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import os
import json
import requests
import sseclient
from pingpong import PingPong
from pingpong.pingpong import PPManager
from pingpong.pingpong import PromptFmt
from pingpong.pingpong import UIFmt
from pingpong.gradio import GradioChatUIFmt
class LLaMA2ChatPromptFmt(PromptFmt):
@classmethod
def ctx(cls, context):
if context is None or context == "":
return ""
else:
return f"""<<SYS>>
{context}
<</SYS>>
"""
@classmethod
def prompt(cls, pingpong, truncate_size):
ping = pingpong.ping[:truncate_size]
pong = "" if pingpong.pong is None else pingpong.pong[:truncate_size]
return f"""[INST] {ping} [/INST] {pong}"""
class LLaMA2ChatPPManager(PPManager):
def build_prompts(self, from_idx: int=0, to_idx: int=-1, fmt: PromptFmt=LLaMA2ChatPromptFmt, truncate_size: int=None):
if to_idx == -1 or to_idx >= len(self.pingpongs):
to_idx = len(self.pingpongs)
results = fmt.ctx(self.ctx)
for idx, pingpong in enumerate(self.pingpongs[from_idx:to_idx]):
results += fmt.prompt(pingpong, truncate_size=truncate_size)
return results
class GradioLLaMA2ChatPPManager(LLaMA2ChatPPManager):
def build_uis(self, from_idx: int=0, to_idx: int=-1, fmt: UIFmt=GradioChatUIFmt):
if to_idx == -1 or to_idx >= len(self.pingpongs):
to_idx = len(self.pingpongs)
results = []
for pingpong in self.pingpongs[from_idx:to_idx]:
results.append(fmt.ui(pingpong))
return results
async def gen_text(
prompt,
hf_model='meta-llama/Llama-2-70b-chat-hf',
hf_token=None,
parameters=None
):
if hf_token is None:
raise ValueError("Hugging Face Token is not set")
if parameters is None:
parameters = {
'max_new_tokens': 512,
'do_sample': True,
'return_full_text': False,
'temperature': 1.0,
'top_k': 50,
# 'top_p': 1.0,
'repetition_penalty': 1.2
}
url = f'https://api-inference.huggingface.co/models/{hf_model}'
headers={
'Authorization': f'Bearer {hf_token}',
'Content-type': 'application/json'
}
data = {
'inputs': prompt,
'stream': True,
'options': {
'use_cache': False,
},
'parameters': parameters
}
r = requests.post(
url,
headers=headers,
data=json.dumps(data),
stream=True
)
client = sseclient.SSEClient(r)
for event in client.events():
yield json.loads(event.data)['token']['text']
def gen_text_none_stream(
prompt,
hf_model='meta-llama/Llama-2-70b-chat-hf',
hf_token=None,
):
parameters = {
'max_new_tokens': 64,
'do_sample': True,
'return_full_text': False,
'temperature': 0.7,
'top_k': 10,
# 'top_p': 1.0,
'repetition_penalty': 1.2
}
url = f'https://api-inference.huggingface.co/models/{hf_model}'
headers={
'Authorization': f'Bearer {hf_token}',
'Content-type': 'application/json'
}
data = {
'inputs': prompt,
'stream': False,
'options': {
'use_cache': False,
},
'parameters': parameters
}
r = requests.post(
url,
headers=headers,
data=json.dumps(data),
)
return json.loads(r.text)[0]["generated_text"] |