feat: add MiniMax provider (M3 default) to RAG templates

templates/adaptive_rag/.env.example

@@ -1 +1,2 @@
 OPENAI_API_KEY="sk-***"
+# MINIMAX_API_KEY="your-minimax-api-key"  # Optional: use MiniMax instead of OpenAI

templates/adaptive_rag/app.yaml

@@ -54,6 +54,17 @@ $llm: !pw.xpacks.llm.llms.OpenAIChat
   temperature: 0
   capacity: 8
 
+# Alternatively, use MiniMax with its OpenAI-compatible API (https://api.minimax.io/v1):
+# $llm: !pw.xpacks.llm.llms.OpenAIChat
+#   model: "MiniMax-M3"
+#   api_key: $MINIMAX_API_KEY
+#   base_url: "https://api.minimax.io/v1"
+#   retry_strategy: !pw.udfs.ExponentialBackoffRetryStrategy
+#     max_retries: 6
+#   cache_strategy: !pw.udfs.DefaultCache {}
+#   temperature: 1.0
+#   capacity: 8
+
 # Specifies the embedder model for converting text into embeddings.
 $embedder: !pw.xpacks.llm.embedders.OpenAIEmbedder
   model: "text-embedding-3-small"

templates/multimodal_rag/.env.example

@@ -1 +1,2 @@
 OPENAI_API_KEY="sk-***"
+# MINIMAX_API_KEY="your-minimax-api-key"  # Optional: use MiniMax instead of OpenAI

templates/multimodal_rag/app.yaml

@@ -55,6 +55,18 @@ $llm: !pw.xpacks.llm.llms.OpenAIChat
   capacity: 8
   async_mode: "fully_async"
 
+# Alternatively, use MiniMax with its OpenAI-compatible API (https://api.minimax.io/v1):
+# $llm: !pw.xpacks.llm.llms.OpenAIChat
+#   model: "MiniMax-M3"
+#   api_key: $MINIMAX_API_KEY
+#   base_url: "https://api.minimax.io/v1"
+#   retry_strategy: !pw.udfs.ExponentialBackoffRetryStrategy
+#     max_retries: 6
+#   cache_strategy: !pw.udfs.DefaultCache {}
+#   temperature: 1.0
+#   capacity: 8
+#   async_mode: "fully_async"
+
 # Specifies the embedder model for converting text into embeddings.
 $embedder: !pw.xpacks.llm.embedders.OpenAIEmbedder
   model: "text-embedding-3-small"

templates/question_answering_rag/.env.example

@@ -1 +1,2 @@
 OPENAI_API_KEY="sk-***"
+# MINIMAX_API_KEY="your-minimax-api-key"  # Optional: use MiniMax instead of OpenAI

templates/question_answering_rag/app.yaml

@@ -54,6 +54,18 @@ $llm: !pw.xpacks.llm.llms.OpenAIChat
   capacity: 8
   async_mode: "fully_async"
 
+# Alternatively, use MiniMax with its OpenAI-compatible API (https://api.minimax.io/v1):
+# $llm: !pw.xpacks.llm.llms.OpenAIChat
+#   model: "MiniMax-M3"
+#   api_key: $MINIMAX_API_KEY
+#   base_url: "https://api.minimax.io/v1"
+#   retry_strategy: !pw.udfs.ExponentialBackoffRetryStrategy
+#     max_retries: 6
+#   cache_strategy: !pw.udfs.DefaultCache {}
+#   temperature: 1.0
+#   capacity: 8
+#   async_mode: "fully_async"
+
 # Specifies the embedder model for converting text into embeddings.
 $embedder: !pw.xpacks.llm.embedders.OpenAIEmbedder
   model: "text-embedding-3-small"

templates/slides_ai_search/.env.example

@@ -1,2 +1,3 @@
 OPENAI_API_KEY="YOUR OPENAI_API_KEY"
 PATHWAY_LICENSE_KEY="YOUR PATHWAY KEY"  # can be obtained here: https://pathway.com/user/license
+# MINIMAX_API_KEY="your-minimax-api-key"  # Optional: use MiniMax instead of OpenAI

templates/slides_ai_search/app.yaml

@@ -55,6 +55,20 @@ llm: !pw.xpacks.llm.llms.OpenAIChat
   capacity: 8 # reduce this in case you are hitting API throttle limits
   async_mode: "fully_async"
 
+# Alternatively, use MiniMax with its OpenAI-compatible API (https://api.minimax.io/v1):
+# llm: !pw.xpacks.llm.llms.OpenAIChat
+#   model: "MiniMax-M3"
+#   api_key: $MINIMAX_API_KEY
+#   base_url: "https://api.minimax.io/v1"
+#   retry_strategy: !pw.udfs.ExponentialBackoffRetryStrategy
+#     max_retries: 6
+#     initial_delay: 2500
+#     backoff_factor: 2.5
+#   cache_strategy: !pw.udfs.DefaultCache {}
+#   temperature: 1.0
+#   capacity: 8
+#   async_mode: "fully_async"
+
 # Specifies the embedder model for converting text into embeddings.
 $embedder: !pw.xpacks.llm.embedders.OpenAIEmbedder
   cache_strategy: !pw.udfs.DefaultCache {}