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| import sys | |
| import os | |
| import json | |
| import re | |
| from langchain_groq import ChatGroq | |
| from langchain_core.messages import HumanMessage | |
| # Add project root to path | |
| sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) | |
| from app.core.config import settings | |
| from app.services.neocortex import _is_valid_node, _sanitize_relation | |
| def extract_and_debug(text: str, user_id: str = "default_user"): | |
| api_key = settings.GROQ_API_KEY if settings.GROQ_API_KEY else "dummy_key" | |
| llm = ChatGroq(model="llama-3.1-8b-instant", api_key=api_key) | |
| owner = user_id.upper() | |
| prompt = f"""You are a child's brain learning about the world. Read the text and pick out SIMPLE facts as connections between concepts. | |
| Think like a child drawing a mind-map: | |
| - "{owner}" is the person speaking. If they say "I like X" → {owner} --LIKES--> X | |
| - Extract only SHORT concept names (1-3 words). Never use full sentences as names. | |
| - Focus on: people, places, things, hobbies, foods, animals, feelings, skills, jobs | |
| RULES: | |
| 1. Nodes must be 1-3 word concept names, ALL CAPS. Example: "CRICKET", "DELHI", "MOM", "CODING" | |
| 2. Relations must be simple verbs: LIKES, IS_A, LIVES_IN, PLAYS, WORKS_AT, HAS, KNOWS, STUDIES, etc. | |
| 3. "I" or "my" in the text refers to "{owner}" — always use "{owner}" as the node name for the speaker. | |
| 4. DO NOT create nodes named "USER", "SOMA", "AI", "ASSISTANT", or any chat/bot terms. | |
| 5. If the text is just greetings or small talk with zero factual content, return an empty triples list. | |
| Text: | |
| {text} | |
| Return the extracted facts ONLY as a valid JSON block in this exact format: | |
| {{ | |
| "triples": [ | |
| {{"subject": "SUBJECT", "relation": "RELATION", "object": "OBJECT"}} | |
| ] | |
| }} | |
| Do not write any other explanation or thoughts outside the JSON block. If there are no facts, return: {{"triples": []}}""" | |
| response = llm.invoke([HumanMessage(content=prompt)]) | |
| content = response.content.strip() | |
| print("RAW RESPONSE:") | |
| print(content) | |
| match = re.search(r'\{.*\}', content, re.DOTALL) | |
| if match: | |
| data = json.loads(match.group(0)) | |
| for t in data.get("triples", []): | |
| subj = str(t.get("subject", "")).strip().upper() | |
| rel = _sanitize_relation(str(t.get("relation", ""))) | |
| obj = str(t.get("object", "")).strip().upper() | |
| print(f"\nTriple: {subj} --{rel}--> {obj}") | |
| print(f" Valid Subject ({subj}): {_is_valid_node(subj)}") | |
| print(f" Valid Object ({obj}): {_is_valid_node(obj)}") | |
| print(f" Equal: {subj == obj}") | |
| extract_and_debug("Dr. Aris is the creator of the Soma Project. The Soma Project is an advanced cognitive architecture.") | |