An LLM-powered automated quarterly earnings review tool for Chinese A-share companies. Enter a company name or stock code with a reporting period, and it collects financial data and generates a professional research report.

• Automated data collection - Calls 28 AKShare financial data interfaces, covering income statements, balance sheets, cash flow statements, financial indicators, peer comparisons, earnings forecasts, and more.
• ReAct data completion - A Phase 2 ReAct loop lets the LLM decide which extra data to collect, with up to 30 tool calls.
• Professional report generation - Produces a 5-section report: performance and operations, outlook and investment thesis, earnings forecast and valuation, risk factors, and executive summary.
• Traceable data citations - Each analysis paragraph includes DATA_REFS references that trace back to specific data sources.
• File-based caching - Uses three TTL tiers (7 days / 1 day / 1 hour) to avoid repeated API calls.
• Flexible LLM configuration - Supports OpenAI-compatible APIs and configurable models.

git clone https://github.com/DreamWalkerXZ/a-share-analyst.git
cd a-share-analyst
uv sync

cp .env.example .env

Edit .env and set the required API keys:

Optional LangSmith tracing variables are documented in .env.example.

# Use a company name
uv run main.py "贵州茅台 2025 Q4"

# Use a stock code
uv run main.py "600519 2025 Q4"

Reports are written to the output/ directory. Example:

output/贵州茅台_2025Q4_20260426_231909.md

uv run main.py "<company name or stock code> <year> <quarter>"

Supported quarters: Q1, Q2, Q3, Q4.

Force fresh data collection and skip the local cache:

DISABLE_DATA_CACHE=1 uv run main.py "贵州茅台 2025 Q4"

graph LR;
    data_collection[data_collection<br>Phase 1: 12 AKShare pre-fetch<br>Phase 2: ReAct loop]
    report_generation[report_generation<br>Sections 1-4 then Section 0<br>LLM validate + retry]
    output[output<br>Assemble Markdown + refs]

    data_collection --> report_generation --> output

Data collection is orchestrated with LangGraph. In Phase 2, the LLM schedules calls across three tools:

uv run pytest

src/
├── agent/          # LangGraph workflow: graph, nodes, subgraph, state
├── prompts/        # LLM prompts for data collection and report sections
├── tools/          # Tool wrappers for AKShare, Serper search, and calculator
└── utils/          # Utilities for LLM factory, cache, and data formatting

• Python 3.11+
• LangGraph - Workflow orchestration
• LangChain + langchain-openai - LLM calls
• AKShare - Chinese A-share financial data
• simpleeval - Safe expression evaluation