LLM-As-Chatbot / chats /central.py
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from chats import stablelm
from chats import alpaca
from chats import koalpaca
from chats import flan_alpaca
from chats import os_stablelm
from chats import vicuna
from chats import starchat
from chats import redpajama
from chats import mpt
from chats import alpacoom
from chats import baize
from chats import guanaco
def chat_stream(
idx, local_data, user_message, state, model_num,
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,
):
model_type = state["model_type"]
if model_type == "stablelm":
cs = stablelm.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "baize":
cs = baize.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "alpaca":
cs = alpaca.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "alpaca-gpt4":
cs = alpaca.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "alpacoom":
cs = alpacoom.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "llama-deus":
cs = alpaca.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "camel":
cs = alpaca.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "koalpaca-polyglot":
cs = koalpaca.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "flan-alpaca":
cs = flan_alpaca.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "os-stablelm":
cs = os_stablelm.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "t5-vicuna":
cs = vicuna.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "stable-vicuna":
cs = vicuna.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "vicuna":
cs = vicuna.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "evolinstruct-vicuna":
cs = vicuna.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "starchat":
cs = starchat.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "mpt":
cs = mpt.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "redpajama":
cs = redpajama.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "guanaco":
cs = guanaco.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
elif model_type == "nous-hermes":
cs = alpaca.chat_stream(
idx, local_data, user_message, state, model_num,
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,
)
for idx, x in enumerate(cs):
yield x