'[/] to change the OpenRouter model")
rprint(" âĸ Type [bold magenta]'reasoning'[/] to toggle reasoning visibility")
rprint(" âĸ Type [bold magenta]'clear'[/] to clear chat history\n")
-
+
while True:
try:
user_input = session.prompt("\nYou: ", style=style).strip()
-
- if user_input.lower() == 'quit':
+
+ if user_input.lower() == "quit":
print("\nGoodbye! đ")
break
- if user_input.lower() == 'clear':
+ if user_input.lower() == "clear":
chain.deepseek_messages = []
chain.openrouter_messages = []
rprint("\n[magenta]Chat history cleared![/]\n")
continue
-
- if user_input.lower().startswith('model '):
+
+ if user_input.lower().startswith("model "):
new_model = user_input[6:].strip()
chain.set_model(new_model)
print(f"\nChanged model to: {chain.get_model_display_name()}\n")
continue
- if user_input.lower() == 'reasoning':
+ if user_input.lower() == "reasoning":
chain.show_reasoning = not chain.show_reasoning
status = "visible" if chain.show_reasoning else "hidden"
rprint(f"\n[magenta]Reasoning process is now {status}[/]\n")
continue
-
+
reasoning = chain.get_deepseek_reasoning(user_input)
- openrouter_response = chain.get_openrouter_response(user_input, reasoning)
-
+ openrouter_response = chain.get_openrouter_response(user_input, reasoning) # noqa: F841
+
except KeyboardInterrupt:
continue
except EOFError:
break
+
if __name__ == "__main__":
- main()
\ No newline at end of file
+ main()
diff --git a/rat/ui.py b/rat/ui.py
new file mode 100644
index 0000000..011754c
--- /dev/null
+++ b/rat/ui.py
@@ -0,0 +1,348 @@
+import streamlit as st
+from utils.model_fetcher import (
+ get_top_weekly_models,
+)
+
+from rat import ModelChain
+
+# Initialize session state variables
+if "chain" not in st.session_state:
+ st.session_state.chain = ModelChain()
+if "messages" not in st.session_state:
+ st.session_state.messages = []
+if "show_reasoning" not in st.session_state:
+ st.session_state.show_reasoning = True
+if "top_models" not in st.session_state:
+ # Initialize with an empty list (models will be fetched on request)
+ st.session_state.top_models = []
+if "show_models_dropdown" not in st.session_state:
+ st.session_state.show_models_dropdown = False
+
+# Set up the page configuration
+st.set_page_config(
+ page_title="RAT - Retrieval Augmented Thinking",
+ layout="wide",
+ initial_sidebar_state="expanded",
+)
+
+# Page header
+st.title("RAT (Retrieval Augmented Thinking)")
+st.markdown("*Happy Hacking*")
+
+# Sidebar settings
+with st.sidebar:
+ # Collapsers for settings sections
+ with st.expander("đ ī¸ Model Settings", expanded=True):
+ # Display current model
+ current_model = st.session_state.chain.get_model_display_name()
+ st.markdown(f"**Current model:** `{current_model}`")
+
+ # Initialize values for syncing fields
+ if "manual_model" not in st.session_state:
+ st.session_state.manual_model = current_model
+ if "selected_dropdown_model" not in st.session_state:
+ st.session_state.selected_dropdown_model = None
+
+ # Function to get the full model name with provider if not present
+ def get_full_model_name(model_name):
+ """Adds a provider prefix to the model name if not present."""
