improve logging (#66)

examples/mrkl.ipynb

@@ -20,9 +20,9 @@
    "source": [
     "llm = OpenAI(temperature=0)\n",
     "search = SerpAPIChain()\n",
-    "llm_math_chain = LLMMathChain(llm=llm)\n",
+    "llm_math_chain = LLMMathChain(llm=llm, verbose=True)\n",
     "db = SQLDatabase.from_uri(\"sqlite:///../notebooks/Chinook.db\")\n",
-    "db_chain = SQLDatabaseChain(llm=llm, database=db)\n",
+    "db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)\n",
     "chains = [\n",
     "    ChainConfig(\n",
     "        action_name = \"Search\",\n",
@@ -63,6 +63,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new chain...\u001b[0m\n",
       "What is the age of Olivia Wilde's boyfriend raised to the 0.23 power?\n",
       "Thought:\u001b[102m I need to find the age of Olivia Wilde's boyfriend\n",
       "Action: Search\n",
@@ -75,10 +78,23 @@
       "Thought:\u001b[102m I need to calculate 28 to the 0.23 power\n",
       "Action: Calculator\n",
       "Action Input: 28^0.23\u001b[0m\n",
+      "\n",
+      "\u001b[1m> Entering new chain...\u001b[0m\n",
+      "28^0.23\u001b[102m\n",
+      "\n",
+      "```python\n",
+      "print(28**0.23)\n",
+      "```\n",
+      "\u001b[0m\n",
+      "Answer: \u001b[103m2.1520202182226886\n",
+      "\u001b[0m\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n",
+      "\n",
       "Observation: \u001b[103mAnswer: 2.1520202182226886\n",
       "\u001b[0m\n",
       "Thought:\u001b[102m I now know the final answer\n",
-      "Final Answer: 2.1520202182226886\u001b[0m"
+      "Final Answer: 2.1520202182226886\u001b[0m\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
     },
     {
@@ -106,6 +122,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new chain...\u001b[0m\n",
       "Who recently released an album called 'The Storm Before the Calm' and are they in the FooBar database? If so, what albums of theirs are in the FooBar database?\n",
       "Thought:\u001b[102m I need to find an album called 'The Storm Before the Calm'\n",
       "Action: Search\n",
@@ -114,13 +133,30 @@
       "Thought:\u001b[102m I need to check if Alanis is in the FooBar database\n",
       "Action: FooBar DB\n",
       "Action Input: \"Does Alanis Morissette exist in the FooBar database?\"\u001b[0m\n",
+      "\n",
+      "\u001b[1m> Entering new chain...\u001b[0m\n",
+      "Does Alanis Morissette exist in the FooBar database?\n",
+      "SQLQuery:\u001b[102m SELECT * FROM Artist WHERE Name = 'Alanis Morissette'\u001b[0m\n",
+      "SQLResult: \u001b[103m[(4, 'Alanis Morissette')]\u001b[0m\n",
+      "Answer:\u001b[102m Yes\u001b[0m\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n",
+      "\n",
       "Observation: \u001b[101m Yes\u001b[0m\n",
       "Thought:\u001b[102m I need to find out what albums of Alanis's are in the FooBar database\n",
       "Action: FooBar DB\n",
       "Action Input: \"What albums by Alanis Morissette are in the FooBar database?\"\u001b[0m\n",
+      "\n",
+      "\u001b[1m> Entering new chain...\u001b[0m\n",
+      "What albums by Alanis Morissette are in the FooBar database?\n",
+      "SQLQuery:\u001b[102m SELECT Title FROM Album WHERE ArtistId = (SELECT ArtistId FROM Artist WHERE Name = 'Alanis Morissette')\u001b[0m\n",
+      "SQLResult: \u001b[103m[('Jagged Little Pill',)]\u001b[0m\n",
+      "Answer:\u001b[102m The album \"Jagged Little Pill\" by Alanis Morissette is in the FooBar database.\u001b[0m\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n",
+      "\n",
       "Observation: \u001b[101m The album \"Jagged Little Pill\" by Alanis Morissette is in the FooBar database.\u001b[0m\n",
       "Thought:\u001b[102m I now know the final answer\n",
-      "Final Answer: The album \"Jagged Little Pill\" by Alanis Morissette is the only album by Alanis Morissette in the FooBar database.\u001b[0m"
+      "Final Answer: The album \"Jagged Little Pill\" by Alanis Morissette is the only album by Alanis Morissette in the FooBar database.\u001b[0m\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
     },
     {

langchain/chains/base.py

@@ -2,10 +2,15 @@
 from abc import ABC, abstractmethod
 from typing import Any, Dict, List
 
+from pydantic import BaseModel
 
-class Chain(ABC):
+
+class Chain(BaseModel, ABC):
     """Base interface that all chains should implement."""
 
+    verbose: bool = False
+    """Whether to print out the code that was executed."""
+
     @property
     @abstractmethod
     def input_keys(self) -> List[str]:
@@ -36,6 +41,10 @@ class Chain(ABC):
     def __call__(self, inputs: Dict[str, Any]) -> Dict[str, str]:
         """Run the logic of this chain and add to output."""
         self._validate_inputs(inputs)
+        if self.verbose:
+            print("\n\n\033[1m> Entering new chain...\033[0m")
         outputs = self._run(inputs)
+        if self.verbose:
+            print("\n\033[1m> Finished chain.\033[0m")
         self._validate_outputs(outputs)
         return {**inputs, **outputs}

langchain/chains/llm_math/base.py

@@ -23,8 +23,6 @@ class LLMMathChain(Chain, BaseModel):
 
     llm: LLM
     """LLM wrapper to use."""
-    verbose: bool = False
-    """Whether to print out the code that was executed."""
     input_key: str = "question"  #: :meta private:
     output_key: str = "answer"  #: :meta private:
 

langchain/chains/mrkl/base.py

@@ -72,8 +72,6 @@ class MRKLChain(Chain, BaseModel):
     """Prompt to use as router."""
     action_to_chain_map: Dict[str, Callable]
     """Mapping from action name to chain to execute."""
-    verbose: bool = False
-    """Whether to print out the code that was executed."""
     input_key: str = "question"  #: :meta private:
     output_key: str = "answer"  #: :meta private:
 

langchain/chains/react/base.py

@@ -49,7 +49,6 @@ class ReActChain(Chain, BaseModel):
     """LLM wrapper to use."""
     docstore: Docstore
     """Docstore to use."""
-    verbose: bool = False
     input_key: str = "question"  #: :meta private:
     output_key: str = "answer"  #: :meta private:
 

langchain/chains/self_ask_with_search/base.py

@@ -89,7 +89,6 @@ class SelfAskWithSearchChain(Chain, BaseModel):
     """LLM wrapper to use."""
     search_chain: SerpAPIChain
     """Search chain to use."""
-    verbose: bool = False
     input_key: str = "question"  #: :meta private:
     output_key: str = "answer"  #: :meta private:
 

langchain/chains/sql_database/base.py

@@ -26,7 +26,6 @@ class SQLDatabaseChain(Chain, BaseModel):
     """LLM wrapper to use."""
     database: SQLDatabase
     """SQL Database to connect to."""
-    verbose: bool = False
     input_key: str = "query"  #: :meta private:
     output_key: str = "result"  #: :meta private: