feat: keep last k images

This commit is contained in:
Ivan087
2025-01-08 17:30:47 +08:00
parent 21ecfdbb76
commit ab966fba16
2 changed files with 64 additions and 11 deletions

View File

@ -12,13 +12,13 @@ import requests
import base64
import copy
import ast
import random
from time import time
import io
from PIL import Image
from lmdeploy.serve.openai.api_client import APIClient
import io
from PIL import Image
from lmdeploy.serve.openai.api_client import APIClient
def is_base64(value) -> bool:
try:
@ -50,8 +50,8 @@ class VLMS(Blackbox):
- ignore_eos (bool): indicator for ignoring eos
- skip_special_tokens (bool): Whether or not to remove special tokens
in the decoding. Default to be True."""
self.url = vlm_config.url
self.model_dict = vlm_config.urls
self.model_url = None
self.temperature: float = 0.7
self.top_p:float = 1
self.max_tokens: (int |None) = 512
@ -81,7 +81,7 @@ class VLMS(Blackbox):
data = args[0]
return isinstance(data, list)
def processing(self, prompt:str, images:str | bytes, settings: dict, model_name: Optional[str] = None, user_context: List[dict] = None) -> str:
def processing(self, prompt:str | None, images:str | bytes | None, settings: dict, model_name: Optional[str] = None, user_context: List[dict] = None) -> str:
"""
Args:
prompt: a string query to the model.
@ -105,6 +105,9 @@ class VLMS(Blackbox):
else:
settings = {}
if not prompt:
prompt = '你是一个辅助机器人请就此图做一个简短的概括性描述包括图中的主体物品及状态不超过50字。' if images else '你好'
# Transform the images into base64 format where openai format need.
if images:
if is_base64(images): # image as base64 str
@ -148,7 +151,11 @@ class VLMS(Blackbox):
# 'content': '图片中主要展示了一只老虎,它正在绿色的草地上休息。草地上有很多可以让人坐下的地方,而且看起来相当茂盛。背景比较模糊,可能是因为老虎的影响,让整个图片的其他部分都变得不太清晰了。'
# }
# ]
api_client = APIClient(self.url)
user_context = self.keep_last_k_images(user_context,k = 1)
if self.model_url is None: self.model_url = self._get_model_url(model_name)
api_client = APIClient(self.model_url)
# api_client = APIClient("http://10.6.80.91:23333")
model_name = api_client.available_models[0]
# Reformat input into openai format to request.
@ -198,10 +205,28 @@ class VLMS(Blackbox):
print(item["choices"][0]["message"]['content'])
responses += item["choices"][0]["message"]['content']
# total_token_usage += item['usage']['total_tokens'] # 'usage': {'prompt_tokens': *, 'total_tokens': *, 'completion_tokens': *}
user_context = messages + [{'role': 'assistant', 'content': responses}]
self.custom_print(user_context)
return responses, user_context
def _get_model_url(self,model_name:str | None):
available_models = {}
for model, url in self.model_dict.items():
try:
response = requests.get(url,timeout=3)
if response.status_code == 200:
available_models[model] = url
except Exception as e:
# print(e)
pass
if not available_models: print("There are no available running models and please check your endpoint urls.")
if model_name and model_name in available_models:
return available_models[model_name]
else:
model = random.choice(list(available_models.keys()))
print(f"No such model {model_name}, using {model} instead.") if model_name else print(f"Using random model {model}.")
return available_models[model]
def _into_openai_format(self, context:List[list]) -> List[dict]:
"""
Convert the data into openai format.
@ -255,7 +280,35 @@ class VLMS(Blackbox):
return user_context
def keep_last_k_images(self, user_context: list, k:int=2):
count = 0
result =[]
for item in user_context[::-1]:
if item['role'] == 'user' and len(item['content']) > 1:
for idx, info in enumerate(item['content']):
if info['type'] in ('image_url','image') and count >= k:
item['content'].pop(idx)
# item['content'].insert(idx, {'type': 'text', 'text': '<IMAGE>'})
elif info['type'] in ('image_url','image') and count < k:
count += 1
else:
continue
result.append(item)
return result[::-1]
def custom_print(self, user_context: list):
result = []
for item in user_context:
if item['role'] == 'user':
for idx, info in enumerate(item['content']):
if info['type'] in ('image_url','image'):
item['content'].pop(idx)
item['content'].insert(idx, {'type': 'image', 'image': '##<IMAGE>##'})
else:
continue
result.append(item)
print(result)
async def fast_api_handler(self, request: Request) -> Response:
## TODO: add support for multiple images and support image in form-data format
json_request = True
@ -291,8 +344,8 @@ class VLMS(Blackbox):
if prompt is None:
return JSONResponse(content={'error': "Question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
if model_name is None or model_name.isspace():
model_name = "Qwen-VL-Chat"
# if model_name is None or model_name.isspace():
# model_name = "Qwen-VL-Chat"
response, history = self.processing(prompt, img_data,settings, model_name,user_context=user_context)
# jsonresp = str(JSONResponse(content={"response": self.processing(prompt, img_data, model_name)}).body, "utf-8")

View File

@ -153,4 +153,4 @@ class VLMConf():
@inject
def __init__(self, config: Configuration) -> None:
self.url = config.get("vlms.url")
self.urls = config.get("vlms.urls")