change the gemini model

agent_direct_llm_sections.py

@@ -31,17 +31,6 @@ except ImportError:
 
 
 
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 def configure_settings():
     """Configure LLM and embedding settings"""
     print("Configuring LLM (Google GenAI)...")
@@ -49,21 +38,11 @@ def configure_settings():
     Settings.embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")
     if not gemini_api_key:
         raise ValueError("GOOGLE_API_KEY environment variable not set! Required for Agent LLM.")
-    Settings.llm = GoogleGenAI(model_name="models/gemini-2.5-pro-latest", api_key=gemini_api_key)
+    Settings.llm = GoogleGenAI(model_name="models/gemini-2.0-flash", api_key=gemini_api_key)
     print(f"LLM for Agent: {Settings.llm.model}")
 
 
 
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 def query_section_directly(
     section_file_path: str,
     section_id_for_log: str, 
@@ -139,21 +118,6 @@ def query_section_directly(
 
 
 
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 def create_agent_instance():
     """Create and return an agent instance for API use"""
     # Section tool definitions
@@ -227,21 +191,6 @@ def create_agent_instance():
 
 
 
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     print("\n--- Creating Function Tools for API Agent ---")
     tools_list = []
     section_files_dir = Path(SECTION_FILES_PATH)
@@ -276,16 +225,16 @@ def create_agent_instance():
     # Add API tools if available
     if API_CALLERS_AVAILABLE:
         print("   Creating .NET API Tools...")
-        stats_api_tool = FunctionTool.from_defaults(
-            fn=get_vaccination_statistics,
-            name="get_vaccination_statistics_tool",
-            description=(
-                "Fetches current vaccination statistics for a specified Algerian Wilaya (province/state) "
-                "from an external API, such as coverage rates. "
-                "The input should be the name of the Wilaya (e.g., 'Algiers', 'Sétif')."
-            )
-        )
-        tools_list.append(stats_api_tool)
+        # stats_api_tool = FunctionTool.from_defaults(
+        #     fn=get_vaccination_statistics,
+        #     name="get_vaccination_statistics_tool",
+        #     description=(
+        #         "Fetches current vaccination statistics for a specified Algerian Wilaya (province/state) "
+        #         "from an external API, such as coverage rates. "
+        #         "The input should be the name of the Wilaya (e.g., 'Algiers', 'Sétif')."
+        #     )
+        # )
+      ##  tools_list.append(stats_api_tool)
 
         patient_record_api_tool = FunctionTool.from_defaults(
             fn=get_patient_vaccination_record,
@@ -297,18 +246,18 @@ def create_agent_instance():
         )
         tools_list.append(patient_record_api_tool)
 
-        image_retrieval_tool = FunctionTool.from_defaults(
-            fn=find_relevant_image_info,
-            name="image_retrieval_tool",
-            description=(
-                "Searches for and provides information about relevant images, figures, diagrams, or flowcharts "
-                "from the Algerian vaccination protocol document based on a textual description of the desired image. "
-                "Use this if the user asks for a specific figure (e.g., 'Figure 4.1'), an illustration of a concept "
-                "(e.g., 'diagram of cold chain levels'), or a visual representation."
-                "the input for the tool should be a description of the image (e.g., 'Figure 4.1', 'diagram of cold chain levels')."
-            )
-        )
-        tools_list.append(image_retrieval_tool)
+        # image_retrieval_tool = FunctionTool.from_defaults(
+        #     fn=find_relevant_image_info,
+        #     name="image_retrieval_tool",
+        #     description=(
+        #         "Searches for and provides information about relevant images, figures, diagrams, or flowcharts "
+        #         "from the Algerian vaccination protocol document based on a textual description of the desired image. "
+        #         "Use this if the user asks for a specific figure (e.g., 'Figure 4.1'), an illustration of a concept "
+        #         "(e.g., 'diagram of cold chain levels'), or a visual representation."
+        #         "the input for the tool should be a description of the image (e.g., 'Figure 4.1', 'diagram of cold chain levels')."
+        #     )
+        # )
+       ## tools_list.append(image_retrieval_tool)
 
     # Add WHO document tool if available
     who_doc_index_dir_name = "who_guidelines_index"
@@ -342,24 +291,6 @@ def create_agent_instance():
         raise Exception("No tools were created for the agent. Check file paths and tool definitions.")
 
 
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     # Create custom system prompt
     custom_system_prompt = f"""
     You are an expert assistant for Algerian vaccination protocols and related health data.
@@ -398,28 +329,6 @@ def create_agent_instance():
 
 
 
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 def run_direct_protocol_agent():
     """Original CLI function - kept for backward compatibility"""
     if not Path(SECTION_FILES_PATH).is_dir():
@@ -455,21 +364,6 @@ def run_direct_protocol_agent():
             traceback.print_exc()
 
 
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 # Add this function for the FastAPI to use
 def run_direct_protocol_agent_for_api():
     """This function was referenced in the original FastAPI but not needed for the simple version"""

api_callers.py

@@ -36,7 +36,6 @@ def get_vaccination_statistics(wilaya: str) -> str:
 
 
 
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 def get_patient_vaccination_record(patient_id: str) -> str:
     """
     Retrieves the vaccination record for a specific patient using their unique ID.

ingest_and_index_supplementary_doc.py

@@ -20,12 +20,6 @@ SUPPLEMENTARY_INDEXES_BASE_PATH_FOR_AGENT = "./storage/supplementary_indices"
 
 
 
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 def configure_indexing_settings():
     """Configures global Embedding model and optional LLM settings."""
 
@@ -37,7 +31,7 @@ def configure_indexing_settings():
 
     gemini_api_key = os.getenv("GOOGLE_API_KEY")
     if gemini_api_key:
-        Settings.llm = GoogleGenAI(model_name="models/gemini-1.5-flash-latest", api_key=gemini_api_key)
+        Settings.llm = GoogleGenAI(model_name="models/gemini-2.0-flash", api_key=gemini_api_key)
         print(f"LLM (Optional for indexing): {Settings.llm.model}")
     else:
         Settings.llm = None
@@ -45,20 +39,6 @@ def configure_indexing_settings():
 
 
 
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 def process_and_index_document(doc_file_path_str: str, index_persist_path_str: str):
     """
     Ingests a single document, creates a VectorStoreIndex (in memory first),
@@ -118,18 +98,6 @@ def process_and_index_document(doc_file_path_str: str, index_persist_path_str: s
 
 
 
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 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Ingest a single supplementary document and create its VectorStoreIndex.")
     parser.add_argument("document_path", help="Full path to the supplementary document file (e.g., PDF).")