pjlab-adg / drivelikeahuman Goto Github PK

> Finished chain.
Moviepy - Building video /data/GitHub/DriveLikeAHuman/results-video/highwayv0-episode-0.mp4.
Moviepy - Writing video /data/GitHub/DriveLikeAHuman/results-video/highwayv0-episode-0.mp4

                                                  
Moviepy - Done !
Moviepy - video ready /data/GitHub/DriveLikeAHuman/results-video/highwayv0-episode-0.mp4

---------------------------------------------------------------------------
TimeoutError                              Traceback (most recent call last)
File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/connection.py:203, in HTTPConnection._new_conn(self)
    202 try:
--> 203     sock = connection.create_connection(
    204         (self._dns_host, self.port),
    205         self.timeout,
    206         source_address=self.source_address,
    207         socket_options=self.socket_options,
    208     )
    209 except socket.gaierror as e:

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/util/connection.py:85, in create_connection(address, timeout, source_address, socket_options)
     84 try:
---> 85     raise err
     86 finally:
     87     # Break explicitly a reference cycle

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/util/connection.py:73, in create_connection(address, timeout, source_address, socket_options)
     72     sock.bind(source_address)
---> 73 sock.connect(sa)
     74 # Break explicitly a reference cycle

TimeoutError: [Errno 110] Connection timed out

The above exception was the direct cause of the following exception:

ConnectTimeoutError                       Traceback (most recent call last)
File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/connectionpool.py:790, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    789 # Make the request on the HTTPConnection object
--> 790 response = self._make_request(
    791     conn,
    792     method,
    793     url,
    794     timeout=timeout_obj,
    795     body=body,
    796     headers=headers,
    797     chunked=chunked,
    798     retries=retries,
    799     response_conn=response_conn,
    800     preload_content=preload_content,
    801     decode_content=decode_content,
    802     **response_kw,
    803 )
    805 # Everything went great!

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/connectionpool.py:491, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    490         new_e = _wrap_proxy_error(new_e, conn.proxy.scheme)
--> 491     raise new_e
    493 # conn.request() calls http.client.*.request, not the method in
    494 # urllib3.request. It also calls makefile (recv) on the socket.

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/connectionpool.py:467, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length)
    466 try:
--> 467     self._validate_conn(conn)
    468 except (SocketTimeout, BaseSSLError) as e:

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/connectionpool.py:1092, in HTTPSConnectionPool._validate_conn(self, conn)
   1091 if conn.is_closed:
-> 1092     conn.connect()
   1094 if not conn.is_verified:

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/connection.py:611, in HTTPSConnection.connect(self)
    610 sock: socket.socket | ssl.SSLSocket
--> 611 self.sock = sock = self._new_conn()
    612 server_hostname: str = self.host

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/connection.py:212, in HTTPConnection._new_conn(self)
    211 except SocketTimeout as e:
--> 212     raise ConnectTimeoutError(
    213         self,
    214         f"Connection to {self.host} timed out. (connect timeout={self.timeout})",
    215     ) from e
    217 except OSError as e:

ConnectTimeoutError: (<urllib3.connection.HTTPSConnection object at 0x7f0c0bb01480>, 'Connection to openaipublic.blob.core.windows.net timed out. (connect timeout=None)')

The above exception was the direct cause of the following exception:

MaxRetryError                             Traceback (most recent call last)
File ~/anaconda3/envs/llama/lib/python3.10/site-packages/requests/adapters.py:486, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    485 try:
--> 486     resp = conn.urlopen(
    487         method=request.method,
    488         url=url,
    489         body=request.body,
    490         headers=request.headers,
    491         redirect=False,
    492         assert_same_host=False,
    493         preload_content=False,
    494         decode_content=False,
    495         retries=self.max_retries,
    496         timeout=timeout,
    497         chunked=chunked,
    498     )
    500 except (ProtocolError, OSError) as err:

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/connectionpool.py:844, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw)
    842     new_e = ProtocolError("Connection aborted.", new_e)
--> 844 retries = retries.increment(
    845     method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2]
    846 )
    847 retries.sleep()

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/urllib3/util/retry.py:515, in Retry.increment(self, method, url, response, error, _pool, _stacktrace)
    514     reason = error or ResponseError(cause)
--> 515     raise MaxRetryError(_pool, url, reason) from reason  # type: ignore[arg-type]
    517 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry)