+ if "/" not in model_name:
+ # List of known providers
+ providers = {
+ "gpt": "openai/",
+ "claude": "anthropic/",
+ "llama": "meta-llama/",
+ "gemini": "google/",
+ "deepseek": "deepseek/",
+ "mistral": "mistralai/",
+ "qwen": "qwen/",
+ }
+
+ # Try to determine the provider based on the start of the model name
+ for prefix, provider in providers.items():
+ if model_name.startswith(prefix):
+ return provider + model_name
+
+ # If provider is not determined, assume OpenAI by default
+ return "openai/" + model_name
+ return model_name
+
+ # Callback functions to handle changes
+ def on_manual_change():
+ # Update the model when the text field changes
+ new_model = st.session_state.manual_model_input
+ st.session_state.manual_model = new_model
+
+ def on_dropdown_change():
+ # Update the manual input when the dropdown value changes
+ if "dropdown_model" in st.session_state and st.session_state.dropdown_model:
+ selected_model = st.session_state.dropdown_model
+ # Get the full model name with provider
+ full_model_name = get_full_model_name(selected_model)
+ st.session_state.manual_model = full_model_name
+
+ st.markdown("##### Manual Model Selection")
+ # Use the session_state value for initial setup
+ manual_model_input = st.text_input(
+ "Enter model name:",
+ value=st.session_state.manual_model,
+ key="manual_model_input",
+ on_change=on_manual_change,
+ help="Type provider/model (e.g. openai/gpt-4o-mini)",
+ )
+
+ # Full-width button
+ if st.button(
+ "Apply Model", use_container_width=True, key="apply_btn", type="primary"
+ ):
+ model_to_apply = st.session_state.manual_model_input
+ # Check if provider is present
+ model_to_apply = get_full_model_name(model_to_apply)
+ st.session_state.chain.set_model(model_to_apply)
+ st.session_state.manual_model = model_to_apply
+ st.toast(f"Model changed to: {model_to_apply}", icon="â
")
+
+ st.divider() # Visual divider between manual input and automatic selection
+
+ st.markdown(
+ "##### Discover Models",
+ help="It may take 1-2 minutes because we parse the OpenRouter website ^_^",
+ )
+ # Button to get top models
+ if st.button(
+ "Get Top Weekly Models from OpenRouter",
+ use_container_width=True,
+ key="fetch_models_btn",
+ ):
+ with st.spinner("Fetching models..."):
+ st.session_state.top_models = get_top_weekly_models()
+ st.session_state.show_models_dropdown = True
+ st.toast(f"Found {len(st.session_state.top_models)} models!", icon="đ")
+
+ # Show dropdown only if models have been fetched
+ if st.session_state.show_models_dropdown and st.session_state.top_models:
+ st.caption("Available Top Models")
+
+ # Dropdown with top models in a compact view
+ dropdown_model = st.selectbox(
+ "Select a model:",
+ options=st.session_state.top_models,
+ index=0 if st.session_state.top_models else None,
+ key="dropdown_model",
+ on_change=on_dropdown_change,
+ label_visibility="collapsed",
+ )
+
+ # Button to choose model
+ if st.button(
+ "Use Selected Model",
+ use_container_width=True,
+ key="use_selected_btn",
+ type="primary",
+ ):
+ selected_model = st.session_state.dropdown_model
+ # Get the full model name with provider
+ full_model_name = get_full_model_name(selected_model)
+ st.session_state.chain.set_model(full_model_name)
+ st.session_state.manual_model = (
+ full_model_name # Update for subsequent renders
+ )
+ st.toast(f"Model changed to: {full_model_name}", icon="â
")
+ st.rerun() # Rerun the app to update all fields
+
+ # Second expander for interface settings
+ with st.expander("âī¸ Interface Settings", expanded=True):
+ # Toggle reasoning visibility with a checkbox
+ st.session_state.show_reasoning = st.checkbox(
+ "Show Reasoning Process",
+ value=st.session_state.show_reasoning,
+ help="Toggle visibility of the detailed reasoning process",
+ )
+ st.session_state.chain.show_reasoning = st.session_state.show_reasoning
+
+ # Button to clear chat history
+ if st.button("Clear Chat History", use_container_width=True, type="secondary"):
+ st.session_state.chain.deepseek_messages = []
+ st.session_state.chain.openrouter_messages = []
+ st.session_state.messages = []
+ st.toast("Chat history cleared!", icon="đī¸")
+ st.rerun()
+
+ # Help information (outside the settings sections)
+ with st.expander("âšī¸ About RAT", expanded=False):
+ st.markdown(
+ """
+**Retrieval Augmented Thinking (RAT)** enhances responses through a two-phase process:
+
+1. **Reasoning Phase**: DeepSeek builds detailed reasoning
+2. **Response Phase**: OpenRouter generates the polished answer
+
+### Using RAT
+
+* **Model Selection**:
+ * Enter model name manually with provider (e.g., `openai/gpt-4o-mini`)
+ * Or fetch top weekly models from OpenRouter (parsing may take 1-2 min)
+ * Models are automatically formatted with correct provider prefix
+
+* **Interface Features**:
+ * Toggle reasoning visibility to see detailed thinking process
+ * Token tracking for every response (input, reasoning, output)
+ * Conversation history with model and token usage metrics
+
+RAT provides transparency by showing exactly which model answered your question and how many tokens were used at each step of the process.
