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app.py
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import gradio as gr
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from langchain_openai import ChatOpenAI
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from langchain_core.prompts import ChatPromptTemplate
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from langchain_core.output_parsers import StrOutputParser
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from langchain_community.llms import Ollama
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import os
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from dotenv import load_dotenv
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load_dotenv()
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os.environ["LANGCHAIN_TRACING_V2"] = "true"
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os.environ["LANGCHAIN_API_KEY"] = os.getenv("LANGCHAIN_API_KEY")
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# Prompt Template
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prompt = ChatPromptTemplate.from_messages(
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[
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("system", "You are a helpful assistant. Please respond to the user queries"),
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("user", "Question:{question}")
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]
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)
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# ollama LLama2 LLm
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llm = Ollama(model="llama2")
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output_parser = StrOutputParser()
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chain = prompt | llm | output_parser
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def chatbot_response(input_text):
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if input_text:
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return chain.invoke({"question": input_text})
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return "Please enter a question."
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# Gradio Interface
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gr.Interface(fn=chatbot_response, inputs="text", outputs="text", title="Langchain Demo With LLAMA2 API").launch()
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