Add api method to get LoRA models with prompt
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@ -2,9 +2,8 @@ import glob
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import os
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import re
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import torch
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from typing import Union, List, Optional
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from fastapi import FastAPI
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import gradio as gr
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from typing import Union
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import scripts.api as api
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from modules import shared, devices, sd_models, errors, scripts
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@ -445,12 +444,6 @@ def infotext_pasted(infotext, params):
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if added:
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params["Prompt"] += "\n" + "".join(added)
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def api(_: gr.Blocks, app: FastAPI):
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@app.get("/sdapi/v1/loras")
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async def getloras():
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return [{"name": name, "path": available_loras[name].filename, "prompt": ""} for name in available_loras]
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available_loras = {}
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available_lora_aliases = {}
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loaded_loras = []
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@ -458,6 +451,6 @@ loaded_loras = []
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list_available_loras()
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try:
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import modules.script_callbacks as script_callbacks
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script_callbacks.on_app_started(api)
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script_callbacks.on_app_started(api.api)
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except:
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pass
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31
extensions-builtin/Lora/scripts/api.py
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31
extensions-builtin/Lora/scripts/api.py
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@ -0,0 +1,31 @@
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from fastapi import FastAPI
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import gradio as gr
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import json
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import os
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import lora
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def get_lora_prompts(path):
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directory, filename = os.path.split(path)
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name_without_ext = os.path.splitext(filename)[0]
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new_filename = name_without_ext + '.civitai.info'
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try:
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new_path = os.path.join(directory, new_filename)
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if os.path.exists(new_path):
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with open(new_path, 'r') as f:
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data = json.load(f)
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trained_words = data.get('trainedWords', [])
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if len(trained_words) > 0:
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result = ','.join(trained_words)
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return result
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else:
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return ''
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else:
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return ''
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except Exception as e:
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return ''
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def api(_: gr.Blocks, app: FastAPI):
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@app.get("/sdapi/v1/loras")
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async def get_loras():
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return [{"name": name, "path": lora.available_loras[name].filename, "prompt": get_lora_prompts(lora.available_loras[name].filename)} for name in lora.available_loras]
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