- docstrings, comments, messages and the README section use "memory log", matching TradingMemoryLog and memory_log_path
- the write, read and settle paths are named for what they do, not by design phase
- gpt-6-sol and gpt-6-luna are the new default deep and quick models
- claude-opus-5-5 replaces claude-opus-5 in the picker; opus-5 and gpt-5.4-mini stay known as legacy IDs
- point-in-time integrity across every dated path, and a vendor failure reported as a vendor failure
- SEC EDGAR fundamentals served as filed
- backtesting over a ticker and date grid, and the caller's portfolio as run input
- current model lineups across every provider
- the custom model option does not exist for every provider; name any model ID instead
- alpha is measured against the regional benchmark, not always SPY
- the environment overrides a fixed set of config keys
- list the providers the picker offers, and the macro data key
- drop the example call to a method that was removed
- CI gate, unified verified data-access contract, provider and data-vendor registry
- env-over-CLI config precedence, current-generation model catalog
- programmatic report output, plus sweep fixes for data and structured output
The README reproducibility example named gpt-4.1 and the structured-output smoke
script listed gemini-2.5-flash / deepseek-chat / qwen-plus / grok-4 — all retired
from the catalog. Generalize the note and refresh the smoke defaults.
Verified each provider's hard-coded list against current official docs:
- MiniMax: add MiniMax-M3 (1M ctx, multimodal) as the default; keep M2.7 line.
- Qwen: use the live qwen{3.7,3.6}-{plus,max} IDs.
- GLM: add glm-5.2 as the latest flagship.
- xAI: drop deprecated grok-4-fast-* / grok-4-0709 builds.
- DeepSeek: migrate to deepseek-v4-pro / deepseek-v4-flash (the chat/reasoner
aliases are deprecated 2026-07-24 and now map to V4 Flash).
OpenAI, Anthropic, and Gemini were already current and are unchanged.
Bedrock uses the Converse API (langchain-aws) and the AWS credential chain, so
it has its own client like Anthropic/Google rather than the OpenAI-compatible
registry. langchain-aws is an optional dependency (pip install ".[bedrock]"),
lazy-imported with a clear install hint; importing the package never requires
it. The model name is a Bedrock model ID / inference profile ID.
Each is a one-row entry in the OpenAI-compatible provider registry (base_url,
key env, CLI option); the model is user-specified since they serve many models.
The OpenAI-compatible family (openai, xAI, DeepSeek, Qwen, GLM, MiniMax,
OpenRouter, Ollama) all speak the same Chat Completions API and differ only by
base_url, key, and two narrow wire-format quirks already isolated in subclasses.
Replace the scattered base-URL dict, key handling, and client-class branches with
one ProviderSpec registry that get_llm and the factory drive off; provider quirks
stay in their subclasses. Add a generic "openai_compatible" provider for any
OpenAI-compatible server (vLLM, LM Studio, llama.cpp, relays) via backend_url +
optional key — adding a provider is now one registry row. Native Anthropic/Google
keep their own clients (genuinely different APIs). Also fixes the env backend URL
being ignored when the provider was chosen interactively (#978).
GitHub Actions: pytest across Python 3.10-3.13, a clean-install import smoke
that catches undeclared runtime deps, and a strict Ruff gate (standard rule set)
scoped to the files each PR changes. Declares python-dotenv (imported by the CLI
but previously undeclared) and adds a [dev] extra. Recommends Python 3.12 for
setup, verified from a clean isolated install.
A-shares already resolve through the Yahoo Finance vendor (Shanghai .SS,
Shenzhen .SZ) with correct identity and indicators; add the SSE/SZSE
composite benchmarks so their alpha isn't measured against SPY, and
document the exchange-suffix tickers we support (incl. A-shares, crypto).
Adds a cross-provider temperature config (and TRADINGAGENTS_TEMPERATURE),
forwarded to every LLM client when set, so runs can be made less variable
on models that honor it. Adds a README "Reproducibility" section that
separates the sources of run-to-run variation, what users can control
(temperature, non-reasoning model, pinned date), and what is inherent to
LLM-driven analysis, and notes that the identity and verified-data fixes
already removed the "different companies / fabricated prices" variance.
#178#168
Headline themes in v0.2.5:
- Sentiment Analyst grounded in real data. Renamed from social_media_analyst
and redesigned to pre-fetch Yahoo News, StockTwits, and Reddit before the
LLM is invoked, ending the prior fabrication behavior.
- MiniMax provider with full M2.x catalog and dual-region split. Qwen and
GLM also split into international + China regions with separate API keys
and a clean secondary region prompt in the CLI.
- TRADINGAGENTS_* env-var overlay for DEFAULT_CONFIG with type-aware
coercion; .env loading centralized so every entry point sees the user's
keys. Interactive API-key detection prompts and persists missing keys
to .env on the fly.
- OLLAMA_BASE_URL end-to-end for remote ollama-serve, plus a Custom model
ID option in the Ollama dropdown.
- Configurable news-fetch parameters and configurable alpha benchmark for
non-US tickers (.NS / .T / .HK / .L / .TO / .AX / .BO ship with sensible
regional defaults).