+ """
+ )
+
+ # Add a divider before author information
+ st.divider()
+
+ st.markdown(
+ """
+
+ """,
+ unsafe_allow_html=True,
+ )
+
+
+# Display chat messages
+chat_container = st.container()
+with chat_container:
+ # Display all messages in the chat history
+ for message in st.session_state.messages:
+ if message["role"] == "user":
+ with st.chat_message("user"):
+ st.markdown(message["content"])
+ else:
+ with st.chat_message("assistant"):
+ st.markdown(message["final_answer"])
+
+ # Display metadata for previous messages
+ if "model" in message and "tokens" in message:
+ model = message["model"]
+ model_name = model.split("/")[-1] if "/" in model else model
+ provider = model.split("/")[0] if "/" in model else ""
+ tokens = message["tokens"]
+
+ metadata_html = f"""
+
+ {model_name}
+ {f"({provider})" if provider else ""}
+
+ {tokens['total']} tokens
+
+ (in: {tokens['input']} | reason: {tokens['reasoning']} | out: {tokens['response']})
+
+
+
+ """
+ st.markdown(metadata_html, unsafe_allow_html=True)
+
+ # Show reasoning if it exists and the checkbox is checked
+ if (
+ "reasoning" in message
+ and message["reasoning"]
+ and st.session_state.show_reasoning
+ ):
+ with st.expander("Reasoning Process", expanded=False):
+ st.markdown(message["reasoning"])
+
+# Chat input at the bottom
+user_query = st.chat_input("Ask a question...")
+
+# Process user input when submitted
+if user_query:
+ # Add user message to chat history
+ st.session_state.messages.append({"role": "user", "content": user_query})
+
+ # Display the user message
+ with st.chat_message("user"):
+ st.markdown(user_query)
+
+ # Display assistant response with streaming
+ with st.chat_message("assistant"):
+ # Create placeholders for content
+ answer_container = st.empty()
+ metadata_container = st.container()
+
+ # Stream the reasoning process
+ reasoning_text = ""
+ reasoning_expander = None
+
+ if st.session_state.show_reasoning:
+ reasoning_expander = st.expander("Reasoning Process", expanded=True)
+
+ with st.spinner("Thinking..."):
+ reasoning_placeholder = None
+ if st.session_state.show_reasoning and reasoning_expander:
+ with reasoning_expander:
+ reasoning_placeholder = st.empty()
+
+ for chunk in st.session_state.chain.get_deepseek_reasoning_stream(
+ user_query
+ ):
+ reasoning_text += chunk
+ if reasoning_placeholder:
+ reasoning_placeholder.markdown(reasoning_text)
+
+ # Stream the final answer
+ answer_text = ""
+ with st.spinner("Generating response..."):
+ for chunk in st.session_state.chain.get_openrouter_response_stream(
+ user_query, reasoning_text
+ ):
+ answer_text += chunk
+ answer_container.markdown(answer_text)
+
+ # Retrieve metadata
+ current_model = st.session_state.chain.get_model_display_name()
+ model_name = (
+ current_model.split("/")[-1] if "/" in current_model else current_model
+ )
+ provider = current_model.split("/")[0] if "/" in current_model else ""
+
+ input_tokens = st.session_state.chain.last_input_tokens
+ reasoning_tokens = st.session_state.chain.last_reasoning_tokens
+ response_tokens = st.session_state.chain.last_response_tokens
+ total_tokens = st.session_state.chain.last_total_tokens
+
+ # Display combined metadata
+ with metadata_container:
+ metadata_html = f"""
+
+ {model_name}
+ {f"({provider})" if provider else ""}
+
+ {total_tokens} tokens
+
+ (in: {input_tokens} | reason: {reasoning_tokens} | out: {response_tokens})
+
+
+
+ """
+ st.markdown(metadata_html, unsafe_allow_html=True)
+
+ # Save complete response to session state
+ st.session_state.messages.append(
+ {
+ "role": "assistant",
+ "reasoning": reasoning_text,
+ "final_answer": answer_text,
+ "model": current_model,
+ "tokens": {
+ "input": input_tokens,
+ "reasoning": reasoning_tokens,
+ "response": response_tokens,
+ "total": total_tokens,
+ },
+ }
+ )
diff --git a/rat/utils/model_cache.json b/rat/utils/model_cache.json
new file mode 100644
index 0000000..84e3ccf
--- /dev/null
+++ b/rat/utils/model_cache.json
@@ -0,0 +1 @@
+{"timestamp": 1743394112.093972, "models": ["gemini-flash-1.5", "deepseek-r1-distill-llama-70b", "llama-3.3-70b-instruct", "deepseek-chat-v3-0324", "gemini-2.5-pro-exp-03-25:free", "deepseek-r1:free", "llama-3.1-70b-instruct", "mistral-7b-instruct", "mistral-nemo", "qwen-2.5-7b-instruct", "gemini-2.0-flash-lite-001", "gemini-2.0-flash-exp:free", "llama-3.1-8b-instruct", "gemini-flash-1.5-8b", "mistral-small-24b-instruct-2501", "wizardlm-2-8x22b", "gpt-4o-mini", "deepseek-r1", "gemini-2.0-flash-001", "gemini-2.0-pro-exp-02-05:free"]}
