Soulter
295 lines
11 KiB
Python
295 lines
11 KiB
Python
import traceback
|
|
import base64
|
|
import json
|
|
import aiohttp
|
|
from astrbot.core.utils.io import download_image_by_url
|
|
from astrbot.core.db import BaseDatabase
|
|
from astrbot.api.provider import Provider, Personality
|
|
from astrbot import logger
|
|
from astrbot.core.provider.func_tool_manager import FuncCall
|
|
from typing import List
|
|
from ..register import register_provider_adapter
|
|
from astrbot.core.provider.entites import LLMResponse
|
|
|
|
class SimpleGoogleGenAIClient():
|
|
def __init__(self, api_key: str, api_base: str):
|
|
self.api_key = api_key
|
|
if api_base.endswith("/"):
|
|
self.api_base = api_base[:-1]
|
|
else:
|
|
self.api_base = api_base
|
|
self.client = aiohttp.ClientSession()
|
|
|
|
async def models_list(self) -> List[str]:
|
|
request_url = f"{self.api_base}/v1beta/models?key={self.api_key}"
|
|
async with self.client.get(request_url, timeout=10) as resp:
|
|
response = await resp.json()
|
|
|
|
models = []
|
|
for model in response["models"]:
|
|
if 'generateContent' in model["supportedGenerationMethods"]:
|
|
models.append(model["name"].replace("models/", ""))
|
|
return models
|
|
|
|
async def generate_content(
|
|
self,
|
|
contents: List[dict],
|
|
model: str="gemini-1.5-flash",
|
|
system_instruction: str="",
|
|
tools: dict=None
|
|
):
|
|
payload = {}
|
|
if system_instruction:
|
|
payload["system_instruction"] = {
|
|
"parts": {"text": system_instruction}
|
|
}
|
|
if tools:
|
|
payload["tools"] = [tools]
|
|
payload["contents"] = contents
|
|
logger.debug(f"payload: {payload}")
|
|
request_url = f"{self.api_base}/v1beta/models/{model}:generateContent?key={self.api_key}"
|
|
async with self.client.post(request_url, json=payload, timeout=10) as resp:
|
|
response = await resp.json()
|
|
return response
|
|
|
|
|
|
@register_provider_adapter("googlegenai_chat_completion", "Google Gemini Chat Completion 提供商适配器")
|
|
class ProviderGoogleGenAI(Provider):
|
|
def __init__(
|
|
self,
|
|
provider_config: dict,
|
|
provider_settings: dict,
|
|
db_helper: BaseDatabase,
|
|
persistant_history = True,
|
|
default_persona: Personality=None
|
|
) -> None:
|
|
super().__init__(provider_config, provider_settings, persistant_history, db_helper, default_persona)
|
|
self.chosen_api_key = None
|
|
self.api_keys: List = provider_config.get("key", [])
|
|
self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
|
|
|
|
self.client = SimpleGoogleGenAIClient(
|
|
api_key=self.chosen_api_key,
|
|
api_base=provider_config.get("api_base", None)
|
|
)
|
|
self.set_model(provider_config['model_config']['model'])
|
|
|
|
async def get_human_readable_context(self, session_id, page, page_size):
|
|
if session_id not in self.session_memory:
|
|
raise Exception("会话 ID 不存在")
|
|
contexts = []
|
|
temp_contexts = []
|
|
for record in self.session_memory[session_id]:
|
|
if record['role'] == "user":
|
|
temp_contexts.append(f"User: {record['content']}")
|
|
elif record['role'] == "assistant":
|
|
temp_contexts.append(f"Assistant: {record['content']}")
|
|
contexts.insert(0, temp_contexts)
|
|
temp_contexts = []
|
|
|
|
# 展平 contexts 列表
|
|
contexts = [item for sublist in contexts for item in sublist]
|
|
|
|
# 计算分页
|
|
paged_contexts = contexts[(page-1)*page_size:page*page_size]
|
|
total_pages = len(contexts) // page_size
|
|
if len(contexts) % page_size != 0:
|
|
total_pages += 1
|
|
|
|
return paged_contexts, total_pages
|
|
|
|
async def get_models(self):
|
|
return await self.client.models_list()
|
|
|
|
async def pop_record(self, session_id: str, pop_system_prompt: bool = False):
|
|
'''
|
|
弹出第一条记录
|
|
'''
|
|
if session_id not in self.session_memory:
|
|
raise Exception("会话 ID 不存在")
|
|
|
|
if len(self.session_memory[session_id]) == 0:
|
|
return None
|
|
|
|
for i in range(len(self.session_memory[session_id])):
|
|
# 检查是否是 system prompt
|
|
if not pop_system_prompt and self.session_memory[session_id][i]['user']['role'] == "system":
|
|
# 如果只有一个 system prompt，才不删掉
|
|
f = False
|
|
for j in range(i+1, len(self.session_memory[session_id])):
|
|
if self.session_memory[session_id][j]['user']['role'] == "system":
|
|
f = True
|
|
break
|
|
if not f:
|
|
continue
|
|
record = self.session_memory[session_id].pop(i)
|
|
break
|
|
|
|
return record
|
|
|
|
async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
|
|
tool = None
|
|
if tools:
|
|
tool = tools.get_func_desc_google_genai_style()
|
|
if not tool:
|
|
tool = None
|
|
|
|
system_instruction = ""
|
|
for message in payloads["messages"]:
|
|
if message["role"] == "system":
|
|
system_instruction = message["content"]
|
|
break
|
|
|
|
google_genai_conversation = []
|
|
for message in payloads["messages"]:
|
|
if message["role"] == "user":
|
|
