Improve Offline Chat Model Experience (#494)

- Make offline chat model user configurable. Use `filename` of any [GPT4All supported  model](https://github.com/nomic-ai/gpt4all/blob/main/gpt4all-chat/metadata/models.json) like below:
- Run GPT4All Chat Model on GPU, when available via [GPT4All Vulcan support](https://blog.nomic.ai/posts/gpt4all-gpu-inference-with-vulkan)
- Use default Llama 2 supported by GPT4All
- Make `tokenizer` and `max-prompt-size` of chat model user configurable. E.g When using chat models not in [this pre-defined list](https://github.com/khoj-ai/khoj/blob/master/src/khoj/processor/conversation/utils.py) that support larger context window or a different tokenizer.

Closes #406, #418

src/khoj/configure.py

@@ -19,7 +19,7 @@ from khoj.utils.config import (
 )
 from khoj.utils.helpers import resolve_absolute_path, merge_dicts
 from khoj.utils.fs_syncer import collect_files
-from khoj.utils.rawconfig import FullConfig, ProcessorConfig, ConversationProcessorConfig
+from khoj.utils.rawconfig import FullConfig, OfflineChatProcessorConfig, ProcessorConfig, ConversationProcessorConfig
 from khoj.routers.indexer import configure_content, load_content, configure_search
 
 
@@ -168,9 +168,7 @@ def configure_conversation_processor(
             conversation_config=ConversationProcessorConfig(
                 conversation_logfile=conversation_logfile,
                 openai=(conversation_config.openai if (conversation_config is not None) else None),
-                enable_offline_chat=(
+                offline_chat=conversation_config.offline_chat if conversation_config else OfflineChatProcessorConfig(),
-                    conversation_config.enable_offline_chat if (conversation_config is not None) else False
-                ),
             )
         )
     else:

src/khoj/interface/web/config.html

@@ -236,7 +236,7 @@
                     </h3>
                 </div>
                 <div class="card-description-row">
-                <p class="card-description">Setup chat using OpenAI</p>
+                <p class="card-description">Setup online chat using OpenAI</p>
                 </div>
                 <div class="card-action-row">
                     <a class="card-button" href="/config/processor/conversation/openai">
@@ -261,21 +261,21 @@
                     <img class="card-icon" src="/static/assets/icons/chat.svg" alt="Chat">
                     <h3 class="card-title">
                         Offline Chat
-                        <img id="configured-icon-conversation-enable-offline-chat" class="configured-icon {% if current_config.processor and current_config.processor.conversation and current_config.processor.conversation.enable_offline_chat and current_model_state.conversation_gpt4all %}enabled{% else %}disabled{% endif %}" src="/static/assets/icons/confirm-icon.svg" alt="Configured">
+                        <img id="configured-icon-conversation-enable-offline-chat" class="configured-icon {% if current_config.processor and current_config.processor.conversation and current_config.processor.conversation.offline_chat.enable_offline_chat and current_model_state.conversation_gpt4all %}enabled{% else %}disabled{% endif %}" src="/static/assets/icons/confirm-icon.svg" alt="Configured">
-                        {% if current_config.processor and current_config.processor.conversation and current_config.processor.conversation.enable_offline_chat and not current_model_state.conversation_gpt4all %}
+                        {% if current_config.processor and current_config.processor.conversation and current_config.processor.conversation.offline_chat.enable_offline_chat and not current_model_state.conversation_gpt4all %}
                             <img id="misconfigured-icon-conversation-enable-offline-chat" class="configured-icon" src="/static/assets/icons/question-mark-icon.svg" alt="Not Configured" title="The model was not downloaded as expected.">
                         {% endif %}
                     </h3>
                 </div>
                 <div class="card-description-row">
-                <p class="card-description">Setup offline chat (Llama V2)</p>
+                <p class="card-description">Setup offline chat</p>
                 </div>
-                <div id="clear-enable-offline-chat" class="card-action-row {% if current_config.processor and current_config.processor.conversation and current_config.processor.conversation.enable_offline_chat %}enabled{% else %}disabled{% endif %}">
+                <div id="clear-enable-offline-chat" class="card-action-row {% if current_config.processor and current_config.processor.conversation and current_config.processor.conversation.offline_chat.enable_offline_chat %}enabled{% else %}disabled{% endif %}">
                     <button class="card-button" onclick="toggleEnableLocalLLLM(false)">
                         Disable
                     </button>
                 </div>
-                <div id="set-enable-offline-chat" class="card-action-row {% if current_config.processor and current_config.processor.conversation and current_config.processor.conversation.enable_offline_chat %}disabled{% else %}enabled{% endif %}">
+                <div id="set-enable-offline-chat" class="card-action-row {% if current_config.processor and current_config.processor.conversation and current_config.processor.conversation.offline_chat.enable_offline_chat %}disabled{% else %}enabled{% endif %}">
                     <button class="card-button happy" onclick="toggleEnableLocalLLLM(true)">
                         Enable
                     </button>
@@ -346,7 +346,7 @@
             featuresHintText.classList.add("show");
         }
 
