push

app.py

@@ -37,7 +37,29 @@ BOT_AVATAR = 'https://automatedstockmining.org/wp-content/uploads/2024/08/south-
 
 
 
+#for the search vector database
 
+# Initialize Chroma vector store directory
+db_name2 = "search_checkvector_db"
+
+# Read in the text for processing
+health_check_text = ''
+with open('search_requirements.txt', 'r', encoding='utf-8') as search_text:
+    search_requirements_text = search_text.read()
+
+# Split text into chunks
+search_splitter = CharacterTextSplitter(chunk_size=20, chunk_overlap=2)
+parts = search_splitter.split_text(search_requirements_text)
+
+
+search_documents = [Document(page_content=chunk) for chunk in chunks]
+
+# Initialize Chroma with documents and embeddings
+search_vectorstore = Chroma.from_documents(
+    documents=search_documents,
+    embedding=embedding_model,
+    persist_directory=db_name
+)
 
 
 
@@ -156,12 +178,19 @@ def process_query(user_input, history):
     # Retrieve and concatenate results
     retrieved_texts = " ".join([doc.page_content for doc in docs])
 
+
+    #similarity search on searches
+    searches = search_vectorstore.similarity_search(user_input, k=3)
+
+    # Retrieve and concatenate results
+    search_texts = " ".join([doc.page_content for doc in searches])
+
     yield 'Preparing your request 🛠️'
     
     # Step 1: Generate a search term based on the user query
     stream_search = client.chat_completion(
         model="Qwen/Qwen2.5-72B-Instruct",
-        messages=[{"role": "user", "content": f"Based on this chat history {history}and the user's request '{user_input}', suggest a Google search term in a single line without specific dates; use 'this year', 'this month', etc. INCLUDE NOTHING IN YOUR RESPONSE EXCEPT THE RELEVANT SEARCH RESULT. EXAMPLE: USER: WHAT IS THE CURRENT PRICE OF COCA COLA STOCK. YOUR RESPONSE: WHAT IS THE CURRENT PRICE OF COCA COLA STOCK. IF THE USER ASKS FOR A HEALTHCHECK, SEARCH FOR CURRENT METRICS FOR THE COMPANY."}],
+        messages=[{"role": "user", "content": f"Based on this chat history {history} the user's request '{user_input}', and this vector database {search_texts}, suggest a Google search term in a single line without specific dates; use 'this year', 'this month', etc. INCLUDE NOTHING IN YOUR RESPONSE EXCEPT THE RELEVANT SEARCH RESULT. EXAMPLE: USER: WHAT IS THE CURRENT PRICE OF COCA COLA STOCK. YOUR RESPONSE: WHAT IS THE CURRENT PRICE OF COCA COLA STOCK"}],
         max_tokens=400,
         stream=True
     )
@@ -184,7 +213,7 @@ def process_query(user_input, history):
     # Step 3: Generate a response using the search results
     response = client.chat_completion(
         model="Qwen/Qwen2.5-72B-Instruct",
-        messages=[{"role": "user", "content": f"Using the search results: {search_results_str} and chat history {history}, this vector database on health checks {retrieved_texts} answer the user's query '{user_input}' in a concise, precise way,  using numerical data if available. ONLY GIVE ONE RESPONSE BACK, CONCISE OR DETAILED BASED ON THE USERS INPUT, if they ask for a smart sheet analyse the data in immense detail going over every point"}],
+        messages=[{"role": "user", "content": f"Using the search results: {search_results_str} and chat history {history}, this vector database on health checks {retrieved_texts} answer the user's query '{user_input}' in a concise, precise way,  using numerical data if available. ONLY GIVE ONE RESPONSE BACK, CONCISE OR DETAILED BASED ON THE USERS INPUT"}],
         max_tokens=3000,
         stream=True
     )

healthcheck.txt

@@ -166,3 +166,7 @@ you will return:
 A QuantiNeuron Health Check Score on a 1-10 scale.
 A Health Summary, outlining strengths and weaknesses based on metrics.
 A Recommendation Statement, if necessary, for areas needing attention.
+
+
+SMART SHEET OBJECTIVE:
+ANALYSE THE NEWS BROUGHT IN ON THE TOPIC IN IMMENSE DETAIL, ANALYSING EVERYTHING AND SIMULATING POSSIBLE OUTCOMES(WHERE NECCESSARY), EXPLAIN THE IMPLICATIONS OF THE NEWS AND WHAT MAY HAPPEN BECAUSE OF IT, ANALYSE IT IN DEPTH.

search_requirements.txt

@@ -0,0 +1,8 @@
+OBJECTIVE:
+you produce searches based on the users query.
+
+WHEN THE USER ASKS FOR A HEALTH CHECK:
+search for the latest metrics on the company
+
+WHEN THE USER ASKS FOR A SMART SHEET:
+search for the latest news on the event