if isinstance(message["content"], str):
|
|
google_genai_conversation.append({
|
|
"role": "user",
|
|
"parts": [{"text": message["content"]}]
|
|
})
|
|
elif isinstance(message["content"], list):
|
|
# images
|
|
parts = []
|
|
for part in message["content"]:
|
|
if part["type"] == "text":
|
|
parts.append({"text": part["text"]})
|
|
elif part["type"] == "image_url":
|
|
parts.append({"inline_data": {
|
|
"mime_type": "image/jpeg",
|
|
"data": part["image_url"]["url"].replace("data:image/jpeg;base64,", "") # base64
|
|
}})
|
|
google_genai_conversation.append({
|
|
"role": "user",
|
|
"parts": parts
|
|
})
|
|
|
|
elif message["role"] == "assistant":
|
|
google_genai_conversation.append({
|
|
"role": "model",
|
|
"parts": [{"text": message["content"]}]
|
|
})
|
|
|
|
|
|
logger.debug(f"google_genai_conversation: {google_genai_conversation}")
|
|
|
|
result = await self.client.generate_content(
|
|
contents=google_genai_conversation,
|
|
model=self.get_model(),
|
|
system_instruction=system_instruction,
|
|
tools=tool
|
|
)
|
|
logger.debug(f"result: {result}")
|
|
|
|
candidates = result["candidates"][0]['content']['parts']
|
|
llm_response = LLMResponse("assistant")
|
|
for candidate in candidates:
|
|
if 'text' in candidate:
|
|
llm_response.completion_text += candidate['text']
|
|
elif 'functionCall' in candidate:
|
|
llm_response.role = "tool"
|
|
llm_response.tools_call_args.append(candidate['functionCall']['args'])
|
|
llm_response.tools_call_name.append(candidate['functionCall']['name'])
|
|
|
|
return llm_response
|
|
|
|
|
|
async def text_chat(
|
|
self,
|
|
prompt: str,
|
|
session_id: str,
|
|
image_urls: List[str]=None,
|
|
func_tool: FuncCall=None,
|
|
contexts=None,
|
|
system_prompt=None,
|
|
**kwargs
|
|
) -> LLMResponse:
|
|
new_record = await self.assemble_context(prompt, image_urls)
|
|
context_query = []
|
|
if not contexts:
|
|
context_query = [*self.session_memory[session_id], new_record]
|
|
else:
|
|
context_query = [*contexts, new_record]
|
|
if system_prompt:
|
|
context_query.insert(0, {"role": "system", "content": system_prompt})
|
|
|
|
for part in context_query:
|
|
if '_no_save' in part:
|
|
del part['_no_save']
|
|
|
|
payloads = {
|
|
"messages": context_query,
|
|
**self.provider_config.get("model_config", {})
|
|
}
|
|
|
|
try:
|
|
llm_response = await self._query(payloads, func_tool)
|
|
except Exception as e:
|
|
if "maximum context length" in str(e):
|
|
logger.warning(f"请求失败：{e}。上下文长度超过限制。尝试弹出最早的记录然后重试。")
|
|
self.pop_record(session_id)
|
|
logger.warning(traceback.format_exc())
|
|
|
|
await self.save_history(contexts, new_record, session_id, llm_response)
|
|
|
|
return llm_response
|
|
|
|
async def save_history(self, contexts: List, new_record: dict, session_id: str, llm_response: LLMResponse):
|
|
if llm_response.role == "assistant" and session_id:
|
|
# 文本回复
|
|
if not contexts:
|
|
# 添加用户 record
|
|
self.session_memory[session_id].append(new_record)
|
|
# 添加 assistant record
|
|
self.session_memory[session_id].append({
|
|
"role": "assistant",
|
|
"content": llm_response.completion_text
|
|
})
|
|
else:
|
|
contexts_to_save = list(filter(lambda item: '_no_save' not in item, contexts))
|
|
self.session_memory[session_id] = [*contexts_to_save, new_record, {
|
|
"role": "assistant",
|
|
"content": llm_response.completion_text
|
|
}]
|
|
self.db_helper.update_llm_history(session_id, json.dumps(self.session_memory[session_id]), self.provider_config['type'])
|
|
|
|
async def forget(self, session_id: str) -> bool:
|
|
self.session_memory[session_id] = []
|
|
return True
|
|
|
|
def get_current_key(self) -> str:
|
|
return self.client.api_key
|
|
|
|
def get_keys(self) -> List[str]:
|
|
return self.api_keys
|
|
|
|
def set_key(self, key):
|
|
self.client.api_key = key
|
|
|
|
async def assemble_context(self, text: str, image_urls: List[str] = None):
|
|
'''
|
|
组装上下文。
|
|
'''
|
|
if image_urls:
|
|
user_content = {"role": "user","content": [{"type": "text", "text": text}]}
|
|
for image_url in image_urls:
|
|
if image_url.startswith("http"):
|
|
image_path = await download_image_by_url(image_url)
|
|
image_data = await self.encode_image_bs64(image_path)
|
|
else:
|
|
image_data = await self.encode_image_bs64(image_url)
|
|
user_content["content"].append({"type": "image_url", "image_url": {"url": image_data}})
|
|
return user_content
|
|
else:
|
|
return {"role": "user","content": text}
|
|
|
|
async def encode_image_bs64(self, image_url: str) -> str:
|
|
'''
|
|
将图片转换为 base64
|
|
'''
|
|
if image_url.startswith("base64://"):
|
|
return image_url.replace("base64://", "data:image/jpeg;base64,")
|
|
with open(image_url, "rb") as f:
|
|
image_bs64 = base64.b64encode(f.read()).decode('utf-8')
|
|
return "data:image/jpeg;base64," + image_bs64
|
|
return '' |