-        fetch('/api/config/data/processor/conversation/enable_offline_chat' + '?enable_offline_chat=' + enable, {
+        fetch('/api/config/data/processor/conversation/offline_chat' + '?enable_offline_chat=' + enable, {
             method: 'POST',
             headers: {
                 'Content-Type': 'application/json',

src/khoj/migrations/migrate_offline_chat_schema.py

@@ -0,0 +1,83 @@
+"""
+Current format of khoj.yml
+---
+app:
+    ...
+content-type:
+    ...
+processor:
+  conversation:
+    enable-offline-chat: false
+    conversation-logfile: ~/.khoj/processor/conversation/conversation_logs.json
+    openai:
+        ...
+search-type:
+    ...
+
+New format of khoj.yml
+---
+app:
+    ...
+content-type:
+    ...
+processor:
+  conversation:
+    offline-chat:
+        enable-offline-chat: false
+        chat-model: llama-2-7b-chat.ggmlv3.q4_0.bin
+    tokenizer: null
+    max_prompt_size: null
+    conversation-logfile: ~/.khoj/processor/conversation/conversation_logs.json
+    openai:
+        ...
+search-type:
+    ...
+"""
+import logging
+from packaging import version
+
+from khoj.utils.yaml import load_config_from_file, save_config_to_file
+
+
+logger = logging.getLogger(__name__)
+
+
+def migrate_offline_chat_schema(args):
+    schema_version = "0.12.3"
+    raw_config = load_config_from_file(args.config_file)
+    previous_version = raw_config.get("version")
+
+    if "processor" not in raw_config:
+        return args
+    if raw_config["processor"] is None:
+        return args
+    if "conversation" not in raw_config["processor"]:
+        return args
+
+    if previous_version is None or version.parse(previous_version) < version.parse("0.12.3"):
+        logger.info(
+            f"Upgrading config schema to {schema_version} from {previous_version} to make (offline) chat more configuration"
+        )
+        raw_config["version"] = schema_version
+
+        # Create max-prompt-size field in conversation processor schema
+        raw_config["processor"]["conversation"]["max-prompt-size"] = None
+        raw_config["processor"]["conversation"]["tokenizer"] = None
+
+        # Create offline chat schema based on existing enable_offline_chat field in khoj config schema
+        offline_chat_model = (
+            raw_config["processor"]["conversation"]
+            .get("offline-chat", {})
+            .get("chat-model", "llama-2-7b-chat.ggmlv3.q4_0.bin")
+        )
+        raw_config["processor"]["conversation"]["offline-chat"] = {
+            "enable-offline-chat": raw_config["processor"]["conversation"].get("enable-offline-chat", False),
+            "chat-model": offline_chat_model,
+        }
+
+        # Delete old enable-offline-chat field from conversation processor schema
+        if "enable-offline-chat" in raw_config["processor"]["conversation"]:
+            del raw_config["processor"]["conversation"]["enable-offline-chat"]
+
+        save_config_to_file(raw_config, args.config_file)
+    return args

src/khoj/processor/conversation/gpt4all/chat_model.py

@@ -16,7 +16,7 @@ logger = logging.getLogger(__name__)
 
 def extract_questions_offline(
     text: str,
-    model: str = "llama-2-7b-chat.ggmlv3.q4_K_S.bin",
+    model: str = "llama-2-7b-chat.ggmlv3.q4_0.bin",
     loaded_model: Union[Any, None] = None,
     conversation_log={},
     use_history: bool = True,
@@ -113,7 +113,7 @@ def filter_questions(questions: List[str]):
     ]
     filtered_questions = []
     for q in questions:
-        if not any([word in q.lower() for word in hint_words]):
+        if not any([word in q.lower() for word in hint_words]) and not is_none_or_empty(q):
             filtered_questions.append(q)
 
