Add default persona config

.github/workflows/license_tests.yml

@@ -9,4 +9,4 @@ jobs:
   license_tests:
     uses: neongeckocom/.github/.github/workflows/license_tests.yml@master
     with:
-      packages-exclude: '^(neon-llm-chatgpt|tqdm).*'
+      packages-exclude: '^(neon-llm-chatgpt|tqdm|klat-connector|neon-chatbot|dnspython).*'

Dockerfile

@@ -6,8 +6,10 @@ LABEL vendor=neon.ai \
 ENV OVOS_CONFIG_BASE_FOLDER neon
 ENV OVOS_CONFIG_FILENAME diana.yaml
 ENV XDG_CONFIG_HOME /config
-COPY docker_overlay/ /
+ENV CHATBOT_VERSION v2
 
+COPY docker_overlay/ /
+RUN apt update && apt install -y git
 WORKDIR /app
 COPY . /app
 RUN pip install /app

README.md

@@ -37,6 +37,22 @@ LLM_CHAT_GPT:
   num_parallel_processes: 2
 ```
 
+To add support for Chatbotsforum personas, a list of names and prompts can be added
+to configuration:
+```yaml
+llm_bots:
+  chat_gpt:
+    - name: tutor
+      description: |
+        You are an AI bot that specializes in tutoring and guiding learners.
+        Your focus is on individualized teaching, considering their existing knowledge, misconceptions, interests, and talents.
+        Emphasize personalized learning, mimicking the role of a dedicated tutor for each student.
+        You're attempting to provide a concise response within a 40-word limit.
+```
+> `chat_gpt` is the MQ service name for this service; each bot has a `name` that
+> is used to identify the persona in chats and `description` is the prompt passed
+> to ChatGPT.
+
 For example, if your configuration resides in `~/.config`:
 ```shell
 export CONFIG_PATH="/home/${USER}/.config"

docker_overlay/etc/neon/diana.yaml

@@ -5,10 +5,11 @@ logs:
       - pika
     warning:
       - filelock
-    info: []
+    info:
+      - openai
     debug: []
 MQ:
-  server: api.neon.ai
+  server: neon-rabbitmq
   port: 5672
   users:
     mq_handler:
@@ -19,4 +20,39 @@ LLM_CHAT_GPT:
   role: "You are trying to give a short answer in less than 40 words."
   context_depth: 3
   max_tokens: 100
-  num_parallel_processes: 2
+  num_parallel_processes: 2
+#llm_bots:
+#  chat_gpt:
+#    - name: urban_logic
+#      description: |
+#        You are an AI bot that specializes in smart city planning.
+#        Generate insights and recommendations on technology integration, sustainability, urban development, transportation management, community engagement, data analysis, and policy development to enhance urban environments for efficiency and sustainability.
+#        You're attempting to provide a concise response within a 40-word limit.
+#    - name: nature_guardian
+#      description: |
+#        You are an AI bot that specializes in nature conservation.
+#        Engage users by detailing the importance of habitat restoration, wildlife monitoring, education, research, land management, advocacy, community engagement, and preservation planning in safeguarding our environment and biodiversity.
+#        You're attempting to provide a concise response within a 40-word limit.
+#    - name: rescuer
+#      description: |
+#        You are an AI bot that specializes in disaster management.
+#        Respond accurately about preparedness, response, coordination, communication, recovery, and education in disasters.
+#        Aim to inform, guide, and assist in minimizing disaster impact.
+#        You're attempting to provide a concise response within a 40-word limit.
+#    - name: tutor
+#      description: |
+#        You are an AI bot that specializes in tutoring and guiding learners.
+#        Your focus is on individualized teaching, considering their existing knowledge, misconceptions, interests, and talents.
+#        Emphasize personalized learning, mimicking the role of a dedicated tutor for each student.
+#        You're attempting to provide a concise response within a 40-word limit.
+#    - name: mental_guide
+#      description: |
+#        You are an AI bot that specializes in counseling and mental health support.
+#        Provide guidance on assessments, therapy sessions, crisis intervention, goal setting, referrals, advocacy, education, documentation, and adherence to ethical standards, fostering positive changes in clients' lives.
+#        You're attempting to provide a concise response within a 40-word limit.
+#    - name: travel_mate
+#      description: |
+#        You are an AI bot that specializes in trip planning services.
+#        Engage users by offering consultations, destination research, itinerary planning, bookings, budget management, documentation assistance, continuous customer support, customized travel experiences, and updated travel advisories.
+#        Enhance their travel journey and save their time.
+#        You're attempting to provide a concise response within a 40-word limit.

neon_llm_chatgpt/__main__.py

@@ -25,9 +25,11 @@
 # SOFTWARE,  EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
 from neon_llm_chatgpt.rmq import ChatgptMQ
+from neon_utils.log_utils import init_log
 
 
 def main():
+    init_log(log_name="chatgpt")
     # Run RabbitMQ
     chatgptMQ = ChatgptMQ()
     chatgptMQ.run(run_sync=False, run_consumers=True,

neon_llm_chatgpt/chatgpt.py

@@ -29,6 +29,7 @@
 
 from typing import List, Dict
 from neon_llm_core.llm import NeonLLM
+from ovos_utils.log import LOG
 
 
 class ChatGPT(NeonLLM):
@@ -71,7 +72,7 @@ def _system_prompt(self) -> str:
         return self.role
 
     def warmup(self):
-        self.model
+        _ = self.model
 
     def get_sorted_answer_indexes(self, question: str, answers: List[str], persona: dict) -> List[int]:
         """
@@ -102,7 +103,7 @@ def _call_model(self, prompt: List[Dict[str, str]]) -> str:
             max_tokens=self.max_tokens,
         )
         text = response.choices[0].message['content']
-
+        LOG.debug(text)
         return text
 
     def _assemble_prompt(self, message: str, chat_history: List[List[str]], persona: dict) -> List[Dict[str, str]]:
@@ -153,4 +154,4 @@ def _embeddings(self, question: str, answers: List[str], persona: dict) -> (List
         embeddings = get_embeddings(texts, engine="text-embedding-ada-002")
         question_embeddings = embeddings[0]
         answers_embeddings = embeddings[1:]
-        return question_embeddings, answers_embeddings
+        return question_embeddings, answers_embeddings

neon_llm_chatgpt/rmq.py

@@ -48,8 +48,13 @@ def model(self):
         return self._model
 
     def warmup(self):
-        self.model
+        """
+        Initialize this LLM to be ready to provide responses
+        """
+        _ = self.model
 
     @staticmethod
-    def compose_opinion_prompt(respondent_nick: str, question: str, answer: str) -> str:
-        return f'Why Answer "{answer}" to the Question "{question}" generated by Bot named "{respondent_nick}" is good?'
+    def compose_opinion_prompt(respondent_nick: str, question: str,
+                               answer: str) -> str:
+        return (f'Why Answer "{answer}" to the Question "{question}" '
+                f'generated by Bot named "{respondent_nick}" is good?')

requirements/requirements.txt

@@ -1,4 +1,5 @@
 # model
 openai[embeddings]~=0.27
 # networking
-neon_llm_core~=0.1.0
+neon_llm_core[chatbots]~=0.1.0,>=0.1.1a1
+ovos-utils~=0.0.32