Remove inspect_history from COPRO (stanfordnlp#8033)

* replace print in _inspect_history with logging

* fix calls wihing COPRO

* fix tests

* typo

* remove inspect_history from COPRO

Author: TomeHirata

docs/docs/faqs.md

@@ -115,3 +115,18 @@ Modules can be frozen by setting their `._compiled` attribute to be True, indica
 If you're dealing with "context too long" errors in DSPy, you're likely using DSPy optimizers to include demonstrations within your prompt, and this is exceeding your current context window. Try reducing these parameters (e.g. `max_bootstrapped_demos` and `max_labeled_demos`). Additionally, you can also reduce the number of retrieved passages/docs/embeddings to ensure your prompt is fitting within your model context length.
 
 A more general fix is simply increasing the number of `max_tokens` specified to the LM request (e.g. `lm = dspy.OpenAI(model = ..., max_tokens = ...`).
+
+## Set Verbose Level
+DSPy utilizes the [logging library](https://docs.python.org/3/library/logging.html) to print logs. If you want to debug your DSPy code, set the logging level to DEBUG with the example code below.
+
+```python
+import logging
+logging.getLogger("dspy").setLevel(logging.DEBUG)
+```
+
+Alternatively, if you want to reduce the amount of logs, set the logging level to WARNING or ERROR.
+
+```python
+import logging
+logging.getLogger("dspy").setLevel(logging.WARNING)
+```

dspy/teleprompt/copro_optimizer.py

@@ -319,19 +319,13 @@ def compile(self, student, *, trainset, eval_kwargs):
                         temperature=self.init_temperature,
                     )(attempted_instructions=attempts)
 
-                if self.prompt_model:
-                    logger.debug(
-                        f"(self.prompt_model.inspect_history(n=1)) {self.prompt_model.inspect_history(n=1)}"
-                    )
                 # Get candidates for each predictor
                 new_candidates[id(p_base)] = instr.completions
                 all_candidates[id(p_base)].proposed_instruction.extend(instr.completions.proposed_instruction)
                 all_candidates[id(p_base)].proposed_prefix_for_output_field.extend(
                     instr.completions.proposed_prefix_for_output_field,
                 )
 
-            if self.prompt_model:
-                logger.debug(f"{self.prompt_model.inspect_history(n=1)}")
             latest_candidates = new_candidates
 
         candidates = []