@@ -82,6 +85,7 @@ Our framework decomposes complex trading tasks into specialized roles. This ensu
### Trader Agent + - Composes reports from the analysts and researchers to make informed trading decisions. It determines the timing and magnitude of trades based on comprehensive market insights.@@ -89,6 +93,7 @@ Our framework decomposes complex trading tasks into specialized roles. This ensu
### Risk Management and Portfolio Manager + - Continuously evaluates portfolio risk by assessing market volatility, liquidity, and other risk factors. The risk management team evaluates and adjusts trading strategies, providing assessment reports to the Portfolio Manager for final decision. - The Portfolio Manager approves/rejects the transaction proposal. If approved, the order will be sent to the simulated exchange and executed. @@ -101,18 +106,21 @@ Our framework decomposes complex trading tasks into specialized roles. This ensu ### Installation Clone TradingAgents: + ```bash git clone https://github.com/TauricResearch/TradingAgents.git cd TradingAgents ``` Create a virtual environment in any of your favorite environment managers: + ```bash conda create -n tradingagents python=3.13 conda activate tradingagents ``` Install the package and its dependencies: + ```bash pip install . ``` @@ -127,12 +135,15 @@ export GOOGLE_API_KEY=... # Google (Gemini) export ANTHROPIC_API_KEY=... # Anthropic (Claude) export XAI_API_KEY=... # xAI (Grok) export OPENROUTER_API_KEY=... # OpenRouter +export GROQ_API_KEY=... # Groq +export KILO_API_KEY=... # Kilo Gateway export ALPHA_VANTAGE_API_KEY=... # Alpha Vantage ``` For local models, configure Ollama with `llm_provider: "ollama"` in your config. Alternatively, copy `.env.example` to `.env` and fill in your keys: + ```bash cp .env.example .env ``` @@ -140,10 +151,12 @@ cp .env.example .env ### CLI Usage Launch the interactive CLI: + ```bash tradingagents # installed command python -m cli.main # alternative: run directly from source ``` + You will see a screen where you can select your desired tickers, analysis date, LLM provider, research depth, and more.@@ -164,7 +177,7 @@ An interface will appear showing results as they load, letting you track the age ### Implementation Details -We built TradingAgents with LangGraph to ensure flexibility and modularity. The framework supports multiple LLM providers: OpenAI, Google, Anthropic, xAI, OpenRouter, and Ollama. +We built TradingAgents with LangGraph to ensure flexibility and modularity. The framework supports multiple LLM providers: OpenAI, Google, Anthropic, xAI, OpenRouter, Groq, Kilo Gateway, and Ollama. ### Python Usage @@ -188,7 +201,7 @@ from tradingagents.graph.trading_graph import TradingAgentsGraph from tradingagents.default_config import DEFAULT_CONFIG config = DEFAULT_CONFIG.copy() -config["llm_provider"] = "openai" # openai, google, anthropic, xai, openrouter, ollama +config["llm_provider"] = "openai" # openai, google, anthropic, xai, openrouter, groq, kilo, ollama config["deep_think_llm"] = "gpt-5.2" # Model for complex reasoning config["quick_think_llm"] = "gpt-5-mini" # Model for quick tasks config["max_debate_rounds"] = 2 diff --git a/cli/main.py b/cli/main.py index 53837db2..713d3234 100644 --- a/cli/main.py +++ b/cli/main.py @@ -546,14 +546,19 @@ def get_user_selections(): ) selected_llm_provider, backend_url = select_llm_provider() + # Normalize provider name once for all uses (Kilo Gateway -> kilo) + normalized_provider = selected_llm_provider.lower().replace(" ", "") + if normalized_provider == "kilogateway": + normalized_provider = "kilo" + # Step 6: Thinking agents console.print( create_question_box( "Step 6: Thinking Agents", "Select your thinking agents for analysis" ) ) - selected_shallow_thinker = select_shallow_thinking_agent(selected_llm_provider) - selected_deep_thinker = select_deep_thinking_agent(selected_llm_provider) + selected_shallow_thinker = select_shallow_thinking_agent(normalized_provider) + selected_deep_thinker = select_deep_thinking_agent(normalized_provider) # Step 7: Provider-specific thinking configuration thinking_level = None @@ -586,12 +591,13 @@ def get_user_selections(): ) anthropic_effort = ask_anthropic_effort() + # Use already normalized provider from earlier return { "ticker": selected_ticker, "analysis_date": analysis_date, "analysts": selected_analysts, "research_depth": selected_research_depth, - "llm_provider": selected_llm_provider.lower(), + "llm_provider": normalized_provider, "backend_url": backend_url, "shallow_thinker": selected_shallow_thinker, "deep_thinker": selected_deep_thinker, @@ -635,19 +641,19 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path): analyst_parts = [] if final_state.get("market_report"): 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"])) if final_state.get("sentiment_report"): 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"])) if final_state.get("news_report"): 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"])) if final_state.get("fundamentals_report"): 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"])) if analyst_parts: content = "\n\n".join(f"### {name}\n{text}" for name, text in analyst_parts) @@ -660,15 +666,15 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path): research_parts = [] if debate.get("bull_history"): 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"])) if debate.get("bear_history"): 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"])) if debate.get("judge_decision"): 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"])) if research_parts: content = "\n\n".join(f"### {name}\n{text}" for name, text in research_parts) @@ -678,7 +684,7 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path): if final_state.get("trader_investment_plan"): trading_dir = save_path / "3_trading" 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']}") # 4. Risk Management @@ -688,15 +694,15 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path): risk_parts = [] if risk.get("aggressive_history"): 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"])) if risk.get("conservative_history"): 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"])) if risk.get("neutral_history"): 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"])) if risk_parts: content = "\n\n".join(f"### {name}\n{text}" for name, text in risk_parts) @@ -706,12 +712,12 @@ def save_report_to_disk(final_state, ticker: str, save_path: Path): if risk.get("judge_decision"): portfolio_dir = save_path / "5_portfolio" 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']}") # Write consolidated report 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" @@ -968,7 +974,7 @@ def run_analysis(): func(*args, **kwargs) timestamp, message_type, content = obj.messages[-1] 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") return wrapper @@ -979,7 +985,7 @@ def run_analysis(): func(*args, **kwargs) timestamp, tool_name, args = obj.tool_calls[-1] 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") return wrapper @@ -993,7 +999,7 @@ def run_analysis(): if content: file_name = f"{section_name}.md" 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) return wrapper diff --git a/cli/utils.py b/cli/utils.py index 18abc3a7..3c5d1ad2 100644 --- a/cli/utils.py +++ b/cli/utils.py @@ -162,6 +162,18 @@ def select_shallow_thinking_agent(provider) -> str: ("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"), ], + "groq": [ + ("Llama 3.1 8B Instant - Fastest, cheapest", "llama-3.1-8b-instant"), + ("Llama 3 8B - Simple tasks", "llama-3-8b-8192"), + ("Mixtral 8x7B - Fast mixture of experts", "mixtral-8x7b-32768"), + ("GPT-Oss 120B via Groq - Large model", "openai/gpt-oss-120b"), + ], + "kilo": [ + ("Llama 3.1 8B via Kilo - Fast", "llama-3.1-8b-instant"), + ("Claude Haiku via Kilo - Fast", "anthropic/claude-haiku-4-5"), + ("Gemini 2.5 Flash via Kilo - Balanced", "google/gemini-2.5-flash"), + ("MiniMax M2.5 via Kilo - Free", "minimax/minimax-m2.5:free"), + ], "openrouter": [ ("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"), @@ -229,6 +241,20 @@ def select_deep_thinking_agent(provider) -> str: ("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"), ], + "groq": [ + ("Llama 3.3 70B Versatile - Best overall", "llama-3.3-70b-versatile"), + ("Llama 3.1 70B Versatile - Strong reasoning", "llama-3.1-70b-versatile"), + ("Mixtral 8x22B - Large mixture of experts", "mixtral-8x22b-32768"), + ("Llama 3.1 8B Instant - Fastest", "llama-3.1-8b-instant"), + ("GPT-Oss 120B via Groq - Large model", "openai/gpt-oss-120b"), + ], + "kilo": [ + ("Claude Sonnet 4.5 via Kilo - Balanced", "anthropic/claude-sonnet-4-5"), + ("Claude Opus 4.5 via Kilo - Most capable", "anthropic/claude-opus-4-5"), + ("GPT-5 Mini via Kilo - Fast", "openai/gpt-5-mini"), + ("Gemini 2.5 Pro via Kilo - Reasoning", "google/gemini-2.5-pro"), + ("MiniMax M2.5 via Kilo - Free", "minimax/minimax-m2.5:free"), + ], "openrouter": [ ("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"), @@ -270,6 +296,8 @@ def select_llm_provider() -> tuple[str, str]: ("Google", "https://generativelanguage.googleapis.com/v1"), ("Anthropic", "https://api.anthropic.com/"), ("xAI", "https://api.x.ai/v1"), + ("Groq", "https://api.groq.com/openai/v1"), + ("Kilo Gateway", "https://api.kilo.ai/api/gateway"), ("Openrouter", "https://openrouter.ai/api/v1"), ("Ollama", "http://localhost:11434/v1"), ] diff --git a/tradingagents/llm_clients/factory.py b/tradingagents/llm_clients/factory.py index 93c2a7d3..31d24898 100644 --- a/tradingagents/llm_clients/factory.py +++ b/tradingagents/llm_clients/factory.py @@ -34,7 +34,7 @@ def create_llm_client( """ provider_lower = provider.lower() - if provider_lower in ("openai", "ollama", "openrouter"): + if provider_lower in ("openai", "ollama", "openrouter", "groq", "kilo"): return OpenAIClient(model, base_url, provider=provider_lower, **kwargs) if provider_lower == "xai": diff --git a/tradingagents/llm_clients/openai_client.py b/tradingagents/llm_clients/openai_client.py index fd9b4e33..505c3765 100644 --- a/tradingagents/llm_clients/openai_client.py +++ b/tradingagents/llm_clients/openai_client.py @@ -29,6 +29,8 @@ _PROVIDER_CONFIG = { "xai": ("https://api.x.ai/v1", "XAI_API_KEY"), "openrouter": ("https://openrouter.ai/api/v1", "OPENROUTER_API_KEY"), "ollama": ("http://localhost:11434/v1", None), + "groq": ("https://api.groq.com/openai/v1", "GROQ_API_KEY"), + "kilo": ("https://api.kilo.ai/api/gateway", "KILO_API_KEY"), } diff --git a/tradingagents/llm_clients/validators.py b/tradingagents/llm_clients/validators.py index 1e2388b3..fe300f39 100644 --- a/tradingagents/llm_clients/validators.py +++ b/tradingagents/llm_clients/validators.py @@ -48,17 +48,29 @@ VALID_MODELS = { "grok-4-fast-reasoning", "grok-4-fast-non-reasoning", ], + "groq": [ + # Llama series (hosted by Groq) + "llama-3.3-70b-versatile", + "llama-3.1-70b-versatile", + "llama-3.1-8b-instant", + "llama-3-8b-8192", + # Mixtral series (hosted by Groq) + "mixtral-8x7b-32768", + "mixtral-8x22b-32768", + # Other models via Groq + "openai/gpt-oss-120b", + ], } def validate_model(provider: str, model: str) -> bool: """Check if model name is valid for the given provider. - For ollama, openrouter - any model is accepted. + For ollama, openrouter, kilo - any model is accepted. """ provider_lower = provider.lower() - if provider_lower in ("ollama", "openrouter"): + if provider_lower in ("ollama", "openrouter", "kilo"): return True if provider_lower not in VALID_MODELS: