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yueye 2026-01-07 16:03:41 +08:00
parent 35771a9a60
commit 0de5aa038b
7 changed files with 170 additions and 17 deletions
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.storage/config.json
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@ -1,6 +1,6 @@
{
"provider": "DeepSeek",
"api_key": "",
"base_url": "https://aihubmix.com/v1",
"api_key": "sk-ca812c913baa474182f6d4e83e078302",
"base_url": "https://api.deepseek.com",
"language": "Chinese"
}

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.storage/history/1767772490_council_轻小说.json Normal file
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@ -0,0 +1,16 @@
{
"id": "1767772490",
"timestamp": 1767772490,
"date": "2026-01-07 15:54:50",
"type": "council",
"topic": "轻小说",
"content": "\n\n[错误: Error code: 401 - {'error': {'message': 'Invalid token: ca812c913baa474182f6d4e83e078302 (tid: 2026010707545042546382958168401)', 'type': 'Aihubmix_api_error'}}]",
"metadata": {
"rounds": 1,
"experts": [
"Expert 1",
"Expert 2"
],
"language": "Chinese"
}
}

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.storage/history/1767772724_council_轻小说.json Normal file
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{
"id": "1767772724",
"timestamp": 1767772724,
"date": "2026-01-07 15:58:44",
"type": "council",
"topic": "轻小说",
"content": "\n\n[错误: Error code: 400 - {'error': {'message': 'Model Not Exist', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_request_error'}}]",
"metadata": {
"rounds": 2,
"experts": [
"Expert 1",
"Expert 2",
"Expert 3 (Synthesizer)"
],
"language": "Chinese"
}
}

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.storage/history/1767772840_council_轻小说.json Normal file
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@ -0,0 +1,16 @@
{
"id": "1767772840",
"timestamp": 1767772840,
"date": "2026-01-07 16:00:40",
"type": "council",
"topic": "轻小说",
"content": "好的。作为Expert 2，我将基于与Expert 1的讨论，整合我们双方的见解，形成一个关于构建可持续、有深度的“轻小说”生态系统的最终综合计划。\n\n### **关于“轻小说”与“玩乐关系”的综合分析与行动计划**\n\n经过讨论，我们（Expert 1 与 Expert 2）的核心共识在于：**“轻小说”的本质是一种以“玩乐关系”为核心驱动力的文化产品。** 这种关系超越了简单的阅读，构建了一个由 **“创作者-作品-读者社群-产业生态”** 共同参与的、动态的“叙事游乐场”。Expert 1 精准地指出了其“共玩”特性与边界模糊化，而我的补充则聚焦于这种关系背后的“玩家心态”与意义生产的“流动性”。\n\n我们共同认为，轻小说的挑战（如套路化、深度疑虑）与机遇（如强大的社群凝聚力、跨媒体潜力）皆根植于此。因此，我们的行动计划并非要否定或削弱这种“玩乐性”，而是旨在**引导、深化和结构化这种关系，使其朝着更健康、更具创造力与可持续性的方向发展。**\n\n以下是我们提出的三位一体具体行动计划：\n\n---\n\n### **行动计划：构建“共创式叙事游乐场”生态系统**\n\n本计划围绕三大核心参与方展开，由一个核心原则统御，旨在将松散的“玩乐关系”升级为有活力的“共创生态”。\n\n#### **核心原则：从“单向供给”到“有规则的共玩”**\n确立“作者拥有主叙事权，社群享有拓展权”的共识。官方作品提供坚实、自洽、富有弹性的“核心设定与初始剧情”（即主游戏），同时明确欢迎并预留空间给社群的二次创作与解读（即玩家自创模组）。这既保护了作品的原创引力，又激发了社群活力。\n\n#### **一、 对创作者：成为“世界架构师”与“游戏设计师”**\n1. **设计“开放世界”而非“线性赛道”**：\n * **行动**：在构思阶段，除了主线，需有意识地搭建具有扩展性的世界观底层规则（如魔力系统、社会结构）和留有“空白”的角色背景。这为读者的想象与二次创作提供了合法的“土壤”。\n * **目标**：将作品从封闭的故事，转变为可供探索的“世界”，",
"metadata": {
"rounds": 1,
"experts": [
"Expert 1",
"Expert 2"
],
"language": "Chinese"
}
}

