fix(agent): langchain LLM instantiation (#977)

* fix(agent): langchain LLM instantiation

* replace object with mock

pandasai/agent/base.py

@@ -19,7 +19,7 @@
 from ..helpers.logger import Logger
 from ..helpers.memory import Memory
 from ..llm.base import LLM
-from ..llm.langchain import LangchainLLM
+from ..llm.langchain import LangchainLLM, is_langchain_llm
 from ..pipelines.chat.generate_chat_pipeline import (
     GenerateChatPipeline,
 )
@@ -141,7 +141,7 @@ def get_config(self, config: Union[Config, dict]):
 
         config = load_config_from_json(config)
 
-        if isinstance(config, dict) and config.get("llm") is None:
+        if isinstance(config, dict) and config.get("llm") is not None:
             config["llm"] = self.get_llm(config["llm"])
 
         config = Config(**config)
@@ -161,7 +161,7 @@ def get_llm(self, llm: LLM) -> LLM:
             BadImportError: If the LLM is a Langchain LLM but the langchain package
             is not installed
         """
-        if LangchainLLM.is_langchain_llm(llm):
+        if is_langchain_llm(llm):
             llm = LangchainLLM(llm)
 
         return llm

pandasai/llm/__init__.py

@@ -10,8 +10,6 @@
     "LLM",
     "AzureOpenAI",
     "OpenAI",
-    "Falcon",
-    "GoogleGemini",
     "GooglePalm",
     "GoogleVertexAI",
     "HuggingFaceTextGen",

pandasai/llm/langchain.py

@@ -1,16 +1,16 @@
 from __future__ import annotations
 
 try:
+    from langchain_core.language_models import BaseLanguageModel
     from langchain_core.language_models.chat_models import BaseChatModel
-    from langchain_core.language_models.llms import BaseLLM
 
-    LANGCHAIN_AVAILABLE = True
 except ImportError:
+    from unittest.mock import Mock
+
     # Fallback definitions if langchain_core is not installed
-    BaseLLM = BaseChatModel = object
-    LANGCHAIN_AVAILABLE = False
+    BaseLanguageModel = BaseChatModel = Mock
 
-from typing import TYPE_CHECKING, Union
+from typing import TYPE_CHECKING
 
 from pandasai.prompts.base import BasePrompt
 
@@ -29,15 +29,19 @@
 """
 
 
+def is_langchain_llm(llm) -> bool:
+    return isinstance(llm, BaseLanguageModel)
+
+
 class LangchainLLM(LLM):
     """
     Class to wrap Langchain LLMs and make PandasAI interoperable
     with LangChain.
     """
 
-    langchain_llm = None
+    langchain_llm: BaseLanguageModel
 
-    def __init__(self, langchain_llm: Union[BaseLLM, BaseChatModel]):
+    def __init__(self, langchain_llm: BaseLanguageModel):
         self.langchain_llm = langchain_llm
 
     def call(
@@ -51,10 +55,6 @@ def call(
         res = self.langchain_llm.invoke(prompt)
         return res.content if isinstance(self.langchain_llm, BaseChatModel) else res
 
-    @staticmethod
-    def is_langchain_llm(llm: LLM) -> bool:
-        return hasattr(llm, "_llm_type")
-
     @property
     def type(self) -> str:
         return f"langchain_{self.langchain_llm._llm_type}"