diff --git a/rdagent/app/qlib_rd_loop/RDAgent.py b/rdagent/app/qlib_rd_loop/RDAgent.py
new file mode 100644
index 00000000..dc1bd803
--- /dev/null
+++ b/rdagent/app/qlib_rd_loop/RDAgent.py
@@ -0,0 +1,104 @@
+import pickle
+from rdagent.app.qlib_rd_loop.conf import PROP_SETTING
+from rdagent.core.proposal import (
+    Hypothesis2Experiment,
+    HypothesisExperiment2Feedback,
+    HypothesisGen,
+    Trace,
+)
+from rdagent.core.scenario import Scenario
+from rdagent.core.task_generator import TaskGenerator
+from rdagent.core.utils import import_class
+
+class Model_RD_Agent:
+    def __init__(self):
+        self.scen: Scenario = import_class(PROP_SETTING.qlib_model_scen)()
+        self.hypothesis_gen: HypothesisGen = import_class(PROP_SETTING.qlib_model_hypothesis_gen)(self.scen)
+        self.hypothesis2experiment: Hypothesis2Experiment = import_class(PROP_SETTING.qlib_model_hypothesis2experiment)()
+        self.qlib_model_coder: TaskGenerator = import_class(PROP_SETTING.qlib_model_coder)(self.scen)
+        self.qlib_model_runner: TaskGenerator = import_class(PROP_SETTING.qlib_model_runner)(self.scen)
+        self.qlib_model_summarizer: HypothesisExperiment2Feedback = import_class(PROP_SETTING.qlib_model_summarizer)(self.scen)
+        self.trace = Trace(scen=self.scen)
+
+    def generate_hypothesis(self):
+        hypothesis = self.hypothesis_gen.gen(self.trace)
+        self.dump_objects(hypothesis=hypothesis, trace=self.trace, filename='step_hypothesis.pkl')
+        return hypothesis
+
+    def convert_hypothesis(self, hypothesis):
+        exp = self.hypothesis2experiment.convert(hypothesis, self.trace)
+        self.dump_objects(exp=exp, hypothesis=hypothesis, trace=self.trace, filename='step_experiment.pkl')
+        return exp
+
+    def generate_code(self, exp):
+        exp = self.qlib_model_coder.generate(exp)
+        self.dump_objects(exp=exp, trace=self.trace, filename='step_code.pkl')
+        return exp
+
+    def run_experiment(self, exp):
+        exp = self.qlib_model_runner.generate(exp)
+        self.dump_objects(exp=exp, trace=self.trace, filename='step_run.pkl')
+        return exp
+
+    def generate_feedback(self, exp, hypothesis):
+        feedback = self.qlib_model_summarizer.generateFeedback(exp, hypothesis, self.trace)
+        self.dump_objects(exp=exp, hypothesis=hypothesis, feedback=feedback, trace=self.trace, filename='step_feedback.pkl')
+        return feedback
+
+    def append_to_trace(self, hypothesis, exp, feedback):
+        self.trace.hist.append((hypothesis, exp, feedback))
+        self.dump_objects(trace=self.trace, filename='step_trace.pkl')
+
+    def dump_objects(self, exp=None, hypothesis=None, feedback=None, trace=None, filename='dumped_objects.pkl'):
+        with open(filename, 'wb') as f:
+            pickle.dump((exp, hypothesis, feedback, trace or self.trace), f)
+
+    def load_objects(self, filename):
+        with open(filename, 'rb') as f:
+            return pickle.load(f)
+
+def process_steps(agent):
+    # Load trace if available
+    try:
+        _, _, _, trace = agent.load_objects('step_trace.pkl')
+        agent.trace = trace
+        print(trace)
+    except FileNotFoundError:
+        pass
+
+    # Step 1: Generate hypothesis
+    try:
+        _, hypothesis, _, _ = agent.load_objects('step_hypothesis.pkl')
+    except FileNotFoundError:
+        hypothesis = agent.generate_hypothesis()
+
+    # Step 2: Convert hypothesis
+    try:
+        exp, _, _, _ = agent.load_objects('step_experiment.pkl')
+    except FileNotFoundError:
+        exp = agent.convert_hypothesis(hypothesis)
+
+    # Step 3: Generate code
+    try:
+        exp, _, _, _ = agent.load_objects('step_code.pkl')
+    except FileNotFoundError:
+        exp = agent.generate_code(exp)
+
+    # Step 4: Run experiment
+    try:
+        exp, _, _, _ = agent.load_objects('step_run.pkl')
+    except FileNotFoundError:
+        exp = agent.run_experiment(exp)
+
+    # Step 5: Generate feedback
+    # try:
+    #     _, _, feedback, _ = agent.load_objects('step_feedback.pkl')
+    # except FileNotFoundError:
+    feedback = agent.generate_feedback(exp, hypothesis)
+
+    # Step 6: Append to trace
+    agent.append_to_trace(hypothesis, exp, feedback)
+
+if __name__ == "__main__":
+    agent = Model_RD_Agent()
+    process_steps(agent)
diff --git a/rdagent/scenarios/qlib/docker/Dockerfile b/rdagent/scenarios/qlib/docker/Dockerfile
index 26419c6e..9845c9a5 100644
--- a/rdagent/scenarios/qlib/docker/Dockerfile
+++ b/rdagent/scenarios/qlib/docker/Dockerfile
@@ -1,4 +1,4 @@
-FROM pytorch/pytorch:latest
+FROM pytorch/pytorch:2.3.1-cuda12.1-cudnn8-runtime
 
 # For GPU support, please choose the proper tag from https://hub.docker.com/r/pytorch/pytorch/tags
 
diff --git a/rdagent/scenarios/qlib/prompts.yaml b/rdagent/scenarios/qlib/prompts.yaml
index c4c316a8..e86e46fc 100644
--- a/rdagent/scenarios/qlib/prompts.yaml
+++ b/rdagent/scenarios/qlib/prompts.yaml
@@ -1,7 +1,8 @@
 hypothesis_and_feedback: |-
   {% for hypothesis, experiment, feedback in trace.hist %}
   Hypothesis {{ loop.index }}: {{ hypothesis }}
-  Feedback: {{ feedback }}
+  Feedback Observation : {{ feedback.observations }}
+  New Feedback for Context: 
   {% endfor %}
 
 hypothesis_output_format: |-