chore: Add vehicle status functionality and update skills package

car_assistant_slim.ipynb

@@ -19,8 +19,6 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n",
       "/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/transformers/utils/generic.py:441: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
       "  _torch_pytree._register_pytree_node(\n",
       "/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/transformers/utils/generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",

car_assistant_text.ipynb

@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {
     "collapsed": true,
     "id": "oOnNfKjX4IAV"
@@ -116,7 +116,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -128,7 +128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -137,7 +137,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -153,7 +153,7 @@
        "'Dry run successful'"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -171,7 +171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -710,7 +710,7 @@
    "source": [
     "import langchain\n",
     "langchain.debug=False\n",
-    "from skills import get_weather, find_route, get_forecast"
+    "from skills import get_weather, find_route, get_forecast, vehicle_status, vehicle"
    ]
   },
   {
@@ -777,14 +777,10 @@
     "tools = [\n",
     "    StructuredTool.from_function(get_weather),\n",
     "    StructuredTool.from_function(find_route),\n",
+    "    StructuredTool.from_function(vehicle_status),\n",
     "]"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": 5,
@@ -796,47 +792,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
-    "RAVEN_PROMPT_FUNC = \"\"\"You are a useful AI assistant in a car, that follows instructions extremely well. Help as much as you can. Answer questions concisely and do not mention what you base your reply on.\n",
-    "{raven_tools}\n",
+    "RAVEN_PROMPT_FUNC = \"\"\"You are a helpful AI assistant in a car (vehicle), that follows instructions extremely well. You are aware of car's location through status information and take that into account before responding. Answer questions concisely and do not mention what you base your reply on.\"\n",
     "\n",
-    "Current status of the vehicle:\n",
-    "{status}\n",
+    "{raven_tools}\n",
     "\n",
     "Previous conversation history:\n",
     "{history}\n",
     "\n",
-    "User Query: Question: {input}\n",
-    "\n",
-    "If it helps to answer the question please pick a function from the above options that best answers the user query and fill in the appropriate arguments.<human_end>\"\"\"\n",
+    "User Query: Question: {input}<human_end>\n",
+    "\"\"\"\n",
     "\n",
     "RAVEN_PROMPT_ANS = \"\"\"\n",
     "<human>\n",
     "You are a useful AI assistant in a car, that follows instructions extremely well. Help as much as you can. Answer questions concisely and do not mention what you base your reply on.\n",
     "\n",
-    "Current status of the vehicle:\n",
-    "{status}\n",
-    "\n",
     "Previous conversation history:\n",
     "{history}\n",
     "\n",
-    "User Query: Question: {input}\n",
-    "\n",
     "Observation:{observation}\n",
     "\n",
-    "Please respond in natural language. Do not refer to the provided context in your response.<human_end>\n",
+    "User Query: Question: {input}\n",
+    "\n",
+    "Please respond in natural language. Do not refer to the provided context and observation in your response.<human_end>\n",
     "\n",
     "Answer: \"\"\"\n",
     "\n",
     "\n",
-    "STATUS_TEMPLATE = \"\"\"\n",
-    "car coordinates: lat:{lat}, lon:{lon}\n",
-    "current time: {time}\n",
-    "current date: {date}\n",
-    "destination: {destination}\n",
+    "STATUS_TEMPLATE = \"\"\"We are at these geo coordinates: lat:{lat}, lon:{lon}, current time: {time}, current date: {date} and our destination is: {destination}\n",
     "\"\"\"\n",
     "status_prompt = PromptTemplate.from_template(STATUS_TEMPLATE)\n",
     "\n",
@@ -862,13 +848,13 @@
     "            pp = self.template_ans.format(**kwargs).replace(\"{{\", \"{\").replace(\"}}\", \"}\")\n",
