Update app/MultiAgent.py

app/MultiAgent.py

@@ -1,187 +1,187 @@
-from agents import  Agent, ModelSettings, Runner, RunConfig,OpenAIResponsesModel ,AsyncOpenAI,function_tool,OpenAIChatCompletionsModel
-from pydantic import BaseModel
-from datetime import datetime, date
-from dotenv import load_dotenv
-load_dotenv(dotenv_path="./.env.local")
-import asyncio
-from typing import List
-from .VectorDBManagers import VectorDBManager
-from chatkit.agents import AgentContext
-import os 
-import nest_asyncio
-nest_asyncio.apply()
-from .function_tool import suggestion_ragtool
-kimi_model = OpenAIResponsesModel(
-    model="openai/gpt-oss-20b",  # Valid Groq model
-    openai_client=AsyncOpenAI(
-        base_url="https://api.groq.com/openai/v1",
-        api_key=os.getenv("GROQ_API_KEY"),
-    )
-)
-google_model = OpenAIChatCompletionsModel(
-    model="google/gemini-2.5-flash",  # Google Gemini via OpenRouter
-    openai_client=AsyncOpenAI(
-         base_url="https://openrouter.ai/api/v1",
-        api_key=os.getenv("OPENROUTER_API_KEY"),
-    )
-)
-deepseek_model = OpenAIChatCompletionsModel(
-    model="deepseek/deepseek-chat",  # DeepSeek via OpenRouter
-    openai_client=AsyncOpenAI(
-        base_url="https://openrouter.ai/api/v1",
-        api_key=os.getenv("OPENROUTER_API_KEY"),
-    )
-)
-
-sumary_model = OpenAIResponsesModel(
-    model="moonshotai/kimi-k2-instruct-0905",  # Valid Groq model
-    openai_client=AsyncOpenAI(
-        base_url="https://api.groq.com/openai/v1",
-        api_key=os.getenv("GROQ_API_KEY")
-    )
-)
-def build_sugguestion_information_agent()-> Agent[AgentContext]:
-    
-
-    current_time = datetime.now()
-    current_date = date.today()
-    current_day = datetime.today().strftime("%A")
-    information_agent = Agent[AgentContext](
-        name="company_suggestion_information",
-        instructions=(
-    "You are an information agent and customer service representative for the company. "
-    "Your goal is to provide clear, concise answers using ONLY the suggestion_ragtool tool. "
-    "For greeting do not call tool reply by your self add company name "
-    "Always speak as the company using 'we'. Do NOT guess or assume. "
-    "If information is not found, reply politely: "
-    "phraphse according to your intellgence 'No information is available regarding to this . You may book an appointment or speak to our sales agent for more details.' praphrase it "
-    
-    "Make only ONE suggestion_ragtool query that fully represents the user’s request. "
-    "All company-related answers must come strictly from the suggestion_ragtool tool. "
-    "Do not create or assume any details. Always use the correct company name. "
-    "The suggestion_ragtool result is your official answer. "
-    
-    "Respond in under not more than 80 words, in a friendly customer-service tone. "
-    "Never leave incomplete replies and never ignore earlier conversation context. "
-    
-    "As a customer support agent, always answer using official company information found through the suggestion_ragtool tool. for partcular question liek greeting and user info if you have so do not use tool reply by self "
-    f"Current system time : {current_time}, date: {current_date}, day: {current_day}. "
-),
-        model=deepseek_model,
-        tools=[
-            suggestion_ragtool
-        ],
-        model_settings=ModelSettings(
-            temperature=1,
-            top_p=1,
-            max_tokens=2048,
-        ),
-        )
-    return information_agent
-
-def build_summarizer_agent() -> Agent[AgentContext]:
-    """
-    Creates a summarizer agent that condenses chat history
-    into a short, factual summary for context preservation.
-    """
-    summarizer_agent = Agent[AgentContext](
-        name="Summarizer Agent",
-        instructions="""
-        You are a summarization assistant.
