Update coordinator/task_parser.py

coordinator/task_parser.py

@@ -1,15 +1,24 @@
 # coordinator/task_parser.py
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load model (small model for demo, change to larger if needed)
+MODEL_NAME = "facebook/opt-125m"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
 
 def parse_brief(brief: str):
     """
-    Minimal parser: splits the brief into simple tasks
+    Use a decoder LLM to extract tasks from project brief
     """
-    # Very simple splitting by keywords for demonstration
-    tasks = []
-    if "authentication" in brief:
-        tasks.append("Implement authentication system")
-    if "task sharing" in brief:
-        tasks.append("Implement task sharing feature")
-    if "task management" in brief:
-        tasks.append("Implement task management module")
+    prompt = f"Extract a list of technical tasks from this project brief:\n{brief}\n\nTasks:"
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_new_tokens=150)
+    decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Extract lines after "Tasks:"
+    if "Tasks:" in decoded:
+        decoded = decoded.split("Tasks:")[-1]
+    tasks = [line.strip("- ").strip() for line in decoded.split("\n") if line.strip()]
     return tasks