- Multi-language output now propagates to every user-facing agent
(researchers, risk debators, research manager, trader) instead of only
the analysts and portfolio manager.
- Model catalog refresh across all providers (GPT-5.5 frontier, Claude
Opus 4.7, Gemini 3.1 Flash-Lite GA, Grok 4.20, Qwen 3.6 line).
- Capability-dispatch table drives provider-specific structured-output
quirks (DeepSeek V4/reasoner and MiniMax M2.x tool_choice rejection,
MiniMax reasoning_split) so the general client stays clean.
- Fixes: ticker path-traversal validation (security), dotenv loading via
console script, reports save bug, exchange-suffix truncation in the
ticker prompt, Docker permission errors, deepcopy config isolation,
max_recur_limit plumbing, clearer missing-API-key error.
See CHANGELOG.md for the full per-item list with issue/PR references.
The Required APIs section now mentions the default endpoint,
OLLAMA_BASE_URL for remote ollama-serve, ollama pull, and the
Custom model ID dropdown option, replacing the previous one-liner
that left those details implicit.
The agent ingests news, StockTwits, and Reddit, but CLI labels, the
README description, and the legacy shim docstring still framed it as
social-media-only. Updates all user-visible surfaces so the name and
the implementation match.
Zhipu serves GLM under two brands with separate accounts (Z.AI
international vs BigModel China); the CLI URL pointed at one while
the openai_client default pointed at the other. Split into glm +
glm-cn with secondary region prompt (same UX as Qwen + MiniMax).
Catalog adds glm-5-turbo and glm-4.5-air per docs.z.ai.
M2.x tool_choice is enum-only (none/auto), so route through the
no-tool_choice dispatch. MinimaxChatOpenAI injects reasoning_split
so <think> blocks stay out of content. Catalog rounded out to the
full official M2.x lineup plus forward-compat regex.
Two regional endpoints (global api.minimax.io, China api.minimaxi.com)
with separate API keys. Models M2.7 / M2.5 plus -highspeed variants,
204K context. Follows the existing provider-preset pattern.
#789#609#577#546#395#378
This release bundles substantial work since v0.2.3:
- Structured-output Research Manager, Trader, and Portfolio Manager
(canonical with_structured_output pattern, single LLM call per agent,
rendered markdown preserves the existing report shape).
- LangGraph checkpoint resume for crash recovery (--checkpoint flag).
- Persistent decision log replacing the per-agent BM25 memory, with
deferred reflection driven by yfinance returns + alpha vs SPY.
- DeepSeek, Qwen, GLM, and Azure OpenAI provider support; dynamic
OpenRouter model selection.
- Docker support; cache and logs moved to ~/.tradingagents/ to fix
Docker permission issues.
- Windows UTF-8 encoding fix on every file I/O site.
- 5-tier rating consistency (Buy / Overweight / Hold / Underweight / Sell)
across Research Manager, Portfolio Manager, signal processor, memory log.
Plus the small quality items in this commit:
1. Suppress noisy Pydantic serializer warnings from OpenAI Responses-API
parse path by defaulting structured-output to method="function_calling"
(root-cause fix, not a warnings filter — same typed result, no warnings).
2. Ship scripts/smoke_structured_output.py so contributors can verify
their provider's structured-output path with one command.
3. Add opt-in memory_log_max_entries config — when set, oldest resolved
memory log entries are pruned once the cap is exceeded; pending
entries (unresolved) are never pruned.
4. backend_url default changed from the OpenAI URL to None so the
per-provider client falls back to its native endpoint instead of
leaking OpenAI's URL into Gemini / other clients.
CHANGELOG.md added with the full v0.2.4 entry. 92 tests pass without API keys.
Long analyses can take many minutes; a crash or interruption forced users
to re-run from scratch and re-pay every LLM call. This adds an opt-in
checkpoint layer backed by per-ticker SQLite databases so the graph
resumes from the last successful node.
How to use:
- CLI: tradingagents analyze --checkpoint
- CLI: tradingagents analyze --clear-checkpoints
- Python: config["checkpoint_enabled"] = True
Lifecycle:
- propagate() recompiles the graph with a SqliteSaver when enabled and
injects a deterministic thread_id derived from ticker+date so the
same ticker+date resumes while a different date starts fresh.
- On successful completion the per-thread checkpoint rows are cleared.
- The context manager is closed in a try/finally so a crash never
leaks the SQLite connection or leaves the graph in checkpoint mode.
Storage: ~/.tradingagents/cache/checkpoints/<TICKER>.db
(override via TRADINGAGENTS_CACHE_DIR).
The checkpointer module is new (tradingagents/graph/checkpointer.py)
and the GraphSetup now returns the uncompiled workflow so it can be
recompiled with a saver when needed.
Adds langgraph-checkpoint-sqlite>=2.0.0 dependency. 3 new tests verify
the crash/resume cycle and that a different date starts fresh.
- Point requirements.txt to pyproject.toml as single source of truth
- Resolve welcome.txt path relative to module for CLI portability
- Include cli/static files in package build
- Extract shared normalize_content for OpenAI Responses API and
Gemini 3 list-format responses into base_client.py
- Update README install and CLI usage instructions
Yijia-Xiao
Edward Sun