     return filtered_questions
@@ -123,10 +123,12 @@ def converse_offline(
     references,
     user_query,
     conversation_log={},
-    model: str = "llama-2-7b-chat.ggmlv3.q4_K_S.bin",
+    model: str = "llama-2-7b-chat.ggmlv3.q4_0.bin",
     loaded_model: Union[Any, None] = None,
     completion_func=None,
     conversation_command=ConversationCommand.Default,
+    max_prompt_size=None,
+    tokenizer_name=None,
 ) -> Union[ThreadedGenerator, Iterator[str]]:
     """
     Converse with user using Llama
@@ -158,6 +160,8 @@ def converse_offline(
         prompts.system_prompt_message_llamav2,
         conversation_log,
         model_name=model,
+        max_prompt_size=max_prompt_size,
+        tokenizer_name=tokenizer_name,
     )
 
     g = ThreadedGenerator(references, completion_func=completion_func)

src/khoj/processor/conversation/gpt4all/model_metadata.py

@@ -1,3 +0,0 @@
-model_name_to_url = {
-    "llama-2-7b-chat.ggmlv3.q4_K_S.bin": "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/resolve/main/llama-2-7b-chat.ggmlv3.q4_K_S.bin"
-}

src/khoj/processor/conversation/gpt4all/utils.py

@@ -1,24 +1,8 @@
-import os
 import logging
-import requests
-import hashlib
 
-from tqdm import tqdm
-
-from khoj.processor.conversation.gpt4all import model_metadata
 
 logger = logging.getLogger(__name__)
 
-expected_checksum = {"llama-2-7b-chat.ggmlv3.q4_K_S.bin": "cfa87b15d92fb15a2d7c354b0098578b"}
-
-
-def get_md5_checksum(filename: str):
-    hash_md5 = hashlib.md5()
-    with open(filename, "rb") as f:
-        for chunk in iter(lambda: f.read(8192), b""):
-            hash_md5.update(chunk)
-    return hash_md5.hexdigest()
-
 
 def download_model(model_name: str):
     try:
@@ -27,57 +11,12 @@ def download_model(model_name: str):
         logger.info("There was an error importing GPT4All. Please run pip install gpt4all in order to install it.")
         raise e
 
-    url = model_metadata.model_name_to_url.get(model_name)
+    # Use GPU for Chat Model, if available
-    model_path = os.path.expanduser(f"~/.cache/gpt4all/")
-    if not url:
-        logger.debug(f"Model {model_name} not found in model metadata. Skipping download.")
-        return GPT4All(model_name=model_name, model_path=model_path)
-
-    filename = os.path.expanduser(f"~/.cache/gpt4all/{model_name}")
-    if os.path.exists(filename):
-        # Check if the user is connected to the internet
-        try:
-            requests.get("https://www.google.com/", timeout=5)
-        except:
-            logger.debug("User is offline. Disabling allowed download flag")
-            return GPT4All(model_name=model_name, model_path=model_path, allow_download=False)
-        return GPT4All(model_name=model_name, model_path=model_path)
-
-    # Download the model to a tmp file. Once the download is completed, move the tmp file to the actual file
-    tmp_filename = filename + ".tmp"
-
     try:
-        os.makedirs(os.path.dirname(tmp_filename), exist_ok=True)
+        model = GPT4All(model_name=model_name, device="gpu")
-        logger.debug(f"Downloading model {model_name} from {url} to {filename}...")
+        logger.debug("Loaded chat model to GPU.")
-        with requests.get(url, stream=True) as r:
+    except ValueError:
-            r.raise_for_status()
+        model = GPT4All(model_name=model_name)
-            total_size = int(r.headers.get("content-length", 0))
+        logger.debug("Loaded chat model to CPU.")
-            with open(tmp_filename, "wb") as f, tqdm(
-                unit="B",  # unit string to be displayed.
-                unit_scale=True,  # let tqdm to determine the scale in kilo, mega..etc.
-                unit_divisor=1024,  # is used when unit_scale is true
-                total=total_size,  # the total iteration.
-                desc=model_name,  # prefix to be displayed on progress bar.
-            ) as progress_bar:
-                for chunk in r.iter_content(chunk_size=8192):
-                    f.write(chunk)
-                    progress_bar.update(len(chunk))
 
-        # Verify the checksum
+    return model
-        if expected_checksum.get(model_name) != get_md5_checksum(tmp_filename):
-            logger.error(
-                f"Checksum verification failed for {filename}. Removing the tmp file. Offline model will not be available."
-            )
-            os.remove(tmp_filename)
-            raise ValueError(f"Checksum verification failed for downloading {model_name} from {url}.")
-
-        # Move the tmp file to the actual file
-        os.rename(tmp_filename, filename)
-        logger.debug(f"Successfully downloaded model {model_name} from {url} to {filename}")
-        return GPT4All(model_name)
-    except Exception as e:
-        logger.error(f"Failed to download model {model_name} from {url} to {filename}. Error: {e}", exc_info=True)
-        # Remove the tmp file if it exists
-        if os.path.exists(tmp_filename):
-            os.remove(tmp_filename)
-        return None

src/khoj/processor/conversation/openai/gpt.py

@@ -116,6 +116,8 @@ def converse(
     temperature: float = 0.2,
     completion_func=None,
     conversation_command=ConversationCommand.Default,
+    max_prompt_size=None,
+    tokenizer_name=None,
 ):
     """
     Converse with user using OpenAI's ChatGPT
@@ -141,6 +143,8 @@ def converse(
         prompts.personality.format(),
         conversation_log,
         model,
+        max_prompt_size,
+        tokenizer_name,
     )
     truncated_messages = "\n".join({f"{message.content[:40]}..." for message in messages})
     logger.debug(f"Conversation Context for GPT: {truncated_messages}")

src/khoj/processor/conversation/prompts.py

@@ -23,7 +23,7 @@ no_notes_found = PromptTemplate.from_template(
     """.strip()
 )
 
-system_prompt_message_llamav2 = f"""You are Khoj, a friendly, smart and helpful personal assistant.
+system_prompt_message_llamav2 = f"""You are Khoj, a smart, inquisitive and helpful personal assistant.
 Using your general knowledge and our past conversations as context, answer the following question.
 If you do not know the answer, say 'I don't know.'"""
 
@@ -51,13 +51,13 @@ extract_questions_system_prompt_llamav2 = PromptTemplate.from_template(
 
 general_conversation_llamav2 = PromptTemplate.from_template(
     """
-<s>[INST]{query}[/INST]
+<s>[INST] {query} [/INST]
 """.strip()
 )
 
 chat_history_llamav2_from_user = PromptTemplate.from_template(
     """
-<s>[INST]{message}[/INST]
+<s>[INST] {message} [/INST]
 """.strip()
 )
 
@@ -69,7 +69,7 @@ chat_history_llamav2_from_assistant = PromptTemplate.from_template(
 
 conversation_llamav2 = PromptTemplate.from_template(
     """
-<s>[INST]{query}[/INST]
+<s>[INST] {query} [/INST]
 """.strip()
 )
 
@@ -91,7 +91,7 @@ Question: {query}
 
 notes_conversation_llamav2 = PromptTemplate.from_template(
     """
-Notes:
+User's Notes:
 {references}
 Question: {query}
 """.strip()
@@ -134,19 +134,25 @@ Answer (in second person):"""
 