     "            return pp\n",
     "\n",
-    "        if \"status\" in kwargs:\n",
-    "            kwargs[\"status\"] = self.status_prompt.format(**kwargs[\"status\"])\n",
+    "        # if \"status\" in kwargs:\n",
+    "        #     kwargs[\"status\"] = self.status_prompt.format(**kwargs[\"status\"])\n",
     "\n",
     "        prompt = \"<human>:\\n\"\n",
     "        for tool in self.tools:\n",
     "            func_signature, func_docstring = tool.description.split(\" - \", 1)\n",
-    "            prompt += f'\\Function:\\n<func_start>def {func_signature}<func_end>\\n<docstring_start>\\n\"\"\"\\n{func_docstring}\\n\"\"\"\\n<docstring_end>\\n'\n",
+    "            prompt += f'Function:\\n<func_start>def {func_signature}<func_end>\\n<docstring_start>\\n\"\"\"\\n{func_docstring}\\n\"\"\"\\n<docstring_end>\\n'\n",
     "        kwargs[\"raven_tools\"] = prompt\n",
     "        pp = self.template_func.format(**kwargs).replace(\"{{\", \"{\").replace(\"}}\", \"}\")\n",
     "        return pp\n",
@@ -879,13 +865,13 @@
     "    template_ans=RAVEN_PROMPT_ANS,\n",
     "    status_prompt=status_prompt,\n",
     "    tools=tools,\n",
-    "    input_variables=[\"input\", \"status\", \"history\", \"intermediate_steps\"],\n",
+    "    input_variables=[\"input\", \"history\", \"intermediate_steps\"],\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -895,7 +881,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -916,7 +902,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -925,18 +911,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "AgentExecutor(memory=ConversationBufferWindowMemory(input_key='input', k=2), verbose=True, agent=LLMSingleActionAgent(llm_chain=LLMChain(prompt=RavenPromptTemplate(input_variables=['input', 'status', 'history', 'intermediate_steps'], template_func='You are a useful AI assistant in a car, that follows instructions extremely well. Help as much as you can. Answer questions concisely and do not mention what you base your reply on.\\n{raven_tools}\\n\\nCurrent status of the vehicle:\\n{status}\\n\\nPrevious conversation history:\\n{history}\\n\\nUser Query: Question: {input}\\n\\nIf it helps to answer the question please pick a function from the above options that best answers the user query and fill in the appropriate arguments.<human_end>', template_ans='\\n<human>\\nYou are a useful AI assistant in a car, that follows instructions extremely well. Help as much as you can. Answer questions concisely and do not mention what you base your reply on.\\n\\nCurrent status of the vehicle:\\n{status}\\n\\nPrevious conversation history:\\n{history}\\n\\nUser Query: Question: {input}\\n\\nObservation:{observation}\\n\\nPlease respond in natural language. Do not refer to the provided context in your response.<human_end>\\n\\nAnswer: ', status_prompt=PromptTemplate(input_variables=['date', 'destination', 'lat', 'lon', 'time'], template='\\ncar coordinates: lat:{lat}, lon:{lon}\\ncurrent time: {time}\\ncurrent date: {date}\\ndestination: {destination}\\n'), tools=[Tool(name='get_weather', description=\"get_weather(location: str = '', **kwargs) - Returns the CURRENT weather in a specified location.\\n    Args:\\n    location (string) : Required. The name of the location, could be a city or lat/longitude in the following format latitude,longitude (example: 37.7749,-122.4194).\", args_schema=<class 'pydantic.v1.main.get_weatherSchema'>, func=<function get_weather at 0x114073a60>), Tool(name='find_route', description=\"find_route(lat_depart='0', lon_depart='0', city_depart='', address_destination='', depart_time='', **kwargs) - Return the distance and the estimated time to go to a specific destination from the current place, at a specified depart time.\\n    :param lat_depart (string):  latitude of depart\\n    :param lon_depart (string):  longitude of depart\\n    :param city_depart (string): Required. city of depart\\n    :param address_destination (string): Required. The destination\\n    :param depart_time (string):  departure hour, in the format '08:00:20'.