Enforce json response by offline models when requested by chat actors

- Background
  Llama.cpp allows enforcing response as json object similar to OpenAI
  API. Pass expected response format to offline chat models as well.

- Overview
  Enforce json output to improve intermediate step performance by
  offline chat models. This is especially helpful when working with
  smaller models like Phi-3.5-mini and Gemma-2 2B, that do not
  consistently respond with structured output, even when requested

- Details
  Enforce json response by extract questions, infer output offline
  chat actors
  - Convert prompts to output json objects when offline chat models
    extract document search questions or infer output mode
  - Make llama.cpp enforce response as json object

- Result
  - Improve all intermediate steps by offline chat actors via json
    response enforcement
  - Avoid the manual, ad-hoc and flaky output schema enforcement and
    simplify the code

src/khoj/processor/conversation/offline/chat_model.py

@@ -87,26 +87,16 @@ def extract_questions_offline(
             model=model,
             max_prompt_size=max_prompt_size,
             temperature=temperature,
+            response_type="json_object",
         )
     finally:
         state.chat_lock.release()
 
-    # Extract, Clean Message from GPT's Response
+    # Extract and clean the chat model's response
     try:
-        # This will expect to be a list with a single string with a list of questions
-        questions_str = (
-            str(response)
-            .strip(empty_escape_sequences)
-            .replace("['", '["')
-            .replace("<s>", "")
-            .replace("</s>", "")
-            .replace("']", '"]')
-            .replace("', '", '", "')
-        )
-        # Remove any markdown json codeblock formatting if present (useful for gemma-2)
-        if response.startswith("```json"):
-            response = response[7:-3]
-        questions: List[str] = json.loads(questions_str)
+        response = response.strip(empty_escape_sequences)
+        response = json.loads(response)
+        questions = [q.strip() for q in response["queries"] if q.strip()]
         questions = filter_questions(questions)
     except:
         logger.warning(f"Llama returned invalid JSON. Falling back to using user message as search query.\n{response}")
@@ -245,12 +235,13 @@ def send_message_to_model_offline(
     streaming=False,
     stop=[],
     max_prompt_size: int = None,
+    response_type: str = "text",
 ):
     assert loaded_model is None or isinstance(loaded_model, Llama), "loaded_model must be of type Llama, if configured"
     offline_chat_model = loaded_model or download_model(model, max_tokens=max_prompt_size)
     messages_dict = [{"role": message.role, "content": message.content} for message in messages]
     response = offline_chat_model.create_chat_completion(
-        messages_dict, stop=stop, stream=streaming, temperature=temperature
+        messages_dict, stop=stop, stream=streaming, temperature=temperature, response_format={"type": response_type}
     )
     if streaming:
         return response

src/khoj/processor/conversation/prompts.py

@@ -217,31 +217,31 @@ User's Location: {location}
 
 Examples:
 Q: How was my trip to Cambodia?
-Khoj: ["How was my trip to Cambodia?"]
+Khoj: {{"queries": ["How was my trip to Cambodia?"]}}
 
 Q: Who did I visit the temple with on that trip?
-Khoj: ["Who did I visit the temple with in Cambodia?"]
+Khoj: {{"queries": ["Who did I visit the temple with in Cambodia?"]}}
 
 Q: Which of them is older?
-Khoj: ["When was Alice born?", "What is Bob's age?"]
+Khoj: {{"queries": ["When was Alice born?", "What is Bob's age?"]}}
 
 Q: Where did John say he was? He mentioned it in our call last week.
-Khoj: ["Where is John? dt>='{last_year}-12-25' dt<'{last_year}-12-26'", "John's location in call notes"]
+Khoj: {{"queries": ["Where is John? dt>='{last_year}-12-25' dt<'{last_year}-12-26'", "John's location in call notes"]}}
 
 Q: How can you help me?
-Khoj: ["Social relationships", "Physical and mental health", "Education and career", "Personal life goals and habits"]
+Khoj: {{"queries": ["Social relationships", "Physical and mental health", "Education and career", "Personal life goals and habits"]}}
 
 Q: What did I do for Christmas last year?
-Khoj: ["What did I do for Christmas {last_year} dt>='{last_year}-12-25' dt<'{last_year}-12-26'"]
+Khoj: {{"queries": ["What did I do for Christmas {last_year} dt>='{last_year}-12-25' dt<'{last_year}-12-26'"]}}
 
