Harrison/improve usability of api chain (#247)

improve usability of api chain

langchain/chains/__init__.py

@@ -1,4 +1,5 @@
 """Chains are easily reusable components which can be linked together."""
+from langchain.chains.api.base import APIChain
 from langchain.chains.conversation.base import ConversationChain
 from langchain.chains.llm import LLMChain
 from langchain.chains.llm_math.base import LLMMathChain
@@ -22,4 +23,5 @@ __all__ = [
     "QAWithSourcesChain",
     "VectorDBQAWithSourcesChain",
     "PALChain",
+    "APIChain",
 ]

langchain/chains/api/base.py

@@ -6,9 +6,10 @@ from typing import Any, Dict, List, Optional
 import requests
 from pydantic import BaseModel, root_validator
 
-from langchain import LLMChain
 from langchain.chains.api.prompt import API_RESPONSE_PROMPT, API_URL_PROMPT
 from langchain.chains.base import Chain
+from langchain.chains.llm import LLMChain
+from langchain.input import print_text
 from langchain.llms.base import LLM
 
 
@@ -27,7 +28,7 @@ class APIChain(Chain, BaseModel):
 
     api_request_chain: LLMChain
     api_answer_chain: LLMChain
-    requests_chain: RequestsWrapper
+    requests_wrapper: RequestsWrapper
     api_docs: str
     question_key: str = "question"  #: :meta private:
     output_key: str = "output"  #: :meta private:
@@ -75,7 +76,11 @@ class APIChain(Chain, BaseModel):
         api_url = self.api_request_chain.predict(
             question=question, api_docs=self.api_docs
         )
-        api_response = self.requests_chain.run(api_url)
+        if self.verbose:
+            print_text(api_url, color="green", end="\n")
+        api_response = self.requests_wrapper.run(api_url)
+        if self.verbose:
+            print_text(api_url, color="yellow", end="\n")
         answer = self.api_answer_chain.predict(
             question=question,
             api_docs=self.api_docs,
@@ -93,8 +98,8 @@ class APIChain(Chain, BaseModel):
         requests_wrapper = RequestsWrapper(headers=headers)
         get_answer_chain = LLMChain(llm=llm, prompt=API_RESPONSE_PROMPT)
         return cls(
-            request_chain=get_request_chain,
-            answer_chain=get_answer_chain,
+            api_request_chain=get_request_chain,
+            api_answer_chain=get_answer_chain,
             requests_wrapper=requests_wrapper,
             api_docs=api_docs,
             **kwargs,

tests/unit_tests/chains/test_api.py

@@ -68,11 +68,11 @@ def fake_llm_api_chain(test_api_data: dict) -> APIChain:
     fake_llm = FakeLLM(queries=queries)
     api_request_chain = LLMChain(llm=fake_llm, prompt=API_URL_PROMPT)
     api_answer_chain = LLMChain(llm=fake_llm, prompt=API_RESPONSE_PROMPT)
-    requests_chain = FakeRequestsChain(output=TEST_API_RESPONSE)
+    requests_wrapper = FakeRequestsChain(output=TEST_API_RESPONSE)
     return APIChain(
         api_request_chain=api_request_chain,
         api_answer_chain=api_answer_chain,
-        requests_chain=requests_chain,
+        requests_wrapper=requests_wrapper,
         api_docs=TEST_API_DOCS,
     )