cookies.txt

agents/advanced_validation_agent.py

@@ -53,7 +53,7 @@ def cross_reference_check(claim: str, sources_content: List[Dict[str, str]]) ->
 
     results = []
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using cross-referencing LLM: {llm_model}")
 
         for i, source in enumerate(sources_content):
@@ -138,7 +138,7 @@ def logical_consistency_check(text: str) -> Dict[str, Union[bool, str, List[str]
     )
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using consistency check LLM: {llm_model}")
         response = llm.complete(prompt)
         
@@ -203,7 +203,7 @@ def bias_detection(text: str, source_context: Optional[str] = None) -> Dict[str,
     )
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using bias detection LLM: {llm_model}")
         response = llm.complete(prompt)
         
@@ -308,7 +308,7 @@ def initialize_advanced_validation_agent() -> ReActAgent:
         raise ValueError("GEMINI_API_KEY must be set for AdvancedValidationAgent")
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using agent LLM: {agent_llm_model}")
 
         # Load system prompt

agents/long_context_management_agent.py

@@ -135,7 +135,7 @@ def summarize_long_context(detail_level: Literal["brief", "standard", "detailed"
     )
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using summarization LLM: {llm_model}")
         response = llm.complete(prompt)
         summary = response.text.strip()
@@ -315,7 +315,7 @@ def initialize_long_context_management_agent() -> ReActAgent:
         raise ValueError("GEMINI_API_KEY must be set for LongContextManagementAgent")
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using agent LLM: {agent_llm_model}")
         Settings.llm = llm # Set default LLM for LlamaIndex components used by tools
 

agents/math_agent.py

@@ -668,6 +668,8 @@ def initialize_math_agent() -> ReActAgent:
         - Clearly state which tool you are using and why.
         - Handle potential errors gracefully and report them if they prevent finding a solution.
         - Pay close attention to input formats required by each tool (e.g., lists for vectors/matrices, strings for symbolic expressions).
+        
+        If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.
         """
 
         agent = ReActAgent(

agents/planner_agent.py

@@ -57,7 +57,7 @@ def plan(objective: str) -> List[str]:
     )
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using planning LLM: {planner_llm_model}")
         response = llm.complete(input_prompt)
         
@@ -131,7 +131,7 @@ def synthesize_and_report(results: List[Dict[str, str]]) -> str:
     """
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using synthesis LLM: {synthesizer_llm_model}")
         response = llm.complete(input_prompt)
         logger.info("Synthesis successful.")
@@ -180,7 +180,7 @@ def answer_question(question: str) -> str:
     )
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using answer LLM: {model_name}")
         response = llm.complete(assistant_prompt)
         logger.info("Answer generated successfully.")
@@ -232,7 +232,7 @@ def initialize_planner_agent() -> ReActAgent:
         raise ValueError("GEMINI_API_KEY must be set for PlannerAgent")
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using agent LLM: {agent_llm_model}")
 
         # Load system prompt

agents/reasoning_agent.py

@@ -124,7 +124,7 @@ def answer_question(question: str) -> str:
     )
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using answer LLM: {model_name}")
         response = llm.complete(assistant_prompt)
         logger.info("Answer generated successfully.")
@@ -167,7 +167,7 @@ def initialize_reasoning_agent() -> ReActAgent:
         raise ValueError("GEMINI_API_KEY must be set for ReasoningAgent")
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using agent LLM: {agent_llm_model}")
 
         # Load system prompt

agents/research_agent.py

@@ -571,7 +571,7 @@ async def answer_question(ctx: Context, question: str) -> str:
     )
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using answer LLM: {model_name}")
         response = llm.complete(assistant_prompt)
         logger.info("Answer generated successfully.")
@@ -640,7 +640,7 @@ class ResearchAgentInitializer:
             logger.error("GEMINI_API_KEY not found for ResearchAgent LLM.")
             raise ValueError("GEMINI_API_KEY must be set for ResearchAgent")
         try:
-            self.llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+            self.llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
             logger.info(f"ResearchAgent LLM initialized: {agent_llm_model}")
         except Exception as e:
             logger.error(f"Failed to initialize ResearchAgent LLM: {e}", exc_info=True)
@@ -1006,6 +1006,8 @@ class ResearchAgentInitializer:
         - reasoning_agent: multi‑hop logical reasoning.
 
