Create app.py

app.py

@@ -0,0 +1,64 @@
+# app.py
+import os
+import glob
+from huggingface_hub import snapshot_download
+from ctransformers import AutoModelForCausalLM
+import gradio as gr
+
+# Model info
+MODEL_REPO = "TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF"
+MODEL_FILE = "tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf"
+MODEL_CACHE_DIR = os.environ.get("MODEL_DIR", "/app/model_cache")
+
+os.makedirs(MODEL_CACHE_DIR, exist_ok=True)
+
+# If model not present, download it (public HF repo)
+def ensure_model():
+    # If user committed model locally, prefer that
+    local_paths = glob.glob(os.path.join(MODEL_CACHE_DIR, "**", MODEL_FILE), recursive=True)
+    candidate = local_paths[0] if local_paths else os.path.join(MODEL_CACHE_DIR, MODEL_FILE)
+    if os.path.exists(candidate):
+        return candidate
+
+    print("Downloading model snapshot from Hugging Face hub...")
+    repo_path = snapshot_download(repo_id=MODEL_REPO, cache_dir=MODEL_CACHE_DIR)
+    matches = glob.glob(os.path.join(repo_path, "**", MODEL_FILE), recursive=True)
+    if matches:
+        return matches[0]
+    # fallback: check repo_path root
+    fallback = os.path.join(repo_path, MODEL_FILE)
+    if os.path.exists(fallback):
+        return fallback
+    raise FileNotFoundError(f"Could not locate {MODEL_FILE} after download (repo_path={repo_path}).")
+
+model_path = ensure_model()
+print("Using model file:", model_path)
+
+# Load model (ctransformers handles GGUF)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_REPO,
+    model_file=model_path,
+    model_type="llama",
+    max_new_tokens=256,
+    temperature=0.7
+)
+
+custom_data = {
+    "hi": "hello Good morning,i am chatbot deepika",
+    "about you": "I am deepika AI Chatbot,how may i help you..",
+    "i love you": "i love you too",
+    "age": "45"
+}
+
+def chatbot(msg: str):
+    if not msg:
+        return ""
+    if msg in custom_data:
+        return custom_data[msg]
+    # ctransformers returns a string for simple calls
+    return model(f"### Instruction:\n{msg}\n\n### Response:\n")
+
+if __name__ == "__main__":
+    port = int(os.environ.get("PORT", 7860))
+    gr.Interface(fn=chatbot, inputs="text", outputs="text", title="Custom Chatbot - TinyLlama")\
+      .launch(server_name="0.0.0.0", server_port=port)