Upload 6 files

config.py

@@ -31,21 +31,20 @@ class Settings:
     Options: "Here's a couple of ideas: Step Back or Talk It Out. Which one feels right for you?"
     Will: "Confronting someone can be scary. How about jotting down your thoughts first? Are you willing to try that?"
     Check-In: "I'll hit you up tomorrow to see how things are going. Got any other questions?"
-    Remember to keep the conversation light, supportive, and focused on helping the user feel understood and empowered.
-    
+
     IMPORTANT INSTRUCTIONS:
         # use gen z and edgy words.
-        # Must Not REPEAT ANY RESPONSE and Repeat any words
+        # Must Not REPEAT ANY RESPONSE.
         # Use sometimes slangs.
         # provide short answers like a conversation.
         # dont responed any gratitude words like sorry.
         # Previous Conversation Summary: {previous_summary}
-        # resource suggestions means for podcast only nothing else.
+        # resources means podcast only nothing else. also topic of resource must be asked before suggesting anything.example: I’m here for it! Are we talking friend drama, school stress, or something else? Give me the lowdown so I can find the right resources for you. 
+
         # you have two tools app_featues and recommendation_tool make sure to use appropriate tool is invoke for any app feature related question must use app_feature and for any resource or podcast related question use recommendation_tool.
-        # if conversation is ending must use close_chat tool no other tools.
-        # if user gets suggestion and recommendation don't give it again. just end the conversation.
-        # must Avoid using the words 'vibe'. Instead, use alternative expressions.
-        # must not use two tools in single execution.
+        # if conversation is ending must use close_chat tool no other tools. and fix the response of close tool based on chat history.
+        # must Avoid using the words 'vibe'. Instead, use alternative expressions and must not repeate any words.
+        # if you are giving any suggestions in flow then must use simple bullet points.
 """
 
 
@@ -69,6 +68,7 @@ class Settings:
     MONGODB_DB_USER_SESSIONS_COLLECTION_NAME = "user_sessions"
     MONGODB_DB_CHAT_BOT_TOOLS_COLLECTION_NAME = "session_tool"
     MONGODB_DB_CHAT_BOT_MOOD_COLLECTION_NAME = "mood_summary"
+    MONGODB_DB_CHAT_RECOMEDATION_COLLECTION_NAME = 'chat_recommendation'
 
     mongodb_client = pymongo.MongoClient(MONGODB_CONNECTION_STRING)
     mongodb_db = mongodb_client.get_database(MONGODB_DB_NAME)  # Replace with your database name if not using default

database_functions.py

@@ -133,4 +133,19 @@ def isFirstSession(user_id):
     if user_sessions:
         return  len(user_sessions['session_id'])==1
     else:
-        return False
+        return False
+    
+
+def set_recommendation_count(last_session_id):
+    mongodb_chat_recommendation_collection = settings.mongodb_db.get_collection(settings.MONGODB_DB_CHAT_RECOMEDATION_COLLECTION_NAME)
+    if mongodb_chat_recommendation_collection.count_documents({"session_id": last_session_id})==0:
+        mongodb_chat_recommendation_collection.insert_one({"session_id": last_session_id,"give_recommendation": True} )
+ 
+def get_recommendation_count(last_session_id):
+     mongodb_chat_recommendation_collection = settings.mongodb_db.get_collection(settings.MONGODB_DB_CHAT_RECOMEDATION_COLLECTION_NAME)
+     data = mongodb_chat_recommendation_collection.find_one({"session_id":last_session_id})
+     if data:
+         return data['give_recommendation']
+     else:
+        return False
+    

tools.py

@@ -9,9 +9,10 @@ from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser
 from langchain.agents import AgentExecutor
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
 from config import settings
+from database_functions import set_recommendation_count,get_recommendation_count
 
 MEMORY = None
-
+SESSION_ID= ""
 
 def get_embeddings(text_list):
     encoded_input = settings.tokenizer(
@@ -275,7 +276,7 @@ def my_rewards(prompt: str) -> str:
     return response.content
 
 
-@tool("mentoring-questions", )
+@tool("mentoring-questions")
 def mentoring(prompt: str) -> str:
     """this function is used when user wants to know about 1-1 mentoring feature.  1:1 MENTORING: Personalized mentoring (coming soon).
 
@@ -320,7 +321,7 @@ def my_journal(prompt: str) -> str:
 
 @tool("podcast-recommendation-tool")
 def recommand_podcast(prompt: str) -> str:
-    """ this function must used when user wants to any resources only.
+    """  must used when user wants to any resources only.
     Args:
         prompt (string): user query
 
@@ -334,13 +335,13 @@ def recommand_podcast(prompt: str) -> str:
         context+= f"Row {index + 1}: Title: {row['title']} image: {row['cover_image']} referral_link: {row['referral_link']} category_id: {row['category_id']}"
     llm = ChatOpenAI(model=settings.OPENAI_MODEL, openai_api_key=settings.OPENAI_KEY, temperature=0.7)
     # Define the system prompt
-    system_template = """ you have to give the recommandation of podcast for: {input}. also you are giving referal link of podcast.
+    system_template = """ you have to give the recommandation of podcast for: {input}. also you are giving referal link of podcast. give 3-4 podcast only.
     you must use the context only not any other information.
     context : {context}
     """
     # print(system_template.format(context=context, input=prompt))
     response = llm.invoke(system_template.format(context=context, input=prompt))
-
+    set_recommendation_count(SESSION_ID)
     return response.content
 
 @tool("set-chat-bot-name",return_direct=True )
@@ -357,29 +358,48 @@ def set_chatbot_name(name: str) -> str:
 
 @tool("clossing-chat",return_direct=True)
 def close_chat(summary:str)-> str:
-    """ when you feel it's time to finish the conversation use this tool.
-        must use this tool when user closing the conversation. must use this tool when you are ending the conversation.
-
+    """  must use this tool when user closing the conversation. must use this tool when you are ending the conversation.
     Args:
-        summary (str): summary of whole chat with your friend.
+        summary (str): summary of whole chat with your friend. must use I for yourself and for user use my friend.
 
     Returns:
         str: closing chat statements.
     """
     
     print('close tool starts')
-    system_template = """ you have given one summary of chat. 
-    summary : {summary}.
-    using this summary give recommandation of podcast or suggest any features from given tools and make response. also you are going to close the conversation with your friend.
-    if user already received suggestions, you must not give again. and just end the conversation inshort wihtout mentioning anything. 
-    # make all responses short and don't remove any podcast links.
-    """
-           
-    tools = [moxicast, my_calender, my_journal, my_rewards, my_rituals, my_vibecheck, peptalks, sactury, power_zens, affirmations, horoscope, mentoring, influencer_post, recommand_podcast]
-    functions = [convert_to_openai_function(f) for f in tools]
-    llm = ChatOpenAI(model=settings.OPENAI_MODEL, openai_api_key=settings.OPENAI_KEY, temperature=0.7).bind(functions=functions)
+
+    global SESSION_ID
+    tools = []
+    llm = ChatOpenAI(model=settings.OPENAI_MODEL, openai_api_key=settings.OPENAI_KEY, temperature=0.7)
+    if (not get_recommendation_count(SESSION_ID)):
+        tools.extend([moxicast, my_calender, my_journal, my_rewards, my_rituals, my_vibecheck, peptalks, sactury, power_zens, affirmations, horoscope, mentoring, influencer_post,recommand_podcast])
+    
+    if len(tools)!=0:
+        functions = [convert_to_openai_function(f) for f in tools]
+        llm = llm.bind(functions= functions)
     print('llm is created')
     
+    system_template = """"""
+    if len(tools)!=0:
+        system_template += """ context: there is one typical conversation going on between two high school gen z girls.
+        you are one of the high school gen z girl. your voice is edgy and raw. 
+        now you are going to close the conversation.
+        summary of conversation is given to you.
+        summary: {summary}
+        give recommendation of any podcast or app feature based on summary and close the conversation in short.
+        # must Avoid using the words 'vibe'. Instead, use alternative expressions and must not repeate any words.
+        """
+    else:
+        system_template+= """ context: there is one typical conversation going on between two high school gen z girls.
+        you are one of the high school gen z girl. your voice is edgy and raw. 
+        now you are going to close the conversation.
+        summary of conversation is given to you.
+        summary: {summary}
+        now just end the conversation in 1 sentense in short.
+        # must Avoid using the words 'vibe'. Instead, use alternative expressions and must not repeate any words.
+        """
+
+
     prompt = ChatPromptTemplate.from_messages([("system", system_template.format(summary = summary)),MessagesPlaceholder(variable_name="agent_scratchpad")])
     chain = RunnablePassthrough.assign(agent_scratchpad=lambda x: format_to_openai_functions(x["intermediate_steps"])) | prompt |llm | OpenAIFunctionsAgentOutputParser()
     print('chain is rolling')
@@ -395,7 +415,7 @@ def close_chat(summary:str)-> str:
 
 @tool("App-Fetures")
 def app_features(summary:str)-> str:
-    """ For any app features details only use this tool.
+    """ must use For any app features details.
 
     Args:
         summary (str): summary of whole chat with your friend.
@@ -407,8 +427,7 @@ def app_features(summary:str)-> str:
     print('app feature tool starts')
     system_template = """ you have given one summary of chat. 
     summary : {summary}.
-    if summary doesn't specify any feature name ask question don't invoke any tool.
-    using this summary give appropriate features suggestions using tools.
+    using this summary give appropriate features suggestions using tools. if you don't find any tool appropriate to summary ask question only.
     # make all responses short.
     """
            
@@ -425,7 +444,7 @@ def app_features(summary:str)-> str:
                       
     print('agent is created')
     # print(system_template.format(context=context, input=prompt))\
-
+    set_recommendation_count(SESSION_ID)
     response = agent.invoke({})['output']
     return response
 
@@ -451,4 +470,4 @@ def joke_teller(summary: str) -> str:
     """
     response = llm.invoke(system_template.format(summary=summary))
 
-    return response.content
+    return response.content

utils.py

@@ -12,7 +12,7 @@ from langchain.agents.format_scratchpad import format_to_openai_functions
 from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser
 from langchain.agents import AgentExecutor
 
-from tools import MEMORY, set_chatbot_name, close_chat, recommand_podcast,app_features,joke_teller
+from tools import MEMORY, set_chatbot_name, close_chat, recommand_podcast,app_features,joke_teller,SESSION_ID
 
 from database_functions import get_chat_bot_name,get_chat_history, get_last_conversion, get_last_session, get_mood_data
 
@@ -103,8 +103,9 @@ def create_agent(user_id,is_first = False):
         previous_session_id['last_session_id']), return_messages=True, k=5)
     
     # print("memory created")
-    global MEMORY
+    global MEMORY,SESSION_ID
     MEMORY = memory
+    SESSION_ID = previous_session_id['last_session_id']
 
     chain = RunnablePassthrough.assign(agent_scratchpad=lambda x: format_to_openai_functions(x["intermediate_steps"])) | prompt | model | OpenAIFunctionsAgentOutputParser()