Locally hosted model - Validation error

[SSMK-wq]

My company has hosted the openAI models locally using a internal URL. When I try the below code, it works fine and provides the response. How can we resolve the error? please help. This is a good package and can help a lot

llm = ChatOpenAI(
    model='gpt-4o-mini',
    base_url ='https://abcde.gfh.dummy.com',
    api_key=base64_string,
    default_headers=headers,
    http_client = httpx.Client(verify='ag-bundle.crt'))

res = llm.invoke("How are you?")   
print(res)

but when I pass this llm to the pandasAI SmartDataframe function, I get the below error. We also tried LiteLLM(). details further below

sdf = SmartDataframe(DEM05_data, config={"llm":llm})

---

ValidationError Traceback (most recent call last)
Cell In[43], line 1
----> 1 sdf = SmartDataframe(DEM05_data, config={"llm":llm})

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\smart_dataframe_init_.py:63, in SmartDataframe.init(self, df, name, description, custom_head, config)
53 """
54 Args:
55 df: A supported dataframe type, or a pandasai Connector
(...) 59 config (Config, optional): Config to be used. Defaults to None.
60 """
61 self._original_import = df
---> 63 self._agent = Agent([df], config=config)
65 self.dataframe = self._agent.context.dfs[0]
67 self._table_description = description

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\agent.py:28, in Agent.init(self, dfs, config, memory_size, pipeline, vectorstore, description, judge, security)
15 def init(
16 self,
17 dfs: Union[
(...) 26 security: BaseSecurity = None,
27 ):
---> 28 super().init(
29 dfs, config, memory_size, vectorstore, description, security=security
30 )
32 self.pipeline = (
33 pipeline(
34 self.context,
(...) 51 )
52 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\base.py:75, in BaseAgent.init(self, dfs, config, memory_size, vectorstore, description, security)
72 self.dfs = self.get_dfs(dfs)
74 # Instantiate the context
---> 75 self.config = self.get_config(config)
76 self.context = PipelineContext(
77 dfs=self.dfs,
78 config=self.config,
79 memory=Memory(memory_size, agent_info=description),
80 vectorstore=vectorstore,
81 )
83 # Instantiate the logger

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\base.py:134, in BaseAgent.get_config(self, config)
131 if isinstance(config, dict) and config.get("llm") is not None:
132 config["llm"] = self.get_llm(config["llm"])
--> 134 config = Config(**config)
136 if config.llm is None:
137 config.llm = BambooLLM()

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pydantic\v1\main.py:347, in BaseModel.init(pydantic_self, **data)
345 values, fields_set, validation_error = validate_model(pydantic_self.class, data)
346 if validation_error:
--> 347 raise validation_error
348 try:
349 object_setattr(pydantic_self, 'dict', values)

ValidationError: 1 validation error for Config
llm
instance of LLM expected (type=type_error.arbitrary_type; expected_arbitrary_type=LLM)

LiteLLM Usage

llm = LiteLLM(
    model='gpt-4o-mini',
    api_base ='https://gptabcd.ter.abcd.com',
    api_key=base64_string,
    default_headers=headers,
    http_client = httpx.Client(verify='ac-bundle.crt'))

This also resulted in the similar error

---

TypeError Traceback (most recent call last)
File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:736, in OpenAIChatCompletion.completion(self, model_response, timeout, optional_params, litellm_params, logging_obj, model, messages, print_verbose, api_key, api_base, api_version, dynamic_params, azure_ad_token, acompletion, logger_fn, headers, custom_prompt_dict, client, organization, custom_llm_provider, drop_params)
735 else:
--> 736 raise e
737 except OpenAIError as e:

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:664, in OpenAIChatCompletion.completion(self, model_response, timeout, optional_params, litellm_params, logging_obj, model, messages, print_verbose, api_key, api_base, api_version, dynamic_params, azure_ad_token, acompletion, logger_fn, headers, custom_prompt_dict, client, organization, custom_llm_provider, drop_params)
650 logging_obj.pre_call(
651 input=messages,
652 api_key=openai_client.api_key,
(...) 658 },
659 )
661 (
662 headers,
663 response,
--> 664 ) = self.make_sync_openai_chat_completion_request(
665 openai_client=openai_client,
666 data=data,
667 timeout=timeout,
668 logging_obj=logging_obj,
669 )
671 logging_obj.model_call_details["response_headers"] = headers

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\litellm_core_utils\logging_utils.py:237, in track_llm_api_timing..decorator..sync_wrapper(*args, **kwargs)
236 try:
--> 237 result = func(*args, **kwargs)
238 return result

