Feat/update dialogpt (#170)

* feat: update dialogpt

* fix: codestyle

* fix: book skill false start

assistant_dists/dream/docker-compose.override.yml

@@ -1151,7 +1151,8 @@ services:
       args:
         SERVICE_PORT: 8125
         SERVICE_NAME: dialogpt
-        PRETRAINED_MODEL_NAME_OR_PATH: microsoft/DialoGPT-small
+        PRETRAINED_MODEL_NAME_OR_PATH: microsoft/DialoGPT-medium
+        N_HYPOTHESES_TO_GENERATE: 5
       context: ./services/dialogpt/
     command: flask run -h 0.0.0.0 -p 8125
     environment:

assistant_dists/dream_mini/docker-compose.override.yml

@@ -136,7 +136,8 @@ services:
       args:
         SERVICE_PORT: 8125
         SERVICE_NAME: dialogpt
-        PRETRAINED_MODEL_NAME_OR_PATH: microsoft/DialoGPT-small
+        PRETRAINED_MODEL_NAME_OR_PATH: microsoft/DialoGPT-medium
+        N_HYPOTHESES_TO_GENERATE: 5
       context: ./services/dialogpt/
     command: flask run -h 0.0.0.0 -p 8125
     environment:

services/dialogpt/Dockerfile

@@ -8,6 +8,9 @@ ARG PRETRAINED_MODEL_NAME_OR_PATH
 ENV PRETRAINED_MODEL_NAME_OR_PATH ${PRETRAINED_MODEL_NAME_OR_PATH}
 ARG SERVICE_PORT
 ENV SERVICE_PORT ${SERVICE_PORT}
+ARG N_HYPOTHESES_TO_GENERATE
+ENV N_HYPOTHESES_TO_GENERATE ${N_HYPOTHESES_TO_GENERATE}
+
 
 COPY ./requirements.txt /src/requirements.txt
 RUN pip install -r /src/requirements.txt

services/dialogpt/server.py

@@ -17,6 +17,7 @@
 PRETRAINED_MODEL_NAME_OR_PATH = os.environ.get("PRETRAINED_MODEL_NAME_OR_PATH")
 logging.info(f"PRETRAINED_MODEL_NAME_OR_PATH = {PRETRAINED_MODEL_NAME_OR_PATH}")
 DEFAULT_CONFIDENCE = 0.9
+N_HYPOTHESES_TO_GENERATE = int(os.environ.get("N_HYPOTHESES_TO_GENERATE", 1))
 ZERO_CONFIDENCE = 0.0
 MAX_HISTORY_DEPTH = 3
 
@@ -63,20 +64,27 @@ def respond():
         responses = []
         confidences = []
         for context in contexts:
-            response = generate_response(context, model, tokenizer)
-            if len(response) > 3:
-                # drop too short responses
-                responses += [response]
-                confidences += [DEFAULT_CONFIDENCE]
-            else:
-                responses += [""]
-                confidences += [ZERO_CONFIDENCE]
+            curr_responses = []
+            curr_confidences = []
+            for i in range(N_HYPOTHESES_TO_GENERATE):
+                response = generate_response(context, model, tokenizer)
+                if len(response) > 3:
+                    # drop too short responses
+                    curr_responses += [response]
+                    curr_confidences += [DEFAULT_CONFIDENCE]
+                else:
+                    curr_responses += [""]
+                    curr_confidences += [ZERO_CONFIDENCE]
+
+            responses += [curr_responses]
+            confidences += [curr_confidences]
+
     except Exception as exc:
         logger.exception(exc)
         sentry_sdk.capture_exception(exc)
-        responses = [""] * len(contexts)
-        confidences = [ZERO_CONFIDENCE] * len(contexts)
+        responses = [[""]] * len(contexts)
+        confidences = [[ZERO_CONFIDENCE]] * len(contexts)
 
     total_time = time.time() - st_time
-    logger.info(f"masked_lm exec time: {total_time:.3f}s")
+    logger.info(f"dialogpt exec time: {total_time:.3f}s")
     return jsonify(list(zip(responses, confidences)))

services/dialogpt/test.py

@@ -1,14 +1,19 @@
+import os
 import requests
 
 
+N_HYPOTHESES_TO_GENERATE = int(os.environ.get("N_HYPOTHESES_TO_GENERATE", 1))
+
+
 def test_respond():
     url = "http://0.0.0.0:8125/respond"
 
     contexts = [["hi", "hi. how are you?"], ["let's chat about movies", "cool. what movies do you like?"]]
     gold_result = [["I'm good, how are you?", 0.9], ["I like the new one.", 0.9]]
     result = requests.post(url, json={"utterances_histories": contexts}).json()
     assert [
-        len(sample[0]) > 0 and sample[1] > 0.0 for sample in result
+        len(sample[0]) > 0 and all([len(text) > 0 for text in sample[0]]) and all([conf > 0.0 for conf in sample[1]])
+        for sample in result
     ], f"Got\n{result}\n, but expected:\n{gold_result}"
     print("Success")
 

skills/dff_book_skill/scenario/main.py

@@ -46,13 +46,7 @@
         TRANSITIONS: {
             ("global_flow", "fallback", 1.5): loc_cnd.exit_skill,
             ("books_general", "dislikes_reading", 1.5): loc_cnd.dislikes_reading,
-            ("books_general", "book_start", 5): cnd.all(
-                [
-                    loc_cnd.is_proposed_skill,
-                    cnd.neg(loc_cnd.check_flag("book_skill_active")),
-                    cnd.neg(loc_cnd.check_flag("book_start_visited")),
-                ]
-            ),
+            ("books_general", "book_start"): loc_cnd.start_condition,
             ("books_general", "book_restart"): cnd.all(
                 [
                     loc_cnd.is_proposed_skill,