Changes to include single model represented as multiple personas

README.md

@@ -1 +1,3 @@
-# Neon-AI-Project
+# Neon-AI-Project
+
+Multi-model LLM chatbot.

multi_llm_chatbot_backend/app/api/routes.py

@@ -0,0 +1,40 @@
+from fastapi import APIRouter, Body
+from app.llm.mistral_client import MistralClient
+from app.models.persona import Persona
+from app.core.orchestrator import ChatOrchestrator
+
+router = APIRouter()
+
+# Singleton for now
+llm = MistralClient()
+orchestrator = ChatOrchestrator()
+
+# Register initial personas
+orchestrator.register_persona(Persona(
+    id="methodist",
+    name="Methodist Advisor",
+    system_prompt="You are a highly methodical PhD advisor who believes in structure and planning.",
+    llm=llm
+))
+
+orchestrator.register_persona(Persona(
+    id="theorist",
+    name="Theorist Advisor",
+    system_prompt="You are a philosophical PhD advisor who focuses on abstract theories and ideas.",
+    llm=llm
+))
+
+orchestrator.register_persona(Persona(
+    id="pragmatist",
+    name="Pragmatist Advisor",
+    system_prompt="You are a practical PhD advisor who focuses on real-world outcomes and utility.",
+    llm=llm
+))
+
+@router.post("/chat")
+async def chat(
+    user_input: str = Body(...),
+    active_personas: list[str] = Body(default=["methodist", "theorist", "pragmatist"])
+):
+    orchestrator.set_active_personas(active_personas)
+    return await orchestrator.process_user_input(user_input)

multi_llm_chatbot_backend/app/core/orchestrator.py

@@ -0,0 +1,24 @@
+from app.models.persona import Persona
+
+class ChatOrchestrator:
+    def __init__(self):
+        self.history: list[dict] = []
+        self.personas: dict[str, Persona] = {}
+
+    def register_persona(self, persona: Persona):
+        self.personas[persona.id] = persona
+
+    def set_active_personas(self, ids: list[str]):
+        self.active_ids = [pid for pid in ids if pid in self.personas]
+
+    async def process_user_input(self, user_input: str):
+        self.history.append({"role": "user", "content": user_input})
+        responses = []
+
+        for pid in self.active_ids:
+            persona = self.personas[pid]
+            reply = await persona.respond(self.history)
+            self.history.append({"role": persona.id, "content": reply})
+            responses.append({"persona": persona.name, "response": reply})
+
+        return responses

multi_llm_chatbot_backend/app/llm/llm_client.py

@@ -0,0 +1,7 @@
+from abc import ABC, abstractmethod
+from typing import List
+
+class LLMClient(ABC):
+    @abstractmethod
+    async def generate(self, system_prompt: str, context: List[dict]) -> str:
+        pass

multi_llm_chatbot_backend/app/llm/mistral_client.py

@@ -0,0 +1,25 @@
+import httpx
+from typing import List
+from app.llm.llm_client import LLMClient
+
+OLLAMA_URL = "http://localhost:11434/api/generate"
+
+class MistralClient(LLMClient):
+    async def generate(self, system_prompt: str, context: List[dict]) -> str:
+        # Flatten context into a string
+        formatted = "\n".join(f"{msg['role'].capitalize()}: {msg['content']}" for msg in context)
+        full_prompt = f"{system_prompt}\n\n{formatted}\n\nAssistant:"
+        
+        payload = {
+            "model": "mistral",
+            "prompt": full_prompt,
+            "stream": False
+        }
+
+        try:
+            async with httpx.AsyncClient(timeout=60.0) as client:
+                response = await client.post(OLLAMA_URL, json=payload)
+                response.raise_for_status()
+                return response.json().get("response", "[No response]")
+        except httpx.HTTPError as e:
+            return f"[Error from Mistral: {str(e)}]"

multi_llm_chatbot_backend/app/main.py

@@ -0,0 +1,14 @@
+from fastapi import FastAPI
+from app.api.routes import router
+
+app = FastAPI(
+    title="Multi-LLM Chatbot Backend",
+    version="0.1"
+)
+
+# Include route definitions
+app.include_router(router)
+
+@app.get("/")
+def root():
+    return {"message": "Backend is up and running"}

multi_llm_chatbot_backend/app/models/persona.py

@@ -0,0 +1,11 @@
+from app.llm.llm_client import LLMClient
+
+class Persona:
+    def __init__(self, id: str, name: str, system_prompt: str, llm: LLMClient):
+        self.id = id
+        self.name = name
+        self.system_prompt = system_prompt
+        self.llm = llm
+
+    async def respond(self, context: list[dict]) -> str:
+        return await self.llm.generate(self.system_prompt, context)

multi_llm_chatbot_backend/app/tests/test_mistral.py

@@ -0,0 +1,13 @@
+import requests
+
+url = "http://localhost:11434/api/generate"
+
+payload = {
+    "model": "mistral",
+    "prompt": "You are a professor. Give me PhD advice.",
+    "stream": False
+}
+
+response = requests.post(url, json=payload)
+print(response.status_code)
+print(response.json())

multi_llm_chatbot_backend/requirements.txt

@@ -0,0 +1,3 @@
+fastapi
+uvicorn
+httpx