# Failed to convert text into a Pydantic model with private LLM **URL:** \ **Category:** CrewAI Community Support\ **Created:** [February 14, 2025, 2:05pm UTC](https://community.crewai.com/t/failed-to-convert-text-into-a-pydantic-model-with-private-llm/3845 "2025-02-14T14:05:29Z")\ **Posts on this page:** 6\ **Page:** 1
**Author:** ![adriancappe](https://avatars.discourse-cdn.com/v4/letter/a/ce73a5/32.png) [@adriancappe](https://community.crewai.com/u/adriancappe)\ **Post date:** [February 14, 2025, 2:05pm UTC](https://community.crewai.com/t/failed-to-convert-text-into-a-pydantic-model-with-private-llm/3845/1 "2025-02-14T14:05:29Z")
Hello all, I have configured a crew to "list files from a Sharepoint site, then read that file and lastly provide an executive summary. all my tools are custom and my LLM is private (Azure). the crew woks fine except when in in the task (and some of them) I set output\_pydantic to a Class to get a structured output. there is a very similar situation from another user filed as Bug in Github([[BUG] Pydantic output with azure function calling models failed with litellm auth error · Issue #1572 · crewAIInc/crewAI · GitHub](https://github.com/crewAIInc/crewAI/issues/1572?utm_source=chatgpt.com)) , but no solution has been provided. Here is the out just snipet of the error: indent preformatted text by 4 spaces ```auto Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True'. Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True'. --------------------------------------------------------------------------- AuthenticationError Traceback (most recent call last) File /opt/anaconda3/lib/python3.12/site-packages/litellm/llms/openai/openai.py:707, 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) 706 else: --> 707 raise e 708 except OpenAIError as e: File /opt/anaconda3/lib/python3.12/site-packages/litellm/llms/openai/openai.py:634, 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) 622 logging_obj.pre_call( 623 input=messages, 624 api_key=openai_client.api_key, (...) 630 }, 631 ) 633 headers, response = ( --> 634 self.make_sync_openai_chat_completion_request( 635 openai_client=openai_client, 636 data=data, 637 timeout=timeout, 638 logging_obj=logging_obj, 639 ) 640 ) 642 logging_obj.model_call_details["response_headers"] = headers ..... .... File /opt/anaconda3/lib/python3.12/site-packages/openai/_base_client.py:1064, in SyncAPIClient._request(self, cast_to, options, retries_taken, stream, stream_cls) 1063 log.debug("Re-raising status error") -> 1064 raise self._make_status_error_from_response(err.response) from None 1066 return self._process_response( 1067 cast_to=cast_to, 1068 options=options, (...) 1072 retries_taken=retries_taken, 1073 ) AuthenticationError: Error code: 401 - {'error': {'message': 'Your authentication token is not from a valid issuer.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_issuer'}} During handling of the above exception, another exception occurred: OpenAIError Traceback (most recent call last) File /opt/anaconda3/lib/python3.12/site-packages/litellm/main.py:1626, 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, response_format, seed, tools, tool_choice, logprobs, top_logprobs, parallel_tool_calls, deployment_id, extra_headers, functions, function_call, base_url, api_version, api_key, model_list, **kwargs) 1620 logging.post_call( 1621 input=messages, 1622 api_key=api_key, 1623 original_response=str(e), 1624 additional_args={"headers": headers}, 1625 ) -> 1626 raise e 1628 if optional_params.get("stream", False): 1629 ## LOGGING .... .... 43 if current_attempt < self.max_attempts: 44 return self.to_pydantic(current_attempt + 1) ---> 45 raise ConverterError( 46 f"Failed to convert text into a Pydantic model due to the following error: {e}" 47 ) ConverterError: Failed to convert text into a Pydantic model due to the following error: litellm.BadRequestError: OpenAIException - Error code: 401 - {'error': {'message': 'Your authentication token is not from a valid issuer.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_issuer'}} ``` Here is the code (just part of it for simplicity): ```auto class UseCaseSection(BaseModel): usecase_emoji: str = Field(description="Section emoji (e.g., 🔍, 📊, 🎯)") usecase_title: str = Field(description="Use Case title") usecase_content: str = Field(description="Describe what the use case can deliver, execute or acomplish") key_highlights: List[str] = Field(description="Describe benefits of Use case") UseCaseAgent= Agent( role="IT Use Case Analyst", goal=("Identify and extract IT-related use cases from documeread_file_task" "Output should be in readable markdown documents" ), backstory=( "An expert in IT operations, familiar with networking, security,\ " "and compliance processes. Skilled in analyzing technical documents\ " "to extract key use cases such as device onboarding, configuration\ " "compliance, and software upgrades.\ " "Anything that an action or result is not Device or Network Service related, should not be included as use case.