langchain/docs/extras/integrations/memory/motorhead_memory.ipynb
2023-07-23 23:23:16 -07:00

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"# Motörhead Memory\n",
"[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",
"\n",
"## Setup\n",
"\n",
"See instructions at [Motörhead](https://github.com/getmetal/motorhead) for running the server locally.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from langchain.memory.motorhead_memory import MotorheadMemory\n",
"from langchain import OpenAI, LLMChain, PromptTemplate\n",
"\n",
"template = \"\"\"You are a chatbot having a conversation with a human.\n",
"\n",
"{chat_history}\n",
"Human: {human_input}\n",
"AI:\"\"\"\n",
"\n",
"prompt = PromptTemplate(\n",
" input_variables=[\"chat_history\", \"human_input\"], template=template\n",
")\n",
"memory = MotorheadMemory(\n",
" session_id=\"testing-1\", url=\"http://localhost:8080\", memory_key=\"chat_history\"\n",
")\n",
"\n",
"await memory.init()\n",
"# loads previous state from Motörhead 🤘\n",
"\n",
"llm_chain = LLMChain(\n",
" llm=OpenAI(),\n",
" prompt=prompt,\n",
" verbose=True,\n",
" memory=memory,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mYou are a chatbot having a conversation with a human.\n",
"\n",
"\n",
"Human: hi im bob\n",
"AI:\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"' Hi Bob, nice to meet you! How are you doing today?'"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"llm_chain.run(\"hi im bob\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mYou are a chatbot having a conversation with a human.\n",
"\n",
"Human: hi im bob\n",
"AI: Hi Bob, nice to meet you! How are you doing today?\n",
"Human: whats my name?\n",
"AI:\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"' You said your name is Bob. Is that correct?'"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"llm_chain.run(\"whats my name?\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mYou are a chatbot having a conversation with a human.\n",
"\n",
"Human: hi im bob\n",
"AI: Hi Bob, nice to meet you! How are you doing today?\n",
"Human: whats my name?\n",
"AI: You said your name is Bob. Is that correct?\n",
"Human: whats for dinner?\n",
"AI:\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"\" I'm sorry, I'm not sure what you're asking. Could you please rephrase your question?\""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"llm_chain.run(\"whats for dinner?\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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"display_name": "Python 3 (ipykernel)",
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"language_info": {
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