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Update app.py
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app.py
CHANGED
@@ -62,10 +62,10 @@ def chat_query(question, history):
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query = f"""As an experienced Electrical Engineer, please provide an elaborate, precise, and answer politely pointwise to the question: {question}.
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Also, Please consider the provided chat history: {
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Ensure that your response is detailed, accurate, and addresses each aspect of the question thoroughly.
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If the context of the question doesn't align with
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If don't get the answer, feel free to reply from
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#llm = ChatOpenAI(model=llm_name, temperature=0.1, api_key = OPENAI_API_KEY)
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llm = GoogleGenerativeAI(model="gemini-1.0-pro", google_api_key=GEMINI_API_KEY)
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@@ -78,17 +78,20 @@ def chat_query(question, history):
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# Replace input() with question variable for Gradio
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result = qa({"question": query, "chat_history" : chat_history})
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source_docs = result["source_documents"]
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file_name = os.path.basename(source_docs[0].metadata['source'])
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return result["answer"] + "\n\
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iface = gr.ChatInterface(
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fn=chat_query,
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#title="
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description="""-- Welcome to the Language Model trained on `Model Technical Specifications` of SS-Engg. Dept.\n\n
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-- The Model tries to answer the Query based on TS, GTR & Specific Requirements. \n\n
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-- For precise reply, please input `Specific Keywords` in your Query. \n\n """,
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@@ -104,15 +107,17 @@ iface = gr.ChatInterface(
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)
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Title= "#
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with gr.Blocks(css="style.css", fill_height=True) as demo:
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with gr.Row():
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with gr.Column(scale=1):
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gr.Image("
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with gr.Column(scale=10):
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gr.Markdown(Title)
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iface.render()
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query = f"""As an experienced Electrical Engineer, please provide an elaborate, precise, and answer politely pointwise to the question: {question}.
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Also, Please consider the provided chat history: {history}.
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Ensure that your current response is detailed, accurate, and addresses each aspect of the question thoroughly.
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If the context of the question doesn't align with your last reply, please provide your response in a fresh manner.
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If don't get the answer, feel free to reply from your own knowledge."""
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#llm = ChatOpenAI(model=llm_name, temperature=0.1, api_key = OPENAI_API_KEY)
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llm = GoogleGenerativeAI(model="gemini-1.0-pro", google_api_key=GEMINI_API_KEY)
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# Replace input() with question variable for Gradio
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result = qa({"question": query, "chat_history" : chat_history})
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source_docs = result["source_documents"]
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file_names = get_file(source_docs)
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#file_name = os.path.basename(source_docs[0].metadata['source'])
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file_name = ', '.join([f"{x}" for x in file_names[:3]])
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# print("History : ", history)
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# print("\n Chat_his : ", chat_history)
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return result["answer"] + "\n\nSources : " + file_name
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iface = gr.ChatInterface(
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fn=chat_query,
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#title=" --: Conversational BOT for Model-TS :----- ",
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description="""-- Welcome to the Language Model trained on `Model Technical Specifications` of SS-Engg. Dept.\n\n
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-- The Model tries to answer the Query based on TS, GTR & Specific Requirements. \n\n
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-- For precise reply, please input `Specific Keywords` in your Query. \n\n """,
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)
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Title= "# --: Conversational BOT for Model-TS :-- "
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with gr.Blocks(css="style.css", fill_height=True) as demo:
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with gr.Row():
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with gr.Column(scale=1):
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gr.Image("Chatbot.png", width=50, show_download_button = False, show_label = False, show_share_button = False )
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with gr.Column(scale=10):
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gr.Markdown(Title)
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with gr.Column(scale=1):
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gr.Image("PG Logo.png", width=50, show_download_button = False, show_label = False, show_share_button = False )
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iface.render()
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