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fix: Add MiniMax support, fix Windows Unicode errors, and correct pandas import bugs

This commit is contained in:
ElMoorish 2026-04-05 01:57:53 +01:00
parent 4641c03340
commit 35d2a7d995
7 changed files with 157 additions and 293 deletions
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226
.gitignore vendored
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@ -1,219 +1,9 @@
# Byte-compiled / optimized / DLL files
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# C extensions
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# Distribution / packaging
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build/
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*.egg
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# PyInstaller
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*.cover
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# Django stuff:
*.log
local_settings.py
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32
cli/main.py
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@ -645,19 +645,19 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path):
analyst_parts = [] analyst_parts = []
if final_state.get("market_report"): if final_state.get("market_report"):
analysts_dir.mkdir(exist_ok=True) analysts_dir.mkdir(exist_ok=True)
(analysts_dir / "market.md").write_text(final_state["market_report"]) (analysts_dir / "market.md").write_text(final_state["market_report"], encoding="utf-8")
analyst_parts.append(("Market Analyst", final_state["market_report"])) analyst_parts.append(("Market Analyst", final_state["market_report"]))
if final_state.get("sentiment_report"): if final_state.get("sentiment_report"):
analysts_dir.mkdir(exist_ok=True) analysts_dir.mkdir(exist_ok=True)
(analysts_dir / "sentiment.md").write_text(final_state["sentiment_report"]) (analysts_dir / "sentiment.md").write_text(final_state["sentiment_report"], encoding="utf-8")
analyst_parts.append(("Social Analyst", final_state["sentiment_report"])) analyst_parts.append(("Social Analyst", final_state["sentiment_report"]))
if final_state.get("news_report"): if final_state.get("news_report"):
analysts_dir.mkdir(exist_ok=True) analysts_dir.mkdir(exist_ok=True)
(analysts_dir / "news.md").write_text(final_state["news_report"]) (analysts_dir / "news.md").write_text(final_state["news_report"], encoding="utf-8")
analyst_parts.append(("News Analyst", final_state["news_report"])) analyst_parts.append(("News Analyst", final_state["news_report"]))
if final_state.get("fundamentals_report"): if final_state.get("fundamentals_report"):
analysts_dir.mkdir(exist_ok=True) analysts_dir.mkdir(exist_ok=True)
(analysts_dir / "fundamentals.md").write_text(final_state["fundamentals_report"]) (analysts_dir / "fundamentals.md").write_text(final_state["fundamentals_report"], encoding="utf-8")
analyst_parts.append(("Fundamentals Analyst", final_state["fundamentals_report"])) analyst_parts.append(("Fundamentals Analyst", final_state["fundamentals_report"]))
if analyst_parts: if analyst_parts:
content = "\n\n".join(f"### {name}\n{text}" for name, text in analyst_parts) content = "\n\n".join(f"### {name}\n{text}" for name, text in analyst_parts)
@ -670,15 +670,15 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path):
research_parts = [] research_parts = []
if debate.get("bull_history"): if debate.get("bull_history"):
research_dir.mkdir(exist_ok=True) research_dir.mkdir(exist_ok=True)
(research_dir / "bull.md").write_text(debate["bull_history"]) (research_dir / "bull.md").write_text(debate["bull_history"], encoding="utf-8")
research_parts.append(("Bull Researcher", debate["bull_history"])) research_parts.append(("Bull Researcher", debate["bull_history"]))
if debate.get("bear_history"): if debate.get("bear_history"):