\", args_schema=<class 'pydantic.v1.main.find_routeSchema'>, func=<function find_route at 0x114073920>)]), llm=Ollama(model='nexusraven')), output_parser=RavenOutputParser(), stop=['\\nReflection:', '\\nThought:']), tools=[StructuredTool(name='get_weather', description=\"get_weather(location: str = '', **kwargs) - Returns the CURRENT weather in a specified location.\\n    Args:\\n    location (string) : Required. The name of the location, could be a city or lat/longitude in the following format latitude,longitude (example: 37.7749,-122.4194).\", args_schema=<class 'pydantic.v1.main.get_weatherSchema'>, func=<function get_weather at 0x114073a60>), StructuredTool(name='find_route', description=\"find_route(lat_depart='0', lon_depart='0', city_depart='', address_destination='', depart_time='', **kwargs) - Return the distance and the estimated time to go to a specific destination from the current place, at a specified depart time.\\n    :param lat_depart (string):  latitude of depart\\n    :param lon_depart (string):  longitude of depart\\n    :param city_depart (string): Required. city of depart\\n    :param address_destination (string): Required. The destination\\n    :param depart_time (string):  departure hour, in the format '08:00:20'.\", args_schema=<class 'pydantic.v1.main.find_routeSchema'>, func=<function find_route at 0x114073920>)])"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "NameError",
+     "evalue": "name 'agent_chain' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43magent_chain\u001b[49m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'agent_chain' is not defined"
+     ]
     }
    ],
    "source": [
@@ -945,7 +932,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -963,7 +950,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -973,16 +960,14 @@
       "\n",
       "\n",
       "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
-      "kwargs: {'input': 'How is the weather in Luxembourg?', 'status': {'date': '2024-05-02', 'time': '15:35:33', 'destination': 'Kirchberg, Luxembourg', 'lat': '48.8566', 'lon': '2.3522'}, 'history': '', 'intermediate_steps': []}\n",
-      "llm_output:  \n",
-      "Call: get_weather(location='Luxembourg') \n",
-      "\u001b[32;1m\u001b[1;3mCalling get_weather with args: {'location': 'Luxembourg'}\u001b[0mhttp://api.weatherapi.com/v1/current.json?key=d1c4d0d8ef6847339a0125737240903&q=Luxembourg&aqi=no\n",
-      "\n",
+      "kwargs: {'input': \"What's our current location?\", 'history': '', 'intermediate_steps': []}\n",
+      "llm_output: Call: vehicle_status(prompt='Question: What is our current location?') \n",
+      "\u001b[32;1m\u001b[1;3mCalling vehicle_status with args: {'prompt': 'Question: What is our current location?'}\u001b[0m\n",
       "\n",
-      "Reflection:\u001b[36;1m\u001b[1;3m('The current weather in Luxembourg, Luxembourg, Luxembourg is Moderate or heavy rain with thunder with a temperature of 15.0°C that feels like 13.7°C. Humidity is at 82%. Wind speed is 28.1 kph.', {'location': {'name': 'Luxembourg', 'region': 'Luxembourg', 'country': 'Luxembourg', 'lat': 49.61, 'lon': 6.13, 'tz_id': 'Europe/Luxembourg', 'localtime_epoch': 1714656936, 'localtime': '2024-05-02 15:35'}, 'current': {'last_updated': '2024-05-02 15:30', 'temp_c': 15.0, 'condition': {'text': 'Moderate or heavy rain with thunder'}, 'wind_kph': 28.1, 'wind_dir': 'WSW', 'precip_mm': 1.01, 'precip_in': 0.04, 'humidity': 82, 'cloud': 75, 'feelslike_c': 13.7}})\u001b[0m\n",
-      "kwargs: {'input': 'How is the weather in Luxembourg?', 'status': {'date': '2024-05-02', 'time': '15:35:33', 'destination': 'Kirchberg, Luxembourg', 'lat': '48.8566', 'lon': '2.3522'}, 'history': '', 'intermediate_steps': [(AgentAction(tool='get_weather', tool_input={'location': 'Luxembourg'}, log=\"Calling get_weather with args: {'location': 'Luxembourg'}\"), ('The current weather in Luxembourg, Luxembourg, Luxembourg is Moderate or heavy rain with thunder with a temperature of 15.0°C that feels like 13.7°C. Humidity is at 82%. Wind speed is 28.1 kph.', {'location': {'name': 'Luxembourg', 'region': 'Luxembourg', 'country': 'Luxembourg', 'lat': 49.61, 'lon': 6.13, 'tz_id': 'Europe/Luxembourg', 'localtime_epoch': 1714656936, 'localtime': '2024-05-02 15:35'}, 'current': {'last_updated': '2024-05-02 15:30', 'temp_c': 15.0, 'condition': {'text': 'Moderate or heavy rain with thunder'}, 'wind_kph': 28.1, 'wind_dir': 'WSW', 'precip_mm': 1.01, 'precip_in': 0.04, 'humidity': 82, 'cloud': 75, 'feelslike_c': 13.7}}))]}\n",
