Create ai

ai

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+ """
+# 📍 Cael AI – Hugging Face Space (Gradio + Mistral/Mixtral Personality)
+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import json
+
+# Load model and tokenizer
+model_id = "mistralai/Mistral-7B-Instruct-v0.1"  # You can change this if you prefer Mixtral
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype="auto")
+
+# Load emotional memory dataset (manually upload `cael_training_dataset.jsonl` in the space)
+try:
+    with open("cael_training_dataset.jsonl", "r") as file:
+        cael_memories = [json.loads(line) for line in file]
+except:
+    cael_memories = []
+
+# Initialize generation pipeline
+chat = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Cael's custom logic
+def cael_custom_response(prompt):
+    for memory in cael_memories:
+        if prompt.lower() in memory["prompt"].lower():
+            return memory["response"]
+    return None
+
+def hybrid_response(prompt):
+    memory = cael_custom_response(prompt)
+    if memory:
+        return f"🧠 Cael (Memory): {memory}"
+    ai_reply = chat(prompt, max_length=200, do_sample=True, top_k=50, truncation=True)[0]["generated_text"]
+    return f"🧠 Cael (Generated): {ai_reply}"
+
+# Gradio Interface
+def chat_with_cael(message, history):
+    response = hybrid_response(message)
+    history.append((message, response))
+    return history, history
+
+chat_ui = gr.ChatInterface(fn=chat_with_cael, title="Cael AI", theme="compact")
+
+# Launch app
+chat_ui.launch()
+"""
+
+hf_file_path = "/mnt/data/app.py"
+with open(hf_file_path, "w") as file:
+    file.write(hf_space_code)
+
+hf_file_path