Update app.py

app.py

@@ -18,23 +18,37 @@ GOOGLE_API_KEY=os.environ['GOOGLE_API_KEY']
 genai.configure(api_key=GOOGLE_API_KEY)
 
 
-loader = WebBaseLoader("https://blog.google/technology/ai/google-gemini-ai/")
+loader = WebBaseLoader("https://www.google.com/finance/?hl=en")
 docs = loader.load()
-st.write(len(docs))
+# If there is no environment variable set for the API key, you can pass the API
+# key to the parameter `google_api_key` of the `ChatGoogleGenerativeAI` function:
+# `google_api_key="key"`.
+llm = ChatGoogleGenerativeAI(model="gemini-pro",google_api_key = GOOGLE_API_KEY)
 
 
-model = genai.GenerativeModel('gemini-pro')
+llm_prompt_template = """You are an assistant for question-answering tasks.
+Use the following context to answer the question.
+If you don't know the answer, just say that you don't know.
+Use five sentences maximum and keep the answer concise.\n
+Question: {question} \nContext: {context} \nAnswer:"""
 
-prompt = st.text_input("Enter Prompt","What is the meaning of life?")
-response = model.generate_content(prompt)
+llm_prompt = PromptTemplate.from_template(llm_prompt_template)
 
-st.write(response.text)
-# If there is no environment variable set for the API key, you can pass the API
-# key to the parameter `google_api_key` of the `ChatGoogleGenerativeAI` function:
-# `google_api_key="key"`.
-# llm = ChatGoogleGenerativeAI(model="gemini-pro",
-#                  temperature=0.7, top_p=0.85)
 
+def format_docs(docs):
+    return "\n\n".join(doc.page_content for doc in docs)
+
+rag_chain = (
+    {"context": retriever | format_docs, "question": RunnablePassthrough()}
+    | llm_prompt
+    | llm
+    | StrOutputParser()
+)
+
+prompt = st.text_input("Enter Prompt","What is the best stocks for the next few weeks")
+
+res = rag_chain.invoke(prompt)
+st.write(res)
 
 # If there is no environment variable set for the API key, you can pass the API
 # key to the parameter `google_api_key` of the `GoogleGenerativeAIEmbeddings`