Improve handling of multiple output modes

- Use the generated descriptions / inferred queries to supply context to the model about what it's created and give a richer response
- Stop sending the generated image in user message. This seemed to be confusing the model more than helping.
- Also, rename the open ai converse method to converse_openai to follow patterns with other providers

src/khoj/processor/conversation/anthropic/anthropic_chat.py

@@ -157,10 +157,9 @@ def converse_anthropic(
     query_images: Optional[list[str]] = None,
     vision_available: bool = False,
     query_files: str = None,
-    generated_images: Optional[list[str]] = None,
     generated_files: List[FileAttachment] = None,
-    generated_excalidraw_diagram: Optional[str] = None,
     program_execution_context: Optional[List[str]] = None,
+    generated_asset_results: Dict[str, Dict] = {},
     tracer: dict = {},
 ):
     """
@@ -221,9 +220,8 @@ def converse_anthropic(
         vision_enabled=vision_available,
         model_type=ChatModelOptions.ModelType.ANTHROPIC,
         query_files=query_files,
-        generated_excalidraw_diagram=generated_excalidraw_diagram,
         generated_files=generated_files,
-        generated_images=generated_images,
+        generated_asset_results=generated_asset_results,
         program_execution_context=program_execution_context,
     )
 

src/khoj/processor/conversation/google/gemini_chat.py

@@ -167,9 +167,8 @@ def converse_gemini(
     query_images: Optional[list[str]] = None,
     vision_available: bool = False,
     query_files: str = None,
-    generated_images: Optional[list[str]] = None,
     generated_files: List[FileAttachment] = None,
-    generated_excalidraw_diagram: Optional[str] = None,
+    generated_asset_results: Dict[str, Dict] = {},
     program_execution_context: List[str] = None,
     tracer={},
 ):
@@ -232,9 +231,8 @@ def converse_gemini(
         vision_enabled=vision_available,
         model_type=ChatModelOptions.ModelType.GOOGLE,
         query_files=query_files,
-        generated_excalidraw_diagram=generated_excalidraw_diagram,
         generated_files=generated_files,
-        generated_images=generated_images,
+        generated_asset_results=generated_asset_results,
         program_execution_context=program_execution_context,
     )
 

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

@@ -3,7 +3,7 @@ import logging
 import os
 from datetime import datetime, timedelta
 from threading import Thread
-from typing import Any, Iterator, List, Optional, Union
+from typing import Any, Dict, Iterator, List, Optional, Union
 
 import pyjson5
 from langchain.schema import ChatMessage
@@ -166,6 +166,7 @@ def converse_offline(
     query_files: str = None,
     generated_files: List[FileAttachment] = None,
     additional_context: List[str] = None,
+    generated_asset_results: Dict[str, Dict] = {},
     tracer: dict = {},
 ) -> Union[ThreadedGenerator, Iterator[str]]:
     """
@@ -234,6 +235,7 @@ def converse_offline(
         model_type=ChatModelOptions.ModelType.OFFLINE,
         query_files=query_files,
         generated_files=generated_files,
+        generated_asset_results=generated_asset_results,
         program_execution_context=additional_context,
     )
 

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

@@ -137,7 +137,7 @@ def send_message_to_model(
     )
 
 
-def converse(
+def converse_openai(
     references,
     user_query,
     online_results: Optional[Dict[str, Dict]] = None,
@@ -157,9 +157,8 @@ def converse(
     query_images: Optional[list[str]] = None,
     vision_available: bool = False,
     query_files: str = None,
-    generated_images: Optional[list[str]] = None,
     generated_files: List[FileAttachment] = None,
-    generated_excalidraw_diagram: Optional[str] = None,
+    generated_asset_results: Dict[str, Dict] = {},
     program_execution_context: List[str] = None,
     tracer: dict = {},
 ):
@@ -223,9 +222,8 @@ def converse(
         vision_enabled=vision_available,
         model_type=ChatModelOptions.ModelType.OPENAI,
         query_files=query_files,
-        generated_excalidraw_diagram=generated_excalidraw_diagram,
         generated_files=generated_files,
-        generated_images=generated_images,
+        generated_asset_results=generated_asset_results,
         program_execution_context=program_execution_context,
     )
     logger.debug(f"Conversation Context for GPT: {messages_to_print(messages)}")

src/khoj/processor/conversation/prompts.py

@@ -178,40 +178,41 @@ Improved Prompt:
 """.strip()
 )
 