 extract_questions_llamav2_sample = PromptTemplate.from_template(
     """
-<s>[INST]<<SYS>>Current Date: {current_date}<</SYS>>[/INST]</s>
+<s>[INST] <<SYS>>Current Date: {current_date}<</SYS>> [/INST]</s>
-<s>[INST]How was my trip to Cambodia?[/INST][]</s>
+<s>[INST] How was my trip to Cambodia? [/INST]
-<s>[INST]Who did I visit the temple with on that trip?[/INST]Who did I visit the temple with in Cambodia?</s>
+How was my trip to Cambodia?</s>
-<s>[INST]How should I take care of my plants?[/INST]What kind of plants do I have? What issues do my plants have?</s>
+<s>[INST] Who did I visit the temple with on that trip? [/INST]
-<s>[INST]How many tennis balls fit in the back of a 2002 Honda Civic?[/INST]What is the size of a tennis ball? What is the trunk size of a 2002 Honda Civic?</s>
+Who did I visit the temple with in Cambodia?</s>
-<s>[INST]What did I do for Christmas last year?[/INST]What did I do for Christmas {last_year} dt>='{last_christmas_date}' dt<'{next_christmas_date}'</s>
+<s>[INST] How should I take care of my plants? [/INST]
-<s>[INST]How are you feeling today?[/INST]</s>
+What kind of plants do I have? What issues do my plants have?</s>
-<s>[INST]Is Alice older than Bob?[/INST]When was Alice born? What is Bob's age?</s>
+<s>[INST] How many tennis balls fit in the back of a 2002 Honda Civic? [/INST]
-<s>[INST]<<SYS>>
+What is the size of a tennis ball? What is the trunk size of a 2002 Honda Civic?</s>
+<s>[INST] What did I do for Christmas last year? [/INST]
+What did I do for Christmas {last_year} dt>='{last_christmas_date}' dt<'{next_christmas_date}'</s>
+<s>[INST] How are you feeling today? [/INST]</s>
+<s>[INST] Is Alice older than Bob? [/INST]
+When was Alice born? What is Bob's age?</s>
+<s>[INST] <<SYS>>
 Use these notes from the user's previous conversations to provide a response:
 {chat_history}
-<</SYS>>[/INST]</s>
+<</SYS>> [/INST]</s>
-<s>[INST]{query}[/INST]
+<s>[INST] {query} [/INST]
 """
 )
 

src/khoj/processor/conversation/utils.py

@@ -3,24 +3,27 @@ import logging
 from time import perf_counter
 import json
 from datetime import datetime
+import queue
 import tiktoken
 
 # External packages
 from langchain.schema import ChatMessage
-from transformers import LlamaTokenizerFast
+from transformers import AutoTokenizer
 
 # Internal Packages
-import queue
 from khoj.utils.helpers import merge_dicts
 
+
 logger = logging.getLogger(__name__)
-max_prompt_size = {
+model_to_prompt_size = {
     "gpt-3.5-turbo": 4096,
     "gpt-4": 8192,
-    "llama-2-7b-chat.ggmlv3.q4_K_S.bin": 1548,
+    "llama-2-7b-chat.ggmlv3.q4_0.bin": 1548,
     "gpt-3.5-turbo-16k": 15000,
 }
-tokenizer = {"llama-2-7b-chat.ggmlv3.q4_K_S.bin": "hf-internal-testing/llama-tokenizer"}
+model_to_tokenizer = {
+    "llama-2-7b-chat.ggmlv3.q4_0.bin": "hf-internal-testing/llama-tokenizer",
+}
 
 
 class ThreadedGenerator:
@@ -82,9 +85,26 @@ def message_to_log(
 
 
 def generate_chatml_messages_with_context(
-    user_message, system_message, conversation_log={}, model_name="gpt-3.5-turbo", lookback_turns=2
+    user_message,
+    system_message,
+    conversation_log={},
+    model_name="gpt-3.5-turbo",
+    max_prompt_size=None,
+    tokenizer_name=None,
 ):
     """Generate messages for ChatGPT with context from previous conversation"""
+    # Set max prompt size from user config, pre-configured for model or to default prompt size
+    try:
+        max_prompt_size = max_prompt_size or model_to_prompt_size[model_name]
+    except:
+        max_prompt_size = 2000
+        logger.warning(
+            f"Fallback to default prompt size: {max_prompt_size}.\nConfigure max_prompt_size for unsupported model: {model_name} in Khoj settings to longer context window."
+        )
+
+    # Scale lookback turns proportional to max prompt size supported by model
+    lookback_turns = max_prompt_size // 750
+
     # Extract Chat History for Context
     chat_logs = []
     for chat in conversation_log.get("chat", []):
@@ -105,19 +125,28 @@ def generate_chatml_messages_with_context(
     messages = user_chatml_message + rest_backnforths + system_chatml_message
 
     # Truncate oldest messages from conversation history until under max supported prompt size by model
-    messages = truncate_messages(messages, max_prompt_size[model_name], model_name)
+    messages = truncate_messages(messages, max_prompt_size, model_name, tokenizer_name)
 
