Error : Logger._log() got an unexpected keyword argument 'index'

[Dharmik-Solanki]

Trying to use wren ai with google gemini API, So i downloaded config file & edited accordingly also updated .env file with ( GEMINI_API_KEY=<your_api_key> ).

after that i launched wren AI with launcher application (On windows). Prompt the and asked it .So it will generate explanation but failed to generate SQL and showing the below error described in image .

---

config file:

##

# please upgrade the version of wren-ai-service to at least 0.15.10 first
# you should rename this file to config.yaml and put it in ~/.wrenai
# please pay attention to the comments starting with # and adjust the config accordingly, 3 steps basically:
# 1. you need to use your own llm and embedding models
# 2. you need to use the correct pipe definitions based on https://raw.githubusercontent.com/canner/WrenAI/<WRENAI_VERSION_NUMBER>/docker/config.example.yaml
# 3. you need to fill in correct llm and embedding models in the pipe definitions

type: llm
provider: litellm_llm
models:
  # put GEMINI_API_KEY=<your_api_key> in ~/.wrenai/.env
  - model: gemini/gemini-2.0-flash # gemini/<gemini_model_name>
    alias: default
    timeout: 120
    kwargs:
      n: 1
      temperature: 0
  - model: gemini/gemini-2.0-flash # gemini/<gemini_model_name>
    alias: gemini-llm-for-chart
    timeout: 120
    kwargs:
      n: 1
      temperature: 0
      response_format:
        type: json_object

---
type: embedder
provider: litellm_embedder
models:
  # put GEMINI_API_KEY=<your_api_key> in ~/.wrenai/.env
  - model: gemini/text-embedding-004 # gemini/<gemini_model_name>
    alias: default
    api_base: https://generativelanguage.googleapis.com/v1beta/openai # change this according to your embedding model(cloud.google.com/go/ai/generativelanguage/apiv1beta2)
    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: 768 # put your embedding model dimension here
timeout: 120
recreate_index: true

---
# please change the llm and embedder names to the ones you want to use
# the format of llm and embedder should be <provider>.<model_name> such as litellm_llm.gpt-4o-2024-08-06 or <provider>.<alias> such as litellm_llm.gemini-llm-for-chart
# the pipes may be not the latest version, please refer to the latest version: https://raw.githubusercontent.com/canner/WrenAI/<WRENAI_VERSION_NUMBER>/docker/config.example.yaml
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.gemini-llm-for-chart
  - name: chart_adjustment
    llm: litellm_llm.gemini-llm-for-chart
  - 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


##

---

Let me know if anything is required