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Update app.py
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app.py
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import gradio as gr
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import
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from huggingface_hub import InferenceClient
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#
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response.raise_for_status()
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return response.text.strip()
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except requests.exceptions.RequestException as e:
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return f"Error fetching system message: {str(e)}"
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def respond(message, history):
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# Sabit parametreler
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max_tokens = 512
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temperature = 0.7
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top_p = 0.95
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# Fetch the system message from GitHub
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system_message = fetch_system_message()
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if system_message.startswith("Error"):
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yield system_message
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return
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messages = [{"role": "system", "content": system_message}]
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for val in history:
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if val[0]:
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messages.append({"role": "user", "content": val[0]})
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if val[1]:
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messages.append({"role": "assistant", "content": val[1]})
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messages.append({"role": "user", "content": message})
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response = ""
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for message in client.chat_completion(
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messages,
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max_tokens=max_tokens,
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stream=True,
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temperature=temperature,
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top_p=top_p,
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):
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token = message.choices[0].delta.content
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response += token
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yield response
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# Koyu tema tanımlama
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theme=gr.themes.Soft(
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primary_hue="emerald",
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secondary_hue="emerald",
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neutral_hue="gray",
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font=[
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gr.themes.GoogleFont("Exo"),
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"ui-sans-serif",
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"system-ui",
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"sans-serif"
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]).set(
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body_background_fill_dark="#010409",
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block_background_fill_dark="#010409",
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block_border_width="1px",
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block_title_background_fill_dark="#1e1c26",
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input_background_fill_dark="#161b22",
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button_secondary_background_fill_dark="#21262d",
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border_color_accent_dark="#2f353c",
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border_color_primary_dark="#2f353c",
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background_fill_secondary_dark="#010409",
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color_accent_soft_dark="transparent",
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code_background_fill_dark="#0d1117",
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)
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# Demo başlatılıyor
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demo = gr.ChatInterface(
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respond,
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)
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if __name__ == "__main__":
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demo.launch(share=True)
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import gradio as gr
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
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# Model ve Tokenizer yükleniyor
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model_name = "mistralai/Mistral-7B-Instruct-v0.1"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype="auto")
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# Pipeline oluşturuluyor
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=200)
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# Gradio arayüzü
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def chat_with_ai(prompt):
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result = pipe(prompt)[0]['generated_text']
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return result
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gr.Interface(fn=chat_with_ai,
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inputs=gr.Textbox(label="Patron Soruyu Sor"),
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outputs=gr.Textbox(label="AlpDroid Cevaplıyor"),
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title="AlpDroid 7B - Grok Tarzı Açık AI").launch()
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