update dspy.settings.configure and dspy.settings.context to dspy.configure and dspy.context (#9060)

Author: isaacbmiller

docs/docs/cheatsheet.md

@@ -67,7 +67,7 @@ print(f"Final Predicted Answer (after ReAct process): {result.answer}")
 
 ```python
 colbertv2_wiki17_abstracts = dspy.ColBERTv2(url='http://20.102.90.50:2017/wiki17_abstracts')
-dspy.settings.configure(rm=colbertv2_wiki17_abstracts)
+dspy.configure(rm=colbertv2_wiki17_abstracts)
 
 #Define Retrieve Module
 retriever = dspy.Retrieve(k=3)
@@ -450,7 +450,7 @@ asyncio.run(dspy_program(question="What is DSPy"))
 
 ```python
 import dspy
-dspy.settings.configure(track_usage=True)
+dspy.configure(track_usage=True)
 
 result = dspy.ChainOfThought(BasicQA)(question="What is 2+2?")
 print(f"Token usage: {result.get_lm_usage()}")

docs/docs/learn/programming/language_models.md

@@ -229,7 +229,7 @@ To enable the Responses API, just set `model_type="responses"` when creating the
 import dspy
 
 # Configure DSPy to use the Responses API for your language model
-dspy.settings.configure(
+dspy.configure(
     lm=dspy.LM(
         "openai/gpt-5-mini",
         model_type="responses",

docs/docs/learn/programming/modules.md

@@ -260,7 +260,7 @@ print(hop(claim="Stephen Curry is the best 3 pointer shooter ever in the human h
 DSPy provides built-in tracking of language model usage across all module calls. To enable tracking:
 
 ```python
-dspy.settings.configure(track_usage=True)
+dspy.configure(track_usage=True)
 ```
 
 Once enabled, you can access usage statistics from any `dspy.Prediction` object:
@@ -275,7 +275,7 @@ The usage data is returned as a dictionary that maps each language model name to
 import dspy
 
 # Configure DSPy with tracking enabled
-dspy.settings.configure(
+dspy.configure(
     lm=dspy.LM("openai/gpt-4o-mini", cache=False),
     track_usage=True
 )
@@ -326,7 +326,7 @@ When using DSPy's caching features (either in-memory or on-disk via litellm), ca
 
 ```python
 # Enable caching
-dspy.settings.configure(
+dspy.configure(
     lm=dspy.LM("openai/gpt-4o-mini", cache=True),
     track_usage=True
 )

docs/docs/tutorials/audio/index.ipynb

@@ -117,7 +117,7 @@
     "Now let's configure our LLM which can process input audio. \n",
     "\n",
     "```python\n",
-    "dspy.settings.configure(lm=dspy.LM(model='gpt-4o-mini-audio-preview-2024-12-17'))\n",
+    "dspy.configure(lm=dspy.LM(model='gpt-4o-mini-audio-preview-2024-12-17'))\n",
     "```\n",
     "\n",
     "Note: Using `dspy.Audio` in signatures allows passing in audio directly to the model. "
@@ -332,7 +332,7 @@
     "        audio = generate_dspy_audio(raw_line, out.openai_instruction)\n",
     "        return dspy.Prediction(audio=audio)\n",
     "    \n",
-    "dspy.settings.configure(lm=dspy.LM(model='gpt-4o-mini'))"
+    "dspy.configure(lm=dspy.LM(model='gpt-4o-mini'))"
    ]
   },
   {

docs/docs/tutorials/cache/index.md

@@ -25,7 +25,7 @@ import time
 
 os.environ["OPENAI_API_KEY"] = "{your_openai_key}"
 
-dspy.settings.configure(lm=dspy.LM("openai/gpt-4o-mini"), track_usage=True)
+dspy.configure(lm=dspy.LM("openai/gpt-4o-mini"), track_usage=True)
 
 predict = dspy.Predict("question->answer")
 
@@ -167,7 +167,7 @@ import time
 
 os.environ["OPENAI_API_KEY"] = "{your_openai_key}"
 
-dspy.settings.configure(lm=dspy.LM("openai/gpt-4o-mini"))
+dspy.configure(lm=dspy.LM("openai/gpt-4o-mini"))
 
 predict = dspy.Predict("question->answer")
 
@@ -193,7 +193,7 @@ from hashlib import sha256
 
 os.environ["OPENAI_API_KEY"] = "{your_openai_key}"
 
-dspy.settings.configure(lm=dspy.LM("openai/gpt-4o-mini"))
+dspy.configure(lm=dspy.LM("openai/gpt-4o-mini"))
 
 class CustomCache(dspy.clients.Cache):
 

docs/docs/tutorials/conversation_history/index.md

@@ -12,7 +12,7 @@ import os
 
 os.environ["OPENAI_API_KEY"] = "{your_openai_api_key}"
 
-dspy.settings.configure(lm=dspy.LM("openai/gpt-4o-mini"))
+dspy.configure(lm=dspy.LM("openai/gpt-4o-mini"))
 
 class QA(dspy.Signature):
     question: str = dspy.InputField()
@@ -121,7 +121,7 @@ For example:
 ```python
 import dspy
 
