Rename ResponseWithThought response field to text for better naming

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

@@ -154,7 +154,7 @@ def anthropic_completion_with_backoff(
     if is_promptrace_enabled():
         commit_conversation_trace(messages, aggregated_response, tracer)
 
-    return ResponseWithThought(response=aggregated_response, thought=thoughts)
+    return ResponseWithThought(text=aggregated_response, thought=thoughts)
 
 
 @retry(
@@ -211,10 +211,10 @@ async def anthropic_chat_completion_with_backoff(
             if chunk.type == "message_delta":
                 if chunk.delta.stop_reason == "refusal":
                     yield ResponseWithThought(
-                        response="...I'm sorry, but my safety filters prevent me from assisting with this query."
+                        text="...I'm sorry, but my safety filters prevent me from assisting with this query."
                     )
                 elif chunk.delta.stop_reason == "max_tokens":
-                    yield ResponseWithThought(response="...I'm sorry, but I've hit my response length limit.")
+                    yield ResponseWithThought(text="...I'm sorry, but I've hit my response length limit.")
                 if chunk.delta.stop_reason in ["refusal", "max_tokens"]:
                     logger.warning(
                         f"LLM Response Prevented for {model_name}: {chunk.delta.stop_reason}.\n"
@@ -227,7 +227,7 @@ async def anthropic_chat_completion_with_backoff(
             # Handle streamed response chunk
             response_chunk: ResponseWithThought = None
             if chunk.delta.type == "text_delta":
-                response_chunk = ResponseWithThought(response=chunk.delta.text)
+                response_chunk = ResponseWithThought(text=chunk.delta.text)
                 aggregated_response += chunk.delta.text
             if chunk.delta.type == "thinking_delta":
                 response_chunk = ResponseWithThought(thought=chunk.delta.thinking)

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

@@ -190,7 +190,7 @@ def gemini_completion_with_backoff(
     if is_promptrace_enabled():
         commit_conversation_trace(messages, response_text, tracer)
 
-    return ResponseWithThought(response=response_text, thought=response_thoughts)
+    return ResponseWithThought(text=response_text, thought=response_thoughts)
 
 
 @retry(
@@ -258,7 +258,7 @@ async def gemini_chat_completion_with_backoff(
         # handle safety, rate-limit, other finish reasons
         stop_message, stopped = handle_gemini_response(chunk.candidates, chunk.prompt_feedback)
         if stopped:
-            yield ResponseWithThought(response=stop_message)
+            yield ResponseWithThought(text=stop_message)
             logger.warning(
                 f"LLM Response Prevented for {model_name}: {stop_message}.\n"
                 + f"Last Message by {messages[-1].role}: {messages[-1].content}"
@@ -271,7 +271,7 @@ async def gemini_chat_completion_with_backoff(
                 yield ResponseWithThought(thought=part.text)
             elif part.text:
                 aggregated_response += part.text
-                yield ResponseWithThought(response=part.text)
+                yield ResponseWithThought(text=part.text)
     # Calculate cost of chat
     input_tokens = final_chunk.usage_metadata.prompt_token_count or 0 if final_chunk else 0
     output_tokens = final_chunk.usage_metadata.candidates_token_count or 0 if final_chunk else 0

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

@@ -145,12 +145,12 @@ async def converse_offline(
                 aggregated_response += response_delta
                 # Put chunk into the asyncio queue (non-blocking)
                 try:
-                    queue.put_nowait(ResponseWithThought(response=response_delta))
+                    queue.put_nowait(ResponseWithThought(text=response_delta))
                 except asyncio.QueueFull:
                     # Should not happen with default queue size unless consumer is very slow
                     logger.warning("Asyncio queue full during offline LLM streaming.")
                     # Potentially block here or handle differently if needed
-                    asyncio.run(queue.put(ResponseWithThought(response=response_delta)))
+                    asyncio.run(queue.put(ResponseWithThought(text=response_delta)))
 
             # Log the time taken to stream the entire response
             logger.info(f"Chat streaming took: {perf_counter() - start_time:.3f} seconds")
@@ -221,4 +221,4 @@ def send_message_to_model_offline(
     if is_promptrace_enabled():
         commit_conversation_trace(messages, response_text, tracer)
 
