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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "1ca7b759",
"metadata": {},
"outputs": [],
"source": [
"!pip install -q git+https://github.com/srush/MiniChain\n",
"!git clone https://github.com/srush/MiniChain; cp -fr MiniChain/examples/* . "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cc3f2a69",
"metadata": {
"lines_to_next_cell": 0,
"tags": [
"hide_inp"
]
},
"outputs": [],
"source": [
"desc = \"\"\"\n",
"### Chat\n",
"\n",
"A chat-like example for multi-turn chat with state. [](https://colab.research.google.com/github/srush/MiniChain/blob/master/examples/chat.ipynb)\n",
"\n",
"(Adapted from [LangChain](https://langchain.readthedocs.io/en/latest/modules/memory/examples/chatgpt_clone.html)'s version of this [blog post](https://www.engraved.blog/building-a-virtual-machine-inside/).)\n",
"\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1ca0a1eb",
"metadata": {
"lines_to_next_cell": 2
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "f4ac1417",
"metadata": {},
"outputs": [],
"source": [
"from dataclasses import dataclass, replace\n",
"from typing import List, Tuple\n",
"from minichain import OpenAI, prompt, show"
]
},
{
"cell_type": "markdown",
"id": "56c8ab3d",
"metadata": {},
"source": [
"Generic stateful Memory"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7c3ffeaa",
"metadata": {
"lines_to_next_cell": 1
},
"outputs": [],
"source": [
"MEMORY = 2"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c309a94f",
"metadata": {
"lines_to_next_cell": 1
},
"outputs": [],
"source": [
"@dataclass\n",
"class State:\n",
" memory: List[Tuple[str, str]]\n",
" human_input: str = \"\"\n",
"\n",
" def push(self, response: str) -> \"State\":\n",
" memory = self.memory if len(self.memory) < MEMORY else self.memory[1:]\n",
" return State(memory + [(self.human_input, response)])"
]
},
{
"cell_type": "markdown",
"id": "4c9a82f1",
"metadata": {},
"source": [
"Chat prompt with memory"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "279179dd",
"metadata": {},
"outputs": [],
"source": [
"@prompt(OpenAI(), template_file=\"chat.pmpt.tpl\")\n",
"def chat_prompt(model, state: State) -> State:\n",
" out = model(state)\n",
" result = out.split(\"Assistant:\")[-1]\n",
" return state.push(result)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2d94b22d",
"metadata": {},
"outputs": [],
"source": [
"examples = [\n",
" \"ls ~\",\n",
" \"cd ~\",\n",
" \"{Please make a file jokes.txt inside and put some jokes inside}\",\n",
" \"\"\"echo -e \"x=lambda y:y*5+3;print('Result:' + str(x(6)))\" > run.py && python3 run.py\"\"\",\n",
" \"\"\"echo -e \"print(list(filter(lambda x: all(x%d for d in range(2,x)),range(2,3**10)))[:10])\" > run.py && python3 run.py\"\"\",\n",
" \"\"\"echo -e \"echo 'Hello from Docker\" > entrypoint.sh && echo -e \"FROM ubuntu:20.04\\nCOPY entrypoint.sh entrypoint.sh\\nENTRYPOINT [\\\"/bin/sh\\\",\\\"entrypoint.sh\\\"]\">Dockerfile && docker build . -t my_docker_image && docker run -t my_docker_image\"\"\",\n",
" \"nvidia-smi\"\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d77406cf",
"metadata": {},
"outputs": [],
"source": [
"gradio = show(lambda command, state: chat_prompt(replace(state, human_input=command)),\n",
" initial_state=State([]),\n",
" subprompts=[chat_prompt],\n",
" examples=examples,\n",
" out_type=\"json\",\n",
" description=desc,\n",
")\n",
"if __name__ == \"__main__\":\n",
" gradio.launch()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bd255c7b",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"jupytext": {
"cell_metadata_filter": "tags,-all",
"main_language": "python",
"notebook_metadata_filter": "-all"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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