MaxRetryError: HTTPSConnectionPool(host='openaipublic.blob.core.windows.net', port=443): Max retries exceeded with url: /encodings/cl100k_base.tiktoken (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7f0c0bb01480>, 'Connection to openaipublic.blob.core.windows.net timed out. (connect timeout=None)'))

During handling of the above exception, another exception occurred:

ConnectTimeout                            Traceback (most recent call last)
File /data/GitHub/DriveLikeAHuman/HELLM.py:105
    103 while not (done or truncated):
    104     sce.upateVehicles(obs, frame)
--> 105     DA.agentRun(output)
    106     da_output = DA.exportThoughts()
    107     output = outputParser.agentRun(da_output)

File /data/GitHub/DriveLikeAHuman/LLMDriver/driverAgent.py:72, in DriverAgent.agentRun(self, last_step_decision)
     70     last_step_explanation = "Not available"
     71 with get_openai_callback() as cb:
---> 72     self.agent.run(
     73         f"""
     74         You, the 'ego' car, are now driving a car on a highway. You have already drive for {self.sce.frame} seconds.
     75         The decision you made LAST time step was `{last_step_action}`. Your explanation was `{last_step_explanation}`. 
     76         Here is the current scenario: \n ```json\n{self.sce.export2json()}\n```\n. 
     77         Please make decision for the `ego` car. You have to describe the state of the `ego`, then analyze the possible actions, and finally output your decision. 
     78 
     79         There are several rules you need to follow when you drive on a highway:
     80         {TRAFFIC_RULES}
     81 
     82         Here are your attentions points:
     83         {DECISION_CAUTIONS}
     84         
     85         Let's think step by step. Once you made a final decision, output it in the following format: \n
     86         ```
     87         Final Answer: 
     88             "decision":{{"ego car's decision, ONE of the available actions"}},
     89             "expalanations":{{"your explaination about your decision, described your suggestions to the driver"}}
     90         ``` \n
     91         """,
     92         callbacks=[self.ch]
     93     )
     94 print(cb)
     95 print('[cyan]Final decision:[/cyan]')

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/langchain/chains/base.py:315, in Chain.run(self, callbacks, tags, metadata, *args, **kwargs)
    313     if len(args) != 1:
    314         raise ValueError("`run` supports only one positional argument.")
--> 315     return self(args[0], callbacks=callbacks, tags=tags, metadata=metadata)[
    316         _output_key
    317     ]
    319 if kwargs and not args:
    320     return self(kwargs, callbacks=callbacks, tags=tags, metadata=metadata)[
    321         _output_key
    322     ]

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/langchain/chains/base.py:183, in Chain.__call__(self, inputs, return_only_outputs, callbacks, tags, metadata, include_run_info)
    181     raise e
    182 run_manager.on_chain_end(outputs)
--> 183 final_outputs: Dict[str, Any] = self.prep_outputs(
    184     inputs, outputs, return_only_outputs
    185 )
    186 if include_run_info:
    187     final_outputs[RUN_KEY] = RunInfo(run_id=run_manager.run_id)

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/langchain/chains/base.py:257, in Chain.prep_outputs(self, inputs, outputs, return_only_outputs)
    255 self._validate_outputs(outputs)
    256 if self.memory is not None:
--> 257     self.memory.save_context(inputs, outputs)
    258 if return_only_outputs:
    259     return outputs

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/langchain/memory/token_buffer.py:48, in ConversationTokenBufferMemory.save_context(self, inputs, outputs)
     46 # Prune buffer if it exceeds max token limit
     47 buffer = self.chat_memory.messages
---> 48 curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer)
     49 if curr_buffer_length > self.max_token_limit:
     50     pruned_memory = []

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/langchain/chat_models/openai.py:499, in ChatOpenAI.get_num_tokens_from_messages(self, messages)
    497 if sys.version_info[1] <= 7:
    498     return super().get_num_tokens_from_messages(messages)
--> 499 model, encoding = self._get_encoding_model()
    500 if model.startswith("gpt-3.5-turbo"):
    501     # every message follows <im_start>{role/name}\n{content}<im_end>\n
    502     tokens_per_message = 4

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/langchain/chat_models/openai.py:477, in ChatOpenAI._get_encoding_model(self)
    475 # Returns the number of tokens used by a list of messages.
    476 try:
--> 477     encoding = tiktoken_.encoding_for_model(model)
    478 except KeyError:
    479     logger.warning("Warning: model not found. Using cl100k_base encoding.")

