Update configuration and enhance tool functionality

- Set API_BASE_URL, API_KEY_ENV_VAR, and MODEL_NAME in config.py
- Import ChatOllama in nodes.py and adjust model fetching logic
- Ignore type checking for process_questions in app.py
- Add langchain-ollama dependency in pyproject.toml and uv.lock
- Refactor tool imports in __init__.py and enhance message trimming in wikipedia.py

agent/config.py

@@ -1,12 +1,13 @@
 from typing import Literal
 
-#API_BASE_URL = "https://openrouter.ai/api/v1"
-#MODEL_NAME = "openai/gpt-oss-120b:floor"
-#API_KEY_ENV_VAR = "OPENROUTER_API_KEY"
+API_BASE_URL = "https://openrouter.ai/api/v1"
+API_KEY_ENV_VAR = "OPENROUTER_API_KEY"
+MODEL_NAME = "google/gemini-2.5-pro"
 
-API_BASE_URL = "https://api.openai.com/v1/"
-MODEL_NAME = "gpt-5"
-API_KEY_ENV_VAR = "OPENAI_API_KEY_ORACLEBOT"
+#API_BASE_URL = "https://api.openai.com/v1/"
+#MODEL_NAME = "gpt-5"
+#API_KEY_ENV_VAR = "OPENAI_API_KEY_ORACLEBOT"
+MAX_TOKENS = None
 
 MODEL_TEMPERATURE = 0.7
 

agent/nodes.py

@@ -9,6 +9,7 @@ from langchain_core.language_models.base import LanguageModelInput
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_openai import ChatOpenAI
 from langchain_deepseek import ChatDeepSeek
+from langchain_ollama import ChatOllama
 from pydantic import BaseModel, Field, SecretStr
 from agent.prompts import get_system_prompt
 from agent.state import State
@@ -17,8 +18,9 @@ from langgraph.prebuilt import ToolNode
 import backoff
 import openai
 import re
+from langchain_core.messages.utils import trim_messages, count_tokens_approximately
 
-from agent.config import API_BASE_URL, MODEL_NAME, API_KEY_ENV_VAR, MODEL_TEMPERATURE
+from agent.config import API_BASE_URL, MAX_TOKENS, MODEL_NAME, API_KEY_ENV_VAR, MODEL_TEMPERATURE
 
 from dotenv import load_dotenv
 load_dotenv()
@@ -39,6 +41,16 @@ def _get_model() -> BaseChatModel:
 
     api_key = os.getenv(API_KEY_ENV_VAR)
 
+    # return ChatOllama(
+    #     model=MODEL_NAME,
+    #     temperature=MODEL_TEMPERATURE if MODEL_TEMPERATURE else 0.0,
+    #     metadata={
+    #         "reasoning": {
+    #             "effort": "high"  # Use high reasoning effort
+    #         }
+    #     }
+    # )
+
     return ChatOpenAI(
         api_key=SecretStr(api_key) if api_key else None,
         base_url=API_BASE_URL,
@@ -68,12 +80,25 @@ def _bind_model(model: BaseChatModel) -> Runnable[LanguageModelInput, BaseMessag
 # Call model node
 @backoff.on_exception(
     backoff.runtime,
-    openai.RateLimitError,
+    (openai.RateLimitError, openai.InternalServerError),
     value=lambda e: float(match.group(1)) if (match := re.search(r'try again in (\d+(?:\.\d+)?)s', str(e))) else 10.0,
-    max_tries=20,
+    max_tries=200,
 )
+
 def call_model(state: State, config) -> dict[str, list[BaseMessage]]:
-    messages = state["messages"]
+    if MAX_TOKENS:
+        messages = trim_messages(
+            state["messages"],
+            strategy="last",
+            token_counter=count_tokens_approximately,
+            allow_partial=True,
+            max_tokens=MAX_TOKENS,
+            start_on="human",
+            end_on=("human", "tool"),
+        )
+    else:
+        messages = state["messages"]
+    
     app_name = config.get('configurable', {}).get("app_name", "OracleBot")
     
     # Add system prompt if not already present

app.py

@@ -119,7 +119,7 @@ async def run_and_submit_all( profile: gr.OAuthProfile | None):
     # Use the cache directory for this session
     working_dir = CACHE_DIR
 
-    results_log, answers_payload = await process_questions(agent, questions_data, working_dir)
+    results_log, answers_payload = await process_questions(agent, questions_data, working_dir) # type: ignore
 
     # Remove everything before "FINAL ANSWER: " in submitted answers
     for answer in answers_payload:

pyproject.toml

@@ -15,6 +15,7 @@ dependencies = [
     "langchain-community>=0.3.27",
     "langchain-deepseek>=0.1.4",
     "langchain-google-genai>=2.1.9",
+    "langchain-ollama>=0.3.6",
     "langchain-tavily>=0.2.11",
     "langchain[google-genai,googlegenai,openai]>=0.3.26",
     "langgraph>=0.4.8",

tools/__init__.py

@@ -1,8 +1,6 @@
 from .wikipedia import wiki_fetch_article, wiki_parse_html
 from .search import web_search
 from .code_interpreter import execute_code_multilang
-from .files import *
-from .calculator import *
 from langchain_core.tools import BaseTool
 from . import calculator, files
 
@@ -17,17 +15,14 @@ def get_all_tools() -> list[BaseTool]:
         wiki_fetch_article,
         wiki_parse_html,
         web_search,
-        execute_code_multilang,
+        #execute_code_multilang, # Disabled for the repo, enable at your own risk
     ]
     
