llm Errors

104 entries

Error Code Domain Category Fix Rate Confidence Tier
LLM API response format changes between calls or after model updates — llm api_stability 65% 78% ai_generated
openai.APITimeoutError: Request timed out — llm api_error 70% 85% ai_generated
openai.BadRequestError: This model's maximum context length is 128000 tokens — llm api_error 88% 90% ai_generated
Error: input exceeds maximum context length — llm input_error 85% 88% ai_generated
LLM response quality degrades sharply without any error when approaching context limit — llm context_management 68% 82% ai_generated
RAG retrieval misses relevant docs — cosine similarity threshold too high — llm retrieval 82% 85% ai_generated
Cosine similarity returns nonsense results or vector DB rejects insert due to dimension mismatch — llm embedding 90% 92% ai_generated
ValueError: shapes (1,1536) and (1,768) not aligned — llm config_error 90% 88% ai_generated
Fine-tuned model loses base capabilities after training on domain-specific data — llm fine_tuning 62% 78% ai_generated
Training loss diverging: NaN or increasing — llm training_error 75% 80% ai_generated
InvalidRequestError: function schema validation failed — llm schema_error 85% 88% ai_generated
Verification failed: LLM cited non-existent source — llm output_error 50% 65% ai_generated
Factual inconsistency detected in LLM output — llm quality_error 70% 75% ai_generated
json.decoder.JSONDecodeError: Expecting value when parsing LLM output — llm parsing_error 82% 88% ai_generated
OutOfMemoryError: cannot load model weights — llm memory_error 80% 84% ai_generated
BillingError: Image input token count exceeded budget — llm cost_error 82% 80% ai_generated
json.decoder.JSONDecodeError when parsing OpenAI function call arguments in streaming mode — llm streaming 88% 90% ai_generated
Prompt injection attempt detected in user input — llm security_error 72% 78% ai_generated
LLM output contained system prompt content — llm security_error 45% 70% ai_generated
System prompt leaked via prompt injection — user input not sanitized — llm security 60% 85% ai_generated
Quantized model output quality degraded significantly — llm quality_error 75% 80% ai_generated
RAG retrieval returns irrelevant results despite relevant documents existing in the index — llm retrieval 82% 88% ai_generated
RAG: retrieved context irrelevant to query — llm quality_error 75% 80% ai_generated
Error 429: Too Many Requests - Rate limit exceeded — llm rate_limit_error 88% 90% ai_generated
openai.RateLimitError: Rate limit reached for model — llm api_error 85% 88% ai_generated
JSON parse error during streaming — incomplete JSON in stream chunk — llm streaming 90% 92% ai_generated
Error: Failed to parse SSE stream: unexpected end of data — llm runtime_error 80% 82% ai_generated
UnicodeDecodeError: incomplete multi-byte sequence in stream — llm runtime_error 82% 86% ai_generated
LLM returns values not in the specified enum when generating structured JSON output — llm structured_output 72% 80% ai_generated
LLM ignores system prompt instructions when user message or context is very long — llm prompt_engineering 65% 80% ai_generated
LLM produces different outputs for identical prompts even with temperature=0 — llm reproducibility 60% 85% ai_generated
tiktoken token count doesn't match actual API token usage in response — llm token_counting 70% 82% ai_generated
InvalidRequestError: total tokens exceed model maximum — llm input_error 85% 88% ai_generated
Input silently truncated — total tokens exceed model context window — llm context_management 88% 90% ai_generated
Warning: Input truncated to max_tokens limit — llm config_error 82% 85% ai_generated
JSONDecodeError: Expecting property name at position N — llm runtime_error 78% 80% ai_generated
Tool results conflict — parallel tool calls create race condition — llm function_calling 80% 85% ai_generated
Error: context length exceeded while processing streaming chunks — partial response returned — llm runtime_error 80% 85% ai_generated
InvalidRequestError: function_call arguments must be valid JSON — streaming mode detected malformed JSON — llm data_error 85% 88% ai_generated
ValueError: Token indices sequence length is longer than the specified maximum sequence length — tiktoken vs transformers mismatch — llm type_error 88% 86% ai_generated
Error 429: Rate limit exceeded — Retry-After header missing or malformed — llm network_error 87% 84% ai_generated
ValueError: Query vector dimension (384) does not match index dimension (768) — llm type_error 90% 87% ai_generated
LLM returns value 'medium' not in allowed enum ['low', 'high'] when using JSON mode with constrained decoding — llm data_error 92% 86% ai_generated
