Do not use max prompt size to limit Gemini max output tokens

We should start disambiguating the the max input from output size. Max
prompt size should only be used for the max input context to an LLM.

If required max_output_tokens should be set as a separate new field

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

@@ -79,7 +79,6 @@ def extract_questions_gemini(
         model_name=model,
         temperature=temperature,
         api_key=api_key,
-        max_tokens=max_tokens,
         model_kwargs=model_kwargs,
     )
 
@@ -218,5 +217,4 @@ def converse_gemini(
         api_key=api_key,
         system_prompt=system_prompt,
         completion_func=completion_func,
-        max_prompt_size=max_prompt_size,
     )

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

@@ -4,10 +4,7 @@ from threading import Thread
 
 import google.generativeai as genai
 from google.generativeai.types.answer_types import FinishReason
-from google.generativeai.types.generation_types import (
-    GenerateContentResponse,
-    StopCandidateException,
-)
+from google.generativeai.types.generation_types import StopCandidateException
 from google.generativeai.types.safety_types import (
     HarmBlockThreshold,
     HarmCategory,
@@ -26,7 +23,7 @@ from khoj.processor.conversation.utils import ThreadedGenerator
 logger = logging.getLogger(__name__)
 
 
-DEFAULT_MAX_TOKENS_GEMINI = 8192
+MAX_OUTPUT_TOKENS_GEMINI = 8192
 
 
 @retry(
@@ -36,13 +33,12 @@ DEFAULT_MAX_TOKENS_GEMINI = 8192
     reraise=True,
 )
 def gemini_completion_with_backoff(
-    messages, system_prompt, model_name, temperature=0, api_key=None, model_kwargs=None, max_tokens=None
+    messages, system_prompt, model_name, temperature=0, api_key=None, model_kwargs=None
 ) -> str:
     genai.configure(api_key=api_key)
-    max_tokens = max_tokens or DEFAULT_MAX_TOKENS_GEMINI
     model_kwargs = model_kwargs or dict()
     model_kwargs["temperature"] = temperature
-    model_kwargs["max_output_tokens"] = max_tokens
+    model_kwargs["max_output_tokens"] = MAX_OUTPUT_TOKENS_GEMINI
     model = genai.GenerativeModel(
         model_name,
         generation_config=model_kwargs,
@@ -88,28 +84,24 @@ def gemini_chat_completion_with_backoff(
     temperature,
     api_key,
     system_prompt,
-    max_prompt_size=None,
     completion_func=None,
     model_kwargs=None,
 ):
     g = ThreadedGenerator(compiled_references, online_results, completion_func=completion_func)
     t = Thread(
         target=gemini_llm_thread,
-        args=(g, messages, system_prompt, model_name, temperature, api_key, max_prompt_size, model_kwargs),
+        args=(g, messages, system_prompt, model_name, temperature, api_key, model_kwargs),
     )
     t.start()
     return g
 
 
-def gemini_llm_thread(
-    g, messages, system_prompt, model_name, temperature, api_key, max_prompt_size=None, model_kwargs=None
-):
+def gemini_llm_thread(g, messages, system_prompt, model_name, temperature, api_key, model_kwargs=None):
     try:
         genai.configure(api_key=api_key)
-        max_tokens = max_prompt_size or DEFAULT_MAX_TOKENS_GEMINI
         model_kwargs = model_kwargs or dict()
         model_kwargs["temperature"] = temperature
-        model_kwargs["max_output_tokens"] = max_tokens
+        model_kwargs["max_output_tokens"] = MAX_OUTPUT_TOKENS_GEMINI
         model_kwargs["stop_sequences"] = ["Notes:\n["]
         model = genai.GenerativeModel(
             model_name,