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TradingAgents
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feat: import external reports

This commit is contained in:
Tomortec 2025-07-01 23:53:46 +08:00
parent 3f5ee3f5b2
commit dc93d025fb
9 changed files with 56 additions and 14 deletions
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32
cli/main.py
View File

@ -459,20 +459,28 @@ def get_user_selections():
)
selected_research_depth = select_research_depth()
# Step 5: OpenAI backend
# Step 5: External Reports
console.print(
create_question_box(
get_lang("step5_title"), get_lang("step5_prompt")
)
)
selected_llm_provider, backend_url = select_llm_provider()
# Step 6: Thinking agents
external_reports = get_external_reports()
# Step 6: OpenAI backend
console.print(
create_question_box(
get_lang("step6_title"), get_lang("step6_prompt")
)
)
selected_llm_provider, backend_url = select_llm_provider()
# Step 7: Thinking agents
console.print(
create_question_box(
get_lang("step7_title"), get_lang("step7_prompt")
)
)
selected_shallow_thinker = select_shallow_thinking_agent(selected_llm_provider)
selected_deep_thinker = select_deep_thinking_agent(selected_llm_provider)
@ -483,6 +491,7 @@ def get_user_selections():
"research_depth": selected_research_depth,
"llm_provider": selected_llm_provider.lower(),
"backend_url": backend_url,
"external_reports": external_reports,
"shallow_thinker": selected_shallow_thinker,
"deep_thinker": selected_deep_thinker,
}
@ -511,6 +520,15 @@ def get_analysis_date():
"[red]Error: Invalid date format. Please use YYYY-MM-DD[/red]"
)
def get_external_reports():
"""Get external reports from user input."""
need_external = typer.confirm(
get_lang("step5_prompt"), default=False
)
if need_external:
reports = typer.edit(require_save=False)
return reports.replace("\n", "").split("<END>") if reports else []
return []
def display_complete_report(final_state):
"""Display the complete analysis report with team-based panels."""
@ -761,6 +779,10 @@ def run_analysis():
"System",
f"Selected analysts: {', '.join(analyst.value for analyst in selections['analysts'])}",
)
message_buffer.add_message(
"User",
f"External reports: {'<END>\n'.join(selections['external_reports']) if selections['external_reports'] else 'None'}",
)
update_display(layout)
# Reset agent statuses
@ -786,7 +808,7 @@ def run_analysis():
# Initialize state and get graph args
init_agent_state = graph.propagator.create_initial_state(
selections["ticker"], selections["analysis_date"]
selections["ticker"], selections["analysis_date"], selections["external_reports"]
)
args = graph.propagator.get_graph_args()

5
tradingagents/agents/managers/research_manager.py
View File

@ -10,6 +10,7 @@ def create_research_manager(llm, memory):
sentiment_report = state["sentiment_report"]
news_report = state["news_report"]
fundamentals_report = state["fundamentals_report"]
external_reports = state.get("external_reports", [])
investment_debate_state = state["investment_debate_state"]
@ -23,7 +24,9 @@ def create_research_manager(llm, memory):
prompt = get_prompts("managers", "research_manager") \
.replace("{max_tokens}", str(DEFAULT_CONFIG["max_tokens"])) \
.replace("{past_memory_str}", past_memory_str) \
.replace("{history}", history)
.replace("{history}", history) \
.replace("{external_reports}", "\n".join(external_reports))
response = llm.invoke(prompt)
new_investment_debate_state = {

5
tradingagents/agents/managers/risk_manager.py
View File

@ -14,6 +14,7 @@ def create_risk_manager(llm, memory):
news_report = state["news_report"]
fundamentals_report = state["news_report"]
sentiment_report = state["sentiment_report"]
external_reports = state.get("external_reports", [])
trader_plan = state["investment_plan"]
curr_situation = f"{market_research_report}\n\n{sentiment_report}\n\n{news_report}\n\n{fundamentals_report}"
@ -27,7 +28,9 @@ def create_risk_manager(llm, memory):
.replace("{max_tokens}", str(DEFAULT_CONFIG["max_tokens"])) \
.replace("{trader_plan}", trader_plan) \
.replace("{past_memory_str}", past_memory_str) \
.replace("{history}", history)
.replace("{history}", history) \
.replace("{external_reports}", "\n".join(external_reports))
response = llm.invoke(prompt)
new_risk_debate_state = {

4
tradingagents/agents/trader/trader.py
View File

@ -11,6 +11,7 @@ def create_trader(llm, memory):
sentiment_report = state["sentiment_report"]
news_report = state["news_report"]
fundamentals_report = state["fundamentals_report"]
external_reports = state.get("external_reports", [])
curr_situation = f"{market_research_report}\n\n{sentiment_report}\n\n{news_report}\n\n{fundamentals_report}"
past_memories = memory.get_memories(curr_situation, n_matches=2)
@ -23,7 +24,8 @@ def create_trader(llm, memory):
"role": "user",
"content": get_prompts("trader", "user_message") \
.replace("{company_name}", company_name) \
.replace("{investment_plan}", investment_plan)
.replace("{investment_plan}", investment_plan) \
.replace("{external_reports}", "\n".join(external_reports))
}
messages = [

