Create agents.py

agents.py

@@ -0,0 +1,61 @@
+import os
+import json
+import requests
+
+GLM_API_URL = "https://api.your-glm-provider.com/v1/chat/completions"
+GLM_API_KEY = os.getenv("GLM_API_KEY")
+
+def call_glm(prompt, temperature=0.3):
+    headers = {"Authorization": f"Bearer {GLM_API_KEY}"}
+    payload = {
+        "model": "glm-4.5",
+        "messages": [{"role": "system", "content": "You are an educational assistant."},
+                     {"role": "user", "content": prompt}],
+        "temperature": temperature
+    }
+    response = requests.post(GLM_API_URL, headers=headers, json=payload)
+    result = response.json()
+    return result["choices"][0]["message"]["content"]
+
+class AnalyzerAgent:
+    def analyze(self, answers, question_bank):
+        # Simple deterministic analysis
+        topic_stats = {}
+        for qid, result in answers.items():
+            q = next(item for item in question_bank if str(item["id"]) == qid)
+            for topic in q.get("topics", []):
+                if topic not in topic_stats:
+                    topic_stats[topic] = {"correct": 0, "total": 0}
+                topic_stats[topic]["total"] += 1
+                if result["user"] == result["correct"]:
+                    topic_stats[topic]["correct"] += 1
+        
+        analysis = {t: round(v["correct"]/v["total"], 2) for t,v in topic_stats.items()}
+        return {"topic_accuracy": analysis}
+
+class ForecastAgent:
+    def forecast(self, level, subject):
+        prompt = f"""
+        You are an exam forecast assistant.
+        Predict 3 high-probability topics for {level} {subject} exam.
+        Return JSON: {{"predicted_topics": [{{"topic": "...", "confidence": 0.0}}]}}
+        """
+        try:
+            response = call_glm(prompt)
+            return json.loads(response)
+        except Exception:
+            return {"error": "Forecast unavailable"}
+
+class CoachAgent:
+    def coach(self, analysis, level, subject):
+        prompt = f"""
+        You are a study coach.
+        The student's weaknesses are: {analysis}.
+        Suggest a study plan and 3 practice questions for {level} {subject}.
+        Return JSON: {{"tips": ["..."], "study_plan": "...", "practice_questions": [{{"text": "...", "answer": "..."}}]}}
+        """
+        try:
+            response = call_glm(prompt)
+            return json.loads(response)
+        except Exception:
+            return {"error": "Coach unavailable"}