add readme for building docker images

chemcrow/docker/README.md

@@ -3,7 +3,7 @@
 
 A docker container was prepared for each tool, which exposes an api for requests.
 
-> docker run -d -p 8082:5000 doncamilom/rxnpred:latest
+> docker run -d -p 8052:5000 doncamilom/rxnpred:latest
 
 Where 5000 is fixed, and 8082 is the port to be exposed.
 
@@ -20,35 +20,11 @@ import requests
 
 def reaction_predict(reactants):
     response = requests.post(
-        "http://localhost:8082/api/v1/translate",
+        "http://localhost:8052/api/v1/run",
         headers={"Content-Type": "application/json"},
         data=json.dumps({"smiles": reactants})
     )
     return response.json()['product'][0]
 
 product = reaction_predict('CCOCCCCO.CC(=O)Cl')
 ```
-
-## Tools
-
-- [ ] Retrosynthesis (AiZynthfinder)
-- [ ] Reaction prediction (Molecular Transformer)
-- [ ] Reaction fingerprints (RXNFP)
-
-
-## TO-DO (missing tools)
-
-- [ ] Condition prediction (Coley)
-- [ ] LinChemIn (Syngenta)
-- [ ] Reaction equilibration (Theo)
-- [ ] Literature parsing (Coley, J.Cole, Jasyntho)
-- [ ] Descriptors (?)
-- [ ] Maybe robotic platform/simulator
-- [ ] Other calculation software
-- [ ] Multimodal molecule description, generation (GIT-Mol) https://github.com/AI-HPC-Research-Team/GIT-Mol/tree/main
-- [ ] Multimodal too, SOTA (BioT5+) (https://huggingface.co/QizhiPei/biot5-base)
-- [ ] Text to Mol (https://huggingface.co/spaces/ndhieunguyen/Lang2mol-Diff) -- checkout the app.py
-- [ ] text2mol, mol2text https://github.com/QizhiPei/BioT5 (inference code. different FTs for each task?
-- [ ] MolGrapher https://github.com/DS4SD/MolGrapher  image->smiles. easy as is in huggingface
-
-saccrow-data/papers