     # Return message in chronological order
     return messages[::-1]
 
 
-def truncate_messages(messages: list[ChatMessage], max_prompt_size, model_name) -> list[ChatMessage]:
+def truncate_messages(
+    messages: list[ChatMessage], max_prompt_size, model_name: str, tokenizer_name=None
+) -> list[ChatMessage]:
     """Truncate messages to fit within max prompt size supported by model"""
 
-    if "llama" in model_name:
+    try:
-        encoder = LlamaTokenizerFast.from_pretrained(tokenizer[model_name])
+        if model_name.startswith("gpt-"):
-    else:
+            encoder = tiktoken.encoding_for_model(model_name)
-        encoder = tiktoken.encoding_for_model(model_name)
+        else:
+            encoder = AutoTokenizer.from_pretrained(tokenizer_name or model_to_tokenizer[model_name])
+    except:
+        default_tokenizer = "hf-internal-testing/llama-tokenizer"
+        encoder = AutoTokenizer.from_pretrained(default_tokenizer)
+        logger.warning(
+            f"Fallback to default chat model tokenizer: {default_tokenizer}.\nConfigure tokenizer for unsupported model: {model_name} in Khoj settings to improve context stuffing."
+        )
 
     system_message = messages.pop()
     system_message_tokens = len(encoder.encode(system_message.content))

src/khoj/routers/api.py

@@ -284,10 +284,11 @@ if not state.demo:
         except Exception as e:
             return {"status": "error", "message": str(e)}
 
-    @api.post("/config/data/processor/conversation/enable_offline_chat", status_code=200)
+    @api.post("/config/data/processor/conversation/offline_chat", status_code=200)
     async def set_processor_enable_offline_chat_config_data(
         request: Request,
         enable_offline_chat: bool,
+        offline_chat_model: Optional[str] = None,
         client: Optional[str] = None,
     ):
         _initialize_config()
@@ -301,7 +302,9 @@ if not state.demo:
             state.config.processor = ProcessorConfig(conversation=ConversationProcessorConfig(conversation_logfile=conversation_logfile))  # type: ignore
 
         assert state.config.processor.conversation is not None
-        state.config.processor.conversation.enable_offline_chat = enable_offline_chat
+        state.config.processor.conversation.offline_chat.enable_offline_chat = enable_offline_chat
+        if offline_chat_model is not None:
+            state.config.processor.conversation.offline_chat.chat_model = offline_chat_model
         state.processor_config = configure_processor(state.config.processor, state.processor_config)
 
         update_telemetry_state(
@@ -713,7 +716,7 @@ async def chat(
         conversation_command = ConversationCommand.General
 
     if conversation_command == ConversationCommand.Help:
-        model_type = "offline" if state.processor_config.conversation.enable_offline_chat else "openai"
+        model_type = "offline" if state.processor_config.conversation.offline_chat.enable_offline_chat else "openai"
         formatted_help = help_message.format(model=model_type, version=state.khoj_version)
         return StreamingResponse(iter([formatted_help]), media_type="text/event-stream", status_code=200)
 
@@ -788,7 +791,7 @@ async def extract_references_and_questions(
     # Infer search queries from user message
     with timer("Extracting search queries took", logger):
         # If we've reached here, either the user has enabled offline chat or the openai model is enabled.
-        if state.processor_config.conversation.enable_offline_chat:
+        if state.processor_config.conversation.offline_chat.enable_offline_chat:
             loaded_model = state.processor_config.conversation.gpt4all_model.loaded_model
             inferred_queries = extract_questions_offline(
                 defiltered_query, loaded_model=loaded_model, conversation_log=meta_log, should_extract_questions=False
@@ -804,7 +807,7 @@ async def extract_references_and_questions(
     with timer("Searching knowledge base took", logger):
         result_list = []
         for query in inferred_queries:
-            n_items = min(n, 3) if state.processor_config.conversation.enable_offline_chat else n
+            n_items = min(n, 3) if state.processor_config.conversation.offline_chat.enable_offline_chat else n
             result_list.extend(
                 await search(
                     f"{query} {filters_in_query}",

src/khoj/routers/helpers.py

@@ -113,7 +113,7 @@ def generate_chat_response(
             meta_log=meta_log,
         )
 
