Iniitial commit: CRYPTO_ANALYST_AGENT

.gitignore

@@ -0,0 +1,20 @@
+# python
+__pycache__/
+*.pyc
+
+# gradio artifacts
+.gradio/
+
+# certs / keys
+*.pem
+*.key
+*.crt
+
+# env/secrets
+.env
+*.env
+
+# OS/IDE
+.DS_Store
+.vscode/
+.idea/

README.md

@@ -11,4 +11,89 @@ license: apache-2.0
 short_description: Collect data, analyze and report on crypto
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Crypto Analyst Agent 📈
+
+An interactive **Gradio** app that collects crypto market information, runs analysis (pricing + indicators + sentiment), and generates a concise report to support research and decision-making.
+
+> ⚠️ Educational project only — not financial advice.
+
+## What it does
+- **Fetches market data** (price, market cap, volume, etc.)
+- **Pulls historical data** for trend/returns analysis
+- **Runs analytics** (basic performance + volatility-style metrics depending on configuration)
+- **Incorporates sentiment signals** (tool-based sentiment module)
+- **Generates a structured report** in a single workflow
+
+## Project structure
+```text
+.
+├── app.py
+├── tools/
+│   ├── __init__.py
+│   ├── market_data.py
+│   ├── historical_data_tool.py
+│   ├── analytics_tool.py
+│   └── sentiment_tool.py
+├── requirements.txt
+└── README.md
+```
+
+## Getting started (local)
+### 1. Clone and install
+```bash
+git clone https://github.com/cicboy80/CRYPTO_ANALYST_AGENT.git
+cd CRYPTO_ANALYST_AGENT
+python -m venv .venv
+source .venv/bin/activate   # macOS/Linux
+# .venv\Scripts\activate    # Windows
+pip install -r requirements.txt
+```
+
+### 2. Environment variables
+
+This project uses API keys for **OpenAI** and **CoinGecko**.
+
+Set these as environment variables (recommended), or create a local `.env` file (**do not commit it**).
+
+Required:
+- `OPENAI_API_KEY`
+- `COINGECKO_API_KEY`
+
+Example:
+```bash
+export OPENAI_API_KEY="..."
+export COINGECKO_API_KEY="..."
+```
+
+### 3. Run the app
+```bash
+python app.py
+```
+
+Then open the local Gradio URL printed in the terminal.
+
+## Hugging Face Spaces: Secrets setup
+Add the following under **Settings → Secrets** in your Space:
+- `OPENAI_API_KEY`
+- `COINGECKO_API_KEY`
+
+## Deploying on Hugging Face Spaces
+
+1. Create a new **Gradio** Space
+2. Add your repo files (`app.py`, `tools/`, `requirements.txt`, `README.md`)
+3. Add required keys under Settings → Secrets
+
+## Notes on security
+
+- Never commit secrets (API keys, tokens, .env, certificates)
+- Keep credentials in Hugging Face Secrets (or your cloud provider’s secret manager)
+
+## Roadmap
+
+- Add caching for API responses
+- Expand analytics (risk metrics, drawdown, rolling volatility)
+- Improve reporting format (markdown + export)
+
+## License
+
+Apache-2.0

app.py

@@ -256,7 +256,7 @@ with gr.Blocks(theme=gr.themes.Monochrome()) as app:
             label="Historical Lookback (days)"
         )
 
-    # ← original working button
+    # button
     run_button = gr.Button("🚀 Run Full Analysis", variant="primary")
 
     report_output = gr.Markdown(label="📊 Intelligence Report")

tools/analytics_tool.py

@@ -22,9 +22,9 @@ class AnalyticsTool(BaseTool):
 
     def _run(self, market_data: dict, historical_data: dict, sentiment_data: dict) -> dict:
         try:
-            # ============================================================
-            # 1) Extract fields safely from structured tool outputs
-            # ============================================================
+            # ------------------------------------------------------------
+            # 1) Extract fields from structured tool outputs
+            # ------------------------------------------------------------
 
             price = market_data.get("latest_price")
             pct_change = historical_data.get("pct_change")
@@ -42,9 +42,9 @@ class AnalyticsTool(BaseTool):
 
             sentiment = sentiment.lower()
 
-            # ============================================================
-            # 2) Sentiment strength & confidence (new)
-            # ============================================================
+            # ------------------------------------------------------------
+            # 2) Sentiment strength & confidence
+            # ------------------------------------------------------------
 
             # Pull from SentimentTool if present
             sentiment_strength = sentiment_data.get("sentiment_strength")
@@ -68,18 +68,18 @@ class AnalyticsTool(BaseTool):
             # Effective weighted sentiment
             effective_sentiment = sentiment_strength * sentiment_confidence
 
-            # ============================================================
-            # 3) Alignment logic (upgraded)
-            # ============================================================
+            # ------------------------------------------------------------
+            # 3) Alignment logic
+            # ------------------------------------------------------------
 
             aligned = (
                 (trend == "upward" and effective_sentiment > 0.2) or
                 (trend == "downward" and effective_sentiment < -0.2)
             )
 
-            # ============================================================
-            # 4) Composite score (new formula)
-            # ============================================================
+            # ------------------------------------------------------------
+            # 4) Composite score
+            # ------------------------------------------------------------
 
             score = (
                 (pct_change / 10) +            # Trend effect
@@ -90,9 +90,9 @@ class AnalyticsTool(BaseTool):
             # Bound between [-1, 1]
             score = round(max(-1, min(1, score)), 2)
 
-            # ============================================================
+            # ------------------------------------------------------------
             # 5) Final structured output
-            # ============================================================
+            # ------------------------------------------------------------
 
             return {
                 "price": price,

tools/historical_data_tool.py

@@ -82,7 +82,7 @@ class HistoricalDataTool(BaseTool):
                 "pct_change": round(pct_change, 2),
                 "volatility_pct": round(volatility, 2),
                 "trend": trend,
-                "price_history": history,  # optional but useful for advanced analytics
+                "price_history": history,
             }
 
         except Exception as e:

tools/sentiment_tool.py

@@ -30,9 +30,9 @@ class SentimentInput(BaseModel):
     )
 
 
-# ===================================================================
-#                  SENTIMENT TOOL (NEWS-ONLY VERSION)
-# ===================================================================
+# -------------------------------------------------------------------
+#                  SENTIMENT TOOL
+# -------------------------------------------------------------------
 class SentimentTool(BaseTool):
     """
     Fetches recent crypto news via Serper and produces aggregated sentiment