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Update app.py
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app.py
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@@ -1,12 +1,16 @@
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import os
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import gradio as gr
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from groq import Groq
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def generate_response(prompt, history, model, temperature, max_tokens, top_p):
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client = Groq(
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api_key = os.environ.get("Groq_Api_Key")
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)
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stream = client.chat.completions.create(
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messages=[
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{"role": "system", "content": "you are a helpful assistant."},
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@@ -16,6 +20,7 @@ def generate_response(prompt, history, model, temperature, max_tokens, top_p):
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temperature=temperature,
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max_tokens=max_tokens,
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top_p=top_p,
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stop=None,
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stream=True,
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)
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@@ -23,17 +28,18 @@ def generate_response(prompt, history, model, temperature, max_tokens, top_p):
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response = ""
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for chunk in stream:
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delta_content = chunk.choices[0].delta.content
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return response
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# Define the Gradio chat interface
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additional_inputs = [
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gr.Dropdown(choices=["llama3-70b-8192", "llama3-8b-8192", "mixtral-8x7b-32768", "llama2-70b-4096", "gemma-7b-it"], value="llama3-70b-8192", label="LLM Model"),
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gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.5, label="Temperature"),
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gr.Slider(minimum=1, maximum=4096, step=1, value=4096, label="Max Tokens"),
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gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.5, label="Top P"),
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]
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gr.ChatInterface(
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@@ -41,5 +47,5 @@ gr.ChatInterface(
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chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
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additional_inputs=additional_inputs,
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title="Groq API LLMs AI Models",
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description="Using https://groq.com/ api, ofc as its free it will have some limitations so its better if you duplicate this space with your own api key<br>Hugging Face Space by [Nick088](https://linktr.ee/Nick088)",
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).launch()
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import os
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import random
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import gradio as gr
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from groq import Groq
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def generate_response(prompt, history, model, temperature, max_tokens, top_p, seed):
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client = Groq(
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api_key = os.environ.get("Groq_Api_Key")
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)
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if seed == 0:
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seed = random.randint(1, 100000)
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stream = client.chat.completions.create(
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messages=[
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{"role": "system", "content": "you are a helpful assistant."},
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temperature=temperature,
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max_tokens=max_tokens,
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top_p=top_p,
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seed=seed
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stop=None,
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stream=True,
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)
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response = ""
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for chunk in stream:
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delta_content = chunk.choices[0].delta.content
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response += delta_content
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yield output
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return response
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# Define the Gradio chat interface
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additional_inputs = [
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gr.Dropdown(choices=["llama3-70b-8192", "llama3-8b-8192", "mixtral-8x7b-32768", "llama2-70b-4096", "gemma-7b-it"], value="llama3-70b-8192", label="LLM Model"),
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gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.5, label="Temperature", info="Controls randomness of responses"),
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gr.Slider(minimum=1, maximum=4096, step=1, value=4096, label="Max Tokens", info="The maximum number of tokens that the model can process in a single response"),
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gr.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.5, label="Top P", info="A method of text generation where a model will only consider the most probable next tokens that make up the probability p."),
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gr.Number(precision=0, value=42, label="Seed", info="A starting point to initiate generation, use 0 for random")
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]
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gr.ChatInterface(
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chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
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additional_inputs=additional_inputs,
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title="Groq API LLMs AI Models",
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description="Using https://groq.com/ api, ofc as its free it will have some limitations of requests per minute, so its better if you duplicate this space with your own api key<br>Hugging Face Space by [Nick088](https://linktr.ee/Nick088)",
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).launch()
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