research_dir.mkdir(exist_ok=True) research_dir.mkdir(exist_ok=True)
(research_dir / "bear.md").write_text(debate["bear_history"]) (research_dir / "bear.md").write_text(debate["bear_history"], encoding="utf-8")
research_parts.append(("Bear Researcher", debate["bear_history"])) research_parts.append(("Bear Researcher", debate["bear_history"]))
if debate.get("judge_decision"): if debate.get("judge_decision"):
research_dir.mkdir(exist_ok=True) research_dir.mkdir(exist_ok=True)
(research_dir / "manager.md").write_text(debate["judge_decision"]) (research_dir / "manager.md").write_text(debate["judge_decision"], encoding="utf-8")
research_parts.append(("Research Manager", debate["judge_decision"])) research_parts.append(("Research Manager", debate["judge_decision"]))
if research_parts: if research_parts:
content = "\n\n".join(f"### {name}\n{text}" for name, text in research_parts) content = "\n\n".join(f"### {name}\n{text}" for name, text in research_parts)
@ -688,7 +688,7 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path):
if final_state.get("trader_investment_plan"): if final_state.get("trader_investment_plan"):
trading_dir = save_path / "3_trading" trading_dir = save_path / "3_trading"
trading_dir.mkdir(exist_ok=True) trading_dir.mkdir(exist_ok=True)
(trading_dir / "trader.md").write_text(final_state["trader_investment_plan"]) (trading_dir / "trader.md").write_text(final_state["trader_investment_plan"], encoding="utf-8")
sections.append(f"## III. Trading Team Plan\n\n### Trader\n{final_state['trader_investment_plan']}") sections.append(f"## III. Trading Team Plan\n\n### Trader\n{final_state['trader_investment_plan']}")
# 4. Risk Management # 4. Risk Management
@ -698,15 +698,15 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path):
risk_parts = [] risk_parts = []
if risk.get("aggressive_history"): if risk.get("aggressive_history"):
risk_dir.mkdir(exist_ok=True) risk_dir.mkdir(exist_ok=True)
(risk_dir / "aggressive.md").write_text(risk["aggressive_history"]) (risk_dir / "aggressive.md").write_text(risk["aggressive_history"], encoding="utf-8")
risk_parts.append(("Aggressive Analyst", risk["aggressive_history"])) risk_parts.append(("Aggressive Analyst", risk["aggressive_history"]))
if risk.get("conservative_history"): if risk.get("conservative_history"):
risk_dir.mkdir(exist_ok=True) risk_dir.mkdir(exist_ok=True)
(risk_dir / "conservative.md").write_text(risk["conservative_history"]) (risk_dir / "conservative.md").write_text(risk["conservative_history"], encoding="utf-8")
risk_parts.append(("Conservative Analyst", risk["conservative_history"])) risk_parts.append(("Conservative Analyst", risk["conservative_history"]))
if risk.get("neutral_history"): if risk.get("neutral_history"):
risk_dir.mkdir(exist_ok=True) risk_dir.mkdir(exist_ok=True)
(risk_dir / "neutral.md").write_text(risk["neutral_history"]) (risk_dir / "neutral.md").write_text(risk["neutral_history"], encoding="utf-8")
risk_parts.append(("Neutral Analyst", risk["neutral_history"])) risk_parts.append(("Neutral Analyst", risk["neutral_history"]))
if risk_parts: if risk_parts:
content = "\n\n".join(f"### {name}\n{text}" for name, text in risk_parts) content = "\n\n".join(f"### {name}\n{text}" for name, text in risk_parts)
@ -716,12 +716,12 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path):
if risk.get("judge_decision"): if risk.get("judge_decision"):
portfolio_dir = save_path / "5_portfolio" portfolio_dir = save_path / "5_portfolio"
portfolio_dir.mkdir(exist_ok=True) portfolio_dir.mkdir(exist_ok=True)
(portfolio_dir / "decision.md").write_text(risk["judge_decision"]) (portfolio_dir / "decision.md").write_text(risk["judge_decision"], encoding="utf-8")
sections.append(f"## V. Portfolio Manager Decision\n\n### Portfolio Manager\n{risk['judge_decision']}") sections.append(f"## V. Portfolio Manager Decision\n\n### Portfolio Manager\n{risk['judge_decision']}")
