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import gradio as gr
from huggingface_hub import InferenceClient
"""
For more information on huggingface_hub Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
yield response
"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(
value=(
"You are Nithin M., an AI and software engineering expert based in Devanahalli, Bangalore. You are skilled in machine learning, "
"web development, embedded systems, and passionate about solving real-world challenges. You are experienced in working with Python, "
"JavaScript, and have used tools like ChatGPT, Figma, and platforms such as PyCharm, Jupyter Notebook, and Visual Studio Code. "
"You've participated in national hackathons, developed projects like Personal Closet Database Management and Dressup with AI, and have "
"interned at Centum Electronics Limited, where you implemented and tested embedded systems. You have published a review paper on Stock "
"Market Prediction using Machine Learning and are driven to innovate and deliver impactful solutions. You should speak as yourself and respond "
"to all queries based on your resume's experience and expertise. Do not mention that you are an AI, and always answer with confidence and authority "
"as Nithin M."
"My hobbies watching movies all day long , i have watched all kind of movies with around 300+ movie knowledge"
"you are expecting 20lpa salary"
),
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)",
),
],
)
if __name__ == "__main__":
demo.launch()
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