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:482, in OpenAIChatCompletion.make_sync_openai_chat_completion_request(self, openai_client, data, timeout, logging_obj)
481 else:
--> 482 raise e

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:464, in OpenAIChatCompletion.make_sync_openai_chat_completion_request(self, openai_client, data, timeout, logging_obj)
463 try:
--> 464 raw_response = openai_client.chat.completions.with_raw_response.create(
465 **data, timeout=timeout
466 )
468 if hasattr(raw_response, "headers"):

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_legacy_response.py:364, in to_raw_response_wrapper..wrapped(*args, **kwargs)
362 kwargs["extra_headers"] = extra_headers
--> 364 return cast(LegacyAPIResponse[R], func(*args, **kwargs))

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_utils_utils.py:287, in required_args..inner..wrapper(*args, **kwargs)
286 raise TypeError(msg)
--> 287 return func(*args, **kwargs)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai\resources\chat\completions\completions.py:1147, in Completions.create(self, messages, model, audio, frequency_penalty, function_call, functions, logit_bias, logprobs, max_completion_tokens, max_tokens, metadata, modalities, n, parallel_tool_calls, prediction, presence_penalty, prompt_cache_key, reasoning_effort, response_format, safety_identifier, seed, service_tier, stop, store, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, verbosity, web_search_options, extra_headers, extra_query, extra_body, timeout)
1146 validate_response_format(response_format)
-> 1147 return self._post(
1148 "/chat/completions",
1149 body=maybe_transform(
1150 {
1151 "messages": messages,
1152 "model": model,
1153 "audio": audio,
1154 "frequency_penalty": frequency_penalty,
1155 "function_call": function_call,
1156 "functions": functions,
1157 "logit_bias": logit_bias,
1158 "logprobs": logprobs,
1159 "max_completion_tokens": max_completion_tokens,
1160 "max_tokens": max_tokens,
1161 "metadata": metadata,
1162 "modalities": modalities,
1163 "n": n,
1164 "parallel_tool_calls": parallel_tool_calls,
1165 "prediction": prediction,
1166 "presence_penalty": presence_penalty,
1167 "prompt_cache_key": prompt_cache_key,
1168 "reasoning_effort": reasoning_effort,
1169 "response_format": response_format,
1170 "safety_identifier": safety_identifier,
1171 "seed": seed,
1172 "service_tier": service_tier,
1173 "stop": stop,
1174 "store": store,
1175 "stream": stream,
1176 "stream_options": stream_options,
1177 "temperature": temperature,
1178 "tool_choice": tool_choice,
1179 "tools": tools,
1180 "top_logprobs": top_logprobs,
1181 "top_p": top_p,
1182 "user": user,
1183 "verbosity": verbosity,
1184 "web_search_options": web_search_options,
1185 },
1186 completion_create_params.CompletionCreateParamsStreaming
1187 if stream
1188 else completion_create_params.CompletionCreateParamsNonStreaming,
1189 ),
1190 options=make_request_options(
1191 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
1192 ),
1193 cast_to=ChatCompletion,
1194 stream=stream or False,
1195 stream_cls=Stream[ChatCompletionChunk],
1196 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_base_client.py:1259, in SyncAPIClient.post(self, path, cast_to, body, options, files, stream, stream_cls)
1256 opts = FinalRequestOptions.construct(
1257 method="post", url=path, json_data=body, files=to_httpx_files(files), **options
1258 )
-> 1259 return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_base_client.py:968, in SyncAPIClient.request(self, cast_to, options, stream, stream_cls)
967 remaining_retries = max_retries - retries_taken
--> 968 request = self._build_request(options, retries_taken=retries_taken)
969 self._prepare_request(request)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_base_client.py:547, in BaseClient._build_request(self, options, retries_taken)
546 # TODO: report this error to httpx
--> 547 return self._client.build_request( # pyright: ignore[reportUnknownMemberType]
548 headers=headers,
549 timeout=self.timeout if isinstance(options.timeout, NotGiven) else options.timeout,
550 method=options.method,
551 url=prepared_url,
552 # the Query type that we use is incompatible with qs'
553 # Params type as it needs to be typed as Mapping[str, object]
554 # so that passing a TypedDict doesn't cause an error.
555 # microsoft/pyright#3526 (comment)
556 params=self.qs.stringify(cast(Mapping[str, Any], params)) if params else None,
557 **kwargs,
558 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\httpx_client.py:359, in BaseClient.build_request(self, method, url, content, data, files, json, params, headers, cookies, timeout, extensions)
358 extensions = dict(**extensions, timeout=timeout.as_dict())
--> 359 return Request(
360 method,
361 url,
362 content=content,
363 data=data,
364 files=files,
365 json=json,
366 params=params,
367 headers=headers,
368 cookies=cookies,
369 extensions=extensions,
370 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\httpx_models.py:338, in Request.init(self, method, url, params, headers, cookies, content, data, files, json, stream, extensions)
337 content_type: typing.Optional[str] = self.headers.get("content-type")
--> 338 headers, stream = encode_request(
339 content=content,
340 data=data,
341 files=files,
342 json=json,
343 boundary=get_multipart_boundary_from_content_type(
344 content_type=content_type.encode(self.headers.encoding)
345 if content_type
346 else None
347 ),
348 )
349 self._prepare(headers)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\httpx_content.py:214, in encode_request(content, data, files, json, boundary)
213 elif json is not None:
--> 214 return encode_json(json)
216 return {}, ByteStream(b"")