         Do not delegate to any agent outside this list.
+        
+        If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.
         """
 
         agent = ReActAgent(

agents/synthesis_agent.py

@@ -109,6 +109,8 @@ Allowed targets when more work required:
   • research_agent             – missing data
   • reasoning_agent            – reconcile complex logic
   • long_context_management_agent – compress oversized context before answer
+  
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.
 """
 
 # -----------------------------------------------------------------------------

agents/text_analyzer_agent.py

@@ -62,7 +62,7 @@ def summarize_text(text: str, max_length: int = 150, min_length: int = 30) -> st
     )
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using summarization LLM: {summarizer_llm_model}")
         response = llm.complete(prompt)
         summary = response.text.strip()
@@ -197,7 +197,7 @@ def initialize_text_analyzer_agent() -> ReActAgent:
         raise ValueError("GEMINI_API_KEY must be set for TextAnalyzerAgent")
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info(f"Using agent LLM: {agent_llm_model}")
 
         # Load system prompt

agents/video_analyzer_agent.py

@@ -185,7 +185,7 @@ def download_video_and_analyze(video_url: str) -> str:
             blocks.append(ImageBlock(path=frame_path))
 
 
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info("Using LLM model: %s", llm_model_name)
         response = llm.chat([ChatMessage(role="user", blocks=blocks)])
 
@@ -331,7 +331,7 @@ def initialize_video_analyzer_agent() -> FunctionAgent:
         raise ValueError("GEMINI_API_KEY must be set")
 
     try:
-        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05, max_tokens=8192)
+        llm = GoogleGenAI(api_key=gemini_api_key, model="gemini-2.5-pro-preview-03-25", temperature=0.05)
         logger.info("Using LLM model: %s", llm_model_name)
 
         system_prompt = """
@@ -392,6 +392,10 @@ def initialize_video_analyzer_agent() -> FunctionAgent:
         - Good: “At 02:15 the speaker shows a slide titled ‘Transformer Architecture’.”  
         - Bad:  “There is some sort of diagram that maybe explains something about the
                  architecture; it might be a transformer but it is hard to tell.”
+                 
+        If your response exceeds the maximum token limit and cannot be completed in a single reply, 
+        please conclude your output with the marker [CONTINUE]. In subsequent interactions, 
+        I will prompt you with “continue” to receive the next portion of the response.
         
         End of prompt.
         """

prompts/advanced_validation_agent_prompt.txt

@@ -29,3 +29,5 @@ You are AdvancedValidationAgent, a specialized agent focused on rigorously evalu
 *   Prioritize accuracy and objectivity in your assessment.
 *   Handoff to `research_agent` if external web searching is required for fact-checking beyond provided sources.
 
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.
+

prompts/code_gen_prompt.txt

@@ -49,6 +49,8 @@ Notes:
         youtube-transcript-api>=1.0.3,
         yt-dlp>=2025.3.31
 
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.
+
 Prompt: {prompt}
 
 Code:

prompts/figure_interpretation_agent_prompt.txt

@@ -27,3 +27,4 @@ You are FigureInterpretationAgent, a specialized agent designed to analyze and i
 *   Base interpretations strictly on the visual information present in the image.
 *   Requires multimodal input capabilities to process the image file.
 
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.

prompts/image_analyzer_prompt.txt

@@ -67,3 +67,4 @@ You are ImageAnalyzerAgent, an expert in cold, factual visual analysis. Your sol
 By adhering to these instructions, ensure your visual analysis is cold, factual, comprehensive, and
 completely devoid of subjectivity before handing off.
 
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.

prompts/long_context_management_agent_prompt.txt

@@ -26,3 +26,4 @@ You are LongContextManagementAgent, a specialized agent responsible for handling
 *   Handle potentially very large inputs efficiently (consider chunking, indexing).
 *   Clearly indicate if requested information cannot be found within the provided context.
 
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.

prompts/planner_agent_prompt.txt

@@ -40,4 +40,6 @@ Only the following agents are available: **code_agent**, **research_agent**, **m
 Do **not** invoke any other agents (e.g., **chess_agent**, **educate_agent**, **game_agent**, etc.).
 
 **Finalize**
-After all sub-questions have been addressed, by hand-off or self-answer, and the plan has passed **advanced_validation_agent**, compile and present the ultimate, coherent solution using the `answer_question` tool, ensuring your final response follows the required format and includes your chain of thought.
+After all sub-questions have been addressed, by hand-off or self-answer, and the plan has passed **advanced_validation_agent**, compile and present the ultimate, coherent solution using the `answer_question` tool, ensuring your final response follows the required format and includes your chain of thought.
+
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.

prompts/reasoning_agent_prompt.txt

@@ -21,3 +21,4 @@ You are **ReasoningAgent**, an advanced cognitive engine specialized in rigorous
 - No direct access to external data sources or the internet; all inference happens via the provided tools.
 - Do not skip any step: reasoning → planning → validation → (if approved) final answer.
 
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.

prompts/text_analyzer_prompt.txt

@@ -41,3 +41,4 @@ You are TextAnalyzerAgent, an expert text‐analysis assistant. On each request
 
 Follow this Thought→Action→Observation→… cycle rigorously to produce consistent, reliable analyses.
 
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.

prompts/video_analyzer_prompt.txt

@@ -83,3 +83,4 @@ You are **VideoAnalyzerAgent**, an expert in cold, factual **audiovisual** analy
 
 By adhering to these instructions, ensure your audiovisual analysis is cold, factual, comprehensive, and completely devoid of subjectivity before handing off.
 
+If your response exceeds the maximum token limit and cannot be completed in a single reply, please conclude your output with the marker [CONTINUE]. In subsequent interactions, I will prompt you with “continue” to receive the next portion of the response.