Initial push to Hugging Face Space

app.py

@@ -1,20 +1,26 @@
 from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
 from transformers import pipeline
+from fastapi.responses import StreamingResponse
+import matplotlib.pyplot as plt
+import requests
+import datetime
+from io import BytesIO
 import logging
 import os
+
+# Set environment variables for Hugging Face cache
 os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf_cache"
 os.environ["HF_HOME"] = "/tmp/hf_cache"
 
+# Configure logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
+# Create FastAPI app
 app = FastAPI()
 
-# Set transformers cache directory to a writable location to fix permission errors
-os.environ["TRANSFORMERS_CACHE"] = "/tmp/huggingface"
-
-# Load models once on startup with error handling
+# Load transformers models
 try:
     ner_model = pipeline("ner", model="dslim/bert-base-NER", aggregation_strategy="simple")
     sentiment_model = pipeline("sentiment-analysis", model="ProsusAI/finbert")
@@ -24,9 +30,14 @@ except Exception as e:
     ner_model = None
     sentiment_model = None
 
+# Request body schema for sentiment and NER
 class TextRequest(BaseModel):
     text: str
 
+# Request body schema for chart
+class CoinRequest(BaseModel):
+    coin_id: str
+
 @app.get("/")
 def home():
     return {"message": "Crypto News API is alive!"}
@@ -57,11 +68,50 @@ def analyze_ner(req: TextRequest):
         raise HTTPException(status_code=400, detail="Text cannot be empty")
     try:
         entities = ner_model(text[:512])
-        # Filter relevant entity groups
         relevant = [e['word'] for e in entities if e.get('entity_group') in ['ORG', 'PERSON', 'MISC', 'PRODUCT', 'GPE']]
-        # Remove duplicates preserving order, limit to 5 entities
         unique_entities = list(dict.fromkeys(relevant))[:5]
         return {"entities": unique_entities}
     except Exception as e:
         logger.error(f"NER analysis error: {e}")
         raise HTTPException(status_code=500, detail="NER analysis failed")
+
+@app.post("/chart")
+def generate_chart(req: CoinRequest):
+    coin_id = req.coin_id.strip().lower()
+    if not coin_id:
+        raise HTTPException(status_code=400, detail="coin_id cannot be empty")
+
+    url = f"https://api.coingecko.com/api/v3/coins/{coin_id}/market_chart"
+    params = {"vs_currency": "usd", "days": "1"}
+
+    try:
+        res = requests.get(url, params=params)
+        if res.status_code != 200:
+            logger.error(f"CoinGecko API error: {res.text}")
+            raise HTTPException(status_code=502, detail="Failed to fetch coin data from CoinGecko")
+
+        prices = res.json().get("prices", [])
+        if not prices:
+            raise HTTPException(status_code=404, detail="No price data available")
+
+        times = [datetime.datetime.fromtimestamp(p[0] / 1000) for p in prices]
+        values = [p[1] for p in prices]
+
+        plt.figure(figsize=(12, 6))
+        plt.fill_between(times, values, color="#1f77b4", alpha=0.3)
+        plt.plot(times, values, color="#1f77b4", linewidth=3)
+        plt.title(f"{coin_id.capitalize()} Price (24h)", fontsize=20)
+        plt.xlabel("Time")
+        plt.ylabel("USD Price")
+        plt.grid(True, linestyle='--', alpha=0.5)
+        plt.tight_layout()
+
+        img_bytes = BytesIO()
+        plt.savefig(img_bytes, format="png")
+        plt.close()
+        img_bytes.seek(0)
+
+        return StreamingResponse(img_bytes, media_type="image/png")
+    except Exception as e:
+        logger.error(f"Chart generation error: {e}")
+        raise HTTPException(status_code=500, detail="Failed to generate chart")

requirements.txt

@@ -2,3 +2,5 @@ fastapi
 uvicorn[standard]
 transformers
 torch
+matplotlib
+requests