\ " ), allow_delegation=False, memory=memory_set, # Enable memory to store file list for Agent 2 verbose=True, llm=bridgeit_llm ) use_case_task = Task( name="Use Case Identification Task", description=(""" Read the provided document and identify IT-related use cases such as 'Device Onboarding,' 'Configuration Compliance,' 'Software Upgrade,' or similar. Extract and provide a brief description of each use case """ ), agent=UseCaseAgent, expected_output="A structured list of identified IT use cases with summaries.", output_pydantic=UseCaseSection, output_file="UseCaseReport.md", context= [read_file_task], sync_mode=True ) crew = Crew( agents=[PopulateCredentials, FileBrowser, FileReader, UseCaseAgent, SummarizationAgent, Formatter], tasks=[assign_credentials_task, list_files_task, read_file_task,use_case_task, summarize_task, formatting_task], manager_agent=RequestHandler, process=Process.hierarchical, verbose=True, ) print("Inputs to Crew:", params_agent) result = crew.kickoff(inputs=params_agent) ``` Any guidance or ideas on where the problem might reside will greatly help. I really appreciate any help you can provide. Adrian ---
**Author:** ![adriancappe](https://avatars.discourse-cdn.com/v4/letter/a/ce73a5/32.png) [@adriancappe](https://community.crewai.com/u/adriancappe)\ **Post date:** [February 14, 2025, 9:21pm UTC](https://community.crewai.com/t/failed-to-convert-text-into-a-pydantic-model-with-private-llm/3845/2 "2025-02-14T21:21:41Z")
I did some additional digging and I happened to find the reason for the authenticating error. LiteLLM uses in some cases `https://api.openai.com/v1/"` instead of the api\_base I have provided. For some reason, it does it when out\_pydantic is set in the task associated with the agent. How can I force to get the crew to use my private LLM api\_base and not change it ?? Here is a good case… ```auto POST Request Sent from LiteLLM: curl -X POST \ https://myprivate.llm.com \ -d '{'model': 'gpt-4o', 'messages': [{'role': 'system', 'content': 'You are Handle request. You are a skilled Engineer to generate high-level executive summaries Note the documents might already have an Executive summary. Do not use that executive summary, build your own.\nEnsure the summary is properly formatted\nYour personal goal is: Process the user request: {user_request}\nYou ONLY have access to the following tools, ``` HEre is the case where for some reason it decides to use `https://api.openai.com/v1/`: ```auto POST Request Sent from LiteLLM: curl -X POST \ https://api.openai.com/v1/ \ -d '{'model': 'gpt-4o', 'messages': [{'role': 'user', 'content': '{\n "usecase_emoji": "🔧",\n "usecase_title": "Device Onboarding",\n "usecase_content": "The process of integrating a new device into the enterprise network. This includes establishing secure network access, applying initial configuration settings, and verifying the operational status of the device.",\n "key_highlights": ["Establishing secure network access", "Applying initial configuration settings", "Verifying operational status"` ``` thanks in advance! Adrian ---
**Author:** ![Fuad\_Mefleh](https://sea1.discourse-cdn.com/flex025/user_avatar/community.crewai.com/fuad_mefleh/32/695_2.png) [@Fuad\_Mefleh](https://community.crewai.com/u/Fuad_Mefleh)\ **Post date:** [February 14, 2025, 11:04pm UTC](https://community.crewai.com/t/failed-to-convert-text-into-a-pydantic-model-with-private-llm/3845/3 "2025-02-14T23:04:55Z")
Could this issue help fix the problem? > [@Does \`Crew\` Pydantic output require OpenAI](https://community.crewai.com/t/does-crew-pydantic-output-require-openai/791): > > The docs for [Task](https://docs.crewai.com/concepts/tasks#task-attributes) say Outputs a Pydantic model object, requiring an OpenAI client. Only one output format can be set. Does that mean that I cannot use an opensource LLM and get a Pydantic output from a crew? ---
**Author:** ![pedrosimao](https://sea1.discourse-cdn.com/flex025/user_avatar/community.crewai.com/pedrosimao/32/2621_2.png) [@pedrosimao](https://community.crewai.com/u/pedrosimao)\ **Post date:** [February 17, 2025, 2:05pm UTC](https://community.crewai.com/t/failed-to-convert-text-into-a-pydantic-model-with-private-llm/3845/4 "2025-02-17T14:05:22Z")
> [@adriancappe](#): > > out\_pydantic This seems like a simple bug to fix. I wonder if a fix is already been pushed to the github repo… ---
**Author:** ![adriancappe](https://avatars.discourse-cdn.com/v4/letter/a/ce73a5/32.png) [@adriancappe](https://community.crewai.com/u/adriancappe)\ **Post date:** [February 17, 2025, 6:31pm UTC](https://community.crewai.com/t/failed-to-convert-text-into-a-pydantic-model-with-private-llm/3845/5 "2025-02-17T18:31:57Z")
After some additional debugging I was able to identify the problem: You have to define environment variables in the OS shell: ```auto api_key=os.getenv("OPENAI_API_KEY") api_base = os.getenv("OPENAI_API_BASE") llm_model=os.getenv("OPENAI_MODEL_NAME") ``` Initially, I had only the api\_key. in this case some LLM calls would work and some would not I’ll expand in a later post all the details. But it seems a bug. ---
**Author:** ![system](https://us1.discourse-cdn.com/flex025/uploads/crewai/original/1X/ecda97e72f77c7100e0a761444b1c991925cc789.png) [@system](https://community.crewai.com/u/system)\ **Post date:** [February 18, 2025, 6:33pm UTC](https://community.crewai.com/t/failed-to-convert-text-into-a-pydantic-model-with-private-llm/3845/7 "2025-02-18T18:33:59Z")
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