-generated_image_attachment = PromptTemplate.from_template(
+generated_assets_context = PromptTemplate.from_template(
-    f"""
+    """
-Here is the image you generated based on my query. You can follow-up with a general response to my query. Limit to 1-2 sentences.
+Assets that you created have already been created to respond to the query. Below, there are references to the descriptions used to create the assets.
+You can provide a summary of your reasoning from the information below or use it to respond to the original query.
+
+Generated Assets:
+{generated_assets}
+
+Limit your response to 3 sentences max. Be succinct, clear, and informative.
 """.strip()
 )
 
-generated_diagram_attachment = PromptTemplate.from_template(
-    f"""
-I've successfully created a diagram based on the user's query. The diagram will automatically be shared with the user. I can follow-up with a general response or summary. Limit to 1-2 sentences.
-""".strip()
-)
 
 ## Diagram Generation
 ## --
 
 improve_diagram_description_prompt = PromptTemplate.from_template(
     """
-you are an architect working with a novice digital artist using a diagramming software.
+You are an architect working with a novice digital artist using a diagramming software.
 {personality_context}
 
-you need to convert the user's query to a description format that the novice artist can use very well. you are allowed to use primitives like
+You need to convert the user's query to a description format that the novice artist can use very well. you are allowed to use primitives like
-- text
+- Text
-- rectangle
+- Rectangle
-- ellipse
+- Ellipse
-- line
+- Line
-- arrow
+- Arrow
 
-use these primitives to describe what sort of diagram the drawer should create. the artist must recreate the diagram every time, so include all relevant prior information in your description.
+Use these primitives to describe what sort of diagram the drawer should create. The artist must recreate the diagram every time, so include all relevant prior information in your description.
 
-- include the full, exact description. the artist does not have much experience, so be precise.
+- Include the full, exact description. the artist does not have much experience, so be precise.
-- describe the layout.
+- Describe the layout.
-- you can only use straight lines.
+- You can only use straight lines.
-- use simple, concise language.
+- Use simple, concise language.
-- keep it simple and easy to understand. the artist is easily distracted.
+- Keep it simple and easy to understand. the artist is easily distracted.
 
 Today's Date: {current_date}
 User's Location: {location}
@@ -337,6 +338,17 @@ Diagram Description: {query}
 """.strip()
 )
 
+failed_diagram_generation = PromptTemplate.from_template(
+    """
+You attempted to programmatically generate a diagram but failed due to a system issue. You are normally able to generate diagrams, but you encountered a system issue this time.
+
+You can create an ASCII image of the diagram in response instead.
+
+This is the diagram you attempted to make:
+{attempted_diagram}
+""".strip()
+)
+
 ## Online Search Conversation
 ## --
 online_search_conversation = PromptTemplate.from_template(

src/khoj/processor/conversation/utils.py

@@ -40,6 +40,7 @@ from khoj.utils.helpers import (
     merge_dicts,
 )
 from khoj.utils.rawconfig import FileAttachment
+from khoj.utils.yaml import yaml_dump
 
 logger = logging.getLogger(__name__)
 
@@ -380,9 +381,8 @@ def generate_chatml_messages_with_context(
     model_type="",
     context_message="",
     query_files: str = None,
-    generated_images: Optional[list[str]] = None,
     generated_files: List[FileAttachment] = None,
-    generated_excalidraw_diagram: str = None,
+    generated_asset_results: Dict[str, Dict] = {},
     program_execution_context: List[str] = [],
 ):
     """Generate chat messages with appropriate context from previous conversation to send to the chat model"""
@@ -402,11 +402,15 @@ def generate_chatml_messages_with_context(
         message_context = ""
         message_attached_files = ""
 