-dspy.settings.configure(lm=dspy.LM("openai/gpt-4o-mini"))
+dspy.configure(lm=dspy.LM("openai/gpt-4o-mini"))
 
 
 class QA(dspy.Signature):

docs/docs/tutorials/deployment/index.md

@@ -7,7 +7,7 @@ Below, we'll assume you have the following simple DSPy program that you want to
 ```python
 import dspy
 
-dspy.settings.configure(lm=dspy.LM("openai/gpt-4o-mini"))
+dspy.configure(lm=dspy.LM("openai/gpt-4o-mini"))
 dspy_program = dspy.ChainOfThought("question -> answer")
 ```
 
@@ -40,7 +40,7 @@ class Question(BaseModel):
 
 # Configure your language model and 'asyncify' your DSPy program.
 lm = dspy.LM("openai/gpt-4o-mini")
-dspy.settings.configure(lm=lm, async_max_workers=4) # default is 8
+dspy.configure(lm=lm, async_max_workers=4) # default is 8
 dspy_program = dspy.ChainOfThought("question -> answer")
 dspy_program = dspy.asyncify(dspy_program)
 
@@ -163,7 +163,7 @@ mlflow.set_tracking_uri("http://127.0.0.1:5000/")
 mlflow.set_experiment("deploy_dspy_program")
 
 lm = dspy.LM("openai/gpt-4o-mini")
-dspy.settings.configure(lm=lm)
+dspy.configure(lm=lm)
 
 class MyProgram(dspy.Module):
     def __init__(self):

docs/docs/tutorials/entity_extraction/index.ipynb

@@ -172,7 +172,7 @@
         "Specifically, we'll:\n",
         "- Create a `PeopleExtraction` DSPy Signature to specify the input (`tokens`) and output (`extracted_people`) fields.\n",
         "- Define a `people_extractor` program that uses DSPy's built-in `dspy.ChainOfThought` module to implement the `PeopleExtraction` signature. The program extracts entities referring to people from a list of input tokens using language model (LM) prompting.\n",
-        "- Use the `dspy.LM` class and `dspy.settings.configure()` method to configure the language model that DSPy will use when invoking the program."
+        "- Use the `dspy.LM` class and `dspy.configure()` method to configure the language model that DSPy will use when invoking the program."
       ]
     },
     {
@@ -208,7 +208,7 @@
       "outputs": [],
       "source": [
         "lm = dspy.LM(model=\"openai/gpt-4o-mini\")\n",
-        "dspy.settings.configure(lm=lm)"
+        "dspy.configure(lm=lm)"
       ]
     },
     {

docs/docs/tutorials/image_generation_prompting/index.ipynb

@@ -80,7 +80,7 @@
     "from IPython.display import display\n",
     "\n",
     "lm = dspy.LM(model=\"gpt-4o-mini\", temperature=0.5)\n",
-    "dspy.settings.configure(lm=lm)"
+    "dspy.configure(lm=lm)"
    ]
   },
   {

docs/docs/tutorials/program_of_thought/index.ipynb

@@ -69,7 +69,7 @@
    "source": [
     "llama31_70b = dspy.LM(\"openai/meta-llama/Meta-Llama-3-70b-Instruct\", api_base=\"API_BASE\", api_key=\"None\")\n",
     "\n",
-    "dspy.settings.configure(lm=llama31_70b)"
+    "dspy.configure(lm=llama31_70b)"
    ]
   },
   {