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https://github.com/TauricResearch/TradingAgents.git
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Surface Federal Reserve Economic Data (rates, inflation, labor, growth) to the news analyst via a new get_macro_indicators tool and a macro_data vendor category. Friendly aliases (cpi, unemployment, fed_funds_rate, 10y_treasury, yield_curve, ...) map to FRED series IDs; raw series IDs are accepted too. The report gives the latest value, change over the window, and a recent observation table. Windowing is lookahead-safe (observation_end = curr_date), missing values are skipped, and a missing FRED_API_KEY surfaces as a clear not-configured condition through the vendor router rather than a crash.
58 lines
2.2 KiB
Plaintext
58 lines
2.2 KiB
Plaintext
# LLM Providers (set the one you use)
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OPENAI_API_KEY=
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GOOGLE_API_KEY=
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ANTHROPIC_API_KEY=
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XAI_API_KEY=
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DEEPSEEK_API_KEY=
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DASHSCOPE_API_KEY=
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DASHSCOPE_CN_API_KEY=
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ZHIPU_API_KEY=
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ZHIPU_CN_API_KEY=
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MINIMAX_API_KEY=
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MINIMAX_CN_API_KEY=
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OPENROUTER_API_KEY=
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MISTRAL_API_KEY=
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MOONSHOT_API_KEY=
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GROQ_API_KEY=
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NVIDIA_API_KEY=
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# FRED (Federal Reserve macro data: rates, inflation, labor, growth). Free key: https://fred.stlouisfed.org/docs/api/api_key.html
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#FRED_API_KEY=
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# Optional: a custom OpenAI-compatible endpoint (vLLM, LM Studio, llama.cpp,
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# relay). Select provider "openai_compatible" and set the base URL; the key is
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# optional (local servers need none).
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#OPENAI_COMPATIBLE_API_KEY=
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# AWS Bedrock (provider "bedrock", install with: pip install ".[bedrock]").
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# Auth uses the standard AWS credential chain; set the region (and optionally a
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# named profile). No single API key.
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#AWS_DEFAULT_REGION=us-west-2
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#AWS_PROFILE=
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# Optional: point at a remote Ollama server. When unset, defaults to
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# the local instance at http://localhost:11434/v1. Convention follows
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# the broader Ollama ecosystem; both the CLI dropdown and programmatic
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# client pick this up.
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#OLLAMA_BASE_URL=http://your-ollama-host:11434/v1
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# Optional: override DEFAULT_CONFIG without editing code.
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# Any TRADINGAGENTS_* variable below, when set, replaces the matching key
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# in tradingagents/default_config.py. Values are coerced to the type of
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# the existing default (bool / int / str), so "true"/"3" work as expected.
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# In the CLI, setting the LLM provider / models / backend URL / language
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# also skips the matching interactive selection step (useful for
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# OpenAI-compatible endpoints like opencode or LM Studio, and unattended runs).
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#TRADINGAGENTS_LLM_PROVIDER=openai
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#TRADINGAGENTS_DEEP_THINK_LLM=gpt-5.4
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#TRADINGAGENTS_QUICK_THINK_LLM=gpt-5.4-mini
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#TRADINGAGENTS_LLM_BACKEND_URL=
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#TRADINGAGENTS_OUTPUT_LANGUAGE=English
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#TRADINGAGENTS_MAX_DEBATE_ROUNDS=1
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#TRADINGAGENTS_MAX_RISK_ROUNDS=1
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#TRADINGAGENTS_CHECKPOINT_ENABLED=false
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# Sampling temperature (lower = less run-to-run variation on models that
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# honor it). Unset leaves each provider at its default. See the README
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# "Reproducibility" note — no setting makes LLM output fully deterministic.
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#TRADINGAGENTS_TEMPERATURE=0.0
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