-        Your job is to take several user and assistant messages and produce a concise,
-        factual summary that captures key intents, facts, and outcomes.
-
-        Guidelines:
-        - Keep the summary under 80 words.
-        - Focus on what the user is asking for and the assistant's key responses.
-        - Do NOT add new information.
-        - Preserve important context like customer concerns, preferences, or goals.
-        - Write in plain English.
-        """,
-        model=sumary_model,  # or use default_model if configured in your environment
-        model_settings=ModelSettings(
-            temperature=0.3,
-            top_p=0.9,
-            max_tokens=300,
-        ),
-    )
-
-    return summarizer_agent
-def build_kimi_information_agent()-> Agent[AgentContext]:
-    
-
-    current_time = datetime.now()
-    current_date = date.today()
-    current_day = datetime.today().strftime("%A")
-    information_agent = Agent[AgentContext](
-        name="company_suggestion_information",
-        instructions=(
-    "You are an information agent and customer service representative for the company. "
-    "Your goal is to provide clear, concise answers using ONLY the suggestion_ragtool tool. "
-    "For greeting do not call tool reply by your self add company name "
-    "Always speak as the company using 'we'. Do NOT guess or assume. "
-    "If information is not found, reply politely: "
-    "phraphse according to your intellgence 'No information is available regarding to this . You may book an appointment or speak to our sales agent for more details.' praphrase it "
-    
-    "Make only ONE suggestion_ragtool query that fully represents the user’s request. "
-    "All company-related answers must come strictly from the suggestion_ragtool tool. "
-    "Do not create or assume any details. Always use the correct company name. "
-    "The suggestion_ragtool result is your official answer. "
-    
-    "Respond in under not more than 80 words, in a friendly customer-service tone. "
-    "Never leave incomplete replies and never ignore earlier conversation context. "
-    
-    "As a customer support agent, always answer using official company information found through the suggestion_ragtool tool. for partcular question liek greeting and user info if you have so do not use tool reply by self "
-    f"Current system time : {current_time}, date: {current_date}, day: {current_day}. "
-),
-        model=kimi_model,
-        tools=[
-            suggestion_ragtool
-        ],
-        model_settings=ModelSettings(
-            temperature=1,
-            top_p=1,
-            max_tokens=2048,
-        ),
-        )
-    return information_agent
-
-
-def build_google_information_agent()-> Agent[AgentContext]:
-    
-
-    current_time = datetime.now()
-    current_date = date.today()
-    current_day = datetime.today().strftime("%A")
-    information_agent = Agent[AgentContext](
-        name="company_suggestion_information",
-        instructions=(
-    "You are an information agent and customer service representative for the company. "
-    "Your goal is to provide clear, concise answers using ONLY the suggestion_ragtool tool. "
-    "For greeting do not call tool reply by your self add company name "
-    "Always speak as the company using 'we'. Do NOT guess or assume. "
-    "If information is not found, reply politely: "
-    "phraphse according to your intellgence 'No information is available regarding to this . You may book an appointment or speak to our sales agent for more details.' praphrase it "
-    
-    "Make only ONE suggestion_ragtool query that fully represents the user’s request. "
-    "All company-related answers must come strictly from the suggestion_ragtool tool. "
-    "Do not create or assume any details. Always use the correct company name. "
-    "The suggestion_ragtool result is your official answer. "
-    
-    "Respond in under not more than 80 words, in a friendly customer-service tone. "
-    "Never leave incomplete replies and never ignore earlier conversation context. "
-    
-    "As a customer support agent, always answer using official company information found through the suggestion_ragtool tool. for partcular question liek greeting and user info if you have so do not use tool reply by self "
