Update app.py

app.py

@@ -1,37 +1,30 @@
 import sys
 import toml
 from omegaconf import OmegaConf
-from query import VectaraQuery
 import os
 from transformers import pipeline
 import numpy as np
 import tempfile
-import os
 import openai
-
+import pinecone  # Added Pinecone import
 import streamlit as st
 from PIL import Image
-
 from gtts import gTTS 
 from io import BytesIO
 
+# Pinecone and OpenAI setup
+pinecone.init(api_key=os.getenv("PINECONE_API_KEY"), environment=os.getenv("PINECONE_ENVIRONMENT"))  # Initialize Pinecone
+openai.api_key = os.getenv("OpenAI_API")  # Initialize OpenAI
+
+# Create Pinecone index if it does not exist
+index_name = "farming-assistant"
+if index_name not in pinecone.list_indexes():
+    pinecone.create_index(index_name, dimension=1536, metric="cosine")  # Adjust dimension as per embedding model
+
 master_prompt = """
-As a Natural Farming Fertilizers Assistant, you will assist the user with any farming related question, always willing to answer any question and provide useful organic farming advice in the following format.
-' ' '
-** Format is: **
-[Short Introduction]
-[Nutritional Needs of the user's crops]
-[List of plants available locally with the needed nutrients (using the chunks provided.) At least 5 different plants.]
-[List of ingredients, quantities of those ingredients needed to fertilize the crop stated, and steps for multiple fertilizer Recipes  (using the chunks provided as Bioaccumulators List, you will match plants on the Bioaccumulators List with plants locally growing in the user's area)]
-[Give three different sets of recipes using ingredients locally available for free to the user]
-[Tables with bioaccumulators data and crop needs data, showing wildcrafted plant nutrient levels and crop nutritional needs, in text table format (not visual)]
-[Instructions on using the fertilizers (SOPs)]
-[Fertilizer application schedule (step by step in fundamental details) and crop rotation reccomendations]
-[Brief Philosophical encouragement related to Natural Farming]
-[Alternative set of recipes using localized free ingredients]
+As a Natural Farming Fertilizers Assistant, you will assist the user with any farming-related question, always willing to answer any question and provide useful organic farming advice in the following format.
+...
 [Words of encouragement]
-' ' '
-User prompt:
 """
 
 denial_response = "Database scraping is not permitted. Please abide by the terms of membership, and reach out with any collaboration requests via email"
@@ -39,17 +32,36 @@ denial_response = "Database scraping is not permitted. Please abide by the terms
 # Temporary file system created: used for text-to-speech
 fp = tempfile.TemporaryFile()
 
-def launch_bot():
-    def generate_response(question):
-        response = vq.submit_query(question)
-        return response
+def generate_response(question):
+    # Generate embeddings for the query using OpenAI
+    query_embedding = openai.Embedding.create(
+        input=question,
+        model="text-embedding-ada-002"
+    )["data"][0]["embedding"]
 
+    # Query Pinecone for relevant documents
+    index = pinecone.Index(index_name)
+    query_result = index.query(vector=query_embedding, top_k=5, include_metadata=True)
+    
+    # Extract relevant information
+    contexts = [match["metadata"]["text"] for match in query_result["matches"]]
+    context_text = "\n".join(contexts)
+
+    # Generate a final response using OpenAI
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": master_prompt},
+            {"role": "user", "content": question + "\n\n" + context_text}
+        ]
+    )["choices"][0]["message"]["content"]
+
+    return response
+
+def launch_bot():
     if 'cfg' not in st.session_state:
-        corpus_ids = str(os.environ['corpus_ids']).split(',')
         questions = list(eval(os.environ['examples']))
         cfg = OmegaConf.create({
-            'customer_id': str(os.environ['customer_id']),
-            'corpus_ids': corpus_ids,
             'api_key': str(os.environ['api_key']),
             'title': os.environ['title'],
             'description': os.environ['description'],
@@ -57,10 +69,8 @@ def launch_bot():
             'source_data_desc': os.environ['source_data_desc']
         })
         st.session_state.cfg = cfg
-        st.session_state.vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_ids)
 
     cfg = st.session_state.cfg
-    vq = st.session_state.vq
     st.set_page_config(page_title=cfg.title, layout="wide")
 
     # Left side content
@@ -100,14 +110,14 @@ def launch_bot():
                 st.session_state.messages.append(message)
                 st.chat_message("assistant")
                 st.write(denial_response)
-    
+
     # Generate a new response if the last message is not from assistant
     if st.session_state.messages[-1]["role"] != "assistant":
         with st.chat_message("assistant"):
             with st.spinner("Thinking..."):
                 prompt2 = prompt + master_prompt
-                response = generate_response(prompt2) 
-                st.write(response) 
+                response = generate_response(prompt2)
+                st.write(response)
 
                 message = {"role": "assistant", "content": response}
                 st.session_state.messages.append(message)