update docs

wren-ai-service/docs/config_examples/config.deepseek.yaml

@@ -30,12 +30,13 @@ models:
 
 ---
 type: embedder
-provider: openai_embedder
+provider: litellm_embedder
 models:
-  # find EMBEDDER_OPENAI_API_KEY and fill in value of api key in ~/.wrenai/.env
-  - model: text-embedding-3-large  # put your openai compatible embedder model name here
-url: https://api.openai.com/v1  # change this according to your openai compatible embedder model
-timeout: 120
+  # define OPENAI_API_KEY=<api_key> in ~/.wrenai/.env if you are using openai embedding model
+  # please refer to LiteLLM documentation for more details: https://docs.litellm.ai/docs/providers
+  - model: text-embedding-3-large  # put your embedding model name here, if it is not openai embedding model, should be <provider>/<model_name>
+    api_base: https://api.openai.com/v1  # change this according to your embedding model
+    timeout: 120
 
 ---
 type: engine
@@ -57,20 +58,20 @@ recreate_index: false
 type: pipeline
 pipes:
   - name: db_schema_indexing
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: historical_question_indexing
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: table_description_indexing
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: db_schema_retrieval
     llm: litellm_llm.deepseek/deepseek-coder
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: historical_question_retrieval
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: sql_generation
     llm: litellm_llm.deepseek/deepseek-coder
@@ -106,7 +107,7 @@ pipes:
     llm: litellm_llm.deepseek/deepseek-coder
   - name: question_recommendation_db_schema_retrieval
     llm: litellm_llm.deepseek/deepseek-coder
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: question_recommendation_sql_generation
     llm: litellm_llm.deepseek/deepseek-coder
@@ -117,19 +118,19 @@ pipes:
     llm: litellm_llm.deepseek/deepseek-coder
   - name: intent_classification
     llm: litellm_llm.deepseek/deepseek-coder
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: data_assistance
     llm: litellm_llm.deepseek/deepseek-chat
   - name: sql_pairs_indexing
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
   - name: sql_pairs_deletion
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-3-large 
+    embedder: litellm_embedder.text-embedding-3-large 
   - name: sql_pairs_retrieval
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     llm: litellm_llm.deepseek/deepseek-coder
   - name: preprocess_sql_data
     llm: litellm_llm.deepseek/deepseek-coder

wren-ai-service/docs/config_examples/config.google_ai_studio.yaml

@@ -13,12 +13,12 @@ models:
 
 ---
 type: embedder
-provider: openai_embedder
+provider: litellm_embedder
 models:
-  # find EMBEDDER_OPENAI_API_KEY and fill in value of api key in ~/.wrenai/.env
-  - model: text-embedding-004  # put your openai compatible embedder model name here
-url: https://generativelanguage.googleapis.com/v1beta/openai  # change this according to your openai compatible embedder model
-timeout: 120
+  # put GEMINI_API_KEY=<your_api_key> in ~/.wrenai/.env
+  - model: gemini/text-embedding-004  # gemini/<gemini_model_name>
+    api_base: https://generativelanguage.googleapis.com/v1beta/openai  # change this according to your embedding model
+    timeout: 120
 
 ---
 type: engine
@@ -40,20 +40,20 @@ recreate_index: false
 type: pipeline
 pipes:
   - name: db_schema_indexing
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
     document_store: qdrant
   - name: historical_question_indexing
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
     document_store: qdrant
   - name: table_description_indexing
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
     document_store: qdrant
   - name: db_schema_retrieval
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
     document_store: qdrant
   - name: historical_question_retrieval
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
     document_store: qdrant
   - name: sql_generation
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
@@ -89,7 +89,7 @@ pipes:
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
   - name: question_recommendation_db_schema_retrieval
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
     document_store: qdrant
   - name: question_recommendation_sql_generation
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
@@ -100,19 +100,19 @@ pipes:
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
   - name: intent_classification
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
     document_store: qdrant
   - name: data_assistance
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
   - name: sql_pairs_indexing
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
   - name: sql_pairs_deletion
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-004 
+    embedder: litellm_embedder.text-embedding-004 
   - name: sql_pairs_retrieval
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-004
+    embedder: litellm_embedder.text-embedding-004
     llm: litellm_llm.gemini/gemini-2.0-flash-exp
   - name: preprocess_sql_data
     llm: litellm_llm.gemini/gemini-2.0-flash-exp

wren-ai-service/docs/config_examples/config.groq.yaml

@@ -14,12 +14,13 @@ models:
 
 ---
 type: embedder
-provider: openai_embedder
+provider: litellm_embedder
 models:
-  # find EMBEDDER_OPENAI_API_KEY and fill in value of api key in ~/.wrenai/.env
-  - model: text-embedding-3-large  # put your openai compatible embedder model name here
-url: https://api.openai.com/v1  # change this according to your openai compatible embedder model
-timeout: 120
+  # define OPENAI_API_KEY=<api_key> in ~/.wrenai/.env if you are using openai embedding model
+  # please refer to LiteLLM documentation for more details: https://docs.litellm.ai/docs/providers
+  - model: text-embedding-3-large  # put your embedding model name here, if it is not openai embedding model, should be <provider>/<model_name>
+    api_base: https://api.openai.com/v1  # change this according to your embedding model
+    timeout: 120
 
 ---
 type: engine
@@ -41,20 +42,20 @@ recreate_index: false
 type: pipeline
 pipes:
   - name: db_schema_indexing
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: historical_question_indexing
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: table_description_indexing
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: db_schema_retrieval
     llm: litellm_llm.groq/llama-3.3-70b-specdec
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: historical_question_retrieval
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: sql_generation
     llm: litellm_llm.groq/llama-3.3-70b-specdec
@@ -90,7 +91,7 @@ pipes:
     llm: litellm_llm.groq/llama-3.3-70b-specdec
   - name: question_recommendation_db_schema_retrieval
     llm: litellm_llm.groq/llama-3.3-70b-specdec
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: question_recommendation_sql_generation
     llm: litellm_llm.groq/llama-3.3-70b-specdec
@@ -101,19 +102,19 @@ pipes:
     llm: litellm_llm.groq/llama-3.3-70b-specdec
   - name: intent_classification
     llm: litellm_llm.groq/llama-3.3-70b-specdec
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     document_store: qdrant
   - name: data_assistance
     llm: litellm_llm.groq/llama-3.3-70b-specdec
   - name: sql_pairs_indexing
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
   - name: sql_pairs_deletion
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-3-large 
+    embedder: litellm_embedder.text-embedding-3-large 
   - name: sql_pairs_retrieval
     document_store: qdrant
-    embedder: openai_embedder.text-embedding-3-large
+    embedder: litellm_embedder.text-embedding-3-large
     llm: litellm_llm.groq/llama-3.3-70b-specdec
   - name: preprocess_sql_data
     llm: litellm_llm.groq/llama-3.3-70b-specdec

wren-ai-service/docs/config_examples/config.ollama.yaml

@@ -16,8 +16,8 @@ models:
 type: embedder
 provider: litellm_embedder
 models:
-- model: openai/nomic-embed-text  # put your ollama embedder model name here
-  api_base: http://host.docker.internal:11434/v1  # change this to your ollama host, url should be <ollama_url>
+- model: openai/nomic-embed-text  # put your ollama embedder model name here, openai/<ollama_model_name>
+  api_base: http://host.docker.internal:11434/v1  # change this to your ollama host, api_base should be <ollama_url>/v1
   timeout: 120
 
 ---