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Girish Jeswani commited on
Commit ·
2619dcc
1
Parent(s): 3251fad
add routes for orchestrator
Browse files
multi_llm_chatbot_backend/app/api/routes.py
CHANGED
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@@ -2,39 +2,101 @@ from fastapi import APIRouter, Body
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from app.llm.mistral_client import MistralClient
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from app.models.persona import Persona
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from app.core.orchestrator import ChatOrchestrator
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router = APIRouter()
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#
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llm = MistralClient()
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# Register
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id="methodist",
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name="Methodist Advisor",
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system_prompt="You are a highly methodical PhD advisor who believes in structure and planning.",
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llm=llm
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))
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id="theorist",
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name="Theorist Advisor",
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system_prompt="You are a philosophical PhD advisor who focuses on abstract theories and ideas.",
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llm=llm
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))
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id="pragmatist",
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name="Pragmatist Advisor",
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system_prompt="You are a practical PhD advisor who focuses on real-world outcomes and utility.",
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llm=llm
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))
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@router.post("/chat")
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async def
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user_input: str = Body(...),
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active_personas:
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):
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orchestrator
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from app.llm.mistral_client import MistralClient
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from app.models.persona import Persona
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from app.core.orchestrator import ChatOrchestrator
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from app.core.seamless_orchestrator import SeamlessOrchestrator
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from pydantic import BaseModel
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from typing import Optional, List
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router = APIRouter()
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# Singletons
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llm = MistralClient()
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chat_orchestrator = ChatOrchestrator()
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seamless_orchestrator = SeamlessOrchestrator()
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# Register personas
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chat_orchestrator.register_persona(Persona(
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id="methodist",
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name="Methodist Advisor",
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system_prompt="You are a highly methodical PhD advisor who believes in structure and planning. Provide organized, step-by-step guidance.",
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llm=llm
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))
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chat_orchestrator.register_persona(Persona(
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id="theorist",
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name="Theorist Advisor",
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system_prompt="You are a philosophical PhD advisor who focuses on abstract theories and ideas. Help students think deeply about concepts and frameworks.",
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llm=llm
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))
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chat_orchestrator.register_persona(Persona(
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id="pragmatist",
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name="Pragmatist Advisor",
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system_prompt="You are a practical PhD advisor who focuses on real-world outcomes and utility. Give actionable, concrete advice.",
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llm=llm
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))
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class ChatMessage(BaseModel):
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user_input: str
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session_id: Optional[str] = None
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@router.post("/chat")
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async def chat_with_orchestrator(message: ChatMessage):
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"""Main chat endpoint with seamless orchestrator integration"""
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# Process message through seamless orchestrator
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orchestrator_result = await seamless_orchestrator.process_message(message.user_input)
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if orchestrator_result["status"] == "orchestrator_asking":
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# Orchestrator needs more info - return orchestrator question
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return {
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"type": "orchestrator_question",
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"responses": [{
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"persona": "PhD Advisor Assistant",
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"response": orchestrator_result["orchestrator_question"]
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}],
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"collected_info": orchestrator_result["collected_info"]
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}
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elif orchestrator_result["status"] == "ready_for_advisors":
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# Ready for advisor consultation
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enhanced_context = orchestrator_result["enhanced_context"]
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# Set active advisors
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chat_orchestrator.set_active_personas(["methodist", "theorist", "pragmatist"])
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# Get advisor responses
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advisor_responses = await chat_orchestrator.process_user_input(enhanced_context)
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return {
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"type": "advisor_responses",
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"responses": advisor_responses,
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"collected_info": orchestrator_result["collected_info"]
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}
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# Fallback - shouldn't reach here normally
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return {
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"type": "error",
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"responses": [{
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"persona": "System",
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"response": "I'm having trouble processing your request. Could you please try again?"
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}]
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}
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@router.post("/reset-session")
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async def reset_session():
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"""Reset the orchestrator session"""
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seamless_orchestrator.reset()
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# Also reset chat orchestrator history if needed
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chat_orchestrator.history = []
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return {"status": "reset", "message": "Session reset successfully"}
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# Keep the old endpoints for backward compatibility
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@router.post("/chat-direct")
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async def chat_direct(
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user_input: str = Body(...),
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active_personas: List[str] = Body(default=["methodist", "theorist", "pragmatist"])
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):
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"""Direct chat endpoint bypassing orchestrator (for testing)"""
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chat_orchestrator.set_active_personas(active_personas)
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responses = await chat_orchestrator.process_user_input(user_input)
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return responses
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