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\httpx_content.py:177, in encode_json(json)
176 def encode_json(json: Any) -> Tuple[Dict[str, str], ByteStream]:
--> 177 body = json_dumps(json).encode("utf-8")
178 content_length = str(len(body))

File ~\AppData\Local\Programs\Python\Python311\Lib\json_init_.py:231, in dumps(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
227 if (not skipkeys and ensure_ascii and
228 check_circular and allow_nan and
229 cls is None and indent is None and separators is None and
230 default is None and not sort_keys and not kw):
--> 231 return _default_encoder.encode(obj)
232 if cls is None:

File ~\AppData\Local\Programs\Python\Python311\Lib\json\encoder.py:200, in JSONEncoder.encode(self, o)
197 # This doesn't pass the iterator directly to ''.join() because the
198 # exceptions aren't as detailed. The list call should be roughly
199 # equivalent to the PySequence_Fast that ''.join() would do.
--> 200 chunks = self.iterencode(o, _one_shot=True)
201 if not isinstance(chunks, (list, tuple)):

File ~\AppData\Local\Programs\Python\Python311\Lib\json\encoder.py:258, in JSONEncoder.iterencode(self, o, _one_shot)
254 _iterencode = _make_iterencode(
255 markers, self.default, _encoder, self.indent, floatstr,
256 self.key_separator, self.item_separator, self.sort_keys,
257 self.skipkeys, _one_shot)
--> 258 return _iterencode(o, 0)

File ~\AppData\Local\Programs\Python\Python311\Lib\json\encoder.py:180, in JSONEncoder.default(self, o)
162 """Implement this method in a subclass such that it returns
163 a serializable object for o, or calls the base implementation
164 (to raise a TypeError).
(...) 178
179 """
--> 180 raise TypeError(f'Object of type {o.class.name} '
181 f'is not JSON serializable')

TypeError: Object of type Client is not JSON serializable

During handling of the above exception, another exception occurred:

OpenAIError Traceback (most recent call last)
File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\main.py:2031, in completion(model, messages, timeout, temperature, top_p, n, stream, stream_options, stop, max_completion_tokens, max_tokens, modalities, prediction, audio, presence_penalty, frequency_penalty, logit_bias, user, reasoning_effort, response_format, seed, tools, tool_choice, logprobs, top_logprobs, parallel_tool_calls, web_search_options, deployment_id, extra_headers, functions, function_call, base_url, api_version, api_key, model_list, thinking, **kwargs)
2025 logging.post_call(
2026 input=messages,
2027 api_key=api_key,
2028 original_response=str(e),
2029 additional_args={"headers": headers},
2030 )
-> 2031 raise e
2033 if optional_params.get("stream", False):
2034 ## LOGGING

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\main.py:2004, in completion(model, messages, timeout, temperature, top_p, n, stream, stream_options, stop, max_completion_tokens, max_tokens, modalities, prediction, audio, presence_penalty, frequency_penalty, logit_bias, user, reasoning_effort, response_format, seed, tools, tool_choice, logprobs, top_logprobs, parallel_tool_calls, web_search_options, deployment_id, extra_headers, functions, function_call, base_url, api_version, api_key, model_list, thinking, **kwargs)
2003 else:
-> 2004 response = openai_chat_completions.completion(
2005 model=model,
2006 messages=messages,
2007 headers=headers,
2008 model_response=model_response,
2009 print_verbose=print_verbose,
2010 api_key=api_key,
2011 api_base=api_base,
2012 acompletion=acompletion,
2013 logging_obj=logging,
2014 optional_params=optional_params,
2015 litellm_params=litellm_params,
2016 logger_fn=logger_fn,
2017 timeout=timeout, # type: ignore
2018 custom_prompt_dict=custom_prompt_dict,
2019 client=client, # pass AsyncOpenAI, OpenAI client
2020 organization=organization,
2021 custom_llm_provider=custom_llm_provider,
2022 )
2023 except Exception as e:
2024 ## LOGGING - log the original exception returned

