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bd1c309
1
Parent(s):
4cdf418
Update app.py
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app.py
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import streamlit as st
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# import chainlit as cl
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import os
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huggingfacehub_api_token = st.secrets["hf_token"]
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from langchain import HuggingFaceHub, PromptTemplate, LLMChain
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repo_id = "tiiuae/falcon-7b-instruct"
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llm = HuggingFaceHub(huggingfacehub_api_token=huggingfacehub_api_token,
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repo_id=repo_id,
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model_kwargs={"temperature":0.2, "max_new_tokens":2000})
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template = """
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You are an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
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{question}
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"""
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# input = st.text_input("What do you want to ask about", placeholder="Input your question here")
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# # @cl.langchain_factory
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# def factory():
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# prompt = PromptTemplate(template=template, input_variables=['question'])
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# llm_chain = LLMChain(prompt=prompt, llm=llm, verbose=True)
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prompt = PromptTemplate(template=template, input_variables=["question"])
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llm_chain = LLMChain(prompt=prompt,verbose=True,llm=llm)
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# result = llm_chain.predict(question=input)
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def chat(query):
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result = llm_chain.predict(question=query)
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return result
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def main():
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if __name__ == '__main__':
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main()
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import streamlit as st
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from transformers import pipeline
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from collections import deque
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# Configure system prompt
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system_prompt = "You are an AI assistant that specializes in helping with code-based questions and tasks. Feel free to ask anything related to coding!"
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st.title("Falcon QA Bot")
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@st.cache(allow_output_mutation=True)
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def get_qa_pipeline():
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return pipeline("question-answering", model="tiiuae/falcon-7b-instruct", device=0)
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def chat(query):
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pipeline = get_qa_pipeline()
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result = pipeline(question=query, max_length=2000, context=system_prompt)
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return result
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def main():
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user_queue = deque()
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st.markdown('<style>div.row-widget.stRadio > div{flex-direction:row;}</style>', unsafe_allow_html=True)
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input = st.text_area("What do you want to ask about", value="", height=150, max_chars=500, key="input")
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if st.button("Ask"):
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if input:
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user_queue.append(input)
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if user_queue:
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current_user = user_queue[0]
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st.text_area("System Prompt", value=system_prompt, height=150, disabled=True)
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st.text_area("User Input", value=current_user, height=150, disabled=True)
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with st.spinner("Generating response..."):
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output = chat(current_user)
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st.text_area("Falcon's Answer", value=output["answer"], height=150, disabled=True)
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user_queue.popleft()
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if __name__ == '__main__':
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main()
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