-    return ResponseWithThought(response=response_text)
+    return ResponseWithThought(text=response_text)

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

@@ -181,7 +181,7 @@ def completion_with_backoff(
     if is_promptrace_enabled():
         commit_conversation_trace(messages, aggregated_response, tracer)
 
-    return ResponseWithThought(response=aggregated_response, thought=thoughts)
+    return ResponseWithThought(text=aggregated_response, thought=thoughts)
 
 
 @retry(
@@ -297,7 +297,7 @@ async def chat_completion_with_backoff(
             raise ValueError("No response by model.")
         aggregated_response = response.choices[0].message.content
         final_chunk = response
-        yield ResponseWithThought(response=aggregated_response)
+        yield ResponseWithThought(text=aggregated_response)
     else:
         async for chunk in stream_processor(response):
             # Log the time taken to start response
@@ -313,8 +313,8 @@ async def chat_completion_with_backoff(
             response_chunk: ResponseWithThought = None
             response_delta = chunk.choices[0].delta
             if response_delta.content:
-                response_chunk = ResponseWithThought(response=response_delta.content)
+                response_chunk = ResponseWithThought(text=response_delta.content)
-                aggregated_response += response_chunk.response
+                aggregated_response += response_chunk.text
             elif response_delta.thought:
                 response_chunk = ResponseWithThought(thought=response_delta.thought)
             if response_chunk:

src/khoj/processor/conversation/utils.py

@@ -1187,6 +1187,6 @@ class StructuredOutputSupport(int, Enum):
 
 
 class ResponseWithThought:
-    def __init__(self, response: str = None, thought: str = None):
+    def __init__(self, text: str = None, thought: str = None):
-        self.response = response
+        self.text = text
         self.thought = thought

src/khoj/processor/operator/operator_agent_binary.py

@@ -129,7 +129,7 @@ class BinaryOperatorAgent(OperatorAgent):
                 agent_chat_model=self.reasoning_model,
                 tracer=self.tracer,
             )
-            natural_language_action = raw_response.response
+            natural_language_action = raw_response.text
 
             if not isinstance(natural_language_action, str) or not natural_language_action.strip():
                 raise ValueError(f"Natural language action is empty or not a string. Got {natural_language_action}")
@@ -256,10 +256,10 @@ class BinaryOperatorAgent(OperatorAgent):
 
         # Append summary messages to history
         trigger_summary = AgentMessage(role="user", content=summarize_prompt)
-        summary_message = AgentMessage(role="assistant", content=summary.response)
+        summary_message = AgentMessage(role="assistant", content=summary.text)
         self.messages.extend([trigger_summary, summary_message])
 
-        return summary.response
+        return summary.text
 
     def _compile_response(self, response_content: str | List) -> str:
         """Compile response content into a string, handling OpenAI message structures."""

src/khoj/processor/tools/run_code.py

@@ -161,7 +161,7 @@ async def generate_python_code(
     )
 
     # Extract python code wrapped in markdown code blocks from the response
-    code_blocks = re.findall(r"```(?:python)?\n(.*?)```", response.response, re.DOTALL)
+    code_blocks = re.findall(r"```(?:python)?\n(.*?)```", response.text, re.DOTALL)
 
     if not code_blocks:
         raise ValueError("No Python code blocks found in response")

src/khoj/routers/api_chat.py

@@ -1390,7 +1390,7 @@ async def chat(
                 continue
             if cancellation_event.is_set():
                 break
-            message = item.response
+            message = item.text
             full_response += message if message else ""
             if item.thought:
                 async for result in send_event(ChatEvent.THOUGHT, item.thought):

src/khoj/routers/helpers.py

@@ -304,7 +304,7 @@ async def acreate_title_from_history(
     with timer("Chat actor: Generate title from conversation history", logger):
         response = await send_message_to_model_wrapper(title_generation_prompt, user=user)
 
-    return response.response.strip()
+    return response.text.strip()
 
 
 async def acreate_title_from_query(query: str, user: KhojUser = None) -> str:
@@ -316,7 +316,7 @@ async def acreate_title_from_query(query: str, user: KhojUser = None) -> str:
     with timer("Chat actor: Generate title from query", logger):
         response = await send_message_to_model_wrapper(title_generation_prompt, user=user)
 
