import asyncio import random import os import subprocess import datetime import sys import requests import subprocess from fastapi import FastAPI from typing import Union app = FastAPI() subprocess.run(["ollama", "serve"]) #make sure that our ollama server is started from langchain.callbacks.manager import CallbackManager from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler from langchain_community.llms import Ollama # replace model with the downloaded model you want to use llm = Ollama( model="sparksammy/samai", callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]), ) completeContext = "" # Define URLs for requirements.txt and main.py #REQS_URL = 'https://raw.githubusercontent.com/The-AI-Brain/ai-brain/main/requirements.txt' #MAIN_URL = 'https://raw.githubusercontent.com/The-AI-Brain/ai-brain/main/main.py' # Define paths for local requirements.txt and main.py files REQS_PATH = 'requirements.txt' MAIN_PATH = 'main.py' List = {} # Check for updates def check_updates(): # Download remote requirements.txt file remote_reqs = requests.get(REQS_URL).text # Compare local and remote requirements.txt files with open(REQS_PATH, 'r') as f: local_reqs = f.read() if local_reqs != remote_reqs: # Install updated requirements subprocess.run(['pip', 'install', '-r', REQS_PATH]) # Download updated main.py file remote_main = requests.get(MAIN_URL).text # Write updated main.py file with open(MAIN_PATH, 'w') as f: f.write(remote_main) # Restart the script os.execv(sys.argv[0], sys.argv) emotions = [ "happy", "sad", "angry", "surprised", "disgusted", "fearful", "excited", "nostalgic", "hopeful", "anxious", "relaxed", "curious", "confused", "amused", "bored", "ecstatic", "exhausted", "grateful", "guilty", "embarrassed", "envious", "proud", "ashamed", "content", "depressed", "fascinated", "frustrated", "inspired", "irritated", "jealous", "lonely", "melancholic", "optimistic", "overwhelmed", "peaceful", "playful", "reflective", "remorseful", "restless", "satisfied", "sympathetic", "tense", "terrified", "triumphant", "uncomfortable", "vulnerable", "wistful", "yearning", "zealous" ] # Array of human actions actions = [ "walked the dog", "cooked dinner", "read a book", "went swimming", "played soccer", "listened to music", "watched a movie", "painted a picture", "wrote a story", "rode a bike", "danced in the rain", "visited a museum", "went on a road trip", "went to a concert", "built a sandcastle", "went to the beach", "played video games", "climbed a mountain", "played with a pet", "went for a run", "did yoga", "went camping", "visited a new city", "went to a party", "took a nap", "had a picnic", "played a musical instrument", "tried a new food", "went on a hike", "took a bath", "visited a friend", "went to a theme park", "went to a zoo", "went to a sporting event", "went to a play", "went to a comedy show", "went to a ballet", "went to a musical", "went to a poetry reading", "went to a book club meeting", "went to a cooking class", "went to a painting class", "went to a wine tasting", "went to a beer festival", "went to a farmers' market", "went to a flea market", "went shopping", "went to a garage sale", "went to a thrift store", "volunteered at a charity", "went to a political rally", "went to a religious service", "attended a wedding", "attended a funeral", "graduated from school", "started a new job", "retired from a job", "got married", "got divorced", "had a baby", "raised a child", "adopted a pet", "moved to a new city", "bought a house", "rented an apartment", "remodeled a home", "gardened", "landscaped a yard", "went on a cruise", "went on a safari", "went on a skiing trip", "went on a snowboarding trip", "went on a fishing trip", "went on a hunting trip", "went on a scuba diving trip", "went on a surfing trip", "went on a kayaking trip", "went on a canoeing trip", "went on a rafting trip", "went on a hot air balloon ride", "went on a helicopter ride", "went on a plane ride", "went on a train ride", "went on a road trip", "went skydiving", "went bungee jumping", "went zip lining", "went rock climbing", "went to a spa", "got a massage", "got a facial", "got a manicure", "got a pedicure", "went to a chiropractor", "went to a physical therapist", "went to a dentist", "went to a doctor", "got surgery", "recovered from an illness", "overcame an addiction", "learned a new skill", "learned a new language", "took a class", "ate", "played the piano", "went for a walk" ] # Array of places for the actions places = [ "in the park", "at home", "in the library", "on the beach", "in the movie theater", "at the doctor's office", "at school", "at the spa", "at the airport", "at the gym", "in a cafe", "in a museum", "in a grocery store", "in a restaurant", "at a concert", "at a stadium", "in a hospital", "in a church", "in a mosque", "in a temple", "in a theater", "in a nightclub", "in a casino", "at a zoo", "at a theme park", "at a water park", "in a shopping mall", "in a department store", "at a gas station", "in a parking lot", "in a hotel", "in a motel", "in a hostel", "in a campground", "in a forest", "on a mountain", "in a desert", "in a valley", "by a river", "by a lake", "at sea", "in the ocean", "in a cave", "at a train station", "at a bus station", "at a subway station", "at a ferry terminal", "at a harbor", "in a space station", "in a laboratory" ] # Asynchronous function to print actions def createContext(): action = random.choice(actions) place = random.choice(places) completeContext = f"you just did \"{action}\" and did it \"{place}\"" return complete @app.get("/context") async def get_emote(): return await createContext() @app.get("/chatin/{chatText}") async def get_chatin(chatText: str): return await main(chatText) # Main function to run the program def main(chatin): #check_updates() chatin = "Guest:" + chatin # Get response from ollama message = llm(f"(Additional context for reply: {completeContext}), reply to this: {chatin}") # Print ollama response and what it said print(f"You: {chatin}") print(f"{name}: {message}") return f"You: {chatin}\n${name}: ${message}" # Run the cli function def cli(): while True: toChat = input("brain@localhost:~$ ") main(f"{toChat}") cli()