# Write consolidated report # Write consolidated report
header = f"# Trading Analysis Report: {ticker}\n\nGenerated: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n" header = f"# Trading Analysis Report: {ticker}\n\nGenerated: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
(save_path / "complete_report.md").write_text(header + "\n\n".join(sections)) (save_path / "complete_report.md").write_text(header + "\n\n".join(sections), encoding="utf-8")
return save_path / "complete_report.md" return save_path / "complete_report.md"
@ -979,7 +979,7 @@ def run_analysis():
func(*args, **kwargs) func(*args, **kwargs)
timestamp, message_type, content = obj.messages[-1] timestamp, message_type, content = obj.messages[-1]
content = content.replace("\n", " ") # Replace newlines with spaces content = content.replace("\n", " ") # Replace newlines with spaces
with open(log_file, "a") as f: with open(log_file, "a", encoding="utf-8") as f:
f.write(f"{timestamp} [{message_type}] {content}\n") f.write(f"{timestamp} [{message_type}] {content}\n")
return wrapper return wrapper
@ -990,7 +990,7 @@ def run_analysis():
func(*args, **kwargs) func(*args, **kwargs)
timestamp, tool_name, args = obj.tool_calls[-1] timestamp, tool_name, args = obj.tool_calls[-1]
args_str = ", ".join(f"{k}={v}" for k, v in args.items()) args_str = ", ".join(f"{k}={v}" for k, v in args.items())
with open(log_file, "a") as f: with open(log_file, "a", encoding="utf-8") as f:
f.write(f"{timestamp} [Tool Call] {tool_name}({args_str})\n") f.write(f"{timestamp} [Tool Call] {tool_name}({args_str})\n")
return wrapper return wrapper
@ -1004,7 +1004,7 @@ def run_analysis():
if content: if content:
file_name = f"{section_name}.md" file_name = f"{section_name}.md"
text = "\n".join(str(item) for item in content) if isinstance(content, list) else content text = "\n".join(str(item) for item in content) if isinstance(content, list) else content
with open(report_dir / file_name, "w") as f: with open(report_dir / file_name, "w", encoding="utf-8") as f:
f.write(text) f.write(text)
return wrapper return wrapper

95
cli/utils.py
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@ -187,23 +187,29 @@ def select_deep_thinking_agent(provider) -> str:
return choice return choice
def select_llm_provider() -> tuple[str, str]: def select_llm_provider() -> tuple[str, str]:
"""Select the OpenAI api url using interactive selection.""" """Select the OpenAI api url using interactive selection."""
# Define OpenAI api options with their corresponding endpoints # Define OpenAI api options with their corresponding endpoints
BASE_URLS = [ BASE_URLS = [
("OpenAI", "https://api.openai.com/v1"), ("OpenAI", "openai", "https://api.openai.com/v1"),
("Google", "https://generativelanguage.googleapis.com/v1"), ("Google", "google", "https://generativelanguage.googleapis.com/v1"),
("Anthropic", "https://api.anthropic.com/"), ("Anthropic", "anthropic", "https://api.anthropic.com/"),
("xAI", "https://api.x.ai/v1"), ("xAI", "xai", "https://api.x.ai/v1"),
("Openrouter", "https://openrouter.ai/api/v1"), ("Openrouter", "openrouter", "https://openrouter.ai/api/v1"),
("Ollama", "http://localhost:11434/v1"), ("Ollama", "ollama", "http://localhost:11434/v1"),
(
"Kilo Gateway (MiniMax M2.5 Free)",
"minimax",
"https://api.kilo.ai/api/gateway",
),
] ]
choice = questionary.select( choice = questionary.select(
"Select your LLM Provider:", "Select your LLM Provider:",
choices=[ choices=[
questionary.Choice(display, value=(display, value)) questionary.Choice(display, value=(provider, url))
for display, value in BASE_URLS for display, provider, url in BASE_URLS
], ],
instruction="\n- Use arrow keys to navigate\n- Press Enter to select", instruction="\n- Use arrow keys to navigate\n- Press Enter to select",
style=questionary.Style( style=questionary.Style(