-    return response.response.strip()
+    return response.text.strip()
 
 
 async def acheck_if_safe_prompt(system_prompt: str, user: KhojUser = None, lax: bool = False) -> Tuple[bool, str]:
@@ -340,7 +340,7 @@ async def acheck_if_safe_prompt(system_prompt: str, user: KhojUser = None, lax:
             safe_prompt_check, user=user, response_type="json_object", response_schema=SafetyCheck
         )
 
-        response = response.response.strip()
+        response = response.text.strip()
         try:
             response = json.loads(clean_json(response))
             is_safe = str(response.get("safe", "true")).lower() == "true"
@@ -430,7 +430,7 @@ async def aget_data_sources_and_output_format(
         )
 
     try:
-        response = clean_json(raw_response.response)
+        response = clean_json(raw_response.text)
         response = json.loads(response)
 
         chosen_sources = [s.strip() for s in response.get("source", []) if s.strip()]
@@ -520,7 +520,7 @@ async def infer_webpage_urls(
 
     # Validate that the response is a non-empty, JSON-serializable list of URLs
     try:
-        response = clean_json(raw_response.response)
+        response = clean_json(raw_response.text)
         urls = json.loads(response)
         valid_unique_urls = {str(url).strip() for url in urls["links"] if is_valid_url(url)}
         if is_none_or_empty(valid_unique_urls):
@@ -585,7 +585,7 @@ async def generate_online_subqueries(
 
     # Validate that the response is a non-empty, JSON-serializable list
     try:
-        response = clean_json(raw_response.response)
+        response = clean_json(raw_response.text)
         response = pyjson5.loads(response)
         response = {q.strip() for q in response["queries"] if q.strip()}
         if not isinstance(response, set) or not response or len(response) == 0:
@@ -646,7 +646,7 @@ async def aschedule_query(
 
     # Validate that the response is a non-empty, JSON-serializable list
     try:
-        raw_response = raw_response.response.strip()
+        raw_response = raw_response.text.strip()
         response: Dict[str, str] = json.loads(clean_json(raw_response))
         if not response or not isinstance(response, Dict) or len(response) != 3:
             raise AssertionError(f"Invalid response for scheduling query : {response}")
@@ -684,7 +684,7 @@ async def extract_relevant_info(
         agent_chat_model=agent_chat_model,
         tracer=tracer,
     )
-    return response.response.strip()
+    return response.text.strip()
 
 
 async def extract_relevant_summary(
@@ -727,7 +727,7 @@ async def extract_relevant_summary(
             agent_chat_model=agent_chat_model,
             tracer=tracer,
         )
-    return response.response.strip()
+    return response.text.strip()
 
 
 async def generate_summary_from_files(
@@ -898,7 +898,7 @@ async def generate_better_diagram_description(
             agent_chat_model=agent_chat_model,
             tracer=tracer,
         )
-        response = response.response.strip()
+        response = response.text.strip()
         if response.startswith(('"', "'")) and response.endswith(('"', "'")):
             response = response[1:-1]
 
@@ -926,7 +926,7 @@ async def generate_excalidraw_diagram_from_description(
         raw_response = await send_message_to_model_wrapper(
             query=excalidraw_diagram_generation, user=user, agent_chat_model=agent_chat_model, tracer=tracer
         )
-        raw_response_text = clean_json(raw_response.response)
+        raw_response_text = clean_json(raw_response.text)
         try:
             # Expect response to have `elements` and `scratchpad` keys
             response: Dict[str, str] = json.loads(raw_response_text)
@@ -1049,7 +1049,7 @@ async def generate_better_mermaidjs_diagram_description(
             agent_chat_model=agent_chat_model,
             tracer=tracer,
         )
-        response_text = response.response.strip()
+        response_text = response.text.strip()
         if response_text.startswith(('"', "'")) and response_text.endswith(('"', "'")):
             response_text = response_text[1:-1]
 