openai.BadRequestError: logprobs is not supported when using response_format parameter — llm api_error 95% 88% ai_generated
Warning: seed parameter may not produce deterministic results with temperature close to 0 — llm runtime_error 75% 85% ai_generated
chromadb.errors.DimensionError: Inserted embedding dimension (1536) does not match collection dimension (768) — llm data_error 95% 90% ai_generated
KeyError: 'content' in streaming response chunk — llm runtime_error 90% 87% ai_generated
json.decoder.JSONDecodeError: Unterminated string starting at: line 1 column 1023 (char 1022) in function call arguments stream — llm encoding_error 85% 90% ai_generated
Warning: Prompt caching disabled because system message changed between requests — llm runtime_error 90% 86% ai_generated
openai.BadRequestError: 'response_format' parameter is not supported when using 'tools' parameter — llm config_error 85% 88% ai_generated
Warning: Input text truncated to 8192 tokens for embedding model 'text-embedding-3-small' — embedding quality may degrade — llm data_error 80% 85% ai_generated
Error: Parallel function calls require distinct function names — duplicate 'get_weather' detected — llm config_error 80% 82% ai_generated
KeyError: 'content' — streaming response chunk missing 'content' field in assistant message delta — llm runtime_error 90% 87% ai_generated
PermissionError: [Errno 13] Permission denied: '/app/data/index_store.json' — LlamaIndex cannot persist index to storage — llm system_error 90% 84% ai_generated
OutputParserException: Parsing LLM output produced by 'StructuredOutputParser' failed — value 'large' not in enum ['small', 'medium'] — llm data_error 80% 86% ai_generated
ValueError: Pooling mode 'mean' not supported for this model. Expected 'cls' pooling. — llm type_error 80% 85% ai_generated
KeyError: 'tokenizer_vocab_size' not found in model config for fine-tuning — llm config_error 85% 88% ai_generated
botocore.exceptions.ClientError: An error occurred (AccessDenied) when calling the PutObject operation: Access Denied AccessDenied llm auth_error 90% 90% ai_generated
ValidationError: 1 validation error for ResponseModel color Input should be 'red', 'green', or 'blue' [type=enum, input_value='purple', input_type=str] — llm data_error 75% 82% ai_generated
Warning: Using cached embedding from version 1.0.0, but current model is version 2.0.0. Embedding may be stale. — llm runtime_error 85% 84% ai_generated
InvalidRequestError: Function schema '$defs/Location' not found in definitions. Nested $ref not resolved. — llm config_error 85% 87% ai_generated
chromadb.errors.InternalError: Index corruption detected. Rebuild required. CHROMA-ERR-0042 llm data_error 82% 85% ai_generated
llama_index.core.ingestion.pipeline.IngestionCacheMiss: Cache miss for node 'node_abc123'. Re-processing. LLAMA-ERR-0091 llm runtime_error 78% 82% ai_generated
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU 0 has 8.00 GiB total capacity; 7.80 GiB already allocated. CUDA-OOM-001 llm resource_error 88% 90% ai_generated
openai.BadRequestError: Error code: 400 - {'error': {'message': "Invalid 'response_format': 'type' must be one of ['text', 'json_object', 'json_schema'].", 'type': 'invalid_request_error'}} OAI-ERR-0400 llm config_error 90% 88% ai_generated
langchain_core.exceptions.ToolException: Tool 'search_tool' called with missing required arguments. Expected: ['query'], got: []. LANG-ERR-0078 llm runtime_error 76% 83% ai_generated
llama_cpp.llama_cpp.LlamaError: Model file 'model.gguf' is not a valid GGUF file or is corrupted. Expected magic number 0x46554747, got 0x00000000. LLAMA-CPP-ERR-0003 llm install_error 92% 87% ai_generated
openai.AuthenticationError: Incorrect API key provided: sk-... You can find your API key at https://platform.openai.com/account/api-keys. — llm auth_error 95% 90% ai_generated
openai.RateLimitError: You exceeded your current quota, please check your plan and billing details. — llm resource_error 85% 88% ai_generated
llama_index.core.storage.kvstore.simple_kvstore:ValueError: The 'index_store.json' file is corrupted or contains invalid JSON. — llm data_error 75% 85% ai_generated
openai.BadRequestError: Invalid schema for response_format: 'properties' must be an object with string keys. — llm config_error 90% 90% ai_generated
OSError: Can't load the model 'meta-llama/Llama-2-7b-chat-hf'. If you were trying to load it from 'https://huggingface.co/models', make sure you have access to the model and are logged in. — llm auth_error 85% 90% ai_generated
Error: Incomplete stream response - expected more data but connection closed unexpectedly. — llm network_error 80% 85% ai_generated
LLM hallucinates values for optional fields in structured output when field is missing from context — llm data_error 82% 88% ai_generated