\ No newline at end of file
diff --git a/rat/utils/model_fetcher.py b/rat/utils/model_fetcher.py
new file mode 100644
index 0000000..4a3c9a4
--- /dev/null
+++ b/rat/utils/model_fetcher.py
@@ -0,0 +1,144 @@
+import os
+import json
+import time
+from urllib.parse import urljoin
+
+from selenium import webdriver
+from selenium.webdriver.common.by import By
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.chrome.options import Options
+
+CACHE_FILE = os.path.join(
+ os.path.dirname(os.path.abspath(__file__)), "model_cache.json"
+)
+CACHE_EXPIRY = 24 * 60 * 60
+
+
+def get_top_weekly_models(model_count=20):
+ """
+ Retrieves a list of the top models of the week from OpenRouter using caching.
+
+ Args:
+ model_count (int): The number of models to retrieve (default is 20).
+
+ Returns:
+ list: A list of model names.
+ """
+ if os.path.exists(CACHE_FILE):
+ try:
+ with open(CACHE_FILE, "r") as f:
+ cache_data = json.load(f)
+ if time.time() - cache_data["timestamp"] < CACHE_EXPIRY:
+ return cache_data["models"]
+ except json.JSONDecodeError:
+ # if file does not exists or broken
+ pass
+
+ models = fetch_top_models_from_openrouter(model_count)
+
+ cache_data = {"timestamp": time.time(), "models": models}
+ with open(CACHE_FILE, "w") as f:
+ json.dump(cache_data, f)
+
+ return models
+
+
+def fetch_top_models_from_openrouter(model_count=20):
+ """
+ Parses the OpenRouter page to retrieve the top models of the week.
+ The script scrolls the page down incrementally until the desired number of models is loaded.
+
+ Args:
+ model_count (int): The number of models to retrieve (default is 20).
+
+ Returns:
+ list: A list of model identifiers.
+ """
+
+ chrome_options = Options()
+ chrome_options.add_argument("--headless")
+ chrome_options.add_argument("--disable-gpu")
+ chrome_options.add_argument("--no-sandbox")
+ chrome_options.add_argument("--disable-dev-shm-usage")
+ driver = webdriver.Chrome(options=chrome_options)
+ models = []
+ base_url = "https://openrouter.ai"
+
+ try:
+ start_url = urljoin(base_url, "/models?order=top-weekly")
+
+ driver.get(start_url)
+ wait = WebDriverWait(driver, 10)
+
+ wait.until(
+ EC.presence_of_element_located(
+ (By.XPATH, "//li[contains(@class, 'group')]")
+ )
+ )
+
+ collected_links = set()
+ max_scroll_attempts = 20
+ scroll_step = 1000
+
+ for attempt in range(max_scroll_attempts):
+
+ driver.execute_script("window.scrollBy(0, arguments[0]);", scroll_step)
+ time.sleep(1)
+
+ model_link_elements = driver.find_elements(
+ By.XPATH,
+ "//a[contains(@class, 'transition-colors') and ("
+ "starts-with(@href, '/google/') or starts-with(@href, '/meta-llama/') or "
+ "starts-with(@href, '/openai/') or starts-with(@href, '/anthropic/') or "
+ "starts-with(@href, '/deepseek/') or starts-with(@href, '/mistralai/') or "
+ "starts-with(@href, '/qwen/') or starts-with(@href, '/microsoft/'))]",
+ )
+
+ for elem in model_link_elements:
+ href = urljoin(base_url, elem.get_attribute("href"))
+ collected_links.add(href)
+
+ if len(collected_links) >= model_count:
+
+ break
+
+ hrefs = list(collected_links)[:model_count]
+
+ for href in hrefs:
+
+ try:
+ driver.get(href)
+ except Exception:
+ continue
+
+ try:
+
+ h3_elem = wait.until(
+ EC.presence_of_element_located(
+ (By.XPATH, "//h3[@title='Model identifier for use in the API']")
+ )
+ )
+ except Exception:
+ continue
+
+ text = h3_elem.text.strip()
+
+ if "/" in text:
+ model_name = text.split("/", 1)[1].strip()
+
+ models.append(model_name)
+
+ time.sleep(1)
+
+ finally:
+ driver.quit()
+
+ return models
+
+
+if __name__ == "__main__":
+ models = get_top_weekly_models()
+ print("Top OpenRouter Models:")
+ for model in models:
+ print(f"- {model}")
diff --git a/rat/utils/token_counter.py b/rat/utils/token_counter.py
new file mode 100644
index 0000000..cbcb9ba
--- /dev/null
+++ b/rat/utils/token_counter.py
@@ -0,0 +1,26 @@
+import tiktoken
+
+def get_token_count(text, model=None):
+ """
+ Counts the number of tokens in the text for the specified model.