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:747, in OpenAIChatCompletion.completion(self, model_response, timeout, optional_params, litellm_params, logging_obj, model, messages, print_verbose, api_key, api_base, api_version, dynamic_params, azure_ad_token, acompletion, logger_fn, headers, custom_prompt_dict, client, organization, custom_llm_provider, drop_params)
746 error_headers = getattr(error_response, "headers", None)
--> 747 raise OpenAIError(
748 status_code=status_code,
749 message=error_text,
750 headers=error_headers,
751 body=error_body,
752 )

OpenAIError: Object of type Client is not JSON serializable

During handling of the above exception, another exception occurred:

InternalServerError Traceback (most recent call last)
File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\base.py:165, in Agent.generate_code_with_retries(self, query)
164 try:
--> 165 return self.generate_code(query)
166 except Exception as e:

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\base.py:110, in Agent.generate_code(self, query)
108 prompt = get_chat_prompt_for_sql(self._state)
--> 110 code = self._code_generator.generate_code(prompt)
111 self._state.last_prompt_used = prompt

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\core\code_generation\base.py:47, in CodeGenerator.generate_code(self, prompt)
45 self._context.logger.log(f"Stack Trace:\n{stack_trace}")
---> 47 raise e

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\core\code_generation\base.py:34, in CodeGenerator.generate_code(self, prompt)
33 # Generate the code
---> 34 code = self._context.config.llm.generate_code(prompt, self._context)
35 self._context.last_code_generated = code

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\llm\base.py:172, in LLM.generate_code(self, instruction, context)
162 """
163 Generate the code based on the instruction and the given prompt.
164
(...) 170
171 """
--> 172 response = self.call(instruction, context)
173 return self._extract_code(response)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai_litellm\litellm.py:68, in LiteLLM.call(self, instruction, _)
65 user_prompt = instruction.to_string()
67 return (
---> 68 completion(
69 model=self.model,
70 messages=[{"content": user_prompt, "role": "user"}],
71 **self.params,
72 )
73 .choices[0]
74 .message.content
75 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\utils.py:1344, in client..wrapper(*args, **kwargs)
1341 logging_obj.failure_handler(
1342 e, traceback_exception, start_time, end_time
1343 ) # DO NOT MAKE THREADED - router retry fallback relies on this!
-> 1344 raise e

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\utils.py:1219, in client..wrapper(*args, **kwargs)
1218 # MODEL CALL
-> 1219 result = original_function(*args, **kwargs)
1220 end_time = datetime.datetime.now()

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\main.py:3494, in completion(model, messages, timeout, temperature, top_p, n, stream, stream_options, stop, max_completion_tokens, max_tokens, modalities, prediction, audio, presence_penalty, frequency_penalty, logit_bias, user, reasoning_effort, response_format, seed, tools, tool_choice, logprobs, top_logprobs, parallel_tool_calls, web_search_options, deployment_id, extra_headers, functions, function_call, base_url, api_version, api_key, model_list, thinking, **kwargs)
3492 except Exception as e:
3493 ## Map to OpenAI Exception
-> 3494 raise exception_type(
3495 model=model,
3496 custom_llm_provider=custom_llm_provider,
3497 original_exception=e,
3498 completion_kwargs=args,
3499 extra_kwargs=kwargs,
3500 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\litellm_core_utils\exception_mapping_utils.py:2301, in exception_type(model, original_exception, custom_llm_provider, completion_kwargs, extra_kwargs)
2300 setattr(e, "litellm_response_headers", litellm_response_headers)
-> 2301 raise e
2302 else:

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\litellm_core_utils\exception_mapping_utils.py:501, in exception_type(model, original_exception, custom_llm_provider, completion_kwargs, extra_kwargs)
500 exception_mapping_worked = True
--> 501 raise InternalServerError(
502 message=f"InternalServerError: {exception_provider} - {message}",
503 model=model,
504 llm_provider=custom_llm_provider,
505 response=getattr(original_exception, "response", None),
506 litellm_debug_info=extra_information,
507 )
508 elif original_exception.status_code == 503:

