When using the demo for testing, an error occurred: "columns_and_tables_needed = orjson.loads orjson.JSONDecodeError: unexpected character: line 1 column 1". #1426

wxp2023 · 2025-03-19T06:26:42Z

My question is '‌Information of the three individuals with the highest salaries'
The log content is as follows:

I0319 06:15:48.781 8 wren-ai-service:298] db_schemas token count is greater than 100,000, so we will prune columns
INFO:     172.25.0.3:57886 - "GET /v1/asks/21ad676d-2688-4764-a9c2-f11255ddab8d/result HTTP/1.1" 200 OK
********************************************************************************
> construct_retrieval_results [src.pipelines.retrieval.retrieval.construct_retrieval_results()] encountered an error<
> Node inputs:
{'check_using_db_schemas_without_pruning': "<Task finished name='Task-581' "
                                           'coro=<AsyncGraphAda...',
 'construct_db_schemas': "<Task finished name='Task-580' "
                         'coro=<AsyncGraphAda...',
 'dbschema_retrieval': "<Task finished name='Task-579' coro=<AsyncGraphAda...",
 'filter_columns_in_tables': "<Task finished name='Task-583' "
                             'coro=<AsyncGraphAda...'}
********************************************************************************
Traceback (most recent call last):
  File "/app/.venv/lib/python3.12/site-packages/hamilton/async_driver.py", line 122, in new_fn
    await fn(**fn_kwargs) if asyncio.iscoroutinefunction(fn) else fn(**fn_kwargs)
                                                                  ^^^^^^^^^^^^^^^
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 256, in sync_wrapper
    self._handle_exception(observation, e)
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 520, in _handle_exception
    raise e
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 254, in sync_wrapper
    result = func(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^
  File "/src/pipelines/retrieval/retrieval.py", line 334, in construct_retrieval_results
    columns_and_tables_needed = orjson.loads(
                                ^^^^^^^^^^^^^
orjson.JSONDecodeError: unexpected character: line 1 column 1 (char 0)
-------------------------------------------------------------------
Oh no an error! Need help with Hamilton?
Join our slack and ask for help! https://join.slack.com/t/hamilton-opensource/shared_invite/zt-2niepkra8-DGKGf_tTYhXuJWBTXtIs4g
-------------------------------------------------------------------
E0319 06:15:50.792 8 wren-ai-service:529] ask pipeline - OTHERS: unexpected character: line 1 column 1 (char 0)
Traceback (most recent call last):
  File "/src/web/v1/services/ask.py", line 318, in ask
    retrieval_result = await self._pipelines["retrieval"].run(
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 219, in async_wrapper
    self._handle_exception(observation, e)
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 520, in _handle_exception
    raise e
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 217, in async_wrapper
    result = await func(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/src/pipelines/retrieval/retrieval.py", line 485, in run
    return await self._pipe.execute(
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/app/.venv/lib/python3.12/site-packages/hamilton/async_driver.py", line 375, in execute
    raise e
  File "/app/.venv/lib/python3.12/site-packages/hamilton/async_driver.py", line 366, in execute
    outputs = await self.raw_execute(_final_vars, overrides, display_graph, inputs=inputs)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/app/.venv/lib/python3.12/site-packages/hamilton/async_driver.py", line 326, in raw_execute
    raise e
  File "/app/.venv/lib/python3.12/site-packages/hamilton/async_driver.py", line 321, in raw_execute
    results = await await_dict_of_tasks(task_dict)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/app/.venv/lib/python3.12/site-packages/hamilton/async_driver.py", line 23, in await_dict_of_tasks
    coroutines_gathered = await asyncio.gather(*coroutines)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/app/.venv/lib/python3.12/site-packages/hamilton/async_driver.py", line 36, in process_value
    return await val
           ^^^^^^^^^
  File "/app/.venv/lib/python3.12/site-packages/hamilton/async_driver.py", line 122, in new_fn
    await fn(**fn_kwargs) if asyncio.iscoroutinefunction(fn) else fn(**fn_kwargs)
                                                                  ^^^^^^^^^^^^^^^
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 256, in sync_wrapper
    self._handle_exception(observation, e)
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 520, in _handle_exception
    raise e
  File "/app/.venv/lib/python3.12/site-packages/langfuse/decorators/langfuse_decorator.py", line 254, in sync_wrapper
    result = func(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^
  File "/src/pipelines/retrieval/retrieval.py", line 334, in construct_retrieval_results
    columns_and_tables_needed = orjson.loads(
                                ^^^^^^^^^^^^^
orjson.JSONDecodeError: unexpected character: line 1 column 1 (char 0)

The.env configuration is as follows:

COMPOSE_PROJECT_NAME=wrenai
PLATFORM=linux/amd64

PROJECT_DIR=.