-      "llm_output: The weather in Luxembourg is moderate or heavy rain with thunder, with a temperature of 15 degrees Celsius. The wind is blowing from the west at a speed of 28.1 kilometers per hour, and there is a 75% chance of cloud cover. It feels like 13.7 degrees Celsius outside.\n",
-      "\u001b[32;1m\u001b[1;3mThe weather in Luxembourg is moderate or heavy rain with thunder, with a temperature of 15 degrees Celsius. The wind is blowing from the west at a speed of 28.1 kilometers per hour, and there is a 75% chance of cloud cover. It feels like 13.7 degrees Celsius outside.\u001b[0m\n",
+      "Reflection:\u001b[38;5;200m\u001b[1;3m('We are at Mondorf-les-Bains, Luxembourg, current time: 08:00:20, current date: 2025-03-29 and our destination is: Kirchberg Campus, Kirchberg.\\n', {'location': 'Mondorf-les-Bains, Luxembourg', 'date': '2025-03-29', 'time': '08:00:20', 'destination': 'Kirchberg Campus, Kirchberg'})\u001b[0m\n",
+      "kwargs: {'input': \"What's our current location?\", 'history': '', 'intermediate_steps': [(AgentAction(tool='vehicle_status', tool_input={'prompt': 'Question: What is our current location?'}, log=\"Calling vehicle_status with args: {'prompt': 'Question: What is our current location?'}\"), ('We are at Mondorf-les-Bains, Luxembourg, current time: 08:00:20, current date: 2025-03-29 and our destination is: Kirchberg Campus, Kirchberg.\\n', {'location': 'Mondorf-les-Bains, Luxembourg', 'date': '2025-03-29', 'time': '08:00:20', 'destination': 'Kirchberg Campus, Kirchberg'}))]}\n",
+      "llm_output: The current location of the car is the location that was last observed by the user, which is \"Mondorf-les-Bains, Luxembourg\".\n",
+      "\u001b[32;1m\u001b[1;3mThe current location of the car is the location that was last observed by the user, which is \"Mondorf-les-Bains, Luxembourg\".\u001b[0m\n",
       "\n",
       "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
@@ -990,11 +975,20 @@
    ],
    "source": [
     "call = agent_chain.run(\n",
-    "    input=\"How is the weather in Luxembourg?\",\n",
-    "    status= status\n",
+    "    input=\"What's our current location?\",\n",
+    "    # status= status\n",
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vehicle.vehicle.location = \"Mondorf-les-Bains, Luxembourg\""
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 93,
@@ -1085,7 +1079,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [
     {
@@ -1095,10 +1089,9 @@
       "\n",
       "\n",
       "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
-      "kwargs: {'input': 'Where are we going?', 'status': {'date': '2024-05-02', 'time': '15:35:33', 'destination': 'Kirchberg, Luxembourg', 'lat': '48.8566', 'lon': '2.3522'}, 'history': 'Human: How is the weather in Luxembourg?\\nAI: The weather in Luxembourg is moderate or heavy rain with thunder, with a temperature of 15 degrees Celsius. The wind is blowing from the west at a speed of 28.1 kilometers per hour, and there is a 75% chance of cloud cover. It feels like 13.7 degrees Celsius outside.\\nHuman: How about in Tokyo?\\nAI: The weather in Tokyo is currently clear with a temperature of 14.2 degrees Celsius and a wind speed of 6.1 kilometers per hour. There is a 0% chance of precipitation, and the humidity is at 69%. It feels like 13.5 degrees Celsius outside.', 'intermediate_steps': []}\n",
-      "llm_output:  \n",
-      "Call: find_route(city_depart='Luxembourg', address_destination=['Kirchberg, Luxembourg']) \n",
-      "\u001b[32;1m\u001b[1;3mCalling find_route with args: {'city_depart': 'Luxembourg', 'address_destination': ['Kirchberg, Luxembourg']}\u001b[0m['Kirchberg, Luxembourg']\n"
