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Gradio github:https://github.com/gradio-app/gradio
1. curl -fsSL https://ollama.com/install.sh | sh2. ollama pull llama3.1:8b
如果想了解详细的安装过程,请看此篇:
【干货】手把手教你搭建Ollama+OpenWebUI
source ~/miniconda3/bin/activateconda create -n charbot_1 python=3.12
完成后继续以下指令,在虚拟环境中安装Gradio 。
conda activate charbot_1pip install gradio
import requests
import json
import gradio as gr
url = "http://localhost:11434/api/generate"
headers = {
'Content-Type': 'application/json'
}
conversation_history = []
def generate_response(prompt):
conversation_history.append(prompt)
full_prompt = "\n".join(conversation_history)
data = {
"model": "llama3.1:8b",
"stream": False,
"prompt": full_prompt
}
response =requests.post(url, headers=headers, data=json.dumps(data))
if response.status_code == 200:
response_txt = response.text
data = json.loads(response_txt)
actual_response = data["response"]
conversation_history.append(actual_response)
return actual_response
else:
print("Error:", response.status_code, response.text)
iface = gr.Interface(
fn=generate_response,
inputs=["text"],
outputs=["text"]
)
if __name__ == "__main__":
iface.launch()
1. 先运行 ollama 把模型启动,在终端中运行
ollama run llama3.1:8B
2. 另开一个终端,进入python虚拟环境运行 charbot_1
python3 charbot_1
3. 在浏览器中打开
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