Create coach.py

engine/coach.py

@@ -0,0 +1,59 @@
+import os
+from transformers import pipeline
+from engine.utils import safe_log
+
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+coach_gen = pipeline(
+    "text-generation",
+    model="HuggingFaceH4/zephyr-7b-beta",
+    token=HF_TOKEN
+)
+
+def generate_coach_feedback(rep_input, persona_response, persona_question, persona, history):
+    """
+    Provides actionable coaching feedback after the persona's turn.
+    """
+    try:
+        traits = persona.get("dynamic_state", {})
+        role = persona.get("role", "Client")
+
+        recent = []
+        for h in history[-5:]:
+            recent.append(f"Rep: {h['rep_input']}")
+            recent.append(f"Persona: {h['persona_response']}")
+            if h.get("persona_question"):
+                recent.append(f"Persona Q: {h['persona_question']}")
+        history_text = "\n".join(recent) if recent else "No prior turns."
+
+        system_prompt = f"""You are a sales coach analyzing a roleplay with a {role}.
+Give specific, practical guidance in 2-4 sentences.
+
+Persona traits: {traits}
+Recent history:
+{history_text}
+
+Current exchange:
+Rep: {rep_input}
+Persona: {persona_response}
+Persona Q: {persona_question}
+
+Instructions:
+- Identify the core objection or concern.
+- Suggest one stronger framing or tactic (e.g., ROI, compliance, discovery).
+- Offer one concise next step or question for the rep to ask.
+- Do NOT break into persona voice; remain the coach.
+"""
+
+        full_prompt = f"<|system|>\n{system_prompt}\n<|user|>\nProvide coaching feedback.\n<|assistant|>\n"
+
+        out = coach_gen(full_prompt, max_new_tokens=180, do_sample=True, temperature=0.7)
+        text = out[0].get("generated_text") or out[0].get("text") or ""
+        if "<|assistant|>" in text:
+            text = text.split("<|assistant|>")[-1].strip()
+
+        return text.strip() or "Focus on clarifying value and risk mitigation. Ask one discovery question next."
+
+    except Exception as e:
+        safe_log("Coach feedback error", str(e))
+        return "Consider addressing the core objection directly, then bridge to measurable outcomes and a discovery question."