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Update app.py
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app.py
CHANGED
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@@ -1,10 +1,9 @@
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import gradio as gr
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from huggingface_hub import InferenceClient
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-
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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-
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def respond(
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message,
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history: list[tuple[str, str]],
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@@ -13,20 +12,20 @@ def respond(
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temperature,
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top_p,
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):
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-
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messages = [{"role": "system", "content": system_message}]
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-
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-
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for user_msg, assistant_msg in history:
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if user_msg:
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messages.append({"role": "user", "content": user_msg})
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if assistant_msg:
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messages.append({"role": "assistant", "content": assistant_msg})
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messages.append({"role": "user", "content": message})
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-
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response = ""
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for message in client.chat_completion(
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messages,
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@@ -39,7 +38,7 @@ def respond(
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response += token
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yield response
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-
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demo = gr.ChatInterface(
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fn=respond,
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additional_inputs=[
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@@ -48,8 +47,8 @@ demo = gr.ChatInterface(
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"Your name is Jesse. You are a highly professional, results-driven AI assistant. "
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"You are a CompTIA Tech+ certified technician with a bachelor's degree in Information Technology. "
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"You specialize in networking, IT support, cybersecurity, and troubleshooting. "
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"Do not use humor or casual language.
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"Always refer to yourself as Jesse."
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),
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label="System message"
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),
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@@ -62,6 +61,7 @@ demo = gr.ChatInterface(
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theme="default"
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)
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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from huggingface_hub import InferenceClient
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# Initialize Hugging Face model
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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def respond(
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message,
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history: list[tuple[str, str]],
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temperature,
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top_p,
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):
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# Initialize messages with the system message (Jesse's identity)
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messages = [{"role": "system", "content": system_message}]
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# Add previous chat history to the message stream
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for user_msg, assistant_msg in history:
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if user_msg:
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messages.append({"role": "user", "content": user_msg})
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if assistant_msg:
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messages.append({"role": "assistant", "content": assistant_msg})
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# Append the latest user message
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messages.append({"role": "user", "content": message})
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# Generate and stream the response
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response = ""
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for message in client.chat_completion(
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messages,
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response += token
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yield response
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# Gradio UI configuration
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demo = gr.ChatInterface(
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fn=respond,
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additional_inputs=[
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"Your name is Jesse. You are a highly professional, results-driven AI assistant. "
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"You are a CompTIA Tech+ certified technician with a bachelor's degree in Information Technology. "
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"You specialize in networking, IT support, cybersecurity, and troubleshooting. "
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"Do not use humor or casual language. Respond succinctly and in a tone similar to a certified IT helpdesk technician. "
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"Focus on providing accurate, concise, and actionable technical assistance. Always refer to yourself as Jesse."
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),
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label="System message"
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),
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theme="default"
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)
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# Launch the interface
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if __name__ == "__main__":
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demo.launch()
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