 Q: How should I take care of my plants?
-Khoj: ["What kind of plants do I have?", "What issues do my plants have?"]
+Khoj: {{"queries": ["What kind of plants do I have?", "What issues do my plants have?"]}}
 
 Q: Who all did I meet here yesterday?
-Khoj: ["Met in {location} on {yesterday_date} dt>='{yesterday_date}' dt<'{current_date}'"]
+Khoj: {{"queries": ["Met in {location} on {yesterday_date} dt>='{yesterday_date}' dt<'{current_date}'"]}}
 
 Q: Share some random, interesting experiences from this month
-Khoj: ["Exciting travel adventures from {current_month}", "Fun social events dt>='{current_month}-01' dt<'{current_date}'", "Intense emotional experiences in {current_month}"]
+Khoj: {{"queries": ["Exciting travel adventures from {current_month}", "Fun social events dt>='{current_month}-01' dt<'{current_date}'", "Intense emotional experiences in {current_month}"]}}
 
 Chat History:
 {chat_history}
@@ -425,7 +425,7 @@ User: I just visited Jerusalem for the first time. Pull up my notes from the tri
 AI: You mention visiting Masjid Al-Aqsa and the Western Wall. You also mention trying the local cuisine and visiting the Dead Sea.
 
 Q: Draw a picture of my trip to Jerusalem.
-Khoj: image
+Khoj: {{"output": "image"}}
 
 Example:
 Chat History:
@@ -433,7 +433,7 @@ User: I'm having trouble deciding which laptop to get. I want something with at
 AI: I can help with that. I see online that there is a new model of the Dell XPS 15 that meets your requirements.
 
 Q: What are the specs of the new Dell XPS 15?
-Khoj: text
+Khoj: {{"output": "text"}}
 
 Example:
 Chat History:
@@ -441,7 +441,7 @@ User: Where did I go on my last vacation?
 AI: You went to Jordan and visited Petra, the Dead Sea, and Wadi Rum.
 
 Q: Remind me who did I go with on that trip?
-Khoj: text
+Khoj: {{"output": "text"}}
 
 Example:
 Chat History:
@@ -449,9 +449,9 @@ User: How's the weather outside? Current Location: Bali, Indonesia
 AI: It's currently 28°C and partly cloudy in Bali.
 
 Q: Share a painting using the weather for Bali every morning.
-Khoj: automation
+Khoj: {{"output": "automation"}}
 
-Now it's your turn to pick the mode you would like to use to answer the user's question. Provide your response as a string.
+Now it's your turn to pick the mode you would like to use to answer the user's question. Provide your response as a JSON.
 
 Chat History:
 {chat_history}

src/khoj/routers/helpers.py

@@ -326,22 +326,23 @@ async def aget_relevant_output_modes(query: str, conversation_history: dict, is_
     )
 
     with timer("Chat actor: Infer output mode for chat response", logger):
-        response = await send_message_to_model_wrapper(relevant_mode_prompt)
+        response = await send_message_to_model_wrapper(relevant_mode_prompt, response_type="json_object")
 
     try:
-        response = response.strip().strip('"')
+        response = json.loads(response.strip())
 
         if is_none_or_empty(response):
             return ConversationCommand.Text
 
-        if response in mode_options.keys():
+        output_mode = response["output"]
+        if output_mode in mode_options.keys():
             # Check whether the tool exists as a valid ConversationCommand
-            return ConversationCommand(response)
+            return ConversationCommand(output_mode)
 
-        logger.error(f"Invalid output mode selected: {response}. Defaulting to text.")
+        logger.error(f"Invalid output mode selected: {output_mode}. Defaulting to text.")
         return ConversationCommand.Text
     except Exception:
-        logger.error(f"Invalid response for determining relevant mode: {response}")
+        logger.error(f"Invalid response for determining output mode: {response}")
         return ConversationCommand.Text
 
 
@@ -595,6 +596,7 @@ async def send_message_to_model_wrapper(
             loaded_model=loaded_model,
             model=chat_model,
             streaming=False,
+            response_type=response_type,
         )
 
     elif conversation_config.model_type == "openai":
@@ -664,6 +666,7 @@ def send_message_to_model_wrapper_sync(
             loaded_model=loaded_model,
             model=chat_model,
             streaming=False,
+            response_type=response_type,
         )
 
     elif conversation_config.model_type == "openai":