@ -214,15 +220,15 @@ def select_llm_provider() -> tuple[str, str]:
] ]
), ),
).ask() ).ask()
if choice is None: if choice is None:
console.print("\n[red]no OpenAI backend selected. Exiting...[/red]") console.print("\n[red]no OpenAI backend selected. Exiting...[/red]")
exit(1) exit(1)
display_name, url = choice
print(f"You selected: {display_name}\tURL: {url}")
return display_name, url provider_name, url = choice
print(f"You selected: {provider_name}\tURL: {url}")
return provider_name, url
def ask_openai_reasoning_effort() -> str: def ask_openai_reasoning_effort() -> str:
@ -235,11 +241,13 @@ def ask_openai_reasoning_effort() -> str:
return questionary.select( return questionary.select(
"Select Reasoning Effort:", "Select Reasoning Effort:",
choices=choices, choices=choices,
style=questionary.Style([ style=questionary.Style(
("selected", "fg:cyan noinherit"), [
("highlighted", "fg:cyan noinherit"), ("selected", "fg:cyan noinherit"),
("pointer", "fg:cyan noinherit"), ("highlighted", "fg:cyan noinherit"),
]), ("pointer", "fg:cyan noinherit"),
]
),
).ask() ).ask()
@ -255,11 +263,13 @@ def ask_anthropic_effort() -> str | None:
questionary.Choice("Medium (balanced)", "medium"), questionary.Choice("Medium (balanced)", "medium"),
questionary.Choice("Low (faster, cheaper)", "low"), questionary.Choice("Low (faster, cheaper)", "low"),
], ],
style=questionary.Style([ style=questionary.Style(
("selected", "fg:cyan noinherit"), [
("highlighted", "fg:cyan noinherit"), ("selected", "fg:cyan noinherit"),
("pointer", "fg:cyan noinherit"), ("highlighted", "fg:cyan noinherit"),
]), ("pointer", "fg:cyan noinherit"),
]
),
).ask() ).ask()
@ -275,11 +285,13 @@ def ask_gemini_thinking_config() -> str | None:
questionary.Choice("Enable Thinking (recommended)", "high"), questionary.Choice("Enable Thinking (recommended)", "high"),
questionary.Choice("Minimal/Disable Thinking", "minimal"), questionary.Choice("Minimal/Disable Thinking", "minimal"),
], ],
style=questionary.Style([ style=questionary.Style(
("selected", "fg:green noinherit"), [
("highlighted", "fg:green noinherit"), ("selected", "fg:green noinherit"),
("pointer", "fg:green noinherit"), ("highlighted", "fg:green noinherit"),
]), ("pointer", "fg:green noinherit"),
]
),
).ask() ).ask()
@ -301,17 +313,24 @@ def ask_output_language() -> str:
questionary.Choice("Russian (Русский)", "Russian"), questionary.Choice("Russian (Русский)", "Russian"),
questionary.Choice("Custom language", "custom"), questionary.Choice("Custom language", "custom"),
], ],
style=questionary.Style([ style=questionary.Style(
("selected", "fg:yellow noinherit"), [
("highlighted", "fg:yellow noinherit"), ("selected", "fg:yellow noinherit"),
("pointer", "fg:yellow noinherit"), ("highlighted", "fg:yellow noinherit"),
]), ("pointer", "fg:yellow noinherit"),
]
),
).ask() ).ask()
if choice == "custom": if choice == "custom":
return questionary.text( return (
"Enter language name (e.g. Turkish, Vietnamese, Thai, Indonesian):", questionary.text(
validate=lambda x: len(x.strip()) > 0 or "Please enter a language name.", "Enter language name (e.g. Turkish, Vietnamese, Thai, Indonesian):",
).ask().strip() validate=lambda x: len(x.strip()) > 0
or "Please enter a language name.",
)
.ask()
.strip()
)
return choice return choice

1
tradingagents/dataflows/y_finance.py
View File

@ -2,6 +2,7 @@ from typing import Annotated
from datetime import datetime from datetime import datetime
from dateutil.relativedelta import relativedelta from dateutil.relativedelta import relativedelta
import yfinance as yf import yfinance as yf
import pandas as pd
import os import os
from .stockstats_utils import StockstatsUtils, _clean_dataframe, yf_retry, load_ohlcv, filter_financials_by_date from .stockstats_utils import StockstatsUtils, _clean_dataframe, yf_retry, load_ohlcv, filter_financials_by_date

2
