Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+from PyPDF2 import PdfReader
+import os
+
+# Load the Gemma model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-9b-it")
+model = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b-it")
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Helper functions for document processing
+def get_pdf_text(pdf_file):
+    text = ""
+    pdf_reader = PdfReader(pdf_file)
+    for page in pdf_reader.pages:
+        text += page.extract_text()
+    return text
+
+def load_farming_knowledge_base(pdf_path="ai-farming.pdf"):
+    if not os.path.exists(pdf_path):
+        raise FileNotFoundError(f"PDF document '{pdf_path}' not found.")
+    return get_pdf_text(pdf_path)
+
+# Load knowledge base from the farming PDF
+knowledge_base = load_farming_knowledge_base()
+
+# Chatbot response generation
+def chatbot_response(user_message):
+    # Check if the question relates to the knowledge base
+    if user_message.lower() in knowledge_base.lower():
+        context = "This information is extracted from the AI Farming Guide:"
+        input_text = f"{context}\n{user_message}\n"
+    else:
+        context = "Answer based on general farming knowledge:"
+        input_text = f"{context}\n{user_message}\n"
+
+    # Generate a response using the Gemma model
+    response = pipe(input_text, max_length=512, temperature=0.7, top_p=0.9)
+    return response[0]["generated_text"]
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# 🌾 AI Agri Farmer Chat Bot 🌿")
+    gr.Markdown(
+        "Welcome to the AI Agri Farmer Chat Bot! 🤖 Ask your farming-related questions, "
+        "such as crop management, soil health, fertilizers, or pest control. If your "
+        "question isn't found in the farming guide, the bot will answer based on general knowledge."
+    )
+
+    with gr.Row():
+        user_input = gr.Textbox(
+            label="💬 Ask your farming question:",
+            placeholder="Example: 'What is the best fertilizer for wheat?'",
+        )
+        chatbot_output = gr.Textbox(label="🤖 Chat Bot Response:")
+
+    example_inputs = gr.Examples(
+        examples=[
+            "What is the best fertilizer for rice?",
+            "How much water does maize need weekly?",
+            "What crops grow well in clay soil?",
+        ],
+        inputs=user_input,
+    )
+
+    def respond(input_text):
+        return chatbot_response(input_text)
+
+    user_input.submit(respond, inputs=user_input, outputs=chatbot_output)
+
+    gr.Markdown("### 📄 About the Knowledge Base")
+    gr.Markdown(
+        "The chatbot uses information from the AI Farming Guide (`ai-farming.pdf`) as its primary source. "
+        "For topics not covered, it falls back on general farming knowledge."
+    )
+
+# Launch the Gradio app
+demo.launch()