InternalServerError: litellm.InternalServerError: InternalServerError: OpenAIException - Object of type Client is not JSON serializable

During handling of the above exception, another exception occurred:

TypeError Traceback (most recent call last)
File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:736, in OpenAIChatCompletion.completion(self, model_response, timeout, optional_params, litellm_params, logging_obj, model, messages, print_verbose, api_key, api_base, api_version, dynamic_params, azure_ad_token, acompletion, logger_fn, headers, custom_prompt_dict, client, organization, custom_llm_provider, drop_params)
735 else:
--> 736 raise e
737 except OpenAIError as e:

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:664, in OpenAIChatCompletion.completion(self, model_response, timeout, optional_params, litellm_params, logging_obj, model, messages, print_verbose, api_key, api_base, api_version, dynamic_params, azure_ad_token, acompletion, logger_fn, headers, custom_prompt_dict, client, organization, custom_llm_provider, drop_params)
650 logging_obj.pre_call(
651 input=messages,
652 api_key=openai_client.api_key,
(...) 658 },
659 )
661 (
662 headers,
663 response,
--> 664 ) = self.make_sync_openai_chat_completion_request(
665 openai_client=openai_client,
666 data=data,
667 timeout=timeout,
668 logging_obj=logging_obj,
669 )
671 logging_obj.model_call_details["response_headers"] = headers

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\litellm_core_utils\logging_utils.py:237, in track_llm_api_timing..decorator..sync_wrapper(*args, **kwargs)
236 try:
--> 237 result = func(*args, **kwargs)
238 return result

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:482, in OpenAIChatCompletion.make_sync_openai_chat_completion_request(self, openai_client, data, timeout, logging_obj)
481 else:
--> 482 raise e

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:464, in OpenAIChatCompletion.make_sync_openai_chat_completion_request(self, openai_client, data, timeout, logging_obj)
463 try:
--> 464 raw_response = openai_client.chat.completions.with_raw_response.create(
465 **data, timeout=timeout
466 )
468 if hasattr(raw_response, "headers"):

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_legacy_response.py:364, in to_raw_response_wrapper..wrapped(*args, **kwargs)
362 kwargs["extra_headers"] = extra_headers
--> 364 return cast(LegacyAPIResponse[R], func(*args, **kwargs))