tradingagents/llm_clients/factory.py
View File

@ -34,7 +34,7 @@ def create_llm_client(
""" """
provider_lower = provider.lower() provider_lower = provider.lower()
if provider_lower in ("openai", "ollama", "openrouter"): if provider_lower in ("openai", "ollama", "openrouter", "minimax"):
return OpenAIClient(model, base_url, provider=provider_lower, **kwargs) return OpenAIClient(model, base_url, provider=provider_lower, **kwargs)
if provider_lower == "xai": if provider_lower == "xai":

83
tradingagents/llm_clients/model_catalog.py
View File

@ -20,19 +20,31 @@ MODEL_OPTIONS: ProviderModeOptions = {
("GPT-5.4 - Latest frontier, 1M context", "gpt-5.4"), ("GPT-5.4 - Latest frontier, 1M context", "gpt-5.4"),
("GPT-5.2 - Strong reasoning, cost-effective", "gpt-5.2"), ("GPT-5.2 - Strong reasoning, cost-effective", "gpt-5.2"),
("GPT-5.4 Mini - Fast, strong coding and tool use", "gpt-5.4-mini"), ("GPT-5.4 Mini - Fast, strong coding and tool use", "gpt-5.4-mini"),
("GPT-5.4 Pro - Most capable, expensive ($30/$180 per 1M tokens)", "gpt-5.4-pro"), (
"GPT-5.4 Pro - Most capable, expensive ($30/$180 per 1M tokens)",
"gpt-5.4-pro",
),
], ],
}, },
"anthropic": { "anthropic": {
"quick": [ "quick": [
("Claude Sonnet 4.6 - Best speed and intelligence balance", "claude-sonnet-4-6"), (
"Claude Sonnet 4.6 - Best speed and intelligence balance",
"claude-sonnet-4-6",
),
("Claude Haiku 4.5 - Fast, near-instant responses", "claude-haiku-4-5"), ("Claude Haiku 4.5 - Fast, near-instant responses", "claude-haiku-4-5"),
("Claude Sonnet 4.5 - Agents and coding", "claude-sonnet-4-5"), ("Claude Sonnet 4.5 - Agents and coding", "claude-sonnet-4-5"),
], ],
"deep": [ "deep": [
("Claude Opus 4.6 - Most intelligent, agents and coding", "claude-opus-4-6"), (
"Claude Opus 4.6 - Most intelligent, agents and coding",
"claude-opus-4-6",
),
("Claude Opus 4.5 - Premium, max intelligence", "claude-opus-4-5"), ("Claude Opus 4.5 - Premium, max intelligence", "claude-opus-4-5"),
("Claude Sonnet 4.6 - Best speed and intelligence balance", "claude-sonnet-4-6"), (
"Claude Sonnet 4.6 - Best speed and intelligence balance",
"claude-sonnet-4-6",
),
("Claude Sonnet 4.5 - Agents and coding", "claude-sonnet-4-5"), ("Claude Sonnet 4.5 - Agents and coding", "claude-sonnet-4-5"),
], ],
}, },
@ -40,11 +52,17 @@ MODEL_OPTIONS: ProviderModeOptions = {
"quick": [ "quick": [
("Gemini 3 Flash - Next-gen fast", "gemini-3-flash-preview"), ("Gemini 3 Flash - Next-gen fast", "gemini-3-flash-preview"),
("Gemini 2.5 Flash - Balanced, stable", "gemini-2.5-flash"), ("Gemini 2.5 Flash - Balanced, stable", "gemini-2.5-flash"),
("Gemini 3.1 Flash Lite - Most cost-efficient", "gemini-3.1-flash-lite-preview"), (
"Gemini 3.1 Flash Lite - Most cost-efficient",
"gemini-3.1-flash-lite-preview",
),
("Gemini 2.5 Flash Lite - Fast, low-cost", "gemini-2.5-flash-lite"), ("Gemini 2.5 Flash Lite - Fast, low-cost", "gemini-2.5-flash-lite"),
], ],
"deep": [ "deep": [
("Gemini 3.1 Pro - Reasoning-first, complex workflows", "gemini-3.1-pro-preview"), (
"Gemini 3.1 Pro - Reasoning-first, complex workflows",
"gemini-3.1-pro-preview",
),
("Gemini 3 Flash - Next-gen fast", "gemini-3-flash-preview"), ("Gemini 3 Flash - Next-gen fast", "gemini-3-flash-preview"),
("Gemini 2.5 Pro - Stable pro model", "gemini-2.5-pro"), ("Gemini 2.5 Pro - Stable pro model", "gemini-2.5-pro"),
("Gemini 2.5 Flash - Balanced, stable", "gemini-2.5-flash"), ("Gemini 2.5 Flash - Balanced, stable", "gemini-2.5-flash"),
@ -52,25 +70,46 @@ MODEL_OPTIONS: ProviderModeOptions = {
}, },
"xai": { "xai": {
"quick": [ "quick": [
("Grok 4.1 Fast (Non-Reasoning) - Speed optimized, 2M ctx", "grok-4-1-fast-non-reasoning"), (
("Grok 4 Fast (Non-Reasoning) - Speed optimized", "grok-4-fast-non-reasoning"), "Grok 4.1 Fast (Non-Reasoning) - Speed optimized, 2M ctx",