# service port
WREN_ENGINE_PORT=8080
WREN_ENGINE_SQL_PORT=7432
WREN_AI_SERVICE_PORT=5555
WREN_UI_PORT=3000
IBIS_SERVER_PORT=8000
WREN_UI_ENDPOINT=http://wren-ui:${WREN_UI_PORT}

# ai service settings
QDRANT_HOST=qdrant
SHOULD_FORCE_DEPLOY=1

# vendor keys
LLM_OPENAI_API_KEY=
EMBEDDER_OPENAI_API_KEY=
LLM_AZURE_OPENAI_API_KEY=
EMBEDDER_AZURE_OPENAI_API_KEY=
QDRANT_API_KEY=

# version
# CHANGE THIS TO THE LATEST VERSION
WREN_PRODUCT_VERSION=0.16.0
WREN_ENGINE_VERSION=0.14.5
WREN_AI_SERVICE_VERSION=0.16.2
IBIS_SERVER_VERSION=0.14.5
WREN_UI_VERSION=0.21.0
WREN_BOOTSTRAP_VERSION=0.1.5

# user id (uuid v4)
USER_UUID=

# for other services
POSTHOG_API_KEY=phc_nhF32aj4xHXOZb0oqr2cn4Oy9uiWzz6CCP4KZmRq9aE
POSTHOG_HOST=https://app.posthog.com
TELEMETRY_ENABLED=true
# this is for telemetry to know the model, i think ai-service might be able to provide a endpoint to get the information
GENERATION_MODEL=gpt-4o-mini
LANGFUSE_SECRET_KEY=
LANGFUSE_PUBLIC_KEY=

# the port exposes to the host
# OPTIONAL: change the port if you have a conflict
HOST_PORT=3000
AI_SERVICE_FORWARD_PORT=5555

# Wren UI
EXPERIMENTAL_ENGINE_RUST_VERSION=false

LLM_OLLAMA_API_KEY=random
EMBEDDER_OLLAMA_API_KEY=random
EMBEDDER_OLLAMA_URL=http://132.120.139.194:11434
LLM_OLLAMA_URL=http://132.120.132.44:11434
OPENAI_API_KEY=dummy-key

The config configuration is as follows:

type: llm
provider: litellm_llm
timeout: 120
models:
- model: openai/qwen2.5:7b
  api_base: http://132.120.132.44:11434/v1
  api_key_name: LLM_OLLAMA_API_KEY
  kwargs:
    temperature: 0
    n: 1
    # for better consistency of llm response, refer: https://platform.openai.com/docs/api-reference/chat/create#chat-create-seed
#    seed: 0
#    max_tokens: 4096
- model: gpt-4o-2024-08-06
  api_base: https://api.openai.com/v1
  api_key_name: LLM_OPENAI_API_KEY
  kwargs:
    temperature: 0
    n: 1
    # for better consistency of llm response, refer: https://platform.openai.com/docs/api-reference/chat/create#chat-create-seed
    seed: 0
    max_tokens: 4096
- model: o3-mini-2025-01-31
  api_base: https://api.openai.com/v1
  api_key_name: LLM_OPENAI_API_KEY
  kwargs:
    n: 1
    seed: 0
    max_completion_tokens: 4096
    reasoning_effort: low

---
type: embedder
provider: litellm_embedder
models:
- model: openai/bge-m3:567m-fp16
  api_base: http://132.120.139.194:11434/v1
  api_key_name: EMBEDDER_OLLAMA_API_KEY
  timeout: 120

---
type: engine
provider: wren_ui
endpoint: http://wren-ui:3000

---
type: document_store
provider: qdrant
location: http://qdrant:6333
embedding_model_dim: 1024
timeout: 120
recreate_index: true

