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import torch | |
from transformers import StoppingCriteria, StoppingCriteriaList | |
import copy | |
import json | |
import global_vars | |
from chats import pre, post | |
from pingpong import PingPong | |
from gens.batch_gen import get_output_batch | |
from chats.utils import build_prompts, text_stream, internet_search | |
class StopOnTokens(StoppingCriteria): | |
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs) -> bool: | |
stop_ids = [11] | |
for stop_id in stop_ids: | |
if input_ids[0][-1] == stop_id: | |
return True | |
return False | |
def chat_stream( | |
idx, local_data, user_message, state, | |
global_context, ctx_num_lconv, ctx_sum_prompt, | |
res_temp, res_topp, res_topk, res_rpen, res_mnts, res_beams, res_cache, res_sample, res_eosid, res_padid, | |
sum_temp, sum_topp, sum_topk, sum_rpen, sum_mnts, sum_beams, sum_cache, sum_sample, sum_eosid, sum_padid, | |
internet_option, serper_api_key | |
): | |
res = [ | |
state["ppmanager_type"].from_json(json.dumps(ppm)) | |
for ppm in local_data | |
] | |
ppm = res[idx] | |
# add_ping returns a prompt structured in Alpaca form | |
ppm.add_pingpong( | |
PingPong(user_message, "") | |
) | |
prompt = build_prompts(ppm, global_context, ctx_num_lconv) | |
####### | |
if internet_option: | |
search_prompt = None | |
for tmp_prompt, uis in internet_search(ppm, serper_api_key, global_context, ctx_num_lconv): | |
search_prompt = tmp_prompt | |
yield "", uis, prompt, str(res) | |
# prepare text generating streamer & start generating | |
gen_kwargs, streamer = pre.build( | |
search_prompt if internet_option else prompt, | |
res_temp, res_topp, res_topk, res_rpen, res_mnts, | |
res_beams, res_cache, res_sample, res_eosid, res_padid, | |
return_token_type_ids=False | |
) | |
pre.start_gen(gen_kwargs) | |
# handling stream | |
for ppmanager, uis in text_stream(ppm, streamer): | |
yield "", uis, prompt, str(res) | |
ppm = post.strip_pong(ppm) | |
yield "", ppm.build_uis(), prompt, str(res) |