Create query.py

query.py

@@ -0,0 +1,35 @@
+import re
+import os
+import google.generativeai as genai
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+
+# Now you can use hugging_face_api_key in your code
+
+genai.configure(api_key=GOOGLE_API_KEY)
+model = genai.GenerativeModel('gemini-pro')  # Load the model
+
+def get_Answer(query):
+    res = collection.query(  # Assuming `collection` is defined elsewhere
+        query_texts=query,
+        n_results=2
+    )
+    system = f"""You are a teacher. You will be provided some context, 
+    your task is to analyze the relevant context and answer the below question:
+    - {query}
+    """
+    context = " ".join([re.sub(r'[^\x00-\x7F]+', ' ', r) for r in res['documents'][0]])
+    prompt = f"### System: {system} \n\n ###: User: {context} \n\n ### Assistant:\n"
+    answer = model.generate_content(prompt).text
+    return answer
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=get_Answer,
+    inputs=gr.Textbox(lines=5, placeholder="Ask a question"),  # Textbox for query
+    outputs="textbox",  # Display the generated answer in a textbox
+    title="Answer Questions with Gemini-Pro",
+    description="Ask a question and get an answer based on context from a ChromaDB collection.",
+)
+
+# Launch the Gradio app
+iface.launch(debug=True,share=True)