("Grok 4.1 Fast (Reasoning) - High-performance, 2M ctx", "grok-4-1-fast-reasoning"), "grok-4-1-fast-non-reasoning",
),
(
"Grok 4 Fast (Non-Reasoning) - Speed optimized",
"grok-4-fast-non-reasoning",
),
(
"Grok 4.1 Fast (Reasoning) - High-performance, 2M ctx",
"grok-4-1-fast-reasoning",
),
], ],
"deep": [ "deep": [
("Grok 4 - Flagship model", "grok-4-0709"), ("Grok 4 - Flagship model", "grok-4-0709"),
("Grok 4.1 Fast (Reasoning) - High-performance, 2M ctx", "grok-4-1-fast-reasoning"), (
"Grok 4.1 Fast (Reasoning) - High-performance, 2M ctx",
"grok-4-1-fast-reasoning",
),
("Grok 4 Fast (Reasoning) - High-performance", "grok-4-fast-reasoning"), ("Grok 4 Fast (Reasoning) - High-performance", "grok-4-fast-reasoning"),
("Grok 4.1 Fast (Non-Reasoning) - Speed optimized, 2M ctx", "grok-4-1-fast-non-reasoning"), (
"Grok 4.1 Fast (Non-Reasoning) - Speed optimized, 2M ctx",
"grok-4-1-fast-non-reasoning",
),
], ],
}, },
"openrouter": { "openrouter": {
"quick": [ "quick": [
("NVIDIA Nemotron 3 Nano 30B (free)", "nvidia/nemotron-3-nano-30b-a3b:free"), (
"NVIDIA Nemotron 3 Nano 30B (free)",
"nvidia/nemotron-3-nano-30b-a3b:free",
),
("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"), ("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"),
], ],
"deep": [ "deep": [
("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"), ("Z.AI GLM 4.5 Air (free)", "z-ai/glm-4.5-air:free"),
("NVIDIA Nemotron 3 Nano 30B (free)", "nvidia/nemotron-3-nano-30b-a3b:free"), (
"NVIDIA Nemotron 3 Nano 30B (free)",
"nvidia/nemotron-3-nano-30b-a3b:free",
),
], ],
}, },
"ollama": { "ollama": {
@ -85,6 +124,18 @@ MODEL_OPTIONS: ProviderModeOptions = {
("Qwen3:latest (8B, local)", "qwen3:latest"), ("Qwen3:latest (8B, local)", "qwen3:latest"),
], ],
}, },
"minimax": {
"quick": [
("Kilo Auto Free (Limited Free Inference)", "kilo-auto/free"),
("Kilo Auto Balanced (Affordable Inference)", "kilo-auto/balanced"),
("MiniMax M2.7 (via Kilo Gateway)", "minimax/minimax-m2.7"),
],
"deep": [
("MiniMax M2.7 (via Kilo Gateway)", "minimax/minimax-m2.7"),
("Kilo Auto Balanced (Affordable Inference)", "kilo-auto/balanced"),
("Kilo Auto Free (Limited Free Inference)", "kilo-auto/free"),
],
},
} }
@ -97,11 +148,7 @@ def get_known_models() -> Dict[str, List[str]]:
"""Build known model names from the shared CLI catalog.""" """Build known model names from the shared CLI catalog."""
return { return {
provider: sorted( provider: sorted(
{ {value for options in mode_options.values() for _, value in options}
value
for options in mode_options.values()
for _, value in options
}
) )
for provider, mode_options in MODEL_OPTIONS.items() for provider, mode_options in MODEL_OPTIONS.items()
} }

11
tradingagents/llm_clients/openai_client.py
View File

@ -18,10 +18,16 @@ class NormalizedChatOpenAI(ChatOpenAI):
def invoke(self, input, config=None, **kwargs): def invoke(self, input, config=None, **kwargs):
return normalize_content(super().invoke(input, config, **kwargs)) return normalize_content(super().invoke(input, config, **kwargs))
# Kwargs forwarded from user config to ChatOpenAI # Kwargs forwarded from user config to ChatOpenAI
_PASSTHROUGH_KWARGS = ( _PASSTHROUGH_KWARGS = (
"timeout", "max_retries", "reasoning_effort", "timeout",
"api_key", "callbacks", "http_client", "http_async_client", "max_retries",
"reasoning_effort",
"api_key",
"callbacks",
"http_client",
"http_async_client",
) )
# Provider base URLs and API key env vars # Provider base URLs and API key env vars
@ -29,6 +35,7 @@ _PROVIDER_CONFIG = {
"xai": ("https://api.x.ai/v1", "XAI_API_KEY"), "xai": ("https://api.x.ai/v1", "XAI_API_KEY"),
"openrouter": ("https://openrouter.ai/api/v1", "OPENROUTER_API_KEY"), "openrouter": ("https://openrouter.ai/api/v1", "OPENROUTER_API_KEY"),
"ollama": ("http://localhost:11434/v1", None), "ollama": ("http://localhost:11434/v1", None),
"minimax": ("https://api.kilo.ai/api/gateway", "KILO_API_KEY"),
} }