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| #conda create -n gradioenv | |
| #conda activate gradioenv | |
| #conda install -c conda-forge gradio | |
| #don't forget to set conda env as interpreter in VS Code | |
| import requests, json | |
| import gradio as gr | |
| model = 'phi3' #llama3 | |
| context = [] | |
| import gradio as gr | |
| #Call Ollama API | |
| def generate(prompt, context, top_k, top_p, temp): | |
| r = requests.post('http://localhost:11434/api/generate', | |
| json={ | |
| 'model': model, | |
| 'prompt': prompt, | |
| 'context': context, | |
| 'options':{ | |
| 'top_k': top_k, | |
| 'temperature':top_p, | |
| 'top_p': temp | |
| } | |
| }, | |
| stream=False) | |
| r.raise_for_status() | |
| response = "" | |
| for line in r.iter_lines(): | |
| body = json.loads(line) | |
| response_part = body.get('response', '') | |
| print(response_part) | |
| if 'error' in body: | |
| raise Exception(body['error']) | |
| response += response_part | |
| if body.get('done', False): | |
| context = body.get('context', []) | |
| return response, context | |
| def chat(input, chat_history, top_k, top_p, temp): | |
| chat_history = chat_history or [] | |
| global context | |
| output, context = generate(input, context, top_k, top_p, temp) | |
| chat_history.append((input, output)) | |
| return chat_history, chat_history | |
| #the first history in return history, history is meant to update the | |
| #chatbot widget, and the second history is meant to update the state | |
| #(which is used to maintain conversation history across interactions) | |
| #########################Gradio Code########################## | |
| block = gr.Blocks() | |
| with block: | |
| gr.Markdown("""<h1><center> Arztbrief Center </center></h1> | |
| """) | |
| chatbot = gr.Chatbot() | |
| message = gr.Textbox(placeholder="Ihre Nachricht") | |
| state = gr.State() | |
| with gr.Row(): | |
| top_k = gr.Slider(0.0,100.0, label="top_k", value=40, info="Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)") | |
| top_p = gr.Slider(0.0,1.0, label="top_p", value=0.9, info=" Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)") | |
| temp = gr.Slider(0.0,2.0, label="temperature", value=0.8, info="The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)") | |
| submit = gr.Button("SEND") | |
| submit.click(chat, inputs=[message, state, top_k, top_p, temp], outputs=[chatbot, state]) | |
| #To create a public link, set `share=True` in `launch()`. | |
| block.launch(debug=True, share=True) |