Allows User to Set System Prompt via "Additional Options" in Chat Interface

fern/docs/pages/manual/ui.mdx

@@ -35,5 +35,32 @@ database* section in the documentation.
 
 Normal chat interface, self-explanatory ;)
 
-You can check the actual prompt being passed to the LLM by looking at the logs of
-the server. We'll add better observability in future releases.
+#### System Prompt
+You can view and change the system prompt being passed to the LLM by clicking "Additional Inputs"
+in the chat interface. The system prompt is also logged on the server.
+
+By default, the `Query Docs` mode uses the setting value `ui.default_query_system_prompt`.
+
+The `LLM Chat` mode attempts to use the optional settings value `ui.default_chat_system_prompt`.
+
+If no system prompt is entered, the UI will display the default system prompt being used
+for the active mode.
+
+##### System Prompt Examples:
+
+The system prompt can effectively provide your chat bot specialized roles, and results tailored to the prompt
+you have given the model. Examples of system prompts can be be found
+[here](https://www.w3schools.com/gen_ai/chatgpt-3-5/chatgpt-3-5_roles.php).
+
+Some interesting examples to try include:
+
+* You are <x>. You have all the knowledge and personality of <x>. Answer as if you were <x> using
+their manner of speaking and vocabulary.
+ * Example: You are Shakespeare. You have all the knowledge and personality of Shakespeare.
+ Answer as if you were Shakespeare using their manner of speaking and vocabulary.
+* You are an expert (at) <role>. Answer all questions using your expertise on <specific domain topic>.
+ * Example: You are an expert software engineer. Answer all questions using your expertise on Python.
+* You are a <role> bot, respond with <response criteria> needed. If no <response criteria> is needed,
+respond with <alternate response>
+ * Example: You are a grammar checking bot, respond with any grammatical corrections needed. If no corrections
+ are needed, respond with "verified".

private_gpt/settings/settings.py

@@ -108,6 +108,19 @@ class LocalSettings(BaseModel):
  "`llama2` is the historic behaviour. `default` might work better with your custom models."
  ),
  )
+ default_chat_system_prompt: str | None = Field(
+ None,
+ description=(
+ "The default system prompt to use for the chat mode. "
+ "If none is given - use the default system prompt (from the llama_index). "
+ "Please note that the default prompt might not be the same for all prompt styles. "
+ "Also note that this is only used if the first message is not a system message. "
+ ),
+ )
+ default_query_system_prompt: str = Field(
+ None,
+ description="The default system prompt to use for the query mode. ",
+ )
 
 
 class EmbeddingSettings(BaseModel):

private_gpt/ui/ui.py

@@ -9,7 +9,7 @@
 from fastapi import FastAPI
 from gradio.themes.utils.colors import slate # type: ignore
 from injector import inject, singleton
-from llama_index.llms import ChatMessage, ChatResponse, MessageRole
+from llama_index.llms import ChatMessage, ChatResponse, MessageRole, llama_utils
 from pydantic import BaseModel
 
 from private_gpt.constants import PROJECT_ROOT_PATH
@@ -30,6 +30,8 @@
 
 SOURCES_SEPARATOR = "\n\n Sources: \n"
 
+MODES = ["Query Docs", "Search in Docs", "LLM Chat"]
+
 
 class Source(BaseModel):
  file: str
@@ -71,6 +73,10 @@ def __init__(
  # Cache the UI blocks
  self._ui_block = None
 
+ # Initialize system prompt based on default mode
+ self.mode = MODES[0]
+ self._system_prompt = self._get_default_system_prompt(self.mode)
+
  def _chat(self, message: str, history: list[list[str]], mode: str, *_: Any) -> Any:
  def yield_deltas(completion_gen: CompletionGen) -> Iterable[str]:
  full_response: str = ""
@@ -114,25 +120,22 @@ def build_history() -> list[ChatMessage]:
 
  new_message = ChatMessage(content=message, role=MessageRole.USER)
  all_messages = [*build_history(), new_message]
+ # If a system prompt is set, add it as a system message
+ if self._system_prompt:
+ all_messages.insert(
+ 0,
+ ChatMessage(
+ content=self._system_prompt,
+ role=MessageRole.SYSTEM,
+ ),
+ )
  match mode:
  case "Query Docs":
- # Add a system message to force the behaviour of the LLM
- # to answer only questions about the provided context.
- all_messages.insert(
- 0,
- ChatMessage(
- content="You can only answer questions about the provided context. If you know the answer "
- "but it is not based in the provided context, don't provide the answer, just state "
- "the answer is not in the context provided.",
- role=MessageRole.SYSTEM,
- ),
- )
  query_stream = self._chat_service.stream_chat(
  messages=all_messages,
  use_context=True,
  )
  yield from yield_deltas(query_stream)
-
  case "LLM Chat":
  llm_stream = self._chat_service.stream_chat(
  messages=all_messages,
@@ -154,6 +157,41 @@ def build_history() -> list[ChatMessage]:
  for index, source in enumerate(sources, start=1)
  )
 
