first app

.gitignore

@@ -1 +1,2 @@
-app_bk.py
+app_bk.py
+app_bk2.py

app.py

@@ -1,81 +1,12 @@
-import os
 import gradio as gr
-from huggingface_hub import InferenceClient, login
 
+def selam_ver(isim):
+    return f"Merhaba, {isim}!"
 
-# ---- HF token & login integration ----
-HF_TOKEN = (os.environ.get("HUGGINGFACE_HUB_TOKEN", "") or "").strip()
-
-if HF_TOKEN:
-    # Authenticate this environment (useful for gated models, higher rate limits, etc.)
-    login(token=HF_TOKEN)
-else:
-    print("UYARI: HF_TOKEN / HUGGINGFACE_HUB_TOKEN bulunamadı, gated modellere erişilemeyebilir.")
-
-
-# Create a single shared client (reuse across requests)
-client = InferenceClient(
-    model="openai/gpt-oss-20b",
-    token=HF_TOKEN if HF_TOKEN else None,  # will still work for public models without token
-)
-
-def respond(
-    message,
-    history: list[dict[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    """
-    Streaming chat using Hugging Face Inference API.
-    History is a list of {"role": "...", "content": "..."} dicts.
-    """
-
-    # Build messages list
-    messages = [{"role": "system", "content": system_message}]
-    messages.extend(history)
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    # Stream tokens from the model
-    for chunk in client.chat_completion(
-        messages=messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        choices = chunk.choices
-        token_text = ""
-        if len(choices) and choices[0].delta.content:
-            token_text = choices[0].delta.content
-
-        response += token_text
-        yield response
-
-
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    title="Basit Chat Botu",
-    description="Küçük bir sohbet botu, HF Inference API ile çalışıyor.",
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+demo = gr.Interface(
+    fn=selam_ver,
+    inputs=gr.Textbox(label="İsminiz"),
+    outputs=gr.Textbox(label="Selam")
 )
 
-demo = chatbot  # no login UI needed now
-
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()