Include the option of choosing Gemini LLMs

app.py

@@ -3,6 +3,8 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+import sys
+import time
 from dotenv import load_dotenv
 from smolagents import DuckDuckGoSearchTool, OpenAIServerModel, CodeAgent, Tool
 from blablador import Models
@@ -18,18 +20,43 @@ load_dotenv()
 
 class BasicAgent:
 
-    def __init__(self):
-        models = Models(api_key=os.getenv("Blablador_API_KEY")).get_model_ids()
-        model_id_blablador = 4
-        model_name = " ".join(
-            models[model_id_blablador].split(" - ")[1].split()[:2])
-        print("The agent uses the following model:", model_name)
-        answer_llm = OpenAIServerModel(
-            model_id=models[model_id_blablador],
-            api_base="https://helmholtz-blablador.fz-juelich.de:8000/v1",
-            api_key=os.getenv("Blablador_API_KEY"),
-            flatten_messages_as_text=True,
-            temperature=0.2)
+    def __init__(self, model_provider: str = "Blablador"):
+        self.model_provider = model_provider
+
+        if model_provider == "Blablador":
+
+            models = Models(
+                api_key=os.getenv("Blablador_API_KEY")).get_model_ids()
+            model_id_blablador = 5
+            model_name = " ".join(
+                models[model_id_blablador].split(" - ")[1].split()[:2])
+            print("The agent uses the following model:", model_name)
+
+            answer_llm = OpenAIServerModel(
+                model_id=models[model_id_blablador],
+                api_base="https://helmholtz-blablador.fz-juelich.de:8000/v1",
+                api_key=os.getenv("Blablador_API_KEY"),
+                flatten_messages_as_text=True,
+                temperature=0.2)
+
+        elif model_provider == "Gemini":
+
+            # model_name = "gemini-2.5-flash-preview-05-20"
+            model_name = "gemini-2.0-flash"
+            print("The agent uses the following model:", model_name)
+
+            answer_llm = OpenAIServerModel(
+                model_id=model_name,
+                api_base=
+                "https://generativelanguage.googleapis.com/v1beta/openai/",
+                api_key=os.getenv("Gemini_API_KEY2"),
+                temperature=0.2)
+        else:
+            print(
+                f"Error: Unsupported model provider '{model_provider}'. Only 'Blablador' and 'Gemini' are supported."
+            )
+            sys.exit(1)
+
         self.agent = CodeAgent(
             tools=[DuckDuckGoSearchTool()],
             model=answer_llm,
@@ -38,31 +65,113 @@ class BasicAgent:
             # verbosity_level=LogLevel.ERROR,
         )
 
-    def __call__(self, question: str) -> str:
+    def __call__(self,
+                 question: str,
+                 file_url: str = "",
+                 file_ext: str = "") -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
 