+
+ Args:
+ text: The text to count tokens from.
+ model: The name of the model (if None, a universal encoder is used).
+
+ Returns:
+ int: The number of tokens.
+ """
+ if not text:
+ return 0
+
+ try:
+ encoding = tiktoken.get_encoding("cl100k_base")
+ tokens = encoding.encode(text)
+ return len(tokens)
+
+ except Exception as e:
+ print(f"Error counting tokens: {e}")
+ # if there is an error, we will estimate approximate amout of tokens
+ # (4 symbols in 1 token)
+ return len(text) // 4
\ No newline at end of file
diff --git a/uv.lock b/uv.lock
index 0828829..974b3dd 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,26 @@
version = 1
+revision = 1
requires-python = ">=3.11"
+resolution-markers = [
+ "python_full_version >= '3.12'",
+ "python_full_version < '3.12'",
+]
+
+[[package]]
+name = "altair"
+version = "5.5.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+ { name = "jinja2" },
+ { name = "jsonschema" },
+ { name = "narwhals" },
+ { name = "packaging" },
+ { name = "typing-extensions", marker = "python_full_version < '3.14'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/16/b1/f2969c7bdb8ad8bbdda031687defdce2c19afba2aa2c8e1d2a17f78376d8/altair-5.5.0.tar.gz", hash = "sha256:d960ebe6178c56de3855a68c47b516be38640b73fb3b5111c2a9ca90546dd73d", size = 705305 }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/aa/f3/0b6ced594e51cc95d8c1fc1640d3623770d01e4969d29c0bd09945fafefa/altair-5.5.0-py3-none-any.whl", hash = "sha256:91a310b926508d560fe0148d02a194f38b824122641ef528113d029fcd129f8c", size = 731200 },
+]
[[package]]
name = "annotated-types"
@@ -42,6 +63,33 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/46/eb/e7f063ad1fec6b3178a3cd82d1a3c4de82cccf283fc42746168188e1cdd5/anyio-4.8.0-py3-none-any.whl", hash = "sha256:b5011f270ab5eb0abf13385f851315585cc37ef330dd88e27ec3d34d651fd47a", size = 96041 },
]
+[[package]]
+name = "attrs"
+version = "25.3.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/5a/b0/1367933a8532ee6ff8d63537de4f1177af4bff9f3e829baf7331f595bb24/attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b", size = 812032 }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/77/06/bb80f5f86020c4551da315d78b3ab75e8228f89f0162f2c3a819e407941a/attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3", size = 63815 },
+]
+
+[[package]]
+name = "blinker"
+version = "1.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/21/28/9b3f50ce0e048515135495f198351908d99540d69bfdc8c1d15b73dc55ce/blinker-1.9.0.tar.gz", hash = "sha256:b4ce2265a7abece45e7cc896e98dbebe6cead56bcf805a3d23136d145f5445bf", size = 22460 }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/10/cb/f2ad4230dc2eb1a74edf38f1a38b9b52277f75bef262d8908e60d957e13c/blinker-1.9.0-py3-none-any.whl", hash = "sha256:ba0efaa9080b619ff2f3459d1d500c57bddea4a6b424b60a91141db6fd2f08bc", size = 8458 },
+]
+
+[[package]]
+name = "cachetools"
+version = "5.5.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/6c/81/3747dad6b14fa2cf53fcf10548cf5aea6913e96fab41a3c198676f8948a5/cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4", size = 28380 }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/72/76/20fa66124dbe6be5cafeb312ece67de6b61dd91a0247d1ea13db4ebb33c2/cachetools-5.5.2-py3-none-any.whl", hash = "sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a", size = 10080 },
+]
+
[[package]]
name = "certifi"
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