ValueError: Could not load tokenizer cache from /home/user/.cache/huggingface/hub — file is corrupted or truncated — llm resource_error 88% 85% ai_generated
RAG hybrid search returns no results because dense and sparse scores are on different scales — llm data_error 80% 87% ai_generated
json.decoder.JSONDecodeError: Expecting property name enclosed in double quotes: line 1 column 1024 (char 1023) when parsing streaming function call arguments — llm protocol_error 85% 89% ai_generated
openai.BadRequestError: vector length must be 1 for cosine similarity — llm data_error 80% 85% ai_generated
openai.BadRequestError: function_call arguments must be valid JSON - truncated input detected — llm input_error 85% 88% ai_generated
Error: streaming response chunk order mismatch - expected index 5 but got 7 — llm protocol_error 75% 82% ai_generated
KeyError: 'tokenizer_vocab_size' not found in model config — llm config_error 90% 87% ai_generated
ValidationError: 1 validation error for ToolCall value Input should be a valid integer [type=int_parsing, input_value='42.5', input_type=str] — llm type_error 80% 86% ai_generated
ValueError: Encountered unknown token ID 100000 in cached sequence. Tokenizer vocabulary mismatch. — llm data_error 80% 85% ai_generated
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU 0 has a total capacity of 79.15 GiB of which 2.00 GiB is free. Including non-blocking allocations, current allocated: 77.15 GiB. — llm resource_error 85% 88% ai_generated
OutputParserException: Parsing LLM output produced by 'PydanticOutputParser' failed. Error: 1 validation error for WeatherResponse temperature Input should be a valid number [type=float_type, input_value='72.5°F', input_type=str] — llm data_error 78% 82% ai_generated
ValueError: Embedding dimension mismatch: index has dimension 1536 but new embeddings have dimension 768. Rebuild index or set allow_dangerous_deserialization=True. — llm data_error 90% 87% ai_generated
ValueError: The tokenizer's chat_template is not compatible with the model's expected format. Expected 'llama' format, got 'chatml'. — llm config_error 92% 90% ai_generated
json.decoder.JSONDecodeError: Expecting property name at position N — llm data_error 85% 81% ai_generated
chromadb.errors.DimensionError: Inserted embedding dimension (512) does not match collection dimension (768) DimensionError llm data_error 85% 88% ai_generated
ValueError: You have to provide either 'max_length' or 'padding' and 'truncation' to use padding side 'left' with batch size > 1 — llm config_error 85% 88% ai_generated
RuntimeError: OutOfMemoryError: Unable to allocate memory for KV cache block. Requested block size: 16, free blocks: 0 — llm resource_error 80% 85% ai_generated
ValidationError: 1 validation error for ResponseModel name Field required [type=missing, input_value={'title': 'Test'}, input_type=dict] — llm data_error 82% 87% ai_generated
error: failed to load model: incompatible GGUF version: model version is 3, but llama.cpp supports version 2 — llm install_error 95% 90% ai_generated
Error: pull model manifest: file does not exist: /usr/share/ollama/.ollama/models/blobs/sha256-... — llm install_error 88% 86% ai_generated
ValueError: Embedding dimension mismatch: query embedding dimension (384) does not match index embedding dimension (768) — llm config_error 90% 89% ai_generated
Warning: Token count mismatch — prompt tokens (4500) + completion tokens (1200) = 5700, but API reports total_tokens=5800 — llm data_error 75% 82% ai_generated
openai.BadRequestError: Invalid parameter: value for parameter 'temperature' is not a valid number: 'hot' — llm type_error 80% 88% ai_generated
openai.BadRequestError: Invalid training file: 'messages' must be a list of objects, but got <class 'str'> for line 42 — llm data_error 88% 90% ai_generated
openai.BadRequestError: Invalid schema for response_format: 'properties' must be an object invalid_response_format llm config_error 88% 85% ai_generated
OSError: Unable to load weights from huggingface checkpoint. Error: file is corrupted or truncated — llm resource_error 90% 82% ai_generated
ValueError: Cannot create Document from empty text. Node content is None or empty string. — llm data_error 92% 88% ai_generated
TypeError: 'NoneType' object is not iterable in tool call arguments parsing — llm type_error 87% 84% ai_generated
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU 0 has a total capacity of 79.15 GiB of which 0 bytes is free. CUDA OOM llm resource_error 80% 86% ai_generated
openai.NotFoundError: Resource not found. Deployment '<deployment-name>' does not exist. DeploymentNotFound llm config_error 95% 90% ai_generated