-        SYSTEM_PROMPT = "You are a general AI assistant. I will ask you a question. " \
-        "Report your thoughts, and finish your answer with the following template: " \
-        "FINAL ANSWER: [YOUR FINAL ANSWER]. " \
-        "YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. " \
-        "If you are asked for a number, don't use comma to write your number neither use units " \
-        "such as $ or percent sign unless specified otherwise. " \
-        "If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), " \
-        "and write the digits in plain text unless specified otherwise. " \
-        "If you are asked for a comma separated list, " \
-        "apply the above rules depending of whether the element to be put in the list is a number or a string."
-
-        # Combine system prompt with the user question
-        full_prompt = f"{SYSTEM_PROMPT}\n\nQuestion: {question}"
+        SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question. 
+        Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. 
+        YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. 
+        If you are asked for a number, don't use comma to write your number 
+        neither use units such as $ or percent sign unless specified otherwise. 
+        If you are asked for a string, don't use articles, neither ABBREVIATIONS, (e.g. for cities), 
+        and write the digits in plain text unless specified otherwise. 
+        If you are asked for a comma separated list, 
+        apply the above rules depending of whether the element to be put in the list is a number or a string.
+        """
+
+        # Prepare additional_args for file handling
+        additional_args = {}
+
+        # Handle file if provided
+        if file_url:
+            # print(f"Downloading file from: {file_url}")
+            # file_content = self._download_file(file_url, file_ext)
+
+            # if file_content is not None:
+            #     # Give the file a clear name based on its extension
+            #     if file_ext.lower() == 'csv':
+            #         # For CSV files, try to load as DataFrame
+            #         try:
+            #             import io
+            #             if isinstance(file_content, str):
+            #                 df = pd.read_csv(io.StringIO(file_content))
+            #             else:
+            #                 df = pd.read_csv(io.BytesIO(file_content))
+            #             additional_args['dataframe'] = df
+            #             additional_args['csv_file'] = file_content
+            #             print(f"Loaded CSV file with shape: {df.shape}")
+            #         except Exception as e:
+            #             print(f"Could not parse CSV file: {e}")
+            #             additional_args['file_content'] = file_content
+
+            #     elif file_ext.lower() in ['json']:
+            #         try:
+            #             import json
+            #             if isinstance(file_content, bytes):
+            #                 file_content = file_content.decode('utf-8')
+            #             json_data = json.loads(file_content)
+            #             additional_args['json_data'] = json_data
+            #             additional_args['file_content'] = file_content
+            #             print(f"Loaded JSON file")
+            #         except Exception as e:
+            #             print(f"Could not parse JSON file: {e}")
+            #             additional_args['file_content'] = file_content
+
+            #     else:
+            #         # For other file types, just pass the content
+            #         additional_args['file_content'] = file_content
+            #         if file_ext:
+            #             additional_args['file_extension'] = file_ext
+            #         print(f"Loaded {file_ext} file")
+
+            # Update the prompt to mention the file
+            # full_prompt = f"{SYSTEM_PROMPT}\n\nQuestion: {question}\n\nNote: A {file_ext} file has been provided and is available for your analysis."
+            additional_args = f"{file_url}_{file_ext}"
+            full_prompt = f"{SYSTEM_PROMPT}\n\nQuestion: {question}\n\nNote: A {file_ext} file has been provided and is available for your analysis."
+
+            # else:
+            # full_prompt = f"{SYSTEM_PROMPT}\n\nQuestion: {question}\n\nNote: Could not retrieve the file from {file_url}."
+        else:
+            full_prompt = f"{SYSTEM_PROMPT}\n\nQuestion: {question}"
+
+        # # Combine system prompt with the user question
+        # full_prompt = f"{SYSTEM_PROMPT}\n\nQuestion: {question}"
 
         try:
             answer = self.agent.run(full_prompt)
+            # answer = self.agent.run(
+            #     task=full_prompt,
+            #     additional_args=additional_args if additional_args else None)
             print(f"Agent returning answer: {answer}")
+            if self.model_provider == "Gemini":
+                time.sleep(10)
             return answer
         except Exception as e:
             print(f"Error running agent: {e}")
             return f"Error: {e}"
 
+    def _download_file(self, file_url: str, file_ext: str = "") -> str:
+        """Download file content from URL and return as text or bytes"""
+        try:
+            response = requests.get(file_url, timeout=30)
+            response.raise_for_status()
+
+            # For text files, return as string
+            if file_ext.lower() in [
+                    'txt', 'csv', 'json', 'md', 'py', 'js', 'html', 'xml'
+            ]:
+                return response.text
+            else:
+                # For binary files, return the content as bytes
+                return response.content
+
+        except Exception as e:
+            print(f"Error downloading file from {file_url}: {e}")
+            return None
+
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
@@ -86,7 +195,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = BasicAgent()
+        agent = BasicAgent("Blablador")
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
@@ -130,8 +239,13 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         file_ext = None
         file_url = None
 
+        if file_name:
+            file_ext = file_name.split('.')[-1].lower()
+            file_url = f"{api_url}/files/{task_id}"
+
         try:
             submitted_answer = agent(question_text)
+            # submitted_answer = agent(question_text, file_url, file_ext)
             answers_payload.append({
                 "task_id": task_id,
                 "submitted_answer": submitted_answer