1 files changed, 152 insertions, 0 deletions
diff --git a/gnqa/paper1_eval/src/apis/process.py b/gnqa/paper1_eval/src/apis/process.py
new file mode 100644
index 0000000..37f2d73
--- /dev/null
+++ b/gnqa/paper1_eval/src/apis/process.py
@@ -0,0 +1,152 @@
+"""this module contains code for processing response from fahamu client.py"""
+import os
+import string
+import json
+
+from urllib.parse import urljoin
+from urllib.parse import quote
+import logging
+import requests
+
+from apis.gnqaclient import GeneNetworkQAClient
+from apis.resp import DocIDs
+
+
+BASE_URL = 'https://genenetwork.fahamuai.com/api/tasks'
+
+
+# pylint: disable=C0301
+
+
+def format_bibliography_info(bib_info):
+    """Function for formatting bibliography info"""
+    if isinstance(bib_info, str):
+        return bib_info.removesuffix('.txt')
+    elif isinstance(bib_info, dict):
+        return f"{bib_info['author']}.{bib_info['title']}.{bib_info['year']}.{bib_info['doi']} "
+    return bib_info
+
+
+def filter_response_text(val):
+    """helper function for filtering non-printable chars"""
+    return json.loads(''.join([str(char)
+                               for char in val if char in string.printable]))
+
+
+def parse_context(context, get_info_func, format_bib_func):
+    """function to parse doc_ids content"""
+    results = []
+    for doc_ids, summary in context.items():
+        combo_txt = ""
+        for entry in summary:
+            combo_txt += "\t" + entry["text"]
+        doc_info = get_info_func(doc_ids)
+        bib_info = doc_ids if doc_ids == doc_info else format_bib_func(
+            doc_info)
+        results.append(
+            {"doc_id": doc_ids, "bibInfo": bib_info, "comboTxt": combo_txt})
+    return results
+
+
+def rate_document(task_id, doc_id, rating, auth_token):
+    """This method is used to provide feedback for a document by making a rating."""
+    # todo move this to clients
+    try:
+        url = urljoin(BASE_URL,
+                      f"""/feedback?task_id={task_id}&document_id={doc_id}&feedback={rating}""")
+        headers = {"Authorization": f"Bearer {auth_token}"}
+
+        resp = requests.post(url, headers=headers)
+        resp.raise_for_status()
+
+        return {"status": "success", **resp.json()}
+    except requests.exceptions.HTTPError as http_error:
+        raise RuntimeError(f"HTTP Error Occurred:\
+            {http_error.response.text} -with status code- {http_error.response.status_code}") from http_error
+    except Exception as error:
+        raise RuntimeError(f"An error occurred: {str(error)}") from error
+
+
+def load_file(filename, dir_path):
+    """function to open and load json file"""
+    file_path = os.path.join(dir_path, f"{filename}")
+    if not os.path.isfile(file_path):
+        raise FileNotFoundError(f"{filename} was not found or is a directory")
+    with open(file_path, "rb") as file_handler:
+        return json.load(file_handler)
+
+
+def fetch_pubmed(references, file_name, data_dir=""):
+    """method to fetch and populate references with pubmed"""
+
+    try:
+        pubmed = load_file(file_name, os.path.join(data_dir, "gn-meta/lit"))
+        for reference in references:
+            if pubmed.get(reference["doc_id"]):
+                reference["pubmed"] = pubmed.get(reference["doc_id"])
+        return references
+
+    except FileNotFoundError:
+        logging.error("failed to find pubmed_path for %s/%s",
+                      data_dir, file_name)
+        return references
+
+
+def get_gnqa(query, auth_token, tmp_dir=""):
+    """entry function for the gn3 api endpoint()"""
+
+    api_client = GeneNetworkQAClient(requests.Session(), api_key=auth_token)
+    res, task_id = api_client.ask('?ask=' + quote(query), auth_token)
+    if task_id == 0:
+        raise RuntimeError(f"Error connecting to Fahamu Api: {str(res)}")
+    res, success = api_client.get_answer(task_id)
+    if success == 1:
+        resp_text = filter_response_text(res.text)
+        if resp_text.get("data") is None:
+            return task_id, "Please try to rephrase your question to receive feedback", []
+        answer = resp_text['data']['answer']
+        context = resp_text['data']['context']
+        references = parse_context(
+            context, DocIDs().getInfo, format_bibliography_info)
+        #references = fetch_pubmed(references, "pubmed.json", tmp_dir)
+
+        return task_id, answer, references
+    else:
+        return task_id, "Please try to rephrase your question to receive feedback", []
+    
+def get_response_from_taskid(auth_token, task_id):
+    api_client = GeneNetworkQAClient(requests.Session(), api_key=auth_token)
+    res, success = api_client.answer(task_id)
+    if success == 1:
+        resp_text = filter_response_text(res.text)
+        if resp_text.get("data") is None:
+            return task_id, "Please try to rephrase your question to receive feedback", []
+        answer = resp_text['data']['answer']
+        context = resp_text['data']['context']
+        references = parse_context(
+            context, DocIDs().getInfo, format_bibliography_info)
+        #references = fetch_pubmed(references, "pubmed.json", tmp_dir)
+
+        return task_id, answer, references
+    else:
+        return task_id, "Please try to rephrase your question to receive feedback", []
+
+
+def fetch_query_results(query, user_id, redis_conn):
+    """this method fetches prev user query searches"""
+    result = redis_conn.get(f"LLM:{user_id}-{query}")
+    if result:
+        return json.loads(result)
+    return {
+        "query": query,
+        "answer": "Sorry No answer for you",
+        "references": [],
+        "task_id": None
+    }
+
+
+def get_user_queries(user_id, redis_conn):
+    """methods to fetch all queries for a specific user"""
+
+    results = redis_conn.keys(f"LLM:{user_id}*")
+    return [query for query in [result.partition("-")[2] for result in results] if query != ""]