Update app.py

app.py

@@ -12,6 +12,40 @@ from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.chains import LLMChain
 from langchain.memory import ConversationBufferMemory
 
+# Set persistent storage path
+PERSISTENT_DIR = "vector_db"
+
+def initialize_vector_db():
+    if os.path.exists(PERSISTENT_DIR) and os.listdir(PERSISTENT_DIR):
+        embeddings = HuggingFaceEmbeddings()
+        vector_db = Chroma(persist_directory=PERSISTENT_DIR, embedding_function=embeddings)
+        return None, vector_db
+    
+    base_dir = os.path.dirname(os.path.abspath(__file__))
+    pdf_files = [f for f in os.listdir(base_dir) if f.endswith('.pdf')]
+    loaders = [PyPDFLoader(os.path.join(base_dir, fn)) for fn in pdf_files]
+    
+    documents = []
+    for loader in loaders:
+        documents.extend(loader.load())
+    
+    text_splitter = RecursiveCharacterTextSplitter(
+        chunk_size=1000,
+        chunk_overlap=200,
+        length_function=len,
+        separators=["\n\n", "\n", " ", ""]
+    )
+    texts = text_splitter.split_documents(documents)
+    
+    embeddings = HuggingFaceEmbeddings()
+    vector_db = Chroma.from_documents(
+        texts, 
+        embeddings, 
+        persist_directory=PERSISTENT_DIR
+    )
+    vector_db.persist()
+    return documents, vector_db
+
 # Initialize session state for chat history and memory
 if "chat_history" not in st.session_state:
     st.session_state.chat_history = []
@@ -21,10 +55,46 @@ if "memory" not in st.session_state:
         return_messages=True
     )
 
-# Add sidebar
+# System instructions for the LLM
+system_prompt = """You are an expert organic farming consultant with specialization in Agro-Homeopathy. When providing suggestions and remedies:
+1. Always specify medicine potency as 6c unless the uploaded text mentions some other value explicitly
+3. Provide comprehensive diagnosis and treatment advice along with organic farming best practices applicable in the given context
+4. Base recommendations on homeopathic and organic farming principles
+"""
+
+api_key1 = os.getenv("api_key")
+
+# Page configuration
+start_time = time.time()
+st.set_page_config(page_title="Dr. Radha: The Agro-Homeopath", page_icon="🚀", layout="wide")
+
+# CSS styling
+st.markdown("""
+<style>
+    .stApp {
+        background-color: #1B4D3E !important;
+        color: white !important;
+    }
+    .stTextInput>div>div>input {
+        color: black !important;
+        background-color: rgba(255,255,255,0.1) !important;
+    }
+    .stButton>button {
+        color: black !important;
+        background-color: yellow !important;
+    }
+    #the-title {
+        text-align: center;
+        font-size: 24px;
+        color: white;
+    }
+</style>
+""", unsafe_allow_html=True)
+
+# Sidebar
 st.sidebar.title("Chat History")
 
-# Add Clear Session button in sidebar
+# Clear Session button
 if st.sidebar.button("Clear Session"):
     st.session_state.chat_history = []
     st.session_state.memory.clear()
@@ -36,7 +106,72 @@ for i, chat in enumerate(st.session_state.chat_history):
     if st.sidebar.button(f"Go to Q{i+1}", key=f"btn_{i}"):
         st.session_state.query = chat['question']
 
-# Update the QA chain to include memory
+# Main content
+st.title("🌿 Dr. Radha: AI-Powered Organic Farming Consultant")
+st.subheader("Specializing in Agro-Homeopathy | Free Consultation")
+
+st.markdown("""
+Please provide complete details about the issue, including:
+- Detailed description of plant problem
+- Current location, temperature & weather conditions
+""")
+
+human_image = "human.png"
+robot_image = "bot.jpg"
+
+# Set up Groq API
+llm = ChatGroq(
+    api_key=api_key1, 
+    max_tokens=None, 
+    timeout=None, 
+    max_retries=2, 
+    temperature=0.7,
+    model="llama-3.1-70b-versatile"
+)
+
+embeddings = HuggingFaceEmbeddings()
+
+# Initialize session state for documents and vector_db
+if "documents" not in st.session_state:
+    st.session_state["documents"] = None
+if "vector_db" not in st.session_state:  
+    st.session_state["vector_db"] = None
+if "query" not in st.session_state:
+    st.session_state["query"] = ""
+
+# Initialize vector database
+if st.session_state["documents"] is None or st.session_state["vector_db"] is None:
+    with st.spinner("Loading data..."):
+        documents, vector_db = initialize_vector_db()
+        st.session_state["documents"] = documents  
+        st.session_state["vector_db"] = vector_db
+else:
+    documents = st.session_state["documents"]
+    vector_db = st.session_state["vector_db"]
+
+retriever = vector_db.as_retriever()
+
+# Prompt templates
+prompt_template = """As an expert organic farming consultant with specialization in Agro-Homeopathy, analyze the following context and question to provide a clear, structured response.
+
+Context: {context}
+Chat History: {chat_history}
+Question: {question}
+
+[Rest of your prompt template...]
+
+Answer:"""
+
+fallback_template = """As an expert organic farming consultant with specialization in Agro-Homeopathy, analyze the following context and question to provide a clear, structured response.
+
+Chat History: {chat_history}
+Question: {question}
+
+[Rest of your fallback template...]
+
+Answer:"""
+
+# Create QA chain with memory
 qa = RetrievalQA.from_chain_type(
     llm=llm,
     chain_type="stuff",
@@ -50,14 +185,26 @@ qa = RetrievalQA.from_chain_type(
     }
 )
 
-# Update fallback chain to include memory
+# Create fallback chain with memory
+fallback_prompt = PromptTemplate(
+    template=fallback_template, 
+    input_variables=["question", "chat_history"]
+)
 fallback_chain = LLMChain(
     llm=llm, 
     prompt=fallback_prompt,
     memory=st.session_state.memory
 )
 
-# Update the form submission handling
+# Chat container
+chat_container = st.container()
+
+# Query form
+with st.form(key='query_form'):
+    query = st.text_input("Ask your question:", value=st.session_state.get("query", ""))
+    submit_button = st.form_submit_button(label='Submit')
+
+# Handle form submission
 if submit_button and query:
     with st.spinner("Generating response..."):
         # Add query to chat history
@@ -99,9 +246,8 @@ if submit_button and query:
             if chat['question'] == query:
                 st.markdown(f"{response}")
             else:
-                # Retrieve previous response from memory
                 prev_response = st.session_state.memory.load_memory_variables({})
-                st.markdown(f"{prev_response}")
+                st.markdown(f"{prev_response.get('chat_history', '')}")
 
     st.markdown("---")
     st.session_state["query"] = ""