---
type: pipeline
pipes:
  - name: db_schema_indexing
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
    document_store: qdrant
  - name: historical_question_indexing
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
    document_store: qdrant
  - name: table_description_indexing
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
    document_store: qdrant
  - name: db_schema_retrieval
    llm: litellm_llm.openai/qwen2.5:7b
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
    document_store: qdrant
  - name: historical_question_retrieval
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
    document_store: qdrant
  - name: sql_generation
    llm: litellm_llm.openai/qwen2.5:7b
    engine: wren_ui
  - name: sql_correction
    llm: litellm_llm.openai/qwen2.5:7b
    engine: wren_ui
  - name: followup_sql_generation
    llm: litellm_llm.openai/qwen2.5:7b
    engine: wren_ui
  - name: sql_summary
    llm: litellm_llm.openai/qwen2.5:7b
  - name: sql_answer
    llm: litellm_llm.openai/qwen2.5:7b
  - name: sql_breakdown
    llm: litellm_llm.openai/qwen2.5:7b
    engine: wren_ui
  - name: sql_expansion
    llm: litellm_llm.openai/qwen2.5:7b
    engine: wren_ui
  - name: semantics_description
    llm: litellm_llm.openai/qwen2.5:7b
  - name: relationship_recommendation
    llm: litellm_llm.openai/qwen2.5:7b
    engine: wren_ui
  - name: question_recommendation
    llm: litellm_llm.openai/qwen2.5:7b
  - name: question_recommendation_db_schema_retrieval
    llm: litellm_llm.openai/qwen2.5:7b
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
    document_store: qdrant
  - name: question_recommendation_sql_generation
    llm: litellm_llm.openai/qwen2.5:7b
    engine: wren_ui
  - name: intent_classification
    llm: litellm_llm.openai/qwen2.5:7b
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
    document_store: qdrant
  - name: data_assistance
    llm: litellm_llm.openai/qwen2.5:7b
  - name: sql_pairs_indexing
    document_store: qdrant
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
  - name: sql_pairs_retrieval
    document_store: qdrant
    embedder: litellm_embedder.openai/bge-m3:567m-fp16
    llm: litellm_llm.openai/qwen2.5:7b
  - name: preprocess_sql_data
    llm: litellm_llm.openai/qwen2.5:7b
  - name: sql_executor
    engine: wren_ui
  - name: chart_generation
    llm: litellm_llm.openai/qwen2.5:7b
  - name: chart_adjustment
    llm: litellm_llm.openai/qwen2.5:7b
  - name: sql_question_generation
    llm: litellm_llm.openai/qwen2.5:7b
  - name: sql_generation_reasoning
    llm: litellm_llm.openai/qwen2.5:7b
  - name: sql_regeneration
    llm: litellm_llm.openai/qwen2.5:7b
    engine: wren_ui

---
settings:
  engine_timeout: 30
  column_indexing_batch_size: 50
  table_retrieval_size: 10
  table_column_retrieval_size: 100
  allow_using_db_schemas_without_pruning: false
  query_cache_maxsize: 1000
  query_cache_ttl: 3600
  langfuse_host: https://cloud.langfuse.com
  langfuse_enable: true
  logging_level: DEBUG
  development: false

The text was updated successfully, but these errors were encountered:

cyyeh · 2025-03-19T13:48:22Z

@wxp2023 you could setup langfuse through this doc first: https://docs.getwren.ai/oss/ai_service/guide/langfuse_setup
in simple words, the error message means that your llm generates malformed json output. After you setup langfuse, you could check the error details yourself.

zhenglu696 · 2025-03-27T11:52:26Z

@cyyeh could you help me check this config.yaml ,when I use deepseek model. error followes：

--config.yaml---
type: llm
provider: litellm_llm
models:

put DEEPSEEK_API_KEY=<your_api_key> in ~/.wrenai/.env

api_base: https://api.deepseek.com/v1
model: deepseek/deepseek-reasoner
alias: default
timeout: 120
kwargs:
n: 1
temperature: 0
response_format:
type: text
api_base: https://api.deepseek.com/v1
model: deepseek/deepseek-chat
timeout: 120
kwargs:
n: 1
temperature: 0
response_format:
type: text
api_base: https://api.deepseek.com/v1
model: deepseek/deepseek-coder
timeout: 120
kwargs:
n: 1
temperature: 0
response_format:
type: json_object

type: embedder
provider: litellm_embedder
models:

model: deepseek/deepseek-r1-distill-qwen-14b # put your embedding model name here, if it is not openai embedding model, should be /<model_name>
alias: default
api_base: https://api.deepseek.com/v1 # change this according to your embedding model
timeout: 120

type: engine
provider: wren_ui
endpoint: http://wren-ui:3000

type: engine
provider: wren_ibis
endpoint: http://wren-ibis:8000

type: document_store
provider: qdrant
location: http://qdrant:6333
embedding_model_dim: 3072 # put your embedding model dimension here
timeout: 120
recreate_index: true

