Fix app crash: lazy-init OpenAI client, fix delegation typo, add load_dotenv

- Move OpenAI client creation from module-level to inside _analyze_with_llm()
to prevent crash when OPENAI_API_KEY is not set at import time
- Fix allow_delegations (plural) typo to allow_delegation (singular) so
CrewAI actually enables delegation for market, sentiment, and historical agents
- Add load_dotenv() at top of app.py so .env files are loaded before env var access
- Add CLAUDE.md for Claude Code guidance

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

CLAUDE.md

@@ -0,0 +1,69 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+CrewAI-based multi-agent cryptocurrency analysis system with a Gradio web interface. Six specialized AI agents execute sequentially to fetch live market data, analyze historical trends, assess news sentiment, compute composite analytics, formulate trading strategy, and generate a narrative Markdown report.
+
+## Commands
+
+```bash
+# Setup
+python -m venv .venv && source .venv/bin/activate
+pip install -r requirements.txt
+
+# Run locally (launches Gradio on 0.0.0.0:7860)
+python app.py
+```
+
+No test suite or linter is configured. Testing is manual via the Gradio UI.
+
+## Required Environment Variables
+
+Set these before running (or use a `.env` file):
+- `OPENAI_API_KEY` — GPT-4 access for LLM agents and sentiment analysis
+- `SERPER_API_KEY` — Serper search API for fetching crypto news
+- `COINGECKO_API_KEY` — CoinGecko market data (optional but recommended)
+
+## Architecture
+
+**Entry point**: `app.py` — defines all agents, tasks, the CrewAI Crew, and the Gradio UI.
+
+### Agent Pipeline (sequential execution via CrewAI)
+
+```
+User Input (crypto name, currency, lookback days)
+  → Market Agent (gpt-4o-mini) + MarketDataTool     → live price, 24h volume
+  → Historical Agent (gpt-4o-mini) + HistoricalDataTool → price history, % change, volatility, trend
+  → Sentiment Agent (gpt-4.1) + SentimentTool       → news headlines, sentiment score, confidence
+  → Analytics Agent (gpt-4o-mini) + AnalyticsTool    → composite score, alignment, effective sentiment
+  → Strategy Agent (gpt-4.1)                         → trading bias, risk guidance
+  → Reporting Agent (gpt-4.1)                        → final Markdown report (narrative prose, no bullets)
+```
+
+### Tools (`tools/`)
+
+Each tool extends CrewAI's `BaseTool` and returns a structured JSON dict:
+
+| Tool | File | External API | Key Behavior |
+|------|------|-------------|--------------|
+| `MarketDataTool` | `market_data.py` | CoinGecko `/simple/price` | Fetches live price + 24h volume |
+| `HistoricalDataTool` | `historical_data_tool.py` | CoinGecko `/market_chart` | Computes % change, volatility (stdev of daily returns), trend classification |
+| `SentimentTool` | `sentiment_tool.py` | Serper + OpenAI GPT-4.1 | Fetches ~12 headlines, analyzes sentiment with LLM, validates/bounds scores |
+| `AnalyticsTool` | `analytics_tool.py` | None (aggregation) | Composite score = `(pct_change/10) + (effective_sentiment*1.5) - (volatility/100)`, bounded [-1,1] |
+
+### Data Flow
+
+Each tool returns a dict that downstream agents consume. The Analytics Agent aggregates all three data sources (market, historical, sentiment) into a single scored assessment. The Strategy and Reporting agents have no dedicated tools — they reason over prior agent outputs.
+
+## Deployment
+
+Supports HuggingFace Spaces (Gradio SDK). Set API keys as Space secrets. The `README.md` contains the HuggingFace Spaces metadata card.
+
+## Key Patterns
+
+- All tools use 10-second HTTP timeouts and return error dicts on failure
+- Sentiment tool has multi-layer fallbacks: graceful neutral defaults if API keys missing, JSON extraction with substring fallback, bounds validation on all scores
+- LLM model selection is hardcoded per agent in `app.py` (mix of `gpt-4o-mini` for data tasks, `gpt-4.1` for reasoning tasks)
+- The `generate_report()` function in `app.py` is the Gradio callback that instantiates and kicks off the Crew

app.py

@@ -1,6 +1,9 @@
 # import libraries, APis and LLMs
-from crewai import Agent, Task, Crew
 import os
+from dotenv import load_dotenv
+load_dotenv()
+
+from crewai import Agent, Task, Crew
 from tools.market_data import MarketDataTool
 from tools.sentiment_tool import SentimentTool
 from tools.historical_data_tool import HistoricalDataTool
@@ -36,7 +39,7 @@ market_agent = Agent(
         "including price and market liquidity."
     ),
     verbose=False,
-    allow_delegations=True,
+    allow_delegation=True,
     tools=[market_data_tool],
     llm="gpt-4o-mini"
 )
@@ -46,7 +49,7 @@ sentiment_agent = Agent(
     goal="Analyze public sentiment on news & Reddit using Serper + OpenAI. Output structured sentiment JSON.",
     backstory="An expert in NLP-based crypto sentiment interpretation.",
     verbose=False,
-    allow_delegations=True,
+    allow_delegation=True,
     tools=[sentiment_tool],
     llm="gpt-4.1"
 )
@@ -56,7 +59,7 @@ historical_agent = Agent(
     goal="Analyze long-term price trends, volatility, and movement patterns using clean structured JSON.",
     backstory="A quantitative analyst specializing in historical trends.",
     verbose=False,
-    allow_delegations=True,
+    allow_delegation=True,
     tools=[historical_data_tool],
     llm="gpt-4o-mini"
 )

tools/sentiment_tool.py

@@ -16,8 +16,6 @@ from openai import OpenAI
 SERPER_API_KEY = os.getenv("SERPER_API_KEY")
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
-client = OpenAI(api_key=OPENAI_API_KEY)
-
 
 # -----------------------------
 # Input Schema
@@ -85,6 +83,7 @@ class SentimentTool(BaseTool):
     # LLM Sentiment Aggregation
     # -----------------------------------------------------
     def _analyze_with_llm(self, coin: str, headlines: List[str]) -> Dict[str, Any]:
+        client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
 
         if not headlines:
             return {