Spaces:
Runtime error
Runtime error
File size: 2,780 Bytes
458ae42 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
import json
import logging
import textwrap
import uuid
import google.generativeai as genai
import gradio as gr
import PIL
import requests
from modules.presets import i18n
from ..index_func import construct_index
from ..utils import count_token
from .base_model import BaseLLMModel
class GoogleGeminiClient(BaseLLMModel):
def __init__(self, model_name, api_key, user_name="") -> None:
super().__init__(model_name=model_name, user=user_name)
self.api_key = api_key
if "vision" in model_name.lower():
self.multimodal = True
else:
self.multimodal = False
self.image_paths = []
def _get_gemini_style_input(self):
self.history.extend([{"role": "image", "content": i} for i in self.image_paths])
self.image_paths = []
messages = []
for item in self.history:
if item["role"] == "image":
messages.append(PIL.Image.open(item["content"]))
else:
messages.append(item["content"])
return messages
def to_markdown(self, text):
text = text.replace("•", " *")
return textwrap.indent(text, "> ", predicate=lambda _: True)
def handle_file_upload(self, files, chatbot, language):
if files:
if self.multimodal:
for file in files:
if file.name:
self.image_paths.append(file.name)
chatbot = chatbot + [((file.name,), None)]
return None, chatbot, None
else:
construct_index(self.api_key, file_src=files)
status = i18n("索引构建完成")
return gr.Files.update(), chatbot, status
def get_answer_at_once(self):
genai.configure(api_key=self.api_key)
messages = self._get_gemini_style_input()
model = genai.GenerativeModel(self.model_name)
response = model.generate_content(messages)
try:
return self.to_markdown(response.text), len(response.text)
except ValueError:
return (
i18n("由于下面的原因，Google 拒绝返回 Gemini 的回答：\n\n")
+ str(response.prompt_feedback),
0,
)
def get_answer_stream_iter(self):
genai.configure(api_key=self.api_key)
messages = self._get_gemini_style_input()
model = genai.GenerativeModel(self.model_name)
response = model.generate_content(messages, stream=True)
partial_text = ""
for i in response:
response = i.text
partial_text += response
yield partial_text
self.all_token_counts[-1] = count_token(partial_text)
yield partial_text
|