justfile

.ipynb_checkpoints/openaichat-checkpoint.ipynb

@@ -0,0 +1,172 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e49f1e0d",
+   "metadata": {},
+   "source": [
+    "# OpenAIChat\n",
+    "\n",
+    "OpenAI also has a [chat model](https://platform.openai.com/docs/guides/chat) you can use. The interface is very similar to the normal OpenAI model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "522686de",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.llms import OpenAIChat\n",
+    "from langchain import PromptTemplate, LLMChain"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "62e0dbc3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "llm = OpenAIChat(temperature=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "fbb043e6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "template = \"\"\"Question: {question}\"\"\"\n",
+    "\n",
+    "prompt = PromptTemplate(template=template, input_variables=[\"question\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "3f945b76",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "llm_chain = LLMChain(prompt=prompt, llm=llm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "25260808",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\n\\nAs an AI language model, I cannot have a worst or do anything. However, according to the second law of thermodynamics, entropy can never be reversed in a closed system. Entropy always increases over time, leading to a state of maximum disorder or randomness. While it is possible to decrease entropy in a localized system, the overall entropy of the universe will continue to increase.'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "question = \"Can entropy be reversed?\"\n",
+    "\n",
+    "llm_chain.run(question)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "75a05b79",
+   "metadata": {},
+   "source": [
+    "## Prefix Messages\n",
+    "\n",
+    "OpenAI Chat also supports the idea of [prefix messages](https://platform.openai.com/docs/guides/chat/chat-vs-completions), eg messages that would appear before the user input. These can be used as system messages to give more context/purpose the LLM."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "c27a1501",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "prefix_messages = [{\"role\": \"system\", \"content\": \"You are a helpful assistant that is very good at problem solving who thinks step by step.\"}]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "e46a914e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "llm = OpenAIChat(temperature=0, prefix_messages=prefix_messages)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "d683d9f2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "llm_chain = LLMChain(prompt=prompt, llm=llm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "6f5b8e78",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Step 1: Justin Bieber was born on March 1, 1994.\\nStep 2: The Super Bowl is played in February of each year.\\nStep 3: Therefore, the Super Bowl that was played in the year Justin Bieber was born was Super Bowl XXVIII, which was played on January 30, 1994.\\nStep 4: The Dallas Cowboys won Super Bowl XXVIII by defeating the Buffalo Bills with a score of 30-13.\\nStep 5: Therefore, the Dallas Cowboys were the NFL team that won the Super Bowl in the year Justin Bieber was born.'"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
+    "\n",
+    "llm_chain.run(question)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "44c0330d",
+   "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": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

README.md

@@ -0,0 +1,14 @@
+# Getting started
+## Using `just`
+`just shell`
+## Manually
+0. Clone this repo
+1. Install [nix](https://nixos.org/download.html#nix-install-macos)
+2. Run `poetry update`
+3. Run `poetry shell` inside `agent/agent`
+4. ??? (e.g. `python <...>`)
+5. PROFIT!11!!!
+## Appendix
+### Reproducibility
+`nix` and `poetry` allow [packaging for serverless execution](https://github.com/bananaml/serverless-template) with reliable system, package, and other application dependencies like Secrets correctly derived for individual `agent` runtime environment.
+

agent/agent.py

@@ -19,13 +19,13 @@
 
 
 
-documents = PagedPDFSplitter("/Users/barton/Lab/poet/agent/vdf.pdf").load_data()
+# documents = PagedPDFSplitter("/Users/barton/Lab/poet/agent/vdf.pdf").load_data()
 
-index = GPTSimpleVectorIndex(documents)
-index.save_to_disk('index.json')
+# index = GPTSimpleVectorIndex(documents)
+# index.save_to_disk('index.json') # TODO: use Zulip UUID here!
 
 
-pages = loader.load_and_split()
+# pages = loader.load_and_split()
 
 
 
@@ -42,11 +42,11 @@
 llm = OpenAI(temperature=0.42, model="text-davinci-003")
 memory = ConversationSummaryMemory(memory_key="chat_history", llm=llm)
 
-# notagent = initialize_agent(tools,
-#     llm=llm,
-#     agent="conversational-react-description",
-#     verbose=True,
-#     memory=memory)
+notagent = initialize_agent(tools,
+    llm=llm,
+    agent="conversational-react-description",
+    verbose=True,
+    memory=memory)
 
 
 

justfile

@@ -0,0 +1,12 @@
+#!/usr/bin/env -S just --justfile
+
+update:
+    poetry update
+
+nix:
+    nix-shell
+
+shell: nix update
+
+gmi:
+    echo "only GMI in retrospect!"