Show thinking and engage deep thought for gemini 2.5 model series

Gemini models now show (a summary of) their thoughts. Stream this in
research mode, similar to how it is done already for claude, deepseek,
qwen etc.

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

@@ -275,7 +275,8 @@ async def converse_gemini(
         deepthought=deepthought,
         tracer=tracer,
     ):
-        full_response += chunk
+        if chunk.response:
+            full_response += chunk.response
         yield chunk
 
     # Call completion_func once finish streaming and we have the full response

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

@@ -21,6 +21,7 @@ from tenacity import (
 )
 
 from khoj.processor.conversation.utils import (
+    ResponseWithThought,
     commit_conversation_trace,
     get_image_from_base64,
     get_image_from_url,
@@ -110,7 +111,7 @@ def gemini_completion_with_backoff(
         response_schema = clean_response_schema(model_kwargs["response_schema"])
 
     thinking_config = None
-    if deepthought and model_name.startswith("gemini-2-5"):
+    if deepthought and model_name.startswith("gemini-2.5"):
         thinking_config = gtypes.ThinkingConfig(thinking_budget=MAX_REASONING_TOKENS_GEMINI)
 
     seed = int(os.getenv("KHOJ_LLM_SEED")) if os.getenv("KHOJ_LLM_SEED") else None
@@ -178,7 +179,7 @@ async def gemini_chat_completion_with_backoff(
     model_kwargs=None,
     deepthought=False,
     tracer: dict = {},
-) -> AsyncGenerator[str, None]:
+) -> AsyncGenerator[ResponseWithThought, None]:
     client = gemini_clients.get(api_key)
     if not client:
         client = get_gemini_client(api_key, api_base_url)
@@ -187,8 +188,8 @@ async def gemini_chat_completion_with_backoff(
     formatted_messages, system_instruction = format_messages_for_gemini(messages, system_prompt)
 
     thinking_config = None
-    if deepthought and model_name.startswith("gemini-2-5"):
-        thinking_config = gtypes.ThinkingConfig(thinking_budget=MAX_REASONING_TOKENS_GEMINI)
+    if deepthought and model_name.startswith("gemini-2.5"):
+        thinking_config = gtypes.ThinkingConfig(thinking_budget=MAX_REASONING_TOKENS_GEMINI, include_thoughts=True)
 
     seed = int(os.getenv("KHOJ_LLM_SEED")) if os.getenv("KHOJ_LLM_SEED") else None
     config = gtypes.GenerateContentConfig(
@@ -216,18 +217,25 @@ async def gemini_chat_completion_with_backoff(
             logger.info(f"First response took: {perf_counter() - start_time:.3f} seconds")
         # Keep track of the last chunk for usage data
         final_chunk = chunk
-        # Handle streamed response chunk
+
+        # handle safety, rate-limit, other finish reasons
         stop_message, stopped = handle_gemini_response(chunk.candidates, chunk.prompt_feedback)
-        message = stop_message or chunk.text
-        aggregated_response += message
-        yield message
         if stopped:
+            yield ResponseWithThought(response=stop_message)
             logger.warning(
                 f"LLM Response Prevented for {model_name}: {stop_message}.\n"
                 + f"Last Message by {messages[-1].role}: {messages[-1].content}"
             )
             break
 
+        # emit thought vs response parts
+        for part in chunk.candidates[0].content.parts:
+            if part.text:
+                aggregated_response += part.text
+                yield ResponseWithThought(response=part.text)
+            if part.thought:
+                yield ResponseWithThought(thought=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