| # Changelog |
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| All notable changes to this project will be documented in this file. |
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| ## [Phase 6] - Earnings Call Analysis Integration |
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| ### Architecture |
| * **Two-Pipeline Design:** Added a new `Earnings_Agent` backed by an offline ingest pipeline and a runtime inference pipeline, following the same separation pattern as the existing 10-K RAG system. |
| * **Ingest Layer (`core/earnings_tools.py`):** Fetches transcripts from Alpha Vantage (premium) or SEC 8-K filings (free fallback), normalizes them into `Prepared Remarks` and `Q&A Session` segments, extracts keyword frequency counts, and embeds everything into a dedicated ChromaDB collection. |
| * **Inference Layer:** Three new `@tool` functions — `search_earnings_call` (RAG search), `get_earnings_sentiment_divergence` (section comparison), and `get_earnings_keyword_trends` (cross-quarter keyword tracking). |
| * **Graph Extension:** Added `Earnings_Agent` to the LangGraph `members` list, planner capability map, supervisor dispatch edges, and summarizer prompt. |
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| ### Added |
| * `core/earnings_tools.py` — Combined ingest + inference module for earnings-call data. |
| * `scripts/ingest_earnings_calls.py` — CLI tool for batch ingestion (`--tickers AAPL --quarters Q1-2025 Q2-2025`). |
| * Earnings-call example button in the Streamlit sidebar for quick testing. |
| * `ALPHA_VANTAGE_API_KEY` config setting in `.env.example` and `core/config.py`. |
| * Earnings Call Insights section in the Investment Memo (Summarizer) when earnings data is present. |
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| ### Changed |
| * **Planner Prompt:** Extended with `Earnings_Agent` capability mapping for earnings-call queries. |
| * **Summarizer Prompt:** New `## Earnings Call Insights` memo section for divergence and keyword findings. |
| * **Streamlit Sidebar:** Now detects and displays `_earnings` ChromaDB collections alongside `_10k` collections. |
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| ## [Phase 4] - Multi-Agent LangGraph Integration & SEC Pipeline Hardening |
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| ### Architecture Overhaul |
| * **Transitioned to LangGraph:** Replaced the legacy `while` loop with a deterministic StateGraph "Planner-Executor" architecture. |
| * **Dual-Node Governance:** Separated routing logic into a stateless `Planner` (generates JSON task arrays) and a stateful `Supervisor` (manages task queues), eliminating LLM cognitive overload and infinite routing loops. |
| * **Separation of Concerns:** Split worker capabilities into three strict React Agents: `Quant_Agent`, `Fundamental_Agent`, and `Sentiment_Agent`. |
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| ### Added |
| * **The "Honesty Guardrail":** Implemented programmatic checks in `make_worker_node` to verify `ToolMessage` execution. If an agent attempts to answer without triggering a tool, the output is blocked to prevent hallucination. |
| * **Strict Capability Matrix:** Updated the Planner prompt to explicitly map query types (e.g., "Risks", "Supply Chain") to specific RAG tool workflows. |
| * **Broad Query Protocol:** Added fallback logic for the Planner to execute standard Quant/Sentiment tasks when users ask for "general info" on a ticker. |
| * **Pydantic Enum Enforcement:** Added strict `args_schema` to SEC tools using `Literal` types to prevent the LLM from hallucinating invalid XBRL tags. |
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| ### Fixed |
| * **The SEC "2010 Bug":** The SEC API returns unordered historical data. Added Pandas-based datetime sorting, filing deduplication, and a 2-year lookback filter to ensure only modern data is served. |
| * **The SEC "Missing Revenue" Bug:** Implemented recursive fallback logic to try `RevenueFromContractWithCustomerIncludingAssessedTax` if the standard `Revenues` GAAP tag returns 404 (fixing data retrieval for MSFT, AAPL, etc.). |
| * **ChromaDB Deprecation:** Updated imports to `langchain_chroma` and improved SEC HTML `<DOCUMENT>` regex parsing for cleaner 10-K embeddings. |
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| ## [Phase 5] - API Streaming, Web UI & Containerization |
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| ### UI & Architecture |
| * **FastAPI Backend:** Exposed the LangGraph state machine via an asynchronous `GET /chat/stream` utilizing Server-Sent Events (SSE). |
| * **Streamlit Frontend:** Built a responsive agentic UI (`streamlit_app.py`) that visually streams the intermediate ReAct reasoning blocks into dynamically expanding dropdown menus. |
| * **State Persistence:** Rewrote the UI memory loop to preserve "Agent Thoughts" sequentially so historical messages contain dropdown logs linking exactly to how the agents generated their specific conclusions. |
| * **Docker Migration:** Shipped `Dockerfile.api` and `Dockerfile.ui` bridged via a custom network inside `docker-compose.yml`, successfully moving the application payload off MacOS and onto standardized, immutable infrastructure. |
| * **LLM Engine Swap:** Migrated the brain architecture permanently to Groq's `llama-3.1-8b-instant` and `llama3-70b-versatile` endpoints for incredibly fast serverless inference. |
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| ### Performance & Token Thrashing Fixes |
| * **LRU Caching:** Prevented the `SentenceTransformers` model from re-instantiating on disk during every RAG pipeline call, silencing repetitive console logs and saving heavy JVM/Python CPU overhead. |
| * **Groq 'Token Ghosting' Fix:** Squashed a massive token quota error ("Requested 17k tokens") by explicitly declaring `max_tokens=800`. This prevented Groq's load balancer from assuming maximum context window limits and throttling free-tier TPM budgets. |
| * **ReAct Infinite Loop Resolution:** The Fundamental agent historically trapped itself looping `search_10k_filings` tools when ordered to strictly "only output data". Bridged the behavior by injecting a hard "Stop once data is fetched" logic trap inside the system prompt. |
| * **Docker Hot-Reloading:** Injected `- ./:/app` mapping masks and explicitly overrode the Uvicorn execution loop with `--reload` to support real-time Python development without tearing down the containers. |
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| ### Next Steps 🚀 |
| * Final push of the `finagent` backend/frontend images to **Google Cloud Run**. |
