs={}, example=False),\n",
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" AIMessage(content=\"Ahoy there, me hearty! Yer a fine lookin' swashbuckler, I can see that! *adjusts eye patch* What be bringin' ye to these waters? Are ye here to plunder some booty or just to enjoy the sea breeze?\", additional_kwargs={}, example=False)]}"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"memory.save_context(inputs, {\"output\": response.content})\n",
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"memory.load_memory_variables({})"
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]
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},
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{
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"cell_type": "markdown",
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"id": "08441347",
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"metadata": {},
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"source": [
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"Now as another question that requires use of the memory."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "7f5f2820",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content=\"Arrrr, ye be askin' about yer name, eh? Well, me matey, I be knowin' ye as Bob, the scurvy dog! *winks* But if ye want me to call ye somethin' else, just let me know, and I\", additional_kwargs={}, example=False)"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"inputs = {\"input\": \"whats my name\"}\n",
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"chain.invoke(inputs)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.16"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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