fix search.py

colabfold/mmseqs/search.py

@@ -11,12 +11,55 @@
 from argparse import ArgumentParser
 from pathlib import Path
 from typing import List, Union
-import os
+import os, pandas
 
-from colabfold.batch import get_queries, msa_to_str, get_queries_pairwise
+from colabfold.inputs import get_queries, msa_to_str, parse_fasta
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 logger = logging.getLogger(__name__)
 
+def get_queries_pairwise(
+    input_path: Union[str, Path], sort_queries_by: str = "length"
+) -> Tuple[List[Tuple[str, str, Optional[List[str]]]], bool]:
+    """Reads a directory of fasta files, a single fasta file or a csv file and returns a tuple
+    of job name, sequence and the optional a3m lines"""
+    input_path = Path(input_path)
+    if not input_path.exists():
+        raise OSError(f"{input_path} could not be found")
+    if input_path.is_file():
+        if input_path.suffix == ".csv" or input_path.suffix == ".tsv":
+            sep = "\t" if input_path.suffix == ".tsv" else ","
+            df = pandas.read_csv(input_path, sep=sep)
+            assert "id" in df.columns and "sequence" in df.columns
+            queries = [
+                (str(df["id"][0])+'&'+str(seq_id), [df["sequence"][0].upper(),sequence.upper()], None)
+                for i, (seq_id, sequence) in enumerate(df[["id", "sequence"]].itertuples(index=False)) if i!=0 
+            ]
+            for i in range(len(queries)):
+                if len(queries[i][1]) == 1:
+                    queries[i] = (queries[i][0], queries[i][1][0], None)
+        elif input_path.suffix == ".a3m":
+            raise NotImplementedError()
+        elif input_path.suffix in [".fasta", ".faa", ".fa"]:
+            (sequences, headers) = parse_fasta(input_path.read_text())
+            queries = []
+            for i, (sequence, header) in enumerate(zip(sequences, headers)):
+                sequence = sequence.upper()
+                if sequence.count(":") == 0:
+                    # Single sequence
+                    if i==0:
+                        continue
+                    queries.append((headers[0]+'&'+header, [sequences[0],sequence], None))
+                else:
+                    # Complex mode
+                    queries.append((header, sequence.upper().split(":"), None))
+        else:
+            raise ValueError(f"Unknown file format {input_path.suffix}")
+    else:
+        raise NotImplementedError()
+
+    is_complex = True
+    return queries, is_complex
 
 def run_mmseqs(mmseqs: Path, params: List[Union[str, Path]]):
     params_log = " ".join(str(i) for i in params)
@@ -61,8 +104,9 @@ def mmseqs_search_monomer(
         used_dbs.append(template_db)
     if use_env:
         used_dbs.append(metagenomic_db)
-
     for db in used_dbs:
+        if str(db) == '.':
+            continue
         if not dbbase.joinpath(f"{db}.dbtype").is_file():
             raise FileNotFoundError(f"Database {db} does not exist")
         if (