import os from googleapiclient.discovery import build from lang import G4F from fastapi import FastAPI, Request, Path from pydantic import BaseModel from fastapi.middleware.cors import CORSMiddleware from ImageCreator import generate_image_prodia app = FastAPI() app.add_middleware( # add the middleware CORSMiddleware, allow_credentials=True, # allow credentials allow_origins=["*"], # allow all origins allow_methods=["*"], # allow all methods allow_headers=["*"], # allow all headers ) google_api_key = os.environ["GOOGLE_API_KEY"] cse_id = os.environ["GOOGLE_CSE_ID"] def search_google(query): service = build("customsearch", "v1", developerKey=google_api_key) result = service.cse().list( q=query, cx=cse_id ).execute() return result['items'] @app.get("/") def hello(): return "Hello! My name is Linlada." def llm(prompt, model): llm = G4F(model=model) response = llm(prompt) return response def gpt_with_google_search(prompt, model): search_results = search_google(prompt) text = "" ref = "" ref_count = 1 for item in search_results: text += item['title'] + "\n" + item['snippet'] + "\n\n" ref += " [{}] {} ({})\n".format(ref_count, item['title'], item['link']) ref_count += 1 results = llm(prompt = f'Summarize: {text}', model = model) res = "{} \n\n{}".format(results, ref) return res class Linlada(BaseModel): prompt: str web_access: str = True model: str = os.environ['default_model'] @app.post('/linlada') def linlada(request: Linlada): prompt = request.prompt model = request.model web_access = request.web_access if web_access == "True": chat = gpt_with_google_search(prompt, model) else: chat = llm(prompt, model) return chat class User(BaseModel): prompt: str model: str = None sampler: str = None seed: int = None neg: str = None @app.post("/imagen") def generate_image(request: User): prompt = request.prompt model = request.model sampler = request.sampler seed = request.seed neg = request.neg response = generate_image_prodia(prompt, model, sampler, seed, neg) return {"image": response} details = { 1: {'Absolute Reality V1.6': 'absolutereality_V16.safetensors [37db0fc3]', 'Analog V1': 'analog-diffusion-1.0.ckpt [9ca13f02]', 'Anything V3': 'anythingv3_0-pruned.ckpt [2700c435]', 'Anything V4.5': 'anything-v4.5-pruned.ckpt [65745d25]', 'Anything V5': 'anythingV5_PrtRE.safetensors [893e49b9]', 'AbyssOrangeMix V3': 'AOM3A3_orangemixs.safetensors [9600da17]', 'Deliberate V2': 'deliberate_v2.safetensors [10ec4b29]', 'Dreamlike Diffusion V1': 'dreamlike-diffusion-1.0.safetensors [5c9fd6e0]', 'Dreamlike Diffusion V2': 'dreamlike-diffusion-2.0.safetensors [fdcf65e7]', 'Dreamshaper 6 baked vae': 'dreamshaper_6BakedVae.safetensors [114c8abb]', 'Dreamshaper 7': 'dreamshaper_7.safetensors [5cf5ae06]', 'Dreamshaper 8': 'dreamshaper_8.safetensors [9d40847d]', 'Eimis Anime Diffusion V1.0': 'EimisAnimeDiffusion_V1.ckpt [4f828a15]', "Elldreth's Vivid": 'elldreths-vivid-mix.safetensors [342d9d26]', 'Lyriel V1.6': 'lyriel_v16.safetensors [68fceea2]', 'MechaMix V1.0': 'mechamix_v10.safetensors [ee685731]', 'MeinaMix Meina V9': 'meinamix_meinaV9.safetensors [2ec66ab0]', 'MeinaMix Meina V11': 'meinamix_meinaV11.safetensors [b56ce717]', 'Openjourney V4': 'openjourney_V4.ckpt [ca2f377f]', 'Portrait+ V1': 'portraitplus_V1.0.safetensors [1400e684]', 'Realistic Vision V1.4': 'Realistic_Vision_V1.4-pruned-fp16.safetensors [8d21810b]', 'Realistic Vision V4.0': 'Realistic_Vision_V4.0.safetensors [29a7afaa]', 'Realistic Vision V5.0': 'Realistic_Vision_V5.0.safetensors [614d1063]', 'Redshift Diffusion V1.0': 'redshift_diffusion-V10.safetensors [1400e684]', 'ReV Animated V1.2.2': 'revAnimated_v122.safetensors [3f4fefd9]', 'SD V1.4': 'sdv1_4.ckpt [7460a6fa]', 'SD V1.5': 'v1-5-pruned-emaonly.ckpt [81761151]', "Shonin's Beautiful People V1.0": 'shoninsBeautiful_v10.safetensors [25d8c546]', "TheAlly's Mix II": 'theallys-mix-ii-churned.safetensors [5d9225a4]', 'Timeless V1': 'timeless-1.0.ckpt [7c4971d4]' }, 2: { 'Euler': 'Euler', 'Euler a': 'Euler a', 'Heun': 'Heun', 'DPM++ 2M Karras': 'DPM++ 2M Karras', 'DPM++ SDE Karras': 'DPM++ SDE Karras', 'DDIM': 'DDIM' } } @app.get("/imagen-details/{detail_id}") def image_detail(detail_id: int = Path(None, description="The ID of 1.model id and 2.sampler id", gt=0, lt=3)): return details[detail_id] class Test(BaseModel): prompt: str model: str = 'gpt-3.5-turbo' neg: str = True @app.post("/test") def test(request: Test): if neg == True: chat = "hello world" elif neg == "True": chat = "Hi there" else: chat = "Hi world" return chat