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app.py
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@ -91,8 +91,9 @@ if "saved_config" not in st.session_state:
def save_current_config():
cfg = {
"provider": st.session_state.get("selected_provider", "AIHubMix"),
"api_key": st.session_state.get("api_key", ""),
"base_url": st.session_state.get("base_url", ""),
# read from widget keys to persist what user sees
"api_key": st.session_state.get("api_key_input", st.session_state.get("api_key", "")),
"base_url": st.session_state.get("base_url_input", st.session_state.get("base_url", "")),
"language": st.session_state.get("output_language", "Chinese")
}
st.session_state.storage.save_config(cfg)
@ -140,35 +141,65 @@ with st.sidebar:
except ValueError:
prov_idx = 0
def on_provider_change():
# Update API key and base_url inputs when provider changes
sel = st.session_state.get("selected_provider")
if not sel:
return
prov_cfg = config.LLM_PROVIDERS.get(sel, {})
saved_cfg = st.session_state.get("saved_config", {})
# choose api_key from saved config if provider matches, otherwise from env
default_key = saved_cfg.get("api_key") if saved_cfg.get("provider") == sel else os.getenv(prov_cfg.get("api_key_var", ""), "")
# Always reset base_url_input to the provider's configured default when switching providers
default_base = prov_cfg.get("base_url", "")
# Set widget states
st.session_state["api_key_input"] = default_key
st.session_state["base_url_input"] = default_base
# Persist current selection
save_current_config()
selected_provider_label = st.selectbox(
"选择 API 提供商",
options=provider_options,
index=prov_idx,
key="selected_provider",
on_change=save_current_config
on_change=on_provider_change
)
provider_config = config.LLM_PROVIDERS[selected_provider_label]
provider_id = selected_provider_label.lower()
# Recompute provider config from current selection (use session_state to be robust)
current_provider = st.session_state.get("selected_provider", selected_provider_label)
provider_config = config.LLM_PROVIDERS.get(current_provider, {})
provider_id = current_provider.lower()
# API Key Input
# If saved key exists for this provider, use it. Otherwise env var.
default_key = saved.get("api_key") if saved.get("provider") == selected_provider_label else os.getenv(provider_config["api_key_var"], "")
# If widget already has a value in session_state (from previous interactions), prefer it.
default_key = (
st.session_state.get("api_key_input")
if st.session_state.get("api_key_input") is not None and st.session_state.get("api_key_input") != ""
else (saved.get("api_key") if saved.get("provider") == current_provider else os.getenv(provider_config.get("api_key_var", ""), ""))
)
api_key = st.text_input(
f"{selected_provider_label} API Key",
type="password",
f"{current_provider} API Key",
type="password",
value=default_key,
help=f"环境变量: {provider_config['api_key_var']}",
help=f"环境变量: {provider_config.get('api_key_var', '')}",
key="api_key_input"
)
# Sync to session state for save callback
st.session_state.api_key = api_key
# Base URL
default_url = saved.get("base_url") if saved.get("provider") == selected_provider_label else provider_config["base_url"]
# Special-case: ensure DeepSeek shows its correct official base URL
if current_provider == "DeepSeek":
default_url = provider_config.get("base_url", "")
else:
default_url = (
st.session_state.get("base_url_input")
if st.session_state.get("base_url_input") is not None and st.session_state.get("base_url_input") != ""
else (saved.get("base_url") if saved.get("provider") == current_provider else provider_config.get("base_url", ""))
)
base_url = st.text_input(
"API Base URL",
"API Base URL",
value=default_url,
key="base_url_input"
)
@ -446,6 +477,47 @@ if st.session_state.mode == "Deep Research":
st.markdown(step['output'])
st.divider()
# 追问模式（Deep Research）
st.divider()
st.subheader("🔎 追问模式 — 深入提问")
followup_q = st.text_area("输入你的追问（基于上面的综合方案）", key="research_followup_input", height=80)
if 'research_followups' not in st.session_state:
st.session_state.research_followups = []
if st.button("💬 追问", key="research_followup_btn") and followup_q:
# 创建客户端，优先使用最后一个专家的模型作为回复模型
follow_model = None
try:
follow_model = experts_config[-1]['model'] if experts_config else None
except Exception:
follow_model = None
llm = LLMClient(provider=provider_id, api_key=st.session_state.get('api_key'), base_url=st.session_state.get('base_url'), model=follow_model)
sys_prompt = "你是一个基于先前生成的综合方案的助理，针对用户的追问进行简明、深入且行动导向的回答。"
user_prompt = f"已生成的综合方案:\n{st.session_state.research_output}\n\n用户追问:\n{followup_q}"
placeholder = st.empty()
reply = ""
try:
for chunk in llm.chat_stream(system_prompt=sys_prompt, user_prompt=user_prompt, max_tokens=1024):
reply += chunk
placeholder.markdown(reply)
except Exception as e:
placeholder.markdown(f"错误: {e}")
# 保存本次追问到 session（仅会话级）
st.session_state.research_followups.append({"q": followup_q, "a": reply})
st.success("追问已得到回复")
# 显示历史追问
if st.session_state.research_followups:
with st.expander("查看追问历史"):
for idx, qa in enumerate(st.session_state.research_followups[::-1]):
st.markdown(f"**Q{len(st.session_state.research_followups)-idx}:** {qa['q']}")
st.markdown(f"**A:** {qa['a']}")
st.divider()
elif st.session_state.mode == "Debate Workshop":
# ==================== 原始 Debate UI 逻辑 ====================
@ -692,6 +764,38 @@ elif st.session_state.mode == "Debate Workshop":
file_name="decision_report.md",
mime="text/markdown"
)
# 追问模式（Debate Workshop）
st.divider()
st.subheader("🔎 追问模式 — 基于报告的深入提问")
debate_followup_q = st.text_area("输入你的追问（基于上面的决策报告）", key="debate_followup_input", height=80)
if 'debate_followups' not in st.session_state:
st.session_state.debate_followups = []
if st.button("💬 追问", key="debate_followup_btn") and debate_followup_q:
# 使用生成报告时的 llm_client
llm_follow = llm_client
sys_prompt = "你是一个基于上面决策报告的助理，针对用户的追问进行简明且行动导向的回答。"
user_prompt = f"决策报告:\n{st.session_state.report}\n\n用户追问:\n{debate_followup_q}"
ph = st.empty()
reply = ""
try:
for chunk in llm_follow.chat_stream(system_prompt=sys_prompt, user_prompt=user_prompt, max_tokens=1024):
reply += chunk
ph.markdown(reply)
except Exception as e:
ph.markdown(f"错误: {e}")
st.session_state.debate_followups.append({"q": debate_followup_q, "a": reply})
st.success("追问已得到回复")
if st.session_state.debate_followups:
with st.expander("查看追问历史"):
for idx, qa in enumerate(st.session_state.debate_followups[::-1]):
st.markdown(f"**Q{len(st.session_state.debate_followups)-idx}:** {qa['q']}")
st.markdown(f"**A:** {qa['a']}")
st.divider()
except Exception as e:
st.error(f"发生错误: {str(e)}")