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_utils_utils.py:287, in required_args..inner..wrapper(*args, **kwargs)
286 raise TypeError(msg)
--> 287 return func(*args, **kwargs)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai\resources\chat\completions\completions.py:1147, in Completions.create(self, messages, model, audio, frequency_penalty, function_call, functions, logit_bias, logprobs, max_completion_tokens, max_tokens, metadata, modalities, n, parallel_tool_calls, prediction, presence_penalty, prompt_cache_key, reasoning_effort, response_format, safety_identifier, seed, service_tier, stop, store, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, verbosity, web_search_options, extra_headers, extra_query, extra_body, timeout)
1146 validate_response_format(response_format)
-> 1147 return self._post(
1148 "/chat/completions",
1149 body=maybe_transform(
1150 {
1151 "messages": messages,
1152 "model": model,
1153 "audio": audio,
1154 "frequency_penalty": frequency_penalty,
1155 "function_call": function_call,
1156 "functions": functions,
1157 "logit_bias": logit_bias,
1158 "logprobs": logprobs,
1159 "max_completion_tokens": max_completion_tokens,
1160 "max_tokens": max_tokens,
1161 "metadata": metadata,
1162 "modalities": modalities,
1163 "n": n,
1164 "parallel_tool_calls": parallel_tool_calls,
1165 "prediction": prediction,
1166 "presence_penalty": presence_penalty,
1167 "prompt_cache_key": prompt_cache_key,
1168 "reasoning_effort": reasoning_effort,
1169 "response_format": response_format,
1170 "safety_identifier": safety_identifier,
1171 "seed": seed,
1172 "service_tier": service_tier,
1173 "stop": stop,
1174 "store": store,
1175 "stream": stream,
1176 "stream_options": stream_options,
1177 "temperature": temperature,
1178 "tool_choice": tool_choice,
1179 "tools": tools,
1180 "top_logprobs": top_logprobs,
1181 "top_p": top_p,
1182 "user": user,
1183 "verbosity": verbosity,
1184 "web_search_options": web_search_options,
1185 },
1186 completion_create_params.CompletionCreateParamsStreaming
1187 if stream
1188 else completion_create_params.CompletionCreateParamsNonStreaming,
1189 ),
1190 options=make_request_options(
1191 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
1192 ),
1193 cast_to=ChatCompletion,
1194 stream=stream or False,
1195 stream_cls=Stream[ChatCompletionChunk],
1196 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_base_client.py:1259, in SyncAPIClient.post(self, path, cast_to, body, options, files, stream, stream_cls)
1256 opts = FinalRequestOptions.construct(
1257 method="post", url=path, json_data=body, files=to_httpx_files(files), **options
1258 )
-> 1259 return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_base_client.py:968, in SyncAPIClient.request(self, cast_to, options, stream, stream_cls)
967 remaining_retries = max_retries - retries_taken
--> 968 request = self._build_request(options, retries_taken=retries_taken)
969 self._prepare_request(request)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\openai_base_client.py:547, in BaseClient._build_request(self, options, retries_taken)
546 # TODO: report this error to httpx
--> 547 return self._client.build_request( # pyright: ignore[reportUnknownMemberType]
548 headers=headers,
549 timeout=self.timeout if isinstance(options.timeout, NotGiven) else options.timeout,
550 method=options.method,
551 url=prepared_url,
552 # the Query type that we use is incompatible with qs'
553 # Params type as it needs to be typed as Mapping[str, object]
554 # so that passing a TypedDict doesn't cause an error.
555 # microsoft/pyright#3526 (comment)
556 params=self.qs.stringify(cast(Mapping[str, Any], params)) if params else None,
557 **kwargs,
558 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\httpx_client.py:359, in BaseClient.build_request(self, method, url, content, data, files, json, params, headers, cookies, timeout, extensions)
358 extensions = dict(**extensions, timeout=timeout.as_dict())
--> 359 return Request(
360 method,
361 url,
362 content=content,
363 data=data,
364 files=files,
365 json=json,
366 params=params,
367 headers=headers,
368 cookies=cookies,
369 extensions=extensions,
370 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\httpx_models.py:338, in Request.init(self, method, url, params, headers, cookies, content, data, files, json, stream, extensions)
337 content_type: typing.Optional[str] = self.headers.get("content-type")
--> 338 headers, stream = encode_request(
339 content=content,
340 data=data,
341 files=files,
342 json=json,
343 boundary=get_multipart_boundary_from_content_type(
344 content_type=content_type.encode(self.headers.encoding)
345 if content_type
346 else None
347 ),
348 )
349 self._prepare(headers)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\httpx_content.py:214, in encode_request(content, data, files, json, boundary)
213 elif json is not None:
--> 214 return encode_json(json)
216 return {}, ByteStream(b"")

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\httpx_content.py:177, in encode_json(json)
176 def encode_json(json: Any) -> Tuple[Dict[str, str], ByteStream]:
--> 177 body = json_dumps(json).encode("utf-8")
178 content_length = str(len(body))

File ~\AppData\Local\Programs\Python\Python311\Lib\json_init_.py:231, in dumps(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
227 if (not skipkeys and ensure_ascii and
228 check_circular and allow_nan and
229 cls is None and indent is None and separators is None and
230 default is None and not sort_keys and not kw):
--> 231 return _default_encoder.encode(obj)
232 if cls is None:

File ~\AppData\Local\Programs\Python\Python311\Lib\json\encoder.py:200, in JSONEncoder.encode(self, o)
197 # This doesn't pass the iterator directly to ''.join() because the
198 # exceptions aren't as detailed. The list call should be roughly
199 # equivalent to the PySequence_Fast that ''.join() would do.
--> 200 chunks = self.iterencode(o, _one_shot=True)
201 if not isinstance(chunks, (list, tuple)):

File ~\AppData\Local\Programs\Python\Python311\Lib\json\encoder.py:258, in JSONEncoder.iterencode(self, o, _one_shot)
254 _iterencode = _make_iterencode(
255 markers, self.default, _encoder, self.indent, floatstr,
256 self.key_separator, self.item_separator, self.sort_keys,
257 self.skipkeys, _one_shot)
--> 258 return _iterencode(o, 0)

File ~\AppData\Local\Programs\Python\Python311\Lib\json\encoder.py:180, in JSONEncoder.default(self, o)
162 """Implement this method in a subclass such that it returns
163 a serializable object for o, or calls the base implementation
164 (to raise a TypeError).
(...) 178
179 """
--> 180 raise TypeError(f'Object of type {o.class.name} '
181 f'is not JSON serializable')

