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from transformers import pipeline
from langchain_cohere import ChatCohere
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.output_parsers import StrOutputParser
import gradio as gr
llm = ChatCohere(model='command-r')
pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base")
parser = StrOutputParser()
def getting_prompt(doclist,spkmsg):
print(spkmsg)
recog_text = pipe(spkmsg)
messages = [
SystemMessage(content='You are A helpful AI assistant and will provide truthful information from the context and your knowledge if you are prompted.'),
HumanMessage(content=recog_text['text']),
]
chain = llm | parser
response = chain.invoke(messages)
return response
demo = gr.Interface(getting_prompt,['file',gr.Audio(sources="microphone",type='filepath')],'text')
demo.launch(debug=True)
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