+        generated_assets = {}
+
         chat_message = chat.get("message")
         role = "user" if chat["by"] == "you" else "assistant"
 
+        # Legacy code to handle excalidraw diagrams prior to Dec 2024
         if chat["by"] == "khoj" and "excalidraw" in chat["intent"].get("type", ""):
             chat_message = chat["intent"].get("inferred-queries")[0]
+
         if not is_none_or_empty(chat.get("context")):
             references = "\n\n".join(
                 {
@@ -433,15 +437,23 @@ def generate_chatml_messages_with_context(
             reconstructed_context_message = ChatMessage(content=message_context, role="user")
             chatml_messages.insert(0, reconstructed_context_message)
 
-        if chat.get("images") and role == "assistant":
+        if not is_none_or_empty(chat.get("images")) and role == "assistant":
-            # Issue: the assistant role cannot accept an image as a message content, so send it in a separate user message.
+            generated_assets["image"] = {
-            file_attachment_message = construct_structured_message(
+                "query": chat.get("intent", {}).get("inferred-queries", [user_message])[0],
-                message=prompts.generated_image_attachment.format(),
+            }
-                images=chat.get("images"),
+
-                model_type=model_type,
+        if not is_none_or_empty(chat.get("excalidrawDiagram")) and role == "assistant":
-                vision_enabled=vision_enabled,
+            generated_assets["diagram"] = {
+                "query": chat.get("intent", {}).get("inferred-queries", [user_message])[0],
+            }
+
+        if not is_none_or_empty(generated_assets):
+            chatml_messages.append(
+                ChatMessage(
+                    content=f"{prompts.generated_assets_context.format(generated_assets=yaml_dump(generated_assets))}\n",
+                    role="user",
+                )
             )
-            chatml_messages.append(ChatMessage(content=file_attachment_message, role="user"))
 
         message_content = construct_structured_message(
             chat_message, chat.get("images") if role == "user" else [], model_type, vision_enabled
@@ -464,33 +476,22 @@ def generate_chatml_messages_with_context(
                 role="user",
             )
         )
-    if not is_none_or_empty(context_message):
-        messages.append(ChatMessage(content=context_message, role="user"))
-
-    if generated_images:
-        messages.append(
-            ChatMessage(
-                content=construct_structured_message(
-                    prompts.generated_image_attachment.format(), generated_images, model_type, vision_enabled
-                ),
-                role="user",
-            )
-        )
 
     if generated_files:
         message_attached_files = gather_raw_query_files({file.name: file.content for file in generated_files})
         messages.append(ChatMessage(content=message_attached_files, role="assistant"))
 
-    if generated_excalidraw_diagram:
+    if not is_none_or_empty(generated_asset_results):
-        messages.append(ChatMessage(content=prompts.generated_diagram_attachment.format(), role="assistant"))
+        context_message += (
+            f"{prompts.generated_assets_context.format(generated_assets=yaml_dump(generated_asset_results))}\n\n"
+        )
 
     if program_execution_context:
-        messages.append(
+        program_context_text = "\n".join(program_execution_context)
-            ChatMessage(
+        context_message += f"{prompts.additional_program_context.format(context=program_context_text)}\n"
-                content=prompts.additional_program_context.format(context="\n".join(program_execution_context)),
+
-                role="assistant",
+    if not is_none_or_empty(context_message):
-            )
+        messages.append(ChatMessage(content=context_message, role="user"))
-        )
 
     if len(chatml_messages) > 0:
         messages += chatml_messages

src/khoj/routers/api_chat.py

@@ -23,6 +23,7 @@ from khoj.database.adapters import (
     aget_user_name,
 )
 from khoj.database.models import Agent, KhojUser
+from khoj.processor.conversation import prompts
 from khoj.processor.conversation.prompts import help_message, no_entries_found
 from khoj.processor.conversation.utils import defilter_query, save_to_conversation_log
 from khoj.processor.image.generate import text_to_image
@@ -765,6 +766,7 @@ async def chat(
         researched_results = ""
         online_results: Dict = dict()
         code_results: Dict = dict()
+        generated_asset_results: Dict = dict()
         ## Extract Document References
         compiled_references: List[Any] = []
         inferred_queries: List[Any] = []
@@ -1128,6 +1130,10 @@ async def chat(
             else:
                 generated_images.append(generated_image)
 