TypeError: Object of type Client is not JSON serializable

During handling of the above exception, another exception occurred:

OpenAIError Traceback (most recent call last)
File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\main.py:2031, in completion(model, messages, timeout, temperature, top_p, n, stream, stream_options, stop, max_completion_tokens, max_tokens, modalities, prediction, audio, presence_penalty, frequency_penalty, logit_bias, user, reasoning_effort, response_format, seed, tools, tool_choice, logprobs, top_logprobs, parallel_tool_calls, web_search_options, deployment_id, extra_headers, functions, function_call, base_url, api_version, api_key, model_list, thinking, **kwargs)
2025 logging.post_call(
2026 input=messages,
2027 api_key=api_key,
2028 original_response=str(e),
2029 additional_args={"headers": headers},
2030 )
-> 2031 raise e
2033 if optional_params.get("stream", False):
2034 ## LOGGING

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\main.py:2004, in completion(model, messages, timeout, temperature, top_p, n, stream, stream_options, stop, max_completion_tokens, max_tokens, modalities, prediction, audio, presence_penalty, frequency_penalty, logit_bias, user, reasoning_effort, response_format, seed, tools, tool_choice, logprobs, top_logprobs, parallel_tool_calls, web_search_options, deployment_id, extra_headers, functions, function_call, base_url, api_version, api_key, model_list, thinking, **kwargs)
2003 else:
-> 2004 response = openai_chat_completions.completion(
2005 model=model,
2006 messages=messages,
2007 headers=headers,
2008 model_response=model_response,
2009 print_verbose=print_verbose,
2010 api_key=api_key,
2011 api_base=api_base,
2012 acompletion=acompletion,
2013 logging_obj=logging,
2014 optional_params=optional_params,
2015 litellm_params=litellm_params,
2016 logger_fn=logger_fn,
2017 timeout=timeout, # type: ignore
2018 custom_prompt_dict=custom_prompt_dict,
2019 client=client, # pass AsyncOpenAI, OpenAI client
2020 organization=organization,
2021 custom_llm_provider=custom_llm_provider,
2022 )
2023 except Exception as e:
2024 ## LOGGING - log the original exception returned

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\llms\openai\openai.py:747, in OpenAIChatCompletion.completion(self, model_response, timeout, optional_params, litellm_params, logging_obj, model, messages, print_verbose, api_key, api_base, api_version, dynamic_params, azure_ad_token, acompletion, logger_fn, headers, custom_prompt_dict, client, organization, custom_llm_provider, drop_params)
746 error_headers = getattr(error_response, "headers", None)
--> 747 raise OpenAIError(
748 status_code=status_code,
749 message=error_text,
750 headers=error_headers,
751 body=error_body,
752 )

OpenAIError: Object of type Client is not JSON serializable

During handling of the above exception, another exception occurred:

InternalServerError Traceback (most recent call last)
Cell In[16], line 2
1 #DEM05 = SmartDataframe(DEM05_data, config={"llm": llm,"enable_cache": True})
----> 2 res = DEM05.chat('What is the 1st row in this dataframe?')

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\smart_dataframe_init_.py:80, in SmartDataframe.chat(self, query, output_type)
61 def chat(self, query: str, output_type: Optional[str] = None):
62 """
63 Run a query on the dataframe.
64 Args:
(...) 78 ValueError: If the query is empty
79 """
---> 80 return self._agent.chat(query, output_type)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\base.py:94, in Agent.chat(self, query, output_type)
88 raise ValueError(
89 "PandasAI API key does not include LLM credits. Please configure an OpenAI or LiteLLM key. "
90 "Learn more at: https://docs.pandas-ai.com/v3/large-language-models#how-to-set-up-any-llm%3F"
91 )
93 self.start_new_conversation()
---> 94 return self._process_query(query, output_type)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\base.py:273, in Agent._process_query(self, query, output_type)
270 self._state.assign_prompt_id()
272 # Generate code
--> 273 code = self.generate_code_with_retries(query)
275 # Execute code with retries
276 result = self.execute_with_retries(code)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\base.py:170, in Agent.generate_code_with_retries(self, query)
168 while attempts <= max_retries:
169 try:
--> 170 return self._regenerate_code_after_error(
171 self._state.last_code_generated, exception
172 )
173 except Exception as e:
174 exception = e