1
tradingagents/agents/utils/agent_states.py
View File

@ -54,6 +54,7 @@ class AgentState(MessagesState):
sender: Annotated[str, "Agent that sent this message"]
# research step
external_reports: Annotated[list[str], "Reports from the External Expert Researcher"]
market_report: Annotated[str, "Report from the Market Analyst"]
sentiment_report: Annotated[str, "Report from the Social Media Analyst"]
news_report: Annotated[

3
tradingagents/graph/propagation.py
View File

@ -16,7 +16,7 @@ class Propagator:
self.max_recur_limit = max_recur_limit
def create_initial_state(
self, company_name: str, trade_date: str
self, company_name: str, trade_date: str, external_reports: list[str] = []
) -> Dict[str, Any]:
"""Create the initial state for the agent graph."""
return {
@ -39,6 +39,7 @@ class Propagator:
"fundamentals_report": "",
"sentiment_report": "",
"news_report": "",
"external_reports": external_reports,
}
def get_graph_args(self) -> Dict[str, Any]:

6
tradingagents/i18n/interface/en.py
View File

@ -51,10 +51,12 @@ LANG = {
"step3_prompt": "Select your LLM analyst agents for the analysis",
"step4_title": "Step 4: Research Depth",
"step4_prompt": "Select your research depth level",
"step5_title": "Step 5: Thinking Agents",
"step5_prompt": "Select your thinking agents for analysis",
"step5_title": "Step 5: External Reports",
"step5_prompt": "Do you need to import external reports?",
"step6_title": "Step 6: Thinking Agents",
"step6_prompt": "Select your thinking agents for analysis",
"step7_title": "Step 7: Thinking Agents",
"step7_prompt": "Select your thinking agents for analysis",
"default_ticker": "SPY",
"ticker_validate": "Please enter a valid ticker symbol.",
"date_validate": "Please enter a valid date in YYYY-MM-DD format.",

6
tradingagents/i18n/interface/zh.py
View File

@ -51,10 +51,12 @@ LANG = {
"step3_prompt": "请选择用于分析的LLM分析师代理",
"step4_title": "步骤4：研究深度",
"step4_prompt": "请选择研究深度等级",
"step5_title": "步骤5：思考代理",
"step5_prompt": "请选择用于分析的思考代理",
"step5_title": "步骤5：外部报告",
"step5_prompt": "需要导入外部报告吗？",
"step6_title": "步骤6：思考代理",
"step6_prompt": "请选择用于分析的思考代理",
"step7_title": "步骤7：思考代理",
"step7_prompt": "请选择用于分析的思考代理",
"default_ticker": "SPY",
"ticker_validate": "请输入有效的资产代码。",
"date_validate": "请输入有效的日期，格式为YYYY-MM-DD。",

8
tradingagents/i18n/prompts/zh.py
View File

@ -86,6 +86,9 @@ PROMPTS = {
考虑你过去在类似情况下的错误。利用这些见解来完善你的决策，并确保你正在学习和改进。以对话的方式呈现你的分析，就像自然地说话一样，无需特殊的格式。
必须认真考虑外部分析师报告:
{external_reports}
你在过去的错误和反思:
\"{past_memory_str}\"
@ -107,6 +110,9 @@ PROMPTS = {
- 基于辩论与反思的详细理由
- 务必不超过{max_tokens}tokens
必须认真考虑外部分析师报告:
{external_reports}
分析师辩论历史：
{history}"""
#endregion
@ -199,7 +205,7 @@ Here is the current conversation history: {history} Here is the last response fr
},
"trader": {
#region Trader
"user_message": "以下是针对 {company_name} 的投资建议方案，由多个分析师协作提供，涵盖了技术趋势、宏观指标与社交舆情。请将此方案作为下一步交易决策的参考依据：\n\n建议方案：{investment_plan}\n\n请基于此作出合理而有策略的判断。",
"user_message": "以下是针对 {company_name} 的投资建议方案，由多个分析师协作提供，涵盖了技术趋势、宏观指标与社交舆情。请将此方案作为下一步交易决策的参考依据：\n\n建议方案：{investment_plan}\n\n外部专家分析：{external_reports}\n\n请基于此作出合理而有策略的判断。",
"system_message": "你是一名交易代理，负责根据市场数据做出买入、卖出或持有的明确投资决策。分析结束后，请以 “最终投资建议：BUY/HOLD/SELL” 结尾，明确表达立场。请结合历史经验做出更优判断。以下为你在类似情况中总结的教训：{past_memory_str}"
#endregion
},