+                generated_asset_results["images"] = {
+                    "query": improved_image_prompt,
+                }
+
                 async for result in send_event(
                     ChatEvent.GENERATED_ASSETS,
                     {
@@ -1166,6 +1172,10 @@ async def chat(
 
                         generated_excalidraw_diagram = diagram_description
 
+                        generated_asset_results["diagrams"] = {
+                            "query": better_diagram_description_prompt,
+                        }
+
                         async for result in send_event(
                             ChatEvent.GENERATED_ASSETS,
                             {
@@ -1176,7 +1186,9 @@ async def chat(
                     else:
                         error_message = "Failed to generate diagram. Please try again later."
                         program_execution_context.append(
-                            f"AI attempted to programmatically generate a diagram but failed due to a program issue. Generally, it is able to do so, but encountered a system issue this time. AI can suggest text description or rendering of the diagram or user can try again with a simpler prompt."
+                            prompts.failed_diagram_generation.format(
+                                attempted_diagram=better_diagram_description_prompt
+                            )
                         )
 
                         async for result in send_event(ChatEvent.STATUS, error_message):
@@ -1209,6 +1221,7 @@ async def chat(
             generated_files,
             generated_excalidraw_diagram,
             program_execution_context,
+            generated_asset_results,
             tracer,
         )
 

src/khoj/routers/helpers.py

@@ -88,7 +88,10 @@ from khoj.processor.conversation.offline.chat_model import (
     converse_offline,
     send_message_to_model_offline,
 )
-from khoj.processor.conversation.openai.gpt import converse, send_message_to_model
+from khoj.processor.conversation.openai.gpt import (
+    converse_openai,
+    send_message_to_model,
+)
 from khoj.processor.conversation.utils import (
     ChatEvent,
     ThreadedGenerator,
@@ -751,7 +754,7 @@ async def generate_excalidraw_diagram(
         )
     except Exception as e:
         logger.error(f"Error generating Excalidraw diagram for {user.email}: {e}", exc_info=True)
-        yield None, None
+        yield better_diagram_description_prompt, None
         return
 
     scratchpad = excalidraw_diagram_description.get("scratchpad")
@@ -1189,6 +1192,7 @@ def generate_chat_response(
     raw_generated_files: List[FileAttachment] = [],
     generated_excalidraw_diagram: str = None,
     program_execution_context: List[str] = [],
+    generated_asset_results: Dict[str, Dict] = {},
     tracer: dict = {},
 ) -> Tuple[Union[ThreadedGenerator, Iterator[str]], Dict[str, str]]:
     # Initialize Variables
@@ -1251,6 +1255,7 @@ def generate_chat_response(
                 agent=agent,
                 query_files=query_files,
                 generated_files=raw_generated_files,
+                generated_asset_results=generated_asset_results,
                 tracer=tracer,
             )
 
@@ -1258,7 +1263,7 @@ def generate_chat_response(
             openai_chat_config = conversation_config.ai_model_api
             api_key = openai_chat_config.api_key
             chat_model = conversation_config.chat_model
-            chat_response = converse(
+            chat_response = converse_openai(
                 compiled_references,
                 query_to_run,
                 query_images=query_images,
@@ -1278,8 +1283,7 @@ def generate_chat_response(
                 vision_available=vision_available,
                 query_files=query_files,
                 generated_files=raw_generated_files,
-                generated_images=generated_images,
+                generated_asset_results=generated_asset_results,
-                generated_excalidraw_diagram=generated_excalidraw_diagram,
                 program_execution_context=program_execution_context,
                 tracer=tracer,
             )
@@ -1305,8 +1309,7 @@ def generate_chat_response(
                 vision_available=vision_available,
                 query_files=query_files,
                 generated_files=raw_generated_files,
-                generated_images=generated_images,
+                generated_asset_results=generated_asset_results,
-                generated_excalidraw_diagram=generated_excalidraw_diagram,
                 program_execution_context=program_execution_context,
                 tracer=tracer,
             )
@@ -1331,8 +1334,7 @@ def generate_chat_response(
                 vision_available=vision_available,
                 query_files=query_files,
                 generated_files=raw_generated_files,
-                generated_images=generated_images,
+                generated_asset_results=generated_asset_results,
-                generated_excalidraw_diagram=generated_excalidraw_diagram,
                 program_execution_context=program_execution_context,
                 tracer=tracer,
             )

