From 7b81c8a6901f65fe6076fd4d4ca6e6b4ff488859 Mon Sep 17 00:00:00 2001
From: seehi <6580@pm.me>
Date: Mon, 28 Oct 2024 21:12:09 +0800
Subject: [PATCH] make context length configurable

---
 metagpt/configs/llm_config.py | 1 +
 metagpt/rag/factories/llm.py  | 4 +++-
 2 files changed, 4 insertions(+), 1 deletion(-)

diff --git a/metagpt/configs/llm_config.py b/metagpt/configs/llm_config.py
index 60118303c..0d4561a7a 100644
--- a/metagpt/configs/llm_config.py
+++ b/metagpt/configs/llm_config.py
@@ -83,6 +83,7 @@ class LLMConfig(YamlModel):
     logprobs: Optional[bool] = None
     top_logprobs: Optional[int] = None
     timeout: int = 600
+    context_length: Optional[int] = None  # Max input tokens
 
     # For Amazon Bedrock
     region_name: str = None
diff --git a/metagpt/rag/factories/llm.py b/metagpt/rag/factories/llm.py
index 9fd19cab5..c1069cc6c 100644
--- a/metagpt/rag/factories/llm.py
+++ b/metagpt/rag/factories/llm.py
@@ -23,10 +23,12 @@ class RAGLLM(CustomLLM):
     """LlamaIndex's LLM is different from MetaGPT's LLM.
 
     Inherit CustomLLM from llamaindex, making MetaGPT's LLM can be used by LlamaIndex.
+
+    Set context_length or max_token of LLM in config.yaml if you encounter "Calculated available context size -xxx was not non-negative" error.
     """
 
     model_infer: BaseLLM = Field(..., description="The MetaGPT's LLM.")
-    context_window: int = TOKEN_MAX.get(config.llm.model, DEFAULT_CONTEXT_WINDOW)
+    context_window: int = config.llm.context_length or TOKEN_MAX.get(config.llm.model, DEFAULT_CONTEXT_WINDOW)
     num_output: int = config.llm.max_token
     model_name: str = config.llm.model