Rename product to Dabenying QA assistant

This commit is contained in:
2026-07-09 12:28:55 +08:00
parent 6c53566a4e
commit facb3a6a56
15 changed files with 48 additions and 42 deletions

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@@ -25,7 +25,7 @@ from app.services.rag_service import RagResult
router = APIRouter()
DEFAULT_PROMPT = "你是企业飞书知识库 AI 助手。你只能基于提供的知识片段回答,不能编造。"
DEFAULT_PROMPT = "你是大本营答疑助手。你只能基于提供的知识片段回答,不能编造。"
@router.get("/prompt")

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@@ -214,7 +214,7 @@ class ChatService:
# 拼接成文本
import re
role_labels = {"user": "用户", "assistant": "AI助手"}
role_labels = {"user": "用户", "assistant": "大本营答疑助手"}
parts = []
for msg in to_summarize:
content = re.sub(r"<think[\s\S]*?</think\s*>", "", msg.content, flags=re.IGNORECASE).strip()

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@@ -184,7 +184,7 @@ def _call_openai_compatible_model(model: ModelConfig, rag_result: RagResult) ->
payload = {
"model": model.model_name,
"messages": [
{"role": "system", "content": "你是企业知识库问答助手,只能基于已提供的知识片段回答。"},
{"role": "system", "content": "你是大本营答疑助手,只能基于已提供的知识片段回答。"},
{"role": "user", "content": rag_result.prompt},
],
"stream": False,
@@ -217,7 +217,7 @@ def _call_anthropic_messages(model: ModelConfig, rag_result: RagResult) -> str:
payload = {
"model": model.model_name,
"max_tokens": model.max_token or 1024,
"system": "你是企业知识库问答助手,只能基于已提供的知识片段回答。",
"system": "你是大本营答疑助手,只能基于已提供的知识片段回答。",
"messages": [{"role": "user", "content": rag_result.prompt}],
"stream": False,
}
@@ -251,7 +251,7 @@ def _call_gemini_generate_content(model: ModelConfig, rag_result: RagResult) ->
payload = {
"systemInstruction": {
"parts": [{"text": "你是企业知识库问答助手,只能基于已提供的知识片段回答。"}]
"parts": [{"text": "你是大本营答疑助手,只能基于已提供的知识片段回答。"}]
},
"contents": [{"role": "user", "parts": [{"text": rag_result.prompt}]}],
}
@@ -329,14 +329,14 @@ def _call_minimax(model: ModelConfig, rag_result: RagResult) -> str:
payload: dict[str, Any] = {
"model": model.model_name,
"tokens_to_generate": model.max_token or 1024,
"reply_constraints": {"sender_type": "BOT", "sender_name": "AI知识库助手"},
"reply_constraints": {"sender_type": "BOT", "sender_name": "大本营答疑助手"},
"messages": [
{"sender_type": "USER", "sender_name": "用户", "text": rag_result.prompt},
],
"bot_setting": [
{
"bot_name": "AI知识库助手",
"content": "你是企业知识库问答助手,只能基于已提供的知识片段回答。",
"bot_name": "大本营答疑助手",
"content": "你是大本营答疑助手,只能基于已提供的知识片段回答。",
}
],
}

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@@ -162,7 +162,7 @@ def _stream_openai_compatible_model(model: ModelConfig, rag_result: RagResult) -
payload: dict[str, Any] = {
"model": model.model_name,
"messages": [
{"role": "system", "content": "你是企业知识库问答助手,只能基于已提供的知识片段回答。"},
{"role": "system", "content": "你是大本营答疑助手,只能基于已提供的知识片段回答。"},
{"role": "user", "content": rag_result.prompt},
],
"max_tokens": model.max_token or 1024,
@@ -211,7 +211,7 @@ def _openai_stream_payload(model: ModelConfig, rag_result: RagResult) -> dict[st
payload: dict[str, Any] = {
"model": model.model_name,
"messages": [
{"role": "system", "content": "你是企业知识库问答助手,只能基于已提供的知识片段回答。"},
{"role": "system", "content": "你是大本营答疑助手,只能基于已提供的知识片段回答。"},
{"role": "user", "content": rag_result.prompt},
],
"max_tokens": model.max_token or 1024,
@@ -317,7 +317,7 @@ def _stream_anthropic_messages(model: ModelConfig, rag_result: RagResult) -> Ite
payload: dict[str, Any] = {
"model": model.model_name,
"max_tokens": model.max_token or 1024,
"system": "你是企业知识库问答助手,只能基于已提供的知识片段回答。",
"system": "你是大本营答疑助手,只能基于已提供的知识片段回答。",
"messages": [{"role": "user", "content": rag_result.prompt}],
}
_put_if_not_none(payload, "temperature", _decimal_to_float(model.temperature))
@@ -361,7 +361,7 @@ def _anthropic_stream_payload(model: ModelConfig, rag_result: RagResult) -> dict
payload: dict[str, Any] = {
"model": model.model_name,
"max_tokens": model.max_token or 1024,
"system": "你是企业知识库问答助手,只能基于已提供的知识片段回答。",
"system": "你是大本营答疑助手,只能基于已提供的知识片段回答。",
"messages": [{"role": "user", "content": rag_result.prompt}],
}
_put_if_not_none(payload, "temperature", _decimal_to_float(model.temperature))

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@@ -61,7 +61,7 @@ class RagService:
class PromptService:
_default_prompt = (
"你是企业飞书知识库 AI 助手。你只能基于提供的知识片段回答,不能编造。"
"你是大本营答疑助手。你只能基于提供的知识片段回答,不能编造。"
"如果知识片段之间有冲突,需要说明不同来源的观点。"
)
@@ -114,7 +114,7 @@ class PromptService:
# 只保留最近 KEEP_RECENT 轮的原文1 轮 = 1 个 user + 1 个 assistant
recent = history[-(KEEP_RECENT * 2):]
if recent:
role_labels = {"user": "用户", "assistant": "AI助手"}
role_labels = {"user": "用户", "assistant": "大本营答疑助手"}
for msg in recent:
label = role_labels.get(msg.role, msg.role)
content = msg.content.strip()