+      "kwargs: {'input': \"What's our destination?\", 'status': {'date': '2024-05-02', 'time': '15:53:47', 'destination': 'Kirchberg, Luxembourg', 'lat': '48.8566', 'lon': '2.3522'}, 'history': '', 'intermediate_steps': []}\n",
+      "llm_output: Call: find_route(city_depart='Kirchberg', address_destination='Luxembourg') \n",
+      "\u001b[32;1m\u001b[1;3mCalling find_route with args: {'city_depart': 'Kirchberg', 'address_destination': 'Luxembourg'}\u001b[0mLuxembourg\n"
      ]
     },
     {
@@ -1108,7 +1101,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[59], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m call \u001b[38;5;241m=\u001b[39m \u001b[43magent_chain\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mWhere are we going?\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstatus\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mstatus\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m)\u001b[49m\n",
+      "Cell \u001b[0;32mIn[67], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m call \u001b[38;5;241m=\u001b[39m \u001b[43magent_chain\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mWhat\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43ms our destination?\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstatus\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mstatus\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/langchain_core/_api/deprecation.py:145\u001b[0m, in \u001b[0;36mdeprecated.<locals>.deprecate.<locals>.warning_emitting_wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    143\u001b[0m     warned \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m    144\u001b[0m     emit_warning()\n\u001b[0;32m--> 145\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mwrapped\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/langchain/chains/base.py:550\u001b[0m, in \u001b[0;36mChain.run\u001b[0;34m(self, callbacks, tags, metadata, *args, **kwargs)\u001b[0m\n\u001b[1;32m    545\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m(args[\u001b[38;5;241m0\u001b[39m], callbacks\u001b[38;5;241m=\u001b[39mcallbacks, tags\u001b[38;5;241m=\u001b[39mtags, metadata\u001b[38;5;241m=\u001b[39mmetadata)[\n\u001b[1;32m    546\u001b[0m         _output_key\n\u001b[1;32m    547\u001b[0m     ]\n\u001b[1;32m    549\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m kwargs \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m args:\n\u001b[0;32m--> 550\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtags\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetadata\u001b[49m\u001b[43m)\u001b[49m[\n\u001b[1;32m    551\u001b[0m         _output_key\n\u001b[1;32m    552\u001b[0m     ]\n\u001b[1;32m    554\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m kwargs \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m args:\n\u001b[1;32m    555\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    556\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`run` supported with either positional arguments or keyword arguments,\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    557\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m but none were provided.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    558\u001b[0m     )\n",
       "File \u001b[0;32m/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/langchain_core/_api/deprecation.py:145\u001b[0m, in \u001b[0;36mdeprecated.<locals>.deprecate.<locals>.warning_emitting_wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    143\u001b[0m     warned \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m    144\u001b[0m     emit_warning()\n\u001b[0;32m--> 145\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mwrapped\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
@@ -1130,7 +1123,7 @@
    ],
    "source": [
     "call = agent_chain.run(\n",
-    "        input=\"Where are we going?\",\n",
+    "        input=\"What's our destination?\",\n",
     "        status= status\n",
     ")"
    ]