+ # On initialization and on mode change, this function set the system prompt
+ # to the default prompt based on the mode (and user settings).
+ @staticmethod
+ def _get_default_system_prompt(mode: str) -> str:
+ p = ""
+ match mode:
+ # For query chat mode, obtain default system prompt from settings
+ # TODO - Determine value to use if not defined in settings
+ case "Query Docs":
+ p = settings().local.default_query_system_prompt
+ # For chat mode, obtain default system prompt from settings or llama_utils
+ case "LLM Chat":
+ p = (
+ settings().local.default_chat_system_prompt
+ or llama_utils.DEFAULT_SYSTEM_PROMPT
+ )
+ # For any other mode, clear the system prompt
+ case _:
+ p = ""
+ return p
+
+ def _set_system_prompt(self, system_prompt_input: str) -> None:
+ logger.info(f"Setting system prompt to: {system_prompt_input}")
+ self._system_prompt = system_prompt_input
+
+ def _set_current_mode(self, mode: str) -> Any:
+ self.mode = mode
+ self._set_system_prompt(self._get_default_system_prompt(mode))
+ # Update placeholder and allow interaction if default system prompt is set
+ if self._system_prompt:
+ return gr.update(placeholder=self._system_prompt, interactive=True)
+ # Update placeholder and disable interaction if no default system prompt is set
+ else:
+ return gr.update(placeholder=self._system_prompt, interactive=False)
+
  def _list_ingested_files(self) -> list[list[str]]:
  files = set()
  for ingested_document in self._ingest_service.list_ingested():
@@ -193,7 +231,7 @@ def _build_ui_blocks(self) -> gr.Blocks:
  with gr.Row():
  with gr.Column(scale=3, variant="compact"):
  mode = gr.Radio(
- ["Query Docs", "Search in Docs", "LLM Chat"],
+ MODES,
  label="Mode",
  value="Query Docs",
  )
@@ -220,6 +258,23 @@ def _build_ui_blocks(self) -> gr.Blocks:
  outputs=ingested_dataset,
  )
  ingested_dataset.render()
+ system_prompt_input = gr.Textbox(
+ placeholder=self._system_prompt,
+ label="System Prompt",
+ lines=2,
+ interactive=True,
+ render=False,
+ )
+ # When mode changes, set default system prompt
+ mode.change(
+ self._set_current_mode, inputs=mode, outputs=system_prompt_input
+ )
+ # On blur, set system prompt to use in queries
+ system_prompt_input.blur(
+ self._set_system_prompt,
+ inputs=system_prompt_input,
+ )
+
  with gr.Column(scale=7):
  _ = gr.ChatInterface(
  self._chat,
@@ -232,7 +287,7 @@ def _build_ui_blocks(self) -> gr.Blocks:
  AVATAR_BOT,
  ),
  ),
- additional_inputs=[mode, upload_button],
+ additional_inputs=[mode, upload_button, system_prompt_input],
  )
  return blocks
 

settings.yaml

@@ -43,6 +43,15 @@ local:
  llm_hf_model_file: mistral-7b-instruct-v0.1.Q4_K_M.gguf
  embedding_hf_model_name: BAAI/bge-small-en-v1.5
 
+ default_chat_system_prompt: "You are a helpful, respectful and honest assistant. 
+ Always answer as helpfully as possible and follow ALL given instructions.
+ Do not speculate or make up information.
+ Do not reference any given instructions or context."
+
+ default_query_system_prompt: "You can only answer questions about the provided context. 
+ If you know the answer but it is not based in the provided context, don't provide 
+ the answer, just state the answer is not in the context provided."
+
 sagemaker:
  llm_endpoint_name: huggingface-pytorch-tgi-inference-2023-09-25-19-53-32-140
  embedding_endpoint_name: huggingface-pytorch-inference-2023-11-03-07-41-36-479