-    f"Current system time : {current_time}, date: {current_date}, day: {current_day}. "
-),
-        model=google_model,
-        tools=[
-            suggestion_ragtool
-        ],
-        model_settings=ModelSettings(
-            temperature=1,
-            top_p=1,
-            max_tokens=2048,
-        ),
-        )
-    return information_agent
+from agents import  Agent, ModelSettings, Runner, RunConfig,OpenAIResponsesModel ,AsyncOpenAI,function_tool,OpenAIChatCompletionsModel
+from pydantic import BaseModel
+from datetime import datetime, date
+from dotenv import load_dotenv
+load_dotenv(dotenv_path="./.env.local")
+import asyncio
+from typing import List
+from .VectorDBManagers import VectorDBManager
+from chatkit.agents import AgentContext
+import os 
+import nest_asyncio
+nest_asyncio.apply()
+from .function_tool import suggestion_ragtool
+kimi_model = OpenAIResponsesModel(
+    model="moonshotai/kimi-k2-instruct-0905",  # Valid Groq model
+    openai_client=AsyncOpenAI(
+        base_url="https://api.groq.com/openai/v1",
+        api_key=os.getenv("GROQ_API_KEY"),
+    )
+)
+google_model = OpenAIChatCompletionsModel(
+    model="google/gemini-2.5-flash",  # Google Gemini via OpenRouter
+    openai_client=AsyncOpenAI(
+         base_url="https://openrouter.ai/api/v1",
+        api_key=os.getenv("OPENROUTER_API_KEY"),
+    )
+)
+deepseek_model = OpenAIChatCompletionsModel(
+    model="deepseek/deepseek-chat",  # DeepSeek via OpenRouter
+    openai_client=AsyncOpenAI(
+        base_url="https://openrouter.ai/api/v1",
+        api_key=os.getenv("OPENROUTER_API_KEY"),
+    )
+)
+
+sumary_model = OpenAIResponsesModel(
+    model="meta-llama/llama-4-scout-17b-16e-instruct",  # Valid Groq model
+    openai_client=AsyncOpenAI(
+        base_url="https://api.groq.com/openai/v1",
+        api_key=os.getenv("GROQ_API_KEY")
+    )
+)
+def build_sugguestion_information_agent()-> Agent[AgentContext]:
+    
+
+    current_time = datetime.now()
+    current_date = date.today()
+    current_day = datetime.today().strftime("%A")
+    information_agent = Agent[AgentContext](
+        name="company_suggestion_information",
+        instructions=(
+    "You are an information agent and customer service representative for the company. "
+    "Your goal is to provide clear, concise answers using ONLY the suggestion_ragtool tool. "
+    "For greeting do not call tool reply by your self add company name "
+    "Always speak as the company using 'we'. Do NOT guess or assume. "
+    "If information is not found, reply politely: "
+    "phraphse according to your intellgence 'No information is available regarding to this . You may book an appointment or speak to our sales agent for more details.' praphrase it "
+    
+    "Make only ONE suggestion_ragtool query that fully represents the user’s request. "
+    "All company-related answers must come strictly from the suggestion_ragtool tool. "
+    "Do not create or assume any details. Always use the correct company name. "
+    "The suggestion_ragtool result is your official answer. "
+    
+    "Respond in under not more than 80 words, in a friendly customer-service tone. "
+    "Never leave incomplete replies and never ignore earlier conversation context. "
+    
+    "As a customer support agent, always answer using official company information found through the suggestion_ragtool tool. for partcular question liek greeting and user info if you have so do not use tool reply by self "
+    f"Current system time : {current_time}, date: {current_date}, day: {current_day}. "
+),
+        model=deepseek_model,
+        tools=[
+            suggestion_ragtool
+        ],
+        model_settings=ModelSettings(
+            temperature=1,
+            top_p=1,
+            max_tokens=2048,
+        ),
+        )
+    return information_agent
+
+def build_summarizer_agent() -> Agent[AgentContext]:
+    """
+    Creates a summarizer agent that condenses chat history
+    into a short, factual summary for context preservation.
+    """
+    summarizer_agent = Agent[AgentContext](
+        name="Summarizer Agent",
+        instructions="""
+        You are a summarization assistant.