type: pipeline
pipes:

name: db_schema_indexing
embedder: litellm_embedder.default
document_store: qdrant
name: historical_question_indexing
embedder: litellm_embedder.default
document_store: qdrant
name: table_description_indexing
embedder: litellm_embedder.default
document_store: qdrant
name: db_schema_retrieval
llm: litellm_llm.default
embedder: litellm_embedder.default
document_store: qdrant
name: historical_question_retrieval
embedder: litellm_embedder.default
document_store: qdrant
name: sql_generation
llm: litellm_llm.default
engine: wren_ui
name: sql_correction
llm: litellm_llm.default
engine: wren_ui
name: followup_sql_generation
llm: litellm_llm.default
engine: wren_ui
name: sql_summary
llm: litellm_llm.default
name: sql_answer
llm: litellm_llm.default
engine: wren_ui
name: sql_breakdown
llm: litellm_llm.default
engine: wren_ui
name: sql_expansion
llm: litellm_llm.default
engine: wren_ui
name: semantics_description
llm: litellm_llm.default
name: relationship_recommendation
llm: litellm_llm.default
engine: wren_ui
name: question_recommendation
llm: litellm_llm.default
name: question_recommendation_db_schema_retrieval
llm: litellm_llm.default
embedder: litellm_embedder.default
document_store: qdrant
name: question_recommendation_sql_generation
llm: litellm_llm.default
engine: wren_ui
name: chart_generation
llm: litellm_llm.default
name: chart_adjustment
llm: litellm_llm.default
name: intent_classification
llm: litellm_llm.default
embedder: litellm_embedder.default
document_store: qdrant
name: data_assistance
llm: litellm_llm.default
name: sql_pairs_indexing
document_store: qdrant
embedder: litellm_embedder.default
name: sql_pairs_retrieval
document_store: qdrant
embedder: litellm_embedder.default
llm: litellm_llm.default
name: preprocess_sql_data
llm: litellm_llm.default
name: sql_executor
engine: wren_ui
name: sql_question_generation
llm: litellm_llm.default
name: sql_generation_reasoning
llm: litellm_llm.default
name: followup_sql_generation_reasoning
llm: litellm_llm.default
name: sql_regeneration
llm: litellm_llm.default
engine: wren_ui
name: instructions_indexing
embedder: litellm_embedder.default
document_store: qdrant
name: instructions_retrieval
embedder: litellm_embedder.default
document_store: qdrant
name: sql_functions_retrieval
engine: wren_ibis
document_store: qdrant
name: project_meta_indexing
document_store: qdrant

settings:
column_indexing_batch_size: 50
table_retrieval_size: 10
table_column_retrieval_size: 100
allow_using_db_schemas_without_pruning: false # if you want to use db schemas without pruning, set this to true. It will be faster
allow_intent_classification: true
allow_sql_generation_reasoning: true
query_cache_maxsize: 1000
query_cache_ttl: 3600
langfuse_host: https://cloud.langfuse.com
langfuse_enable: true
logging_level: DEBUG
development: true
historical_question_retrieval_similarity_threshold: 0.9
sql_pairs_similarity_threshold: 0.7
sql_pairs_retrieval_max_size: 10
instructions_similarity_threshold: 0.7
instructions_top_k: 10

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When using the demo for testing, an error occurred: "columns_and_tables_needed = orjson.loads orjson.JSONDecodeError: unexpected character: line 1 column 1". #1426

When using the demo for testing, an error occurred: "columns_and_tables_needed = orjson.loads orjson.JSONDecodeError: unexpected character: line 1 column 1". #1426

wxp2023 commented Mar 19, 2025 •

edited

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cyyeh commented Mar 19, 2025

zhenglu696 commented Mar 27, 2025

When using the demo for testing, an error occurred: "columns_and_tables_needed = orjson.loads orjson.JSONDecodeError: unexpected character: line 1 column 1". #1426

When using the demo for testing, an error occurred: "columns_and_tables_needed = orjson.loads orjson.JSONDecodeError: unexpected character: line 1 column 1". #1426

Comments

wxp2023 commented Mar 19, 2025 • edited Loading

cyyeh commented Mar 19, 2025

zhenglu696 commented Mar 27, 2025

put DEEPSEEK_API_KEY=<your_api_key> in ~/.wrenai/.env

wxp2023 commented Mar 19, 2025 •

edited

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