Update app.py

app.py

@@ -1,61 +1,62 @@
-import langchain
-from langchain.chat_models import ChatOpenAI
-from langchain.chains import RetrievalQA
-from langchain_groq import ChatGroq
-from langchain.prompts import PromptTemplate
-from langchain.vectorstores import Chroma
-from langchain.embeddings import TensorflowHubEmbeddings,HuggingFaceEmbeddings
-import gradio as gr
-from langchain.memory import ConversationBufferMemory
-from langchain.chains import ConversationalRetrievalChain
-embeddings=HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2')
-llm=ChatGroq(api_key='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')
-vector_db = Chroma(persist_directory='./db', embedding_function=embeddings)
-# Define a custom prompt template (Modify as needed)
-prompt_template = PromptTemplate.from_template(
-    "Use the following context to answer the question you have no answer tell me i dont know:\n\n{context}\n\nQuestion: {question} "
-)
-memory=ConversationBufferMemory(
-    memory_key='chat_history',
-    return_messages=True
-)
-
-prompt=PromptTemplate.from_template(
-        """You are an AI assistant that provides accurate and concise answers.
-Use the following retrieved documents to answer the question. If you don't know, say "I don't know."
-
-Context:
-{context}
-
-Question:
-{question}
-
-Answer:
-""")
-
-retriever=vector_db.as_retriever(
-    search_type='similarity',
-    search_kwargs={'k':4}
-)
-
-
-con=ConversationalRetrievalChain.from_llm(
-    llm=llm,
-    retriever=retriever,
-    memory=memory,
-    combine_docs_chain_kwargs={'prompt':prompt})
-
-# Use the new RetrievalQA structure
-retriever=vector_db.as_retriever(search_kwargs={"k": 3})
-
-
-def chat(query,history):
-    try:
-        response=con.run({'question':query,'chat_history':history})
-        return str(response)
-    except Exception as e:
-        return 'slow connection'
-
-app=gr.ChatInterface(chat,theme=gr.themes.Soft(),title='Chat With Nasir Hussain'
-                     ,description='I have provide llm Nasir Husssain Youtube Playlist Data Playlist Link Here:https://youtube.com/playlist?list=PLuYWhEqu9a9A7s21UXlZ1yYNPk5ZLfhpH&si=qg8iuts2csW3P4bQ')
-app.launch(share=True)
+import langchain
+from langchain.chat_models import ChatOpenAI
+from langchain.chains import RetrievalQA
+from langchain_groq import ChatGroq
+from langchain.prompts import PromptTemplate
+from langchain.vectorstores import Chroma
+import os
+from langchain.embeddings import TensorflowHubEmbeddings,HuggingFaceEmbeddings
+import gradio as gr
+from langchain.memory import ConversationBufferMemory
+from langchain.chains import ConversationalRetrievalChain
+embeddings=HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2')
+llm=ChatGroq(api_key=os.getenv('groq_api'))
+vector_db = Chroma(persist_directory='./db', embedding_function=embeddings)
+# Define a custom prompt template (Modify as needed)
+prompt_template = PromptTemplate.from_template(
+    "Use the following context to answer the question you have no answer tell me i dont know:\n\n{context}\n\nQuestion: {question} "
+)
+memory=ConversationBufferMemory(
+    memory_key='chat_history',
+    return_messages=True
+)
+
+prompt=PromptTemplate.from_template(
+        """You are an AI assistant that provides accurate and concise answers.
+Use the following retrieved documents to answer the question. If you don't know, say "I don't know."
+
+Context:
+{context}
+
+Question:
+{question}
+
+Answer:
+""")
+
+retriever=vector_db.as_retriever(
+    search_type='similarity',
+    search_kwargs={'k':4}
+)
+
+
+con=ConversationalRetrievalChain.from_llm(
+    llm=llm,
+    retriever=retriever,
+    memory=memory,
+    combine_docs_chain_kwargs={'prompt':prompt})
+
+# Use the new RetrievalQA structure
+retriever=vector_db.as_retriever(search_kwargs={"k": 3})
+
+
+def chat(query,history):
+    try:
+        response=con.run({'question':query,'chat_history':history})
+        return str(response)
+    except Exception as e:
+        return 'slow connection'
+
+app=gr.ChatInterface(chat,theme=gr.themes.Soft(),title='Chat With Nasir Hussain'
+                     ,description='I have provide llm Nasir Husssain Youtube Playlist Data Playlist Link Here:https://youtube.com/playlist?list=PLuYWhEqu9a9A7s21UXlZ1yYNPk5ZLfhpH&si=qg8iuts2csW3P4bQ')
+app.launch(share=True)