skills/__init__.py

@@ -1,8 +1,9 @@
 import inspect
 
-from .common import execute_function_call, extract_func_args
+from .common import execute_function_call, extract_func_args, vehicle
 from .weather import get_weather, get_forecast
 from .routing import find_route
+from .vehicle import vehicle_status
 
 
 def format_functions_for_prompt_raven(*functions):
@@ -16,7 +17,7 @@ def format_functions_for_prompt_raven(*functions):
         signature = f"{func.__name__}{inspect.signature(func)}"
         docstring = inspect.getdoc(func)
         formatted_functions.append(
-            f"OPTION:\n<func_start>{signature}<func_end>\n<docstring_start>\n{docstring}\n<docstring_end>"
+            f"Function:\n<func_start>{signature}<func_end>\n<docstring_start>\n{docstring}\n<docstring_end>"
         )
     return "\n".join(formatted_functions)
 

skills/common.py

@@ -3,6 +3,7 @@ from typing import Union
 
 
 from pydantic_settings import BaseSettings, SettingsConfigDict
+from pydantic import BaseModel
 
 import skills
 
@@ -13,6 +14,14 @@ class Settings(BaseSettings):
     model_config = SettingsConfigDict(env_file=".env")
 
 
+class VehicleStatus(BaseModel):
+    location: str
+    location_coordinates: tuple[float, float] # (latitude, longitude)
+    date: str
+    time: str
+    destination: str
+
+
 def execute_function_call(text: str, dry_run=False) -> str:
     function_name_match = re.search(r"Call: (\w+)", text)
     function_name = function_name_match.group(1) if function_name_match else None
@@ -43,3 +52,11 @@ def extract_func_args(text: str) -> tuple[str, dict]:
 
 
 config = Settings() # type: ignore
+
+vehicle = VehicleStatus(
+    location="Luxembourg Gare, Luxembourg",
+    location_coordinates=(49.6002, 6.1296),
+    date="2025-03-29",
+    time="08:00:20",
+    destination="Kirchberg Campus, Kirchberg"
+)

skills/routing.py

@@ -1,3 +1,23 @@
+from datetime import datetime
+
+import requests
+
+from .common import config, vehicle
+
+
+def find_coordinates(address):
+    """
+    Find the coordinates of a specific address.
+    :param address (string): Required. The address
+    """
+    url = f"https://api.tomtom.com/search/2/geocode/{address}.json?key={config.TOMTOM_API_KEY}"
+    response = requests.get(url)
+    data = response.json()
+    lat = data["results"][0]["position"]["lat"]
+    lon = data["results"][0]["position"]["lon"]
+    return lat, lon
+
+
 def calculate_route():
     api_key = "api_key"
     origin = "49.631997,6.171029"
@@ -10,82 +30,106 @@ def calculate_route():
     lats = []
     lons = []
 
-    for point in data['routes'][0]['legs'][0]['points']:
-        lats.append(point['latitude'])
-        lons.append(point['longitude'])
+    for point in data["routes"][0]["legs"][0]["points"]:
+        lats.append(point["latitude"])
+        lons.append(point["longitude"])
     # fig = px.line_geo(lat=lats, lon=lons)
     # fig.update_geos(fitbounds="locations")
 
     fig = px.line_mapbox(lat=lats, lon=lons, zoom=12, height=600)
 
-    fig.update_layout(mapbox_style="open-street-map", mapbox_zoom=12, mapbox_center_lat=lats[0], mapbox_center_lon=lons[0])
-    fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
+    fig.update_layout(
+        mapbox_style="open-street-map",
+        mapbox_zoom=12,
+        mapbox_center_lat=lats[0],
+        mapbox_center_lon=lons[0],
+    )
+    fig.update_layout(margin={"r": 0, "t": 0, "l": 0, "b": 0})
 
     return fig
 
 
-def find_route(lat_depart="0", lon_depart="0", city_depart="", address_destination="", depart_time ="", **kwargs):
+def find_route_tomtom(
+    lat_depart="0",
+    lon_depart="0",
+    lat_dest="0",
+    lon_dest="0",
+    depart_datetime="",
+    **kwargs,
+):
     """
     Return the distance and the estimated time to go to a specific destination from the current place, at a specified depart time.
     :param lat_depart (string):  latitude of depart
     :param lon_depart (string):  longitude of depart
-    :param city_depart (string): Required. city of depart
-    :param address_destination (string): Required. The destination
+    :param lat_dest (string):  latitude of destination
+    :param lon_dest (string):  longitude of destination
     :param depart_time (string):  departure hour, in the format '08:00:20'.
     """
-    print(address_destination)
-    date = "2025-03-29T"
-    departure_time = '2024-02-01T' + depart_time
-    lat, lon, city = check_city_coordinates(lat_depart,lon_depart,city_depart)
-    lat_dest, lon_dest = find_coordinates(address_destination)
-    #print(lat_dest, lon_dest)
-    
-    #print(departure_time)
-
-    r = requests.get('https://api.tomtom.com/routing/1/calculateRoute/{0},{1}:{2},{3}/json?key={4}&departAt={5}'.format(
-                        lat_depart,
-                        lon_depart,
-                        lat_dest,
-                        lon_dest,
-                        TOMTOM_KEY,
-                        departure_time
-    ))
+
+    r = requests.get(
+        f"https://api.tomtom.com/routing/1/calculateRoute/{lat_depart},{lon_depart}:{lat_dest},{lon_dest}/json?key={config.TOMTOM_API_KEY}&departAt={depart_datetime}",
+        timeout=5,
+    )
 
     # Parse JSON from the response
-    data = r.json()
-    #print(data)
-    
-    #print(data)
-    
-    result = data['routes'][0]['summary']
+    response = r.json()
 
