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| import os | |
| import pandas as pd | |
| from langchain_core.documents import Document | |
| from langchain_community.embeddings import HuggingFaceEmbeddings | |
| from langchain_chroma import Chroma | |
| from langchain_google_genai import ChatGoogleGenerativeAI | |
| from langchain_core.prompts import ChatPromptTemplate | |
| from langchain_core.runnables import RunnablePassthrough | |
| from langchain_core.output_parsers import StrOutputParser | |
| import gradio as gr | |
| # 1. Create the dataset file if it doesn't exist | |
| data = { | |
| "Title": ["Tomb Raider", "Uncharted 4: A Thief's End", "Horizon Zero Dawn", "The Witcher 3: Wild Hunt", "Elden Ring", "Final Fantasy VII Remake", "Hollow Knight", "Hades"], | |
| "Genre": ["Action-Adventure, Puzzle", "Action-Adventure, Shooter", "Action-Adventure, RPG, Sci-Fi", "RPG, Open World, Fantasy", "RPG, Dark Fantasy, Souls-like", "RPG, Turn-based, Cyberpunk", "Indie, Metroidvania, Platformer", "Indie, Rogue-like, Action"], | |
| "Description": [ | |
| "Lara Croft explores ancient tombs, solves challenging puzzles, and fights to survive in a mysterious island full of action and secrets.", | |
| "Nathan Drake hunts for a lost pirate treasure, featuring cinematic action, intense climbing, third-person shooting, and great storytelling.", | |
| "Aloy explores a vibrant open world ruled by robotic creatures, uncovering secrets of a lost technological past with tactical bow combat.", | |
| "Geralt of Rivia, a monster hunter, searches for his adopted daughter in a massive fantasy world filled with deep choices and rich side quests.", | |
| "A challenging dark fantasy action RPG where players explore a vast shattered world, fight brutal bosses, and create their own playstyle.", | |
| "Cloud Strife fights an evil corporation in a cyberpunk city, featuring a mix of real-time action and strategic turn-based command combat.", | |
| "A beautiful, challenging 2D adventure through a ruined kingdom of insects, focusing on exploration, tight combat, and deep lore.", | |
| "Zagreus, the prince of the Underworld, attempts to escape his father's realm in a fast-paced action game with shifting dungeons and rich story." | |
| ] | |
| } | |
| df = pd.DataFrame(data) | |
| df.to_csv("games_dataset.csv", index=False) | |
| # 2. Prepare Documents | |
| documents = [] | |
| for index, row in df.iterrows(): | |
| content = f"Game Title: {row['Title']}\nGenre: {row['Genre']}\nDescription: {row['Description']}" | |
| doc = Document(page_content=content, metadata={"title": row['Title']}) | |
| documents.append(doc) | |
| # 3. Vector Store | |
| embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2") | |
| vector_store = Chroma.from_documents(documents=documents, embedding=embeddings) | |
| retriever = vector_store.as_retriever(search_kwargs={"k": 2}) | |
| # 4. RAG Chain | |
| llm = ChatGoogleGenerativeAI(model="gemini-2.5-flash", temperature=0.7) | |
| system_prompt = ( | |
| "You are an expert Video Game Recommendation Assistant.\n" | |
| "Use the following pieces of retrieved context to answer the user's question.\n" | |
| "If you don't know the answer or if it's not in the context, suggest a close alternative from the context.\n" | |
| "Keep your response enthusiastic, helpful, and focused on video games.\n\n" | |
| "Context:\n{context}\n\n" | |
| "Question: {input}\n" | |
| "Answer:" | |
| ) | |
| prompt = ChatPromptTemplate.from_template(system_prompt) | |
| def format_docs(docs): | |
| return "\n\n".join(doc.page_content for doc in docs) | |
| rag_chain = ( | |
| {"context": retriever | format_docs, "input": RunnablePassthrough()} | |
| | prompt | |
| | llm | |
| | StrOutputParser() | |
| ) | |
| # 5. Gradio Interface | |
| def predict(message, history): | |
| bot_response = rag_chain.invoke(message) | |
| return bot_response | |
| with gr.Blocks(theme="soft") as demo: | |
| gr.ChatInterface( | |
| fn=predict, | |
| title="GamerRadar — Custom RAG Assistant", | |
| description="Ask me for game recommendations or similarities based on our specialized bootcamp dataset!", | |
| examples=["I really liked Tomb Raider. What do you suggest?", "Tell me about adventure games."] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |