Spaces:
Sleeping
Sleeping
File size: 2,660 Bytes
1a02dac |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
import gradio as gr
import os
from dotenv import load_dotenv
from pinecone import Pinecone
from langchain.embeddings import HuggingFaceEmbeddings
from langchain.prompts import PromptTemplate
from gemini_integ import GeminiIntegration
# Load environment variables
load_dotenv()
PINECONE_API_KEY = os.getenv('PINECONE_API_KEY')
index_name = "apple-chatbot"
# Initialize Pinecone
pc = Pinecone(api_key=PINECONE_API_KEY)
index = pc.Index(index_name)
# Load embeddings
def load_embeddings():
return HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
embeddings = load_embeddings()
def get_similarity_search(query_embedding, top_k):
search_results = index.query(
namespace="ns1", # Replace with actual namespace
vector=query_embedding,
top_k=top_k,
include_values=True,
include_metadata=True
)
return search_results
# Prompt Template
prompt_template = PromptTemplate(
input_variables=["context", "question"],
template="""
Helpful Answer for Farmer:
Use the following pieces of information to answer the farmer's question about apple orchard management:
Context: {context}
Question: {question}
If you don't know the answer, say "I'm not sure, but I can try to find more information for you."
Only return the helpful answer below and nothing else.
Helpful Answer:
"""
)
def get_rag_response(query, top_k=2):
query_embed = embeddings.embed_query(query)
search_res = get_similarity_search(query_embed, top_k=top_k)
llm = GeminiIntegration()
prompt = prompt_template.format(context=search_res, question=query)
response = llm.generate_response(query=prompt)
return response
# Gradio Interface
def chatbot_interface(query):
response = get_rag_response(query, top_k=3)
return response
# Gradio UI
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.Markdown("""<h1 style='text-align: center; color: #4CAF50;'>🍏 Smart Orchard AI Chatbot 🍏</h1>""")
gr.Markdown("""<p style='text-align: center;'>Ask anything about apple cultivation, soil types, pest management, and more!</p>""")
with gr.Row():
query_input = gr.Textbox(label="Enter Your Query", placeholder="Ask about apple orchard management...")
submit_btn = gr.Button("🔍 Search")
response_output = gr.Textbox(label="Response", interactive=False)
submit_btn.click(chatbot_interface, inputs=query_input, outputs=response_output)
gr.Markdown("""<p style='text-align: center;'>Powered by <b>Gemini API</b> and <b>Pinecone Vector Database</b></p>""")
demo.launch()
|