-        if state.processor_config.conversation.enable_offline_chat:
+        if state.processor_config.conversation.offline_chat.enable_offline_chat:
             loaded_model = state.processor_config.conversation.gpt4all_model.loaded_model
             chat_response = converse_offline(
                 references=compiled_references,
@@ -122,6 +122,9 @@ def generate_chat_response(
                 conversation_log=meta_log,
                 completion_func=partial_completion,
                 conversation_command=conversation_command,
+                model=state.processor_config.conversation.offline_chat.chat_model,
+                max_prompt_size=state.processor_config.conversation.max_prompt_size,
+                tokenizer_name=state.processor_config.conversation.tokenizer,
             )
 
         elif state.processor_config.conversation.openai_model:
@@ -135,6 +138,8 @@ def generate_chat_response(
                 api_key=api_key,
                 completion_func=partial_completion,
                 conversation_command=conversation_command,
+                max_prompt_size=state.processor_config.conversation.max_prompt_size,
+                tokenizer_name=state.processor_config.conversation.tokenizer,
             )
 
     except Exception as e:

src/khoj/utils/cli.py

@@ -9,6 +9,7 @@ from khoj.utils.yaml import parse_config_from_file
 from khoj.migrations.migrate_version import migrate_config_to_version
 from khoj.migrations.migrate_processor_config_openai import migrate_processor_conversation_schema
 from khoj.migrations.migrate_offline_model import migrate_offline_model
+from khoj.migrations.migrate_offline_chat_schema import migrate_offline_chat_schema
 
 
 def cli(args=None):
@@ -55,7 +56,12 @@ def cli(args=None):
 
 
 def run_migrations(args):
-    migrations = [migrate_config_to_version, migrate_processor_conversation_schema, migrate_offline_model]
+    migrations = [
+        migrate_config_to_version,
+        migrate_processor_conversation_schema,
+        migrate_offline_model,
+        migrate_offline_chat_schema,
+    ]
     for migration in migrations:
         args = migration(args)
     return args

src/khoj/utils/config.py

@@ -84,7 +84,6 @@ class SearchModels:
 
 @dataclass
 class GPT4AllProcessorConfig:
-    chat_model: Optional[str] = "llama-2-7b-chat.ggmlv3.q4_K_S.bin"
     loaded_model: Union[Any, None] = None
 
 
@@ -95,18 +94,20 @@ class ConversationProcessorConfigModel:
     ):
         self.openai_model = conversation_config.openai
         self.gpt4all_model = GPT4AllProcessorConfig()
-        self.enable_offline_chat = conversation_config.enable_offline_chat
+        self.offline_chat = conversation_config.offline_chat
+        self.max_prompt_size = conversation_config.max_prompt_size
+        self.tokenizer = conversation_config.tokenizer
         self.conversation_logfile = Path(conversation_config.conversation_logfile)
         self.chat_session: List[str] = []
         self.meta_log: dict = {}
 
-        if self.enable_offline_chat:
+        if self.offline_chat.enable_offline_chat:
             try:
-                self.gpt4all_model.loaded_model = download_model(self.gpt4all_model.chat_model)
+                self.gpt4all_model.loaded_model = download_model(self.offline_chat.chat_model)
             except ValueError as e:
+                self.offline_chat.enable_offline_chat = False
                 self.gpt4all_model.loaded_model = None
                 logger.error(f"Error while loading offline chat model: {e}", exc_info=True)
-                self.enable_offline_chat = False
         else:
             self.gpt4all_model.loaded_model = None
 

src/khoj/utils/rawconfig.py

@@ -91,10 +91,17 @@ class OpenAIProcessorConfig(ConfigBase):
     chat_model: Optional[str] = "gpt-3.5-turbo"
 
 
+class OfflineChatProcessorConfig(ConfigBase):
+    enable_offline_chat: Optional[bool] = False
+    chat_model: Optional[str] = "llama-2-7b-chat.ggmlv3.q4_0.bin"
+
+
 class ConversationProcessorConfig(ConfigBase):
     conversation_logfile: Path
     openai: Optional[OpenAIProcessorConfig]
-    enable_offline_chat: Optional[bool] = False
+    offline_chat: Optional[OfflineChatProcessorConfig]
+    max_prompt_size: Optional[int]
+    tokenizer: Optional[str]
 
 
 class ProcessorConfig(ConfigBase):

tests/conftest.py

@@ -16,6 +16,7 @@ from khoj.utils.helpers import resolve_absolute_path
 from khoj.utils.rawconfig import (
     ContentConfig,
     ConversationProcessorConfig,
+    OfflineChatProcessorConfig,
     OpenAIProcessorConfig,
     ProcessorConfig,
     TextContentConfig,
@@ -205,8 +206,9 @@ def processor_config_offline_chat(tmp_path_factory):
 
