del

main.py

@@ -1,53 +0,0 @@
-from fastapi import FastAPI, Request
-from fastapi.middleware.cors import CORSMiddleware
-
-api = FastAPI()
-
-api.add_middleware(
-        CORSMiddleware,
-        allow_origins=['*'],
-        allow_credentials=True,
-        allow_methods=['*'],
-        allow_headers=['*']
-        )
-
-from transformers.models.auto.tokenization_auto import AutoTokenizer
-from transformers.models.auto.modeling_auto import AutoModelForCausalLM
-
-tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
-model = AutoModelForCausalLM.from_pretrained("../southpark/output-medium")
-
-def cartman_respond(packet):
-    input_ids = tokenizer(str(packet.get('message')) + tokenizer.eos_token, return_tensors="pt").input_ids
-    outputs = model.generate(
-            input_ids,
-            pad_token_id=tokenizer.eos_token_id,
-            max_new_tokens = int(packet.get('max_new_tokens')),
-            num_beams = int(packet.get('num_beams')),
-            num_beam_groups = int(packet.get('num_beam_groups')),
-            no_repeat_ngram_size = int(packet.get('no_repeat_ngram_size')),
-            length_penalty = float(packet.get('length_penalty')),
-            diversity_penalty = float(packet.get('diversity_penalty')),
-            repetition_penalty = float(packet.get('repetition_penalty')),
-            early_stopping = bool(packet.get('early_stopping')),
-
-          # do_sample = True,
-          # top_k = 100,
-          # top_p = 0.7,
-          # temperature = 0.8,
-            )
-    return tokenizer.decode(outputs[:, input_ids.shape[-1]:][0], skip_special_tokens=True)
-
-@api.post('/chat/')
-async def getInformation(data : Request):
-    packet = await data.json()
-    print(packet)
-    message = str(packet.get('message'))
-    print(message)
-    response = cartman_respond(packet)
-    print(response)
-
-    return {
-        "Cartman" : response
-    }
-

run

@@ -1,3 +0,0 @@
-#!/bin/zsh
-
-uvicorn main:api --host 10.0.1.1 --reload