fix: kaggle import and large output response issues

instadeepai · May 22, 2024 · 112d400 · 112d400
1 parent 399ad1c
commit 112d400
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Showing 3 changed files with 51 additions and 44 deletions.
diff --git a/debatellm/agents.py b/debatellm/agents.py
@@ -350,6 +350,13 @@ def _infer(
                 "num_messages_removed": history_counter,
             }
             response = response.choices[0].message.content  # type: ignore
+
+            # If the response is to large, we cut off the start of the response
+            # until the response is small enough.
+            max_response_length = 1024
+            if len(str(response)) > max_response_length:
+                response = str(response)[-max_response_length:]
+
         else:
             response = "This is a mock output."  # type: ignore
             usage_info = {"prompt_tokens": 0, "response_tokens": 0, "cost": 0}  # type: ignore

diff --git a/requirements.txt b/requirements.txt
@@ -113,7 +113,7 @@ jupyter_server==2.6.0
 jupyter_server_terminals==0.4.4
 jupyterlab-pygments==0.2.2
 jupyterlab-widgets==3.0.7
-kaggle
+kaggle==1.5.16
 keras==2.12.0
 kiwisolver==1.4.4
 latex==0.7.0

diff --git a/scripts/launch_experiments.py b/scripts/launch_experiments.py
@@ -16,7 +16,7 @@
 
 exp_table = []
 
-agent_type = "gpt"
+agent_type = "mixtral"
 
 # Single agent
 # exp_table.append(
@@ -91,36 +91,36 @@
 # )
 
 # Ensemble Refinement
-# exp_table.extend(
-#     [
-#         {
-#             "system": "ensemble_refinement",
-#             "system.name": "ensemble_refinement",
-#             "system.num_reasoning_steps": 3,
-#             "system.num_aggregation_steps": [1, 9],
-#             "system.agents": gen_agent_config(
-#                 1,
-#                 agent_type=agent_type,
-#                 prompt="er_simple",
-#                 is_es=True,
-#                 use_few_shot_examples=False, # [False, True],
-#             ),
-#         },
-#         {
-#             "system": "ensemble_refinement_er_debate",
-#             "system.name": "ensemble_refinement",
-#             "system.num_reasoning_steps": 3,
-#             "system.num_aggregation_steps": [1, 9],
-#             "system.agents": gen_agent_config(
-#                 1,
-#                 agent_type=agent_type,
-#                 prompt="er_cot",
-#                 is_es=True,
-#                 use_few_shot_examples=False, # [False, True],
-#             ),
-#         },
-#     ]
-# )
+exp_table.extend(
+    [
+        {
+            "system": "ensemble_refinement",
+            "system.name": "ensemble_refinement",
+            "system.num_reasoning_steps": 3,
+            "system.num_aggregation_steps": [1, 9],
+            "system.agents": gen_agent_config(
+                1,
+                agent_type=agent_type,
+                prompt="er_simple",
+                is_es=True,
+                use_few_shot_examples=False, # [False, True],
+            ),
+        },
+        {
+            "system": "ensemble_refinement_er_debate",
+            "system.name": "ensemble_refinement",
+            "system.num_reasoning_steps": 3,
+            "system.num_aggregation_steps": [1, 9],
+            "system.agents": gen_agent_config(
+                1,
+                agent_type=agent_type,
+                prompt="er_cot",
+                is_es=True,
+                use_few_shot_examples=False, # [False, True],
+            ),
+        },
+    ]
+)
 
 # SPP Synergy
 # exp_table.append(
@@ -141,18 +141,18 @@
 #         "system.agreement_intensity": [2, 6],
 #     }
 # )
-exp_table.append(
-    {
-        "system": "google_mad",
-        "system.summarize_answers": [True, False],
-        "system.agents": gen_agent_config(
-            [2, 3, 4],
-            agent_type=agent_type,
-            prompt="cot",
-        ),
-        "system.num_rounds": [2, 3],
-    }
-)
+# exp_table.append(
+#     {
+#         "system": "google_mad",
+#         "system.summarize_answers": [True, False],
+#         "system.agents": gen_agent_config(
+#             [2, 3, 4],
+#             agent_type=agent_type,
+#             prompt="cot",
+#         ),
+#         "system.num_rounds": [2, 3],
+#     }
+# )
 
 
 # # Tsinghua MAD