     # Setup conversation processor
     processor_config = ProcessorConfig()
+    offline_chat = OfflineChatProcessorConfig(enable_offline_chat=True)
     processor_config.conversation = ConversationProcessorConfig(
-        enable_offline_chat=True,
+        offline_chat=offline_chat,
         conversation_logfile=processor_dir.joinpath("conversation_logs.json"),
     )
 

tests/test_gpt4all_chat_actors.py

@@ -24,7 +24,7 @@ from khoj.processor.conversation.gpt4all.utils import download_model
 
 from khoj.processor.conversation.utils import message_to_log
 
-MODEL_NAME = "llama-2-7b-chat.ggmlv3.q4_K_S.bin"
+MODEL_NAME = "llama-2-7b-chat.ggmlv3.q4_0.bin"
 
 
 @pytest.fixture(scope="session")
@@ -128,15 +128,15 @@ def test_extract_multiple_explicit_questions_from_message(loaded_model):
 @pytest.mark.chatquality
 def test_extract_multiple_implicit_questions_from_message(loaded_model):
     # Act
-    response = extract_questions_offline("Is Morpheus taller than Neo?", loaded_model=loaded_model)
+    response = extract_questions_offline("Is Carl taller than Ross?", loaded_model=loaded_model)
 
     # Assert
-    expected_responses = ["height", "taller", "shorter", "heights"]
+    expected_responses = ["height", "taller", "shorter", "heights", "who"]
     assert len(response) <= 3
 
     for question in response:
         assert any([expected_response in question.lower() for expected_response in expected_responses]), (
-            "Expected chat actor to ask follow-up questions about Morpheus and Neo, but got: " + question
+            "Expected chat actor to ask follow-up questions about Carl and Ross, but got: " + question
         )
 
 
@@ -145,7 +145,7 @@ def test_extract_multiple_implicit_questions_from_message(loaded_model):
 def test_generate_search_query_using_question_from_chat_history(loaded_model):
     # Arrange
     message_list = [
-        ("What is the name of Mr. Vader's daughter?", "Princess Leia", []),
+        ("What is the name of Mr. Anderson's daughter?", "Miss Barbara", []),
     ]
 
     # Act
@@ -156,17 +156,22 @@ def test_generate_search_query_using_question_from_chat_history(loaded_model):
         use_history=True,
     )
 
-    expected_responses = [
+    all_expected_in_response = [
-        "Vader",
+        "Anderson",
-        "sons",
+    ]
+
+    any_expected_in_response = [
         "son",
-        "Darth",
+        "sons",
         "children",
     ]
 
     # Assert
     assert len(response) >= 1
-    assert any([expected_response in response[0] for expected_response in expected_responses]), (
+    assert all([expected_response in response[0] for expected_response in all_expected_in_response]), (
+        "Expected chat actor to ask for clarification in response, but got: " + response[0]
+    )
+    assert any([expected_response in response[0] for expected_response in any_expected_in_response]), (
         "Expected chat actor to ask for clarification in response, but got: " + response[0]
     )
 
@@ -176,20 +181,20 @@ def test_generate_search_query_using_question_from_chat_history(loaded_model):
 def test_generate_search_query_using_answer_from_chat_history(loaded_model):
     # Arrange
     message_list = [
-        ("What is the name of Mr. Vader's daughter?", "Princess Leia", []),
+        ("What is the name of Mr. Anderson's daughter?", "Miss Barbara", []),
     ]
 
     # Act
     response = extract_questions_offline(
-        "Is she a Jedi?",
+        "Is she a Doctor?",
         conversation_log=populate_chat_history(message_list),
         loaded_model=loaded_model,
         use_history=True,
     )
 
     expected_responses = [
-        "Leia",
+        "Barbara",
-        "Vader",
+        "Robert",
         "daughter",
     ]