mirror of
https://github.com/hwchase17/langchain
synced 2024-10-29 17:07:25 +00:00
197 lines
4.6 KiB
Plaintext
197 lines
4.6 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Motörhead Memory\n",
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"[Motörhead](https://github.com/getmetal/motorhead) is a memory server implemented in Rust. It automatically handles incremental summarization in the background and allows for stateless applications.\n",
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"\n",
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"## Setup\n",
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"\n",
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"See instructions at [Motörhead](https://github.com/getmetal/motorhead) for running the server locally.\n",
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"\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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.memory.motorhead_memory import MotorheadMemory\n",
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"from langchain import OpenAI, LLMChain, PromptTemplate\n",
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"\n",
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"template = \"\"\"You are a chatbot having a conversation with a human.\n",
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"\n",
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"{chat_history}\n",
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"Human: {human_input}\n",
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"AI:\"\"\"\n",
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"\n",
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"prompt = PromptTemplate(\n",
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" input_variables=[\"chat_history\", \"human_input\"], \n",
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" template=template\n",
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")\n",
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"memory = MotorheadMemory(\n",
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" session_id=\"testing-1\",\n",
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" url=\"http://localhost:8080\",\n",
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" memory_key=\"chat_history\"\n",
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")\n",
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"\n",
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"await memory.init(); # loads previous state from Motörhead 🤘\n",
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"\n",
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"llm_chain = LLMChain(\n",
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" llm=OpenAI(), \n",
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" prompt=prompt, \n",
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" verbose=True, \n",
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" memory=memory,\n",
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")\n",
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"\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": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mYou are a chatbot having a conversation with a human.\n",
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"\n",
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"\n",
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"Human: hi im bob\n",
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"AI:\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"' Hi Bob, nice to meet you! How are you doing today?'"
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]
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},
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"execution_count": 2,
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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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"llm_chain.run(\"hi im bob\")"
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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": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mYou are a chatbot having a conversation with a human.\n",
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"\n",
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"Human: hi im bob\n",
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"AI: Hi Bob, nice to meet you! How are you doing today?\n",
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"Human: whats my name?\n",
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"AI:\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"' You said your name is Bob. Is that correct?'"
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]
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},
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"execution_count": 3,
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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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"llm_chain.run(\"whats my name?\")"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mYou are a chatbot having a conversation with a human.\n",
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"\n",
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"Human: hi im bob\n",
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"AI: Hi Bob, nice to meet you! How are you doing today?\n",
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"Human: whats my name?\n",
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"AI: You said your name is Bob. Is that correct?\n",
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"Human: whats for dinner?\n",
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"AI:\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"\" I'm sorry, I'm not sure what you're asking. Could you please rephrase your question?\""
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]
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},
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"execution_count": 4,
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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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"llm_chain.run(\"whats for dinner?\")"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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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": "3.9.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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