movie recommendation using grok3 (#2547)

examples/misc/movie_recommendation_grok3.py

@@ -0,0 +1,88 @@
+"""
+Memory-Powered Movie Recommendation Assistant (Grok 3 + Mem0)
+This script builds a personalized movie recommender that remembers your preferences
+(e.g. dislikes horror, loves romcoms) using Mem0 as a memory layer and Grok 3 for responses.
+
+In order to run this file, you need to set up your Mem0 API at Mem0 platform and also need an XAI API key.
+export XAI_API_KEY="your_xai_api_key"
+export MEM0_API_KEY="your_mem0_api_key"
+"""
+
+from mem0 import Memory
+from openai import OpenAI
+
+
+# Configure Mem0 with Grok 3 and Qdrant
+config = {
+    "vector_store": {
+        "provider": "qdrant",
+        "config": {
+            "embedding_model_dims": 384
+        }
+    },
+    "llm": {
+        "provider": "xai",
+        "config": {
+            "model": "grok-3-beta",
+            "temperature": 0.1,
+            "max_tokens": 2000,
+        }
+    },
+    "embedder": {
+        "provider": "huggingface",
+        "config": {
+            "model": "all-MiniLM-L6-v2"  # open embedding model
+        }
+    }
+}
+
+# Instantiate memory layer
+memory = Memory.from_config(config)
+
+# Initialize Grok 3 client
+grok_client = OpenAI(
+    api_key=XAI_API_KEY,
+    base_url="https://api.x.ai/v1",
+)
+
+
+def recommend_movie_with_memory(user_id: str, user_query: str):
+    # Retrieve prior memory about movies
+    past_memories = memory.search("movie preferences", user_id=user_id)
+
+    prompt = user_query
+    if past_memories:
+        prompt += f"\nPreviously, the user mentioned: {past_memories}"
+
+    # Generate movie recommendation using Grok 3
+    response = grok_client.chat.completions.create(
+        model="grok-3-beta",
+        messages=[
+            {"role": "user", "content": prompt}
+        ]
+    )
+    recommendation = response.choices[0].message.content
+
+    # Store conversation in memory
+    memory.add(
+        [{"role": "user", "content": user_query},
+         {"role": "assistant", "content": recommendation}],
+        user_id=user_id,
+        metadata={"category": "movie"}
+    )
+
+    return recommendation
+
+
+# Example Usage
+if __name__ == "__main__":
+    user_id = "arshi"
+    recommend_movie_with_memory(user_id, "I'm looking for a movie to watch tonight. Any suggestions?")
+    # OUTPUT: You have watched Intersteller last weekend and you don't like horror movies, maybe you can watch "Purple Hearts" today.
+    recommend_movie_with_memory(user_id, "Can we skip the tearjerkers? I really enjoyed Notting Hill and Crazy Rich Asians.")
+    # OUTPUT: Got it — no sad endings! You might enjoy "The Proposal" or "Love, Rosie". They’re both light-hearted romcoms with happy vibes.
+    recommend_movie_with_memory(user_id, "Any light-hearted movie I can watch after work today?")
+    # OUTPUT: Since you liked Crazy Rich Asians and The Proposal, how about "The Intern" or "Isn’t It Romantic"? Both are upbeat, funny, and perfect for relaxing.
+    recommend_movie_with_memory(user_id, "I’ve already watched The Intern. Something new maybe?")
+    # OUTPUT: No problem! Try "Your Place or Mine" - romcoms that match your taste and are tear-free!
+