Make OpenAI conversation model configurable via khoj.yml

- Default to using `text-davinci-003' if conversation model not
  explicitly configured by user. Stop using the older `davinci' and
  `davinci-instruct' models

- Use `model' instead of `engine' as parameter.
  Usage of `engine' parameter in OpenAI API is deprecated

config/khoj_docker.yml

@@ -51,4 +51,5 @@ search-type:
 processor:
   #conversation:
   #  openai-api-key: null
+  #  model: "text-davinci-003"
   #  conversation-logfile: "/data/embeddings/conversation_logs.json"

config/khoj_sample.yml

@@ -52,4 +52,5 @@ search-type:
 processor:
   conversation:
     openai-api-key: # "YOUR_OPENAI_API_KEY"
+    model: "text-davinci-003"
     conversation-logfile: "~/.khoj/processor/conversation/conversation_logs.json"

src/processor/conversation/gpt.py

@@ -10,7 +10,7 @@ import openai
 from src.utils.constants import empty_escape_sequences
 
 
-def summarize(text, summary_type, user_query=None, api_key=None, temperature=0.5, max_tokens=100):
+def summarize(text, summary_type, model, user_query=None, api_key=None, temperature=0.5, max_tokens=100):
     """
     Summarize user input using OpenAI's GPT
     """
@@ -35,8 +35,8 @@ Summarize the notes in second person perspective and use past tense:'''
 
     # Get Response from GPT
     response = openai.Completion.create(
-        engine="davinci-instruct-beta-v3",
         prompt=prompt,
+        model=model,
         temperature=temperature,
         max_tokens=max_tokens,
         top_p=1,
@@ -49,7 +49,7 @@ Summarize the notes in second person perspective and use past tense:'''
     return str(story).replace("\n\n", "")
 
 
-def extract_search_type(text, api_key=None, temperature=0.5, max_tokens=100, verbose=0):
+def extract_search_type(text, model, api_key=None, temperature=0.5, max_tokens=100, verbose=0):
     """
     Extract search type from user query using OpenAI's GPT
     """
@@ -84,8 +84,8 @@ A:{ "search-type": "notes" }'''
 
     # Get Response from GPT
     response = openai.Completion.create(
-        engine="davinci",
         prompt=prompt,
+        model=model,
         temperature=temperature,
         max_tokens=max_tokens,
         top_p=1,
@@ -98,7 +98,7 @@ A:{ "search-type": "notes" }'''
     return json.loads(story.strip(empty_escape_sequences))
 
 
-def understand(text, api_key=None, temperature=0.5, max_tokens=100, verbose=0):
+def understand(text, model, api_key=None, temperature=0.5, max_tokens=100, verbose=0):
     """
     Understand user input using OpenAI's GPT
     """
@@ -155,8 +155,8 @@ A: { "intent": {"type": "generate", "activity": "chat", "query": "Can you dance
 
     # Get Response from GPT
     response = openai.Completion.create(
-        engine="davinci",
         prompt=prompt,
+        model=model,
         temperature=temperature,
         max_tokens=max_tokens,
         top_p=1,
@@ -169,7 +169,7 @@ A: { "intent": {"type": "generate", "activity": "chat", "query": "Can you dance
     return json.loads(story.strip(empty_escape_sequences))
 
 
-def converse(text, conversation_history=None, api_key=None, temperature=0.9, max_tokens=150):
+def converse(text, model, conversation_history=None, api_key=None, temperature=0.9, max_tokens=150):
     """
     Converse with user using OpenAI's GPT
     """
@@ -189,8 +189,8 @@ The following is a conversation with an AI assistant. The assistant is helpful,
 
     # Get Response from GPT
     response = openai.Completion.create(
-        engine="davinci",
         prompt=prompt,
+        model=model,
         temperature=temperature,
         max_tokens=max_tokens,
         top_p=1,

src/routers/api_beta.py

@@ -38,9 +38,11 @@ def chat(q: str):
     # Load Conversation History
     chat_session = state.processor_config.conversation.chat_session
     meta_log = state.processor_config.conversation.meta_log
+    model = state.processor_config.conversation.model
+    api_key = state.processor_config.conversation.openai_api_key
 
     # Converse with OpenAI GPT
-    metadata = understand(q, api_key=state.processor_config.conversation.openai_api_key, verbose=state.verbose)
+    metadata = understand(q, model=model, api_key=api_key, verbose=state.verbose)
     logger.debug(f'Understood: {get_from_dict(metadata, "intent")}')
 
     if get_from_dict(metadata, "intent", "memory-type") == "notes":
@@ -48,9 +50,9 @@ def chat(q: str):
         result_list = search(query, n=1, t=SearchType.Org, r=True)
         collated_result = "\n".join([item.entry for item in result_list])
         logger.debug(f'Semantically Similar Notes:\n{collated_result}')
-        gpt_response = summarize(collated_result, summary_type="notes", user_query=q, api_key=state.processor_config.conversation.openai_api_key)
+        gpt_response = summarize(collated_result, summary_type="notes", user_query=q, model=model, api_key=api_key)
     else:
-        gpt_response = converse(q, chat_session, api_key=state.processor_config.conversation.openai_api_key)
+        gpt_response = converse(q, model, chat_session, api_key=api_key)
 
     # Update Conversation History
     state.processor_config.conversation.chat_session = message_to_prompt(q, chat_session, gpt_message=gpt_response)
@@ -70,8 +72,9 @@ def shutdown_event():
     chat_session = state.processor_config.conversation.chat_session
     openai_api_key = state.processor_config.conversation.openai_api_key
     conversation_log = state.processor_config.conversation.meta_log
+    model = state.processor_config.conversation.model
     session = {
-        "summary": summarize(chat_session, summary_type="chat", api_key=openai_api_key),
+        "summary": summarize(chat_session, summary_type="chat", model=model, api_key=openai_api_key),
         "session-start": conversation_log.get("session", [{"session-end": 0}])[-1]["session-end"],
         "session-end": len(conversation_log["chat"])
         }

src/utils/config.py

@@ -51,6 +51,7 @@ class SearchModels():
 class ConversationProcessorConfigModel():
     def __init__(self, processor_config: ConversationProcessorConfig):
         self.openai_api_key = processor_config.openai_api_key
+        self.model = processor_config.model
         self.conversation_logfile = Path(processor_config.conversation_logfile)
         self.chat_session = ''
         self.meta_log: dict = {}

src/utils/rawconfig.py

@@ -66,6 +66,7 @@ class SearchConfig(ConfigBase):
 class ConversationProcessorConfig(ConfigBase):
     openai_api_key: str
     conversation_logfile: Path
+    model: Optional[str] = "text-davinci-003"
 
 class ProcessorConfig(ConfigBase):
     conversation: Optional[ConversationProcessorConfig]