Upload app.py

app.py

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+from dataclasses import dataclass
+from typing import Literal
+import streamlit as st
+import os
+# from llamaapi import LlamaAPI
+# from langchain_experimental.llms import ChatLlamaAPI
+from langchain.embeddings import HuggingFaceEmbeddings
+from pinecone import Pinecone
+from langchain.vectorstores import Pinecone
+from langchain.prompts import PromptTemplate
+from langchain.chains import RetrievalQA
+import streamlit.components.v1 as components
+from langchain_groq import ChatGroq
+from langchain.chains import ConversationalRetrievalChain
+from langchain.memory import ChatMessageHistory, ConversationBufferMemory
+import time
+
+HUGGINGFACEHUB_API_TOKEN = st.secrets['HUGGINGFACEHUB_API_TOKEN']
+
+@dataclass
+class Message:
+    """Class for keeping track of a chat message."""
+    origin: Literal["👤 Human", "👨🏻‍⚖️ Ai"]
+    message: str
+
+
+def download_hugging_face_embeddings():
+    embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2')
+    return embeddings
+
+
+def initialize_session_state():
+    if "history" not in st.session_state:
+        st.session_state.history = []
+    if "conversation" not in st.session_state:
+        # llama = LlamaAPI(st.secrets["LlamaAPI"])
+        # model = ChatLlamaAPI(client=llama)
+        chat = ChatGroq(temperature=0.5, groq_api_key=st.secrets["Groq_api"], model_name="mixtral-8x7b-32768")
+
+        embeddings = download_hugging_face_embeddings()
+
+        import os
+        os.environ['PINECONE_API_KEY'] = st.secrets["PINECONE_API_KEY"]
+        pc = Pinecone()
+        index_name = "medical-advisor"  # put in the name of your pinecone index here
+
+        docsearch = Pinecone.from_existing_index(index_name, embeddings)
+
+        prompt_template = """
+            You are a trained bot to guide people about their medical concerns. You will answer user's query with your knowledge and the context provided. 
+            If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
+            Do not say thank you and tell you are an AI Assistant and be open about everything.
+            Use the following pieces of context to answer the users question.
+            Context: {context}
+            Question: {question}
+            Only return the helpful answer below and nothing else.
+            Helpful answer:
+            """
+
+        PROMPT = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
+        
+        #chain_type_kwargs = {"prompt": PROMPT}
+        message_history = ChatMessageHistory()
+        memory = ConversationBufferMemory(
+            memory_key="chat_history",
+            output_key="answer",
+            chat_memory=message_history,
+            return_messages=True,
+            )
+        retrieval_chain = ConversationalRetrievalChain.from_llm(llm=chat,
+                                                      chain_type="stuff",
+                                                      retriever=docsearch.as_retriever(
+                                                          search_kwargs={'k': 2}),
+                                                      return_source_documents=True,
+                                                      combine_docs_chain_kwargs={"prompt": PROMPT},
+                                                      memory= memory
+                                                     )
+
+        st.session_state.conversation = retrieval_chain
+
+
+def on_click_callback():
+    human_prompt = st.session_state.human_prompt
+    st.session_state.human_prompt=""
+    response = st.session_state.conversation(
+        human_prompt
+    )
+    llm_response = response['answer']
+    st.session_state.history.append(
+        Message("👤 Human", human_prompt)
+    )
+    st.session_state.history.append(
+        Message("👨🏻‍⚖️ Ai", llm_response)
+    )
+
+
+initialize_session_state()
+
+st.title("LegalEase Advisor Chatbot 🇮🇳")
+
+# st.markdown(
+#     """
+#     👋 **Namaste! Welcome to LegalEase Advisor!**
+#     I'm here to assist you with your legal queries within the framework of Indian law. Whether you're navigating through specific legal issues or seeking general advice, I'm here to help.
+    
+#     📚 **How I Can Assist:**
+    
+#     - Answer questions on various aspects of Indian law.
+#     - Guide you through legal processes relevant to India.
+#     - Provide information on your rights and responsibilities as per Indian legal standards.
+    
+#     ⚖️ **Disclaimer:**
+    
+#     While I can provide general information, it's essential to consult with a qualified Indian attorney for advice tailored to your specific situation.
+    
+#     🤖 **Getting Started:**
+    
+#     Feel free to ask any legal question related to Indian law, using keywords like "property rights," "labor laws," or "family law." I'm here to assist you!
+#     Let's get started! How can I assist you today?
+#     """
+# )
+
+chat_placeholder = st.container()
+prompt_placeholder = st.form("chat-form")
+
+with chat_placeholder:
+    for chat in st.session_state.history:
+        st.markdown(f"{chat.origin} : {chat.message}")
+
+with prompt_placeholder:
+    st.markdown("**Chat**")
+    cols = st.columns((6, 1))
+    cols[0].text_input(
+        "Chat",
+        label_visibility="collapsed",
+        key="human_prompt",
+    )
+    cols[1].form_submit_button(
+        "Submit",
+        type="primary",
+        on_click=on_click_callback,
+    )