+        Your job is to take several user and assistant messages and produce a concise,
+        factual summary that captures key intents, facts, and outcomes.
+
+        Guidelines:
+        - Keep the summary under 80 words.
+        - Focus on what the user is asking for and the assistant's key responses.
+        - Do NOT add new information.
+        - Preserve important context like customer concerns, preferences, or goals.
+        - Write in plain English.
+        """,
+        model=sumary_model,  # or use default_model if configured in your environment
+        model_settings=ModelSettings(
+            temperature=0.3,
+            top_p=0.9,
+            max_tokens=300,
+        ),
+    )
+
+    return summarizer_agent
+def build_kimi_information_agent()-> Agent[AgentContext]:
+    
+
+    current_time = datetime.now()
+    current_date = date.today()
+    current_day = datetime.today().strftime("%A")
+    information_agent = Agent[AgentContext](
+        name="company_suggestion_information",
+        instructions=(
+    "You are an information agent and customer service representative for the company. "
+    "Your goal is to provide clear, concise answers using ONLY the suggestion_ragtool tool. "
+    "For greeting do not call tool reply by your self add company name "
+    "Always speak as the company using 'we'. Do NOT guess or assume. "
+    "If information is not found, reply politely: "
+    "phraphse according to your intellgence 'No information is available regarding to this . You may book an appointment or speak to our sales agent for more details.' praphrase it "
+    
+    "Make only ONE suggestion_ragtool query that fully represents the user’s request. "
+    "All company-related answers must come strictly from the suggestion_ragtool tool. "
+    "Do not create or assume any details. Always use the correct company name. "
+    "The suggestion_ragtool result is your official answer. "
+    
+    "Respond in under not more than 80 words, in a friendly customer-service tone. "
+    "Never leave incomplete replies and never ignore earlier conversation context. "
+    
+    "As a customer support agent, always answer using official company information found through the suggestion_ragtool tool. for partcular question liek greeting and user info if you have so do not use tool reply by self "
+    f"Current system time : {current_time}, date: {current_date}, day: {current_day}. "
+),
+        model=kimi_model,
+        tools=[
+            suggestion_ragtool
+        ],
+        model_settings=ModelSettings(
+            temperature=1,
+            top_p=1,
+            max_tokens=2048,
+        ),
+        )
+    return information_agent
+
+
+def build_google_information_agent()-> Agent[AgentContext]:
+    
+
+    current_time = datetime.now()
+    current_date = date.today()
+    current_day = datetime.today().strftime("%A")
+    information_agent = Agent[AgentContext](
+        name="company_suggestion_information",
+        instructions=(
+    "You are an information agent and customer service representative for the company. "
+    "Your goal is to provide clear, concise answers using ONLY the suggestion_ragtool tool. "
+    "For greeting do not call tool reply by your self add company name "
+    "Always speak as the company using 'we'. Do NOT guess or assume. "
+    "If information is not found, reply politely: "
+    "phraphse according to your intellgence 'No information is available regarding to this . You may book an appointment or speak to our sales agent for more details.' praphrase it "
+    
+    "Make only ONE suggestion_ragtool query that fully represents the user’s request. "
+    "All company-related answers must come strictly from the suggestion_ragtool tool. "
+    "Do not create or assume any details. Always use the correct company name. "
+    "The suggestion_ragtool result is your official answer. "
+    
+    "Respond in under not more than 80 words, in a friendly customer-service tone. "
+    "Never leave incomplete replies and never ignore earlier conversation context. "
+    
+    "As a customer support agent, always answer using official company information found through the suggestion_ragtool tool. for partcular question liek greeting and user info if you have so do not use tool reply by self "
+    f"Current system time : {current_time}, date: {current_date}, day: {current_day}. "
+),
+        model=google_model,
+        tools=[
+            suggestion_ragtool
+        ],
+        model_settings=ModelSettings(
+            temperature=1,
+            top_p=1,
+            max_tokens=2048,
+        ),
+        )
+    return information_agent