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/tiktoken/model.py:67, in encoding_for_model(model_name)
     65     for model_prefix, model_encoding_name in MODEL_PREFIX_TO_ENCODING.items():
     66         if model_name.startswith(model_prefix):
---> 67             return get_encoding(model_encoding_name)
     69 if encoding_name is None:
     70     raise KeyError(
     71         f"Could not automatically map {model_name} to a tokeniser. "
     72         "Please use `tiktok.get_encoding` to explicitly get the tokeniser you expect."
     73     ) from None

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/tiktoken/registry.py:63, in get_encoding(encoding_name)
     60     raise ValueError(f"Unknown encoding {encoding_name}")
     62 constructor = ENCODING_CONSTRUCTORS[encoding_name]
---> 63 enc = Encoding(**constructor())
     64 ENCODINGS[encoding_name] = enc
     65 return enc

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/tiktoken_ext/openai_public.py:64, in cl100k_base()
     63 def cl100k_base():
---> 64     mergeable_ranks = load_tiktoken_bpe(
     65         "https://openaipublic.blob.core.windows.net/encodings/cl100k_base.tiktoken"
     66     )
     67     special_tokens = {
     68         ENDOFTEXT: 100257,
     69         FIM_PREFIX: 100258,
   (...)
     72         ENDOFPROMPT: 100276,
     73     }
     74     return {
     75         "name": "cl100k_base",
     76         "pat_str": r"""(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+""",
     77         "mergeable_ranks": mergeable_ranks,
     78         "special_tokens": special_tokens,
     79     }

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/tiktoken/load.py:116, in load_tiktoken_bpe(tiktoken_bpe_file)
    114 def load_tiktoken_bpe(tiktoken_bpe_file: str) -> dict[bytes, int]:
    115     # NB: do not add caching to this function
--> 116     contents = read_file_cached(tiktoken_bpe_file)
    117     return {
    118         base64.b64decode(token): int(rank)
    119         for token, rank in (line.split() for line in contents.splitlines() if line)
    120     }

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/tiktoken/load.py:48, in read_file_cached(blobpath)
     45     with open(cache_path, "rb") as f:
     46         return f.read()
---> 48 contents = read_file(blobpath)
     50 os.makedirs(cache_dir, exist_ok=True)
     51 tmp_filename = cache_path + "." + str(uuid.uuid4()) + ".tmp"

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/tiktoken/load.py:24, in read_file(blobpath)
     22         return f.read()
     23 # avoiding blobfile for public files helps avoid auth issues, like MFA prompts
---> 24 resp = requests.get(blobpath)
     25 resp.raise_for_status()
     26 return resp.content

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/requests/api.py:73, in get(url, params, **kwargs)
     62 def get(url, params=None, **kwargs):
     63     r"""Sends a GET request.
     64 
     65     :param url: URL for the new :class:`Request` object.
   (...)
     70     :rtype: requests.Response
     71     """
---> 73     return request("get", url, params=params, **kwargs)

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/requests/api.py:59, in request(method, url, **kwargs)
     55 # By using the 'with' statement we are sure the session is closed, thus we
     56 # avoid leaving sockets open which can trigger a ResourceWarning in some
     57 # cases, and look like a memory leak in others.
     58 with sessions.Session() as session:
---> 59     return session.request(method=method, url=url, **kwargs)

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
    584 send_kwargs = {
    585     "timeout": timeout,
    586     "allow_redirects": allow_redirects,
    587 }
    588 send_kwargs.update(settings)
--> 589 resp = self.send(prep, **send_kwargs)
    591 return resp

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs)
    700 start = preferred_clock()
    702 # Send the request
--> 703 r = adapter.send(request, **kwargs)
    705 # Total elapsed time of the request (approximately)
    706 elapsed = preferred_clock() - start

File ~/anaconda3/envs/llama/lib/python3.10/site-packages/requests/adapters.py:507, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies)
    504 if isinstance(e.reason, ConnectTimeoutError):
    505     # TODO: Remove this in 3.0.0: see #2811
    506     if not isinstance(e.reason, NewConnectionError):
--> 507         raise ConnectTimeout(e, request=request)
    509 if isinstance(e.reason, ResponseError):
    510     raise RetryError(e, request=request)

ConnectTimeout: HTTPSConnectionPool(host='openaipublic.blob.core.windows.net', port=443): Max retries exceeded with url: /encodings/cl100k_base.tiktoken (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7f0c0bb01480>, 'Connection to openaipublic.blob.core.windows.net timed out. (connect timeout=None)'))

python==3.10
urllib3==2.0.4
moviepy==1.0.3
tiktoken==0.4.0