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\agent\base.py:297, in Agent._regenerate_code_after_error(self, code, error)
294 else:
295 prompt = get_correct_error_prompt_for_sql(self._state, code, error_trace)
--> 297 return self._code_generator.generate_code(prompt)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\core\code_generation\base.py:47, in CodeGenerator.generate_code(self, prompt)
44 self._context.logger.log(error_message)
45 self._context.logger.log(f"Stack Trace:\n{stack_trace}")
---> 47 raise e

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\core\code_generation\base.py:34, in CodeGenerator.generate_code(self, prompt)
31 self._context.logger.log(f"Using Prompt: {prompt}")
33 # Generate the code
---> 34 code = self._context.config.llm.generate_code(prompt, self._context)
35 self._context.last_code_generated = code
36 self._context.logger.log(f"Code Generated:\n{code}")

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai\llm\base.py:172, in LLM.generate_code(self, instruction, context)
161 def generate_code(self, instruction: BasePrompt, context: AgentState) -> str:
162 """
163 Generate the code based on the instruction and the given prompt.
164
(...) 170
171 """
--> 172 response = self.call(instruction, context)
173 return self._extract_code(response)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandasai_litellm\litellm.py:68, in LiteLLM.call(self, instruction, _)
52 """Generates a completion response based on the provided instruction.
53
54 This method converts the given instruction into a user prompt string and
(...) 62 Returns:
63 str: The content of the model's response to the user prompt."""
65 user_prompt = instruction.to_string()
67 return (
---> 68 completion(
69 model=self.model,
70 messages=[{"content": user_prompt, "role": "user"}],
71 **self.params,
72 )
73 .choices[0]
74 .message.content
75 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\utils.py:1344, in client..wrapper(*args, **kwargs)
1340 if logging_obj:
1341 logging_obj.failure_handler(
1342 e, traceback_exception, start_time, end_time
1343 ) # DO NOT MAKE THREADED - router retry fallback relies on this!
-> 1344 raise e

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\utils.py:1219, in client..wrapper(*args, **kwargs)
1217 print_verbose(f"Error while checking max token limit: {str(e)}")
1218 # MODEL CALL
-> 1219 result = original_function(*args, **kwargs)
1220 end_time = datetime.datetime.now()
1221 if _is_streaming_request(
1222 kwargs=kwargs,
1223 call_type=call_type,
1224 ):

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\main.py:3494, in completion(model, messages, timeout, temperature, top_p, n, stream, stream_options, stop, max_completion_tokens, max_tokens, modalities, prediction, audio, presence_penalty, frequency_penalty, logit_bias, user, reasoning_effort, response_format, seed, tools, tool_choice, logprobs, top_logprobs, parallel_tool_calls, web_search_options, deployment_id, extra_headers, functions, function_call, base_url, api_version, api_key, model_list, thinking, **kwargs)
3491 return response
3492 except Exception as e:
3493 ## Map to OpenAI Exception
-> 3494 raise exception_type(
3495 model=model,
3496 custom_llm_provider=custom_llm_provider,
3497 original_exception=e,
3498 completion_kwargs=args,
3499 extra_kwargs=kwargs,
3500 )

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\litellm_core_utils\exception_mapping_utils.py:2301, in exception_type(model, original_exception, custom_llm_provider, completion_kwargs, extra_kwargs)
2299 if exception_mapping_worked:
2300 setattr(e, "litellm_response_headers", litellm_response_headers)
-> 2301 raise e
2302 else:
2303 for error_type in litellm.LITELLM_EXCEPTION_TYPES:

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\litellm\litellm_core_utils\exception_mapping_utils.py:501, in exception_type(model, original_exception, custom_llm_provider, completion_kwargs, extra_kwargs)
499 elif original_exception.status_code == 500:
500 exception_mapping_worked = True
--> 501 raise InternalServerError(
502 message=f"InternalServerError: {exception_provider} - {message}",
503 model=model,
504 llm_provider=custom_llm_provider,
505 response=getattr(original_exception, "response", None),
506 litellm_debug_info=extra_information,
507 )
508 elif original_exception.status_code == 503:
509 exception_mapping_worked = True

InternalServerError: litellm.InternalServerError: InternalServerError: OpenAIException - Object of type Client is not JSON serializable
Selection deleted
print(res)

[gdcsinaptik]

To pass LLMs to PandasAI library, depending on the version you are using please make sure to follow either: https://docs.pandas-ai.com/v3/large-language-models for 3.x; or https://docs.pandas-ai.com/v2/llms for 2.x