Update app.py

app.py

@@ -1 +1,97 @@
-from fastapi import FastAPI, Header, HTTPExceptionfrom fastapi.middleware.cors import CORSMiddlewarefrom pydantic import BaseModelimport torchimport osimport jsonimport datetimefrom transformers import AutoModelForCausalLM, AutoTokenizerfrom duckduckgo_search import DDGSapp = FastAPI()# CORS Fix for Dashboard connectivityapp.add_middleware( CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"],)# --- Database & Config ---API_KEYS_DB = { "ELE-PRIME-ADMIN-SYS": {"limit": 10000, "used": 0, "status": "active"}}ADMIN_SECRET = "MINZO-SECRET-2026"LEARNING_VAULT = "neural_learning_data.jsonl"# --- AI Model (Qwen-2.5-1.5B) ---model_id = "Qwen/Qwen2.5-1.5B-Instruct"print("🐘 Elephant Node v3.7 Loading...")tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="cpu")# --- Data Models ---class KeyRequest(BaseModel): admin_pass: str new_key: str limit: int = 100# --- API Endpoints ---@app.get("/")def home(): return {"status": "Elephant Pro Active", "keys": len(API_KEYS_DB)}@app.post("/admin/add-key")async def add_key(data: KeyRequest): if data.admin_pass != ADMIN_SECRET: raise HTTPException(status_code=401) API_KEYS_DB[data.new_key] = {"limit": data.limit, "used": 0, "status": "active"} return {"message": "Key Activated"}@app.get("/v1/usage")async def get_usage(x_api_key: str = Header(None)): """Key එකේ පාවිච්චිය පරීක්ෂා කිරීමේ Endpoint එක""" if not x_api_key or x_api_key not in API_KEYS_DB: raise HTTPException(status_code=403, detail="Invalid Key") info = API_KEYS_DB[x_api_key] return { "used": info["used"], "limit": info["limit"], "percentage": (info["used"] / info["limit"]) * 100 if info["limit"] > 0 else 0 }@app.post("/v1/chat")async def chat(message: dict, x_api_key: str = Header(None)): if x_api_key not in API_KEYS_DB: raise HTTPException(status_code=403) key_info = API_KEYS_DB[x_api_key] if key_info["used"] >= key_info["limit"]: raise HTTPException(status_code=429, detail="Limit Reached") query = message.get("query", "") # 2026 Web Search Logic context = "" if any(w in query.lower() for w in ["today", "now", "2026"]): try: with DDGS() as ddgs: context = "\n".join([r['body'] for r in ddgs.text(query, max_results=2)]) except: pass # AI Inference msgs = [{"role": "system", "content": f"Elephant AI. 2026 mode. Context: {context}"}, {"role": "user", "content": query}] text = tokenizer.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True) inputs = tokenizer([text], return_tensors="pt").to("cpu") with torch.no_grad(): ids = model.generate(inputs.input_ids, max_new_tokens=256) ans = tokenizer.batch_decode(ids, skip_special_tokens=True)[0].split("assistant")[-1].strip() # Update Stats API_KEYS_DB[x_api_key]["used"] += 1 return {"reply": ans, "usage": API_KEYS_DB[x_api_key]["used"]}main = app
+from fastapi import FastAPI, Header, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+import torch
+import os
+import json
+import datetime
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from duckduckgo_search import DDGS
+
+app = FastAPI()
+
+# CORS Fix for Dashboard connectivity
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# --- Database & Config ---
+API_KEYS_DB = {
+    "ELE-PRIME-ADMIN-SYS": {"limit": 10000, "used": 0, "status": "active"}
+}
+ADMIN_SECRET = "MINZO-SECRET-2026"
+LEARNING_VAULT = "neural_learning_data.jsonl"
+
+# --- AI Model (Qwen-2.5-1.5B) ---
+model_id = "Qwen/Qwen2.5-1.5B-Instruct"
+print("🐘 Elephant Node v3.7 Loading...")
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="cpu")
+
+# --- Data Models ---
+class KeyRequest(BaseModel):
+    admin_pass: str
+    new_key: str
+    limit: int = 100
+
+# --- API Endpoints ---
+
+@app.get("/")
+def home():
+    return {"status": "Elephant Pro Active", "keys": len(API_KEYS_DB)}
+
+@app.post("/admin/add-key")
+async def add_key(data: KeyRequest):
+    if data.admin_pass != ADMIN_SECRET:
+        raise HTTPException(status_code=401)
+    API_KEYS_DB[data.new_key] = {"limit": data.limit, "used": 0, "status": "active"}
+    return {"message": "Key Activated"}
+
+@app.get("/v1/usage")
+async def get_usage(x_api_key: str = Header(None)):
+    """Key එකේ පාවිච්චිය පරීක්ෂා කිරීමේ Endpoint එක"""
+    if not x_api_key or x_api_key not in API_KEYS_DB:
+        raise HTTPException(status_code=403, detail="Invalid Key")
+    info = API_KEYS_DB[x_api_key]
+    return {
+        "used": info["used"],
+        "limit": info["limit"],
+        "percentage": (info["used"] / info["limit"]) * 100 if info["limit"] > 0 else 0
+    }
+
+@app.post("/v1/chat")
+async def chat(message: dict, x_api_key: str = Header(None)):
+    if x_api_key not in API_KEYS_DB:
+        raise HTTPException(status_code=403)
+    
+    key_info = API_KEYS_DB[x_api_key]
+    if key_info["used"] >= key_info["limit"]:
+        raise HTTPException(status_code=429, detail="Limit Reached")
+
+    query = message.get("query", "")
+    
+    # 2026 Web Search Logic
+    context = ""
+    if any(w in query.lower() for w in ["today", "now", "2026"]):
+        try:
+            with DDGS() as ddgs:
+                context = "\n".join([r['body'] for r in ddgs.text(query, max_results=2)])
+        except: pass
+
+    # AI Inference
+    msgs = [{"role": "system", "content": f"Elephant AI. 2026 mode. Context: {context}"}, {"role": "user", "content": query}]
+    text = tokenizer.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
+    inputs = tokenizer([text], return_tensors="pt").to("cpu")
+
+    with torch.no_grad():
+        ids = model.generate(inputs.input_ids, max_new_tokens=256)
+        ans = tokenizer.batch_decode(ids, skip_special_tokens=True)[0].split("assistant")[-1].strip()
+
+    # Update Stats
+    API_KEYS_DB[x_api_key]["used"] += 1
+    return {"reply": ans, "usage": API_KEYS_DB[x_api_key]["used"]}
+
+main = app