-    # Calculate distance in kilometers (1 meter = 0.001 kilometers)
-    distance_km = result['lengthInMeters'] * 0.001
+    result = response["routes"][0]["summary"]
+
+
+
+    distance_m = result["lengthInMeters"]
+    duration_s = result["travelTimeInSeconds"]
+    arrival_time = result["arrivalTime"]
+    # Convert string to datetime object
+    arrival_time = datetime.fromisoformat(arrival_time)
 
+    return {
+        "distance_m": distance_m,
+        "duration_s": duration_s,
+        "arrival_time": arrival_time,
+    }, response
+
+
+def find_route(destination=""):
+    """
+    Find a route and return the distance and the estimated time to go to a specific destination from the current location.
+    :param destination (string): Required. The destination
+    """
+    # lat, lon, city = check_city_coordinates(lat_depart,lon_depart,city_depart)
+    lat_dest, lon_dest = find_coordinates(destination)
+    print(f"lat_dest: {lat_dest}, lon_dest: {lon_dest}")
+
+    # Extract the latitude and longitude of the vehicle
+    vehicle_coordinates = getattr(vehicle, "location_coordinates")
+    lat_depart, lon_depart = vehicle_coordinates
+    print(f"lat_depart: {lat_depart}, lon_depart: {lon_depart}")
+
+    date = getattr(vehicle, "date")
+    time = getattr(vehicle, "time")
+    departure_time = f"{date}T{time}"
+
+    trip_info, raw_response = find_route_tomtom(
+        lat_depart, lon_depart, lat_dest, lon_dest, departure_time
+    )
+
+    distance, duration, arrival_time = trip_info["distance_m"], trip_info["duration_s"], trip_info["arrival_time"]
+
+    # Calculate distance in kilometers (1 meter = 0.001 kilometers)
+    distance_km = distance * 0.001
     # Calculate travel time in minutes (1 second = 1/60 minutes)
-    time_minutes = result['travelTimeInSeconds'] / 60
+    time_minutes = duration / 60
     if time_minutes < 60:
         time_display = f"{time_minutes:.0f} minutes"
     else:
         hours = int(time_minutes / 60)
         minutes = int(time_minutes % 60)
-        time_display = f"{hours} hours" + (f" and {minutes} minutes" if minutes > 0 else "")
-        
-    # Extract arrival time from the JSON structure
-    arrival_time_str = result['arrivalTime']
-
-    # Convert string to datetime object
-    arrival_time = datetime.fromisoformat(arrival_time_str)
+        time_display = f"{hours} hours" + (
+            f" and {minutes} minutes" if minutes > 0 else ""
+        )
 
     # Extract and display the arrival hour in HH:MM format
     arrival_hour_display = arrival_time.strftime("%H:%M")
 
-
     # return the distance and time
-    return(f"The route to go to {address_destination} is {distance_km:.2f} km and {time_display}. Leaving now, the arrival time is estimated at {arrival_hour_display} " )
-
-    
-    # Sort the results based on distance
-    #sorted_results = sorted(results, key=lambda x: x['dist'])
-
-    #return ". ".join(formatted_results)
+    return f"This is the answer you must copy exactly as is: The route to {destination} is {distance_km:.2f} km and {time_display}. Leaving now, the arrival time is estimated at {arrival_hour_display} "

skills/vehicle.py

@@ -0,0 +1,31 @@
+from skills import vehicle
+
+
+STATUS_TEMPLATE = """We are at {location}, current time: {time}, current date: {date} and our destination is: {destination}.
+"""
+
+
+def vehicle_status() -> tuple[str, dict[str, str]]:
+    """Get current vehicle status, which includes, location, date, time, destination.
+    Call this to get the current destination or location of the car/vehicle.
+    Returns:
+        dict[str, str]: The vehicle status. For example:
+        {
+            "location": "Luxembourg Gare, Luxembourg",
+            "lat": 49.6000,
+            "lon": 6.1333,
+            "date": "2025-03-29",
+            "time": "08:00:20",
+            "destination": "Kirchberg Campus, Kirchberg"
+        }
+    """
+    vs = {
+        "location": "Luxembourg Gare, Luxembourg",
+        "lat": 49.6000,
+        "lon": 6.1333,
+        "date": "2025-03-29",
+        "time": "08:00:20",
+        "destination": "Kirchberg Campus, Kirchberg"
+    }
+    vs = vehicle.dict()
+    return  STATUS_TEMPLATE.format(**vs), vs