Update llm_clients.py

llm_clients.py

@@ -1,21 +1,130 @@
 import os
+import json
 from groq import Groq
 import google.generativeai as genai
 
-# Load Keys
+# ==========================
+# Setup API Clients
+# ==========================
+
 groq_client = Groq(api_key=os.getenv("GROQ_API_KEY"))
 
 genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
 gemini_model = genai.GenerativeModel("gemini-1.5-flash")
 
-def call_llama(prompt):
+
+# ==========================
+# Llama (Groq)
+# ==========================
+
+def call_llama(messages, temperature=0.7):
+    """
+    messages = [
+        {"role": "system", "content": "..."},
+        {"role": "user", "content": "..."}
+    ]
+    """
+
     response = groq_client.chat.completions.create(
         model="llama-3.1-8b-instant",
-        messages=[{"role": "user", "content": prompt}]
+        messages=messages,
+        temperature=temperature
     )
+
     return response.choices[0].message.content
 
-def call_gemini(prompt):
-    response = gemini_model.generate_content(prompt)
+
+# ==========================
+# Gemini
+# ==========================
+
+def call_gemini(messages, temperature=0.7):
+    """
+    Gemini expects combined prompt.
+    We convert messages into a single string.
+    """
+
+    formatted_prompt = ""
+    for m in messages:
+        formatted_prompt += f"{m['role'].upper()}: {m['content']}\n"
+
+    response = gemini_model.generate_content(
+        formatted_prompt,
+        generation_config={"temperature": temperature}
+    )
+
     return response.text
+
+
+# ==========================
+# AI Classifier
+# ==========================
+
+def classify_prompt(prompt):
+
+    system_prompt = """
+You are an AI intent classifier.
+
+Return ONLY valid JSON in this format:
+
+{
+  "intent": "chat | reasoning | live_data | greeting",
+  "needs_search": true or false,
+  "complexity": "low | medium | high"
+}
+
+Rules:
+- Logical, math, proof, step explanation -> reasoning
+- Current events, weather, news, price, today -> live_data
+- Hello/hi/how are you -> greeting
+- Everything else -> chat
+"""
+
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": prompt}
+    ]
+
+    raw = call_llama(messages, temperature=0)
+
+    try:
+        return json.loads(raw)
+    except:
+        return {
+            "intent": "chat",
+            "needs_search": False,
+            "complexity": "low"
+        }
+
+
+# ==========================
+# LLM Judge (for dual answers)
+# ==========================
+
+def judge_answers(answer1, answer2):
+
+    judge_prompt = f"""
+You are an AI judge.
+
+Choose which answer is better.
+
+Reply ONLY with:
+1  (if answer1 is better)
+2  (if answer2 is better)
+
+Answer 1:
+{answer1}
+
+Answer 2:
+{answer2}
+"""
+
+    result = call_llama(
+        [{"role": "user", "content": judge_prompt}],
+        temperature=0
+    )
+
+    if "2" in result:
+        return 2
+    return 1