@@ -1077,7 +1077,7 @@ async def generate_mermaidjs_diagram_from_description(
         raw_response = await send_message_to_model_wrapper(
             query=mermaidjs_diagram_generation, user=user, agent_chat_model=agent_chat_model, tracer=tracer
         )
-        return clean_mermaidjs(raw_response.response.strip())
+        return clean_mermaidjs(raw_response.text.strip())
 
 
 async def generate_better_image_prompt(
@@ -1152,7 +1152,7 @@ async def generate_better_image_prompt(
             agent_chat_model=agent_chat_model,
             tracer=tracer,
         )
-        response_text = response.response.strip()
+        response_text = response.text.strip()
         if response_text.startswith(('"', "'")) and response_text.endswith(('"', "'")):
             response_text = response_text[1:-1]
 
@@ -1330,7 +1330,7 @@ async def extract_questions(
 
     # Extract questions from the response
     try:
-        response = clean_json(raw_response.response)
+        response = clean_json(raw_response.text)
         response = pyjson5.loads(response)
         queries = [q.strip() for q in response["queries"] if q.strip()]
         if not isinstance(queries, list) or not queries:

src/khoj/routers/research.py

@@ -157,7 +157,7 @@ async def apick_next_tool(
     try:
         # Try parse the response as function call response to infer next tool to use.
         # TODO: Handle multiple tool calls.
-        response_text = raw_response.response
+        response_text = raw_response.text
         parsed_response = [ToolCall(**item) for item in load_complex_json(response_text)][0]
     except Exception as e:
         # Otherwise assume the model has decided to end the research run and respond to the user.

tests/test_online_chat_actors.py

@@ -189,7 +189,7 @@ async def test_chat_with_no_chat_history_or_retrieved_content():
         user_query="Hello, my name is Testatron. Who are you?",
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     expected_responses = ["Khoj", "khoj"]
@@ -217,7 +217,7 @@ async def test_answer_from_chat_history_and_no_content():
         chat_history=populate_chat_history(message_list),
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     expected_responses = ["Testatron", "testatron"]
@@ -250,7 +250,7 @@ async def test_answer_from_chat_history_and_previously_retrieved_content():
         chat_history=populate_chat_history(message_list),
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     assert len(response) > 0
@@ -279,7 +279,7 @@ async def test_answer_from_chat_history_and_currently_retrieved_content():
         chat_history=populate_chat_history(message_list),
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     assert len(response) > 0
@@ -305,7 +305,7 @@ async def test_refuse_answering_unanswerable_question():
         chat_history=populate_chat_history(message_list),
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     expected_responses = [
@@ -359,7 +359,7 @@ Expenses:Food:Dining  10.00 USD""",
         user_query="What did I have for Dinner today?",
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     expected_responses = ["tacos", "Tacos"]
@@ -405,7 +405,7 @@ Expenses:Food:Dining  10.00 USD""",
         user_query="How much did I spend on dining this year?",
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     assert len(response) > 0
@@ -432,7 +432,7 @@ async def test_answer_general_question_not_in_chat_history_or_retrieved_content(
         chat_history=populate_chat_history(message_list),
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     expected_responses = ["test", "bug", "code"]
@@ -473,7 +473,7 @@ My sister, Aiyla is married to Tolga. They have 3 kids, Yildiz, Ali and Ahmet.""
         user_query="How many kids does my older sister have?",
         api_key=api_key,
     )
-    response = "".join([response_chunk.response async for response_chunk in response_gen])
+    response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert
     expected_responses = [
@@ -508,14 +508,14 @@ async def test_agent_prompt_should_be_used(openai_agent):
         user_query="What did I buy?",
         api_key=api_key,
     )
-    no_agent_response = "".join([response_chunk.response async for response_chunk in response_gen])
+    no_agent_response = "".join([response_chunk.text async for response_chunk in response_gen])
     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,
         agent=openai_agent,
     )
-    agent_response = "".join([response_chunk.response async for response_chunk in response_gen])
+    agent_response = "".join([response_chunk.text async for response_chunk in response_gen])
 
     # Assert that the model without the agent prompt does not include the summary of purchases
     assert all([expected_response not in no_agent_response for expected_response in expected_responses]), (