tests/test_online_chat_actors.py

@@ -4,7 +4,7 @@ import freezegun
 import pytest
 from freezegun import freeze_time
 
-from khoj.processor.conversation.openai.gpt import converse, extract_questions
+from khoj.processor.conversation.openai.gpt import converse_openai, extract_questions
 from khoj.processor.conversation.utils import message_to_log
 from khoj.routers.helpers import (
     aget_data_sources_and_output_format,
@@ -158,7 +158,7 @@ def test_generate_search_query_using_question_and_answer_from_chat_history():
 @pytest.mark.chatquality
 def test_chat_with_no_chat_history_or_retrieved_content():
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=[],  # Assume no context retrieved from notes for the user_query
         user_query="Hello, my name is Testatron. Who are you?",
         api_key=api_key,
@@ -183,7 +183,7 @@ def test_answer_from_chat_history_and_no_content():
     ]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=[],  # Assume no context retrieved from notes for the user_query
         user_query="What is my name?",
         conversation_log=populate_chat_history(message_list),
@@ -214,7 +214,7 @@ def test_answer_from_chat_history_and_previously_retrieved_content():
     ]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=[],  # Assume no context retrieved from notes for the user_query
         user_query="Where was I born?",
         conversation_log=populate_chat_history(message_list),
@@ -239,7 +239,7 @@ def test_answer_from_chat_history_and_currently_retrieved_content():
     ]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=[
             {"compiled": "Testatron was born on 1st April 1984 in Testville.", "file": "background.md"}
         ],  # Assume context retrieved from notes for the user_query
@@ -265,7 +265,7 @@ def test_refuse_answering_unanswerable_question():
     ]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=[],  # Assume no context retrieved from notes for the user_query
         user_query="Where was I born?",
         conversation_log=populate_chat_history(message_list),
@@ -318,7 +318,7 @@ Expenses:Food:Dining  10.00 USD""",
     ]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=context,  # Assume context retrieved from notes for the user_query
         user_query="What did I have for Dinner today?",
         api_key=api_key,
@@ -362,7 +362,7 @@ Expenses:Food:Dining  10.00 USD""",
     ]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=context,  # Assume context retrieved from notes for the user_query
         user_query="How much did I spend on dining this year?",
         api_key=api_key,
@@ -386,7 +386,7 @@ def test_answer_general_question_not_in_chat_history_or_retrieved_content():
     ]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=[],  # Assume no context retrieved from notes for the user_query
         user_query="Write a haiku about unit testing in 3 lines. Do not say anything else",
         conversation_log=populate_chat_history(message_list),
@@ -426,7 +426,7 @@ My sister, Aiyla is married to Tolga. They have 3 kids, Yildiz, Ali and Ahmet.""
     ]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=context,  # Assume context retrieved from notes for the user_query
         user_query="How many kids does my older sister have?",
         api_key=api_key,
@@ -459,13 +459,13 @@ def test_agent_prompt_should_be_used(openai_agent):
     expected_responses = ["9.50", "9.5"]
 
     # Act
-    response_gen = converse(
+    response_gen = converse_openai(
         references=context,  # Assume context retrieved from notes for the user_query
         user_query="What did I buy?",
         api_key=api_key,
     )
     no_agent_response = "".join([response_chunk for response_chunk in response_gen])
-    response_gen = converse(
+    response_gen = converse_openai(
         references=context,  # Assume context retrieved from notes for the user_query
         user_query="What did I buy?",
         api_key=api_key,