-    # Automatically add all calculator functions
-    for name in calculator.__all__:
-        tools.append(getattr(calculator, name))
-    
-    # Automatically add all file management functions
-    for name in files.__all__:
-        tools.append(getattr(files, name))
+    # Automatically add all functions for the remaining tools
+    tools.extend([getattr(calculator, name) for name in calculator.__all__])    
+    tools.extend([getattr(files, name) for name in files.__all__])
 
+    #return [] # Disable all tools
     return tools
 
 def list_tools() -> str:

tools/wikipedia.py

@@ -2,6 +2,9 @@ from langchain_core.tools import tool
 import wikipediaapi
 import requests
 from bs4 import BeautifulSoup
+from langchain_core.messages.utils import count_tokens_approximately, trim_messages
+from langchain_core.messages import HumanMessage
+from agent.config import MAX_TOKENS
 
 @tool
 def wiki_fetch_article(article_title: str) -> str:
@@ -86,11 +89,34 @@ def wiki_parse_html(page_title: str, section_id: int | None = None) -> str:
 
             # Optional: collapse excessive whitespace
             text = str(soup)
-            return text
+
+            if MAX_TOKENS:
+                # Use trim_messages to fit max tokens
+                messages = [HumanMessage(content=text)]
+                trimmed_messages = trim_messages(
+                    messages,
+                    strategy="last",
+                    token_counter=count_tokens_approximately,
+                    allow_partial=True,
+                    max_tokens=MAX_TOKENS,
+                )
+            
+            return trimmed_messages[0].content if trimmed_messages else text
         except Exception as e:
             # Fallback to raw HTML if sanitization fails
-            return raw_html
-        
+            messages = [HumanMessage(content=raw_html)]
+
+            if MAX_TOKENS:
+                # Use trim_messages to fit max tokens
+                trimmed_messages = trim_messages(
+                    messages,
+                    strategy="last",
+                    token_counter=count_tokens_approximately,
+                    allow_partial=True,
+                    max_tokens=MAX_TOKENS,
+                )
+            return trimmed_messages[0].content if trimmed_messages else text
+
     except requests.RequestException as e:
         return f"Error fetching page: {str(e)}"
     except Exception as e:

uv.lock

@@ -1289,6 +1289,19 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/84/d8/e1162835d5d6eefaae341c2d1cf750ab53222a421252346905187e53b8a2/langchain_google_genai-2.1.9-py3-none-any.whl", hash = "sha256:8d3aab59706b8f8920a22bcfd63c5000ce430fe61db6ecdec262977d1a0be5b8", size = 49381, upload-time = "2025-08-04T18:51:50.51Z" },
 ]
 
+[[package]]
+name = "langchain-ollama"
+version = "0.3.6"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "langchain-core" },
+    { name = "ollama" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/82/67/93429a78d6fd40e2addf27e881db37e7f0076d712ffe9759ca0d5e10910e/langchain_ollama-0.3.6.tar.gz", hash = "sha256:4270c4b30b3f3d10850cb9a1183b8c77d616195e0d9717ac745ef7f7f6cc2b6e", size = 30479, upload-time = "2025-07-22T17:26:59.605Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/f3/c5/1e559f5b43d62850ea2b44097afc944f38894eac00e7feef3b42f0428916/langchain_ollama-0.3.6-py3-none-any.whl", hash = "sha256:b339bd3fcf913b8d606ad426ef39e7122695532507fcd85aa96271b3f33dc3df", size = 24535, upload-time = "2025-07-22T17:26:58.556Z" },
+]
+
 [[package]]
 name = "langchain-openai"
 version = "0.3.29"
@@ -1648,6 +1661,19 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/67/0e/35082d13c09c02c011cf21570543d202ad929d961c02a147493cb0c2bdf5/numpy-2.2.6-cp313-cp313t-win_amd64.whl", hash = "sha256:6031dd6dfecc0cf9f668681a37648373bddd6421fff6c66ec1624eed0180ee06", size = 12771374, upload-time = "2025-05-17T21:43:35.479Z" },
 ]
 
+[[package]]
+name = "ollama"
+version = "0.5.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "httpx" },
+    { name = "pydantic" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/91/6d/ae96027416dcc2e98c944c050c492789502d7d7c0b95a740f0bb39268632/ollama-0.5.3.tar.gz", hash = "sha256:40b6dff729df3b24e56d4042fd9d37e231cee8e528677e0d085413a1d6692394", size = 43331, upload-time = "2025-08-07T21:44:10.422Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/be/f6/2091e50b8b6c3e6901f6eab283d5efd66fb71c86ddb1b4d68766c3eeba0f/ollama-0.5.3-py3-none-any.whl", hash = "sha256:a8303b413d99a9043dbf77ebf11ced672396b59bec27e6d5db67c88f01b279d2", size = 13490, upload-time = "2025-08-07T21:44:09.353Z" },
+]
+
 [[package]]
 name = "openai"
 version = "1.99.6"
@@ -1851,6 +1877,7 @@ dependencies = [
     { name = "langchain-community" },
     { name = "langchain-deepseek" },
     { name = "langchain-google-genai" },
+    { name = "langchain-ollama" },
     { name = "langchain-tavily" },
     { name = "langgraph" },
     { name = "matplotlib" },
@@ -1887,6 +1914,7 @@ requires-dist = [
     { name = "langchain-community", specifier = ">=0.3.27" },
     { name = "langchain-deepseek", specifier = ">=0.1.4" },
     { name = "langchain-google-genai", specifier = ">=2.1.9" },
+    { name = "langchain-ollama", specifier = ">=0.3.6" },
     { name = "langchain-tavily", specifier = ">=0.2.11" },
     { name = "langgraph", specifier = ">=0.4.8" },
     { name = "matplotlib", specifier = ">=3.10.5" },