nl2sql_library/nl2sql/tasks/column_selection/core.py [179:216]:
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                "table_name": tablename,
                "table_names": list(db.db._usable_tables),
            }
            prepared_prompt = self.prompt.prompt_template.format(
                **{
                    k: v
                    for k, v in prompt_params.items()
                    if k in self.prompt.prompt_template.input_variables
                }
            )
            llm_response = self.llm.generate([prepared_prompt])
            logger.debug(
                f"[{self.tasktype}] : Received LLM Response : {llm_response.json()}"
            )
            try:
                raw_response = llm_response.generations[0][0].text.strip()
            except IndexError as exc:
                raise ValueError(
                    f"Empty / Invalid Response received from LLM : {llm_response.json()}"
                ) from exc

            parsed_response = (
                self.prompt.parser.parse(raw_response)
                if self.prompt.parser
                else raw_response
            )
            processed_response = self.prompt.post_processor(parsed_response)
            intermediate_steps.append(
                {
                    "tasktype": self.tasktype,
                    "table": tablename,
                    "prepared_prompt": prepared_prompt,
                    "llm_response": llm_response.dict(),
                    "raw_response": raw_response,
                    "parsed_response": parsed_response,
                    "processed_response": processed_response,
                }
            )
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nl2sql_library/nl2sql/tasks/table_selection/core.py [170:207]:
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                "table_name": tablename,
                "table_names": list(db.db._usable_tables),
            }
            prepared_prompt = self.prompt.prompt_template.format(
                **{
                    k: v
                    for k, v in prompt_params.items()
                    if k in self.prompt.prompt_template.input_variables
                }
            )
            llm_response = self.llm.generate([prepared_prompt])
            logger.debug(
                f"[{self.tasktype}] : Received LLM Response : {llm_response.json()}"
            )
            try:
                raw_response = llm_response.generations[0][0].text.strip()
            except IndexError as exc:
                raise ValueError(
                    f"Empty / Invalid Response received from LLM : {llm_response.json()}"
                ) from exc

            parsed_response = (
                self.prompt.parser.parse(raw_response)
                if self.prompt.parser
                else raw_response
            )
            processed_response = self.prompt.post_processor(parsed_response)
            intermediate_steps.append(
                {
                    "tasktype": self.tasktype,
                    "table": tablename,
                    "prepared_prompt": prepared_prompt,
                    "llm_response": llm_response.dict(),
                    "raw_response": raw_response,
                    "parsed_response": parsed_response,
                    "processed_response": processed_response,
                }
            )
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