feat: Add SemanticScholarToolkits to integrate Semantic Scholar to camel

camel/toolkits/__init__.py

@@ -45,6 +45,7 @@
 from .stripe_toolkit import StripeToolkit
 from .video_toolkit import VideoDownloaderToolkit
 from .dappier_toolkit import DappierToolkit
+from .semanticscholar_toolkit import SemanticScholarToolkit
 
 __all__ = [
     'BaseToolkit',
@@ -77,4 +78,5 @@
     'MeshyToolkit',
     'OpenBBToolkit',
     'DappierToolkit',
+    'SemanticScholarToolkit',
 ]

camel/toolkits/semanticscholar_toolkit.py

@@ -0,0 +1,257 @@
+# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
+
+import json
+from typing import List
+
+import requests
+
+from camel.toolkits import FunctionTool
+from camel.toolkits.base import BaseToolkit
+
+
+class SemanticScholarToolkit(BaseToolkit):
+    """A toolkit for interacting with the Semantic Scholar
+    API to fetch paper and author data."""
+
+    def __init__(self):
+        """Initializes the SemanticScholarToolkit."""
+        self.base_url = "https://api.semanticscholar.org/graph/v1"
+
+    def fetch_paper_data_title(
+        self,
+        paperTitle: str,
+        fields: str = """title,abstract,authors,year,citationCount,
+        publicationTypes,publicationDate,openAccessPdf""",
+    ) -> dict:
+        r"""Fetches a SINGLE paper from the Semantic Scholar
+        API based on a paper title.
+
+        Args:
+            paperTitle (str): The title of the paper to fetch.
+            fields (str): A comma-separated list of fields to include
+            in the response (default includes title, abstract, authors, year,
+            citation count, publicationTypes, publicationDate, openAccessPdf).
+
+        Returns:
+            dict: The response data from the API or error
+            information if the request fails.
+        """
+        url = f"{self.base_url}/paper/search"
+        query_params = {"query": paperTitle, "fields": fields}
+        response = requests.get(url, params=query_params)
+        if response.status_code == 200:
+            return response.json()
+        else:
+            return {
+                "error": (
+                    f"Request failed with status code {response.status_code}"
+                ),
+                "message": response.text,
+            }
+
+    def fetch_paper_data_id(
+        self,
+        paperID: str,
+        fields: str = """title,abstract,authors,year,citationCount,
+        publicationTypes,publicationDate,openAccessPdf""",
+    ) -> dict:
+        r"""Fetches a SINGLE paper from the Semantic Scholar
+         API based on a paper ID.
+
+        Args:
+            paperID (str): The ID of the paper to fetch.
+            fields (str): A comma-separated list of fields to
+            include in the response (default includes title, abstract,
+            authors, year, citation count, publicationTypes,
+            publicationDate, openAccessPdf).
+
+        Returns:
+            dict: The response data from the API or error information
+            if the request fails.
+        """
+        url = f"{self.base_url}/paper/{paperID}"
+        query_params = {"fields": fields}
+        response = requests.get(url, params=query_params)
+        if response.status_code == 200:
+            return response.json()
+        else:
+            return {
+                "error": (
+                    f"Request failed with status code {response.status_code}"
+                ),
+                "message": response.text,
+            }
+
+    def fetch_bulk_paper_data(
+        self,
+        query: str,
+        year: str = "2023-",
+        fields: str = """title,url,publicationTypes,
+        publicationDate,openAccessPdf""",
+    ) -> dict:
+        r"""Fetches MULTIPLE papers at once from the Semantic Scholar
+         API based on a related topic.
+        Args:
+            query (str):
+                The text query to match against the paper's title
+                and abstract.
+                For example, you can use the following operators
+                and techniques to construct your query:
+                Example 1:
+                    ((cloud computing) | virtualization)
+                    +security -privacy This will match papers
+                    whose title or abstract contains "cloud"
+                    and "computing", or contains the word
+                    "virtualization". The papers must also
+                    include the term "security" but exclude
+                    papers that contain the word "privacy".
+            year (str): The year filter for papers (default is "2023-").
+            fields (str): The fields to include in the response
+            (e.g., 'title,url,publicationTypes,publicationDate,
+            openAccessPdf').
+        Returns:
+            dict: The response data from the API or
+            error information if the request fails.
+        """
+        url = f"{self.base_url}/paper/search/bulk"
+        query_params = {"query": query, "fields": fields, "year": year}
+        response = requests.get(url, params=query_params)
+        if response.status_code == 200:
+            return response.json()
+        else:
+            return {
+                "error": (
+                    f"Request failed with status code {response.status_code}"
+                ),
+                "message": response.text,
+            }
+
+    def fetch_recommended_papers(
+        self,
+        positive_paper_ids: List[str],
+        negative_paper_ids: List[str],
+        fields: str = """title,url,citationCount,authors,
+        publicationTypes,publicationDate,openAccessPdf""",
+        limit: int = 500,
+        save_to_file: bool = False,
+    ) -> dict:
+        r"""Fetches recommended papers from the Semantic Scholar
+        API based on the positive and negative paper IDs.
+
+        Args:
+            positive_paper_ids (list): A list of paper IDs (as strings)
+            that are positively correlated to the recommendation.
+
+            negative_paper_ids (list): A list of paper IDs (as strings)
+            that are negatively correlated to the recommendation.
+
+            fields (str): The fields to include in the response
+            (e.g., 'title,url,citationCount,authors,publicationTypes,
+            publicationDate,openAccessPdf').
+
+            limit (int): The maximum number of recommended papers to return.
+            Default is 500.
+
+            save_to_file (bool): If True, saves the response data to a file
+            (default is False).
+
+        Returns:
+            dict: A dictionary containing recommended papers sorted by
+            citation count.
+        """
+        url = "https://api.semanticscholar.org/recommendations/v1/papers"
+        query_params = {"fields": fields, "limit": str(limit)}
+        data = {
+            "positivePaperIds": positive_paper_ids,
+            "negativePaperIds": negative_paper_ids,
+        }
+
+        try:
+            response = requests.post(url, params=query_params, json=data)
+            response.raise_for_status()
+
+            if response.status_code == 200:
+                papers = response.json()
+
+                # Optionally save the data to a file
+                if save_to_file:
+                    with open('recommended_papers.json', 'w') as output:
+                        json.dump(papers, output)
+                return papers
+
+            else:
+                return {
+                    "error": "Request failed with status code "
+                    f"{response.status_code}"
+                }
+        except requests.exceptions.RequestException as e:
+            return {"error": str(e)}
+
+    def fetch_author_data(
+        self,
+        ids: List[str],
+        fields: str = "name,url,paperCount,hIndex,papers",
+        save_to_file: bool = False,
+    ) -> dict:
+        r"""Fetches author information from the Semantic Scholar
+        API based on author IDs.
+
+        Args:
+            ids (list): A list of author IDs (as strings) to fetch
+            data for.
+
+            fields (str): A comma-separated list of fields to include
+            in the response (default includes name, URL, paper count,
+            hIndex, and papers).
+
+            save_to_file (bool): If True, saves the response data to
+            a file (default is False).
+
+        Returns:
+            dict: The response data from the API or error information if
+            the request fails.
+        """
+        url = f"{self.base_url}/author/batch"
+        query_params = {"fields": fields}
+        data = {"ids": ids}
+        try:
+            response = requests.post(url, params=query_params, json=data)
+            response.raise_for_status()
+            response_data = response.json()
+
+            # Optionally save the data to a file
+            if save_to_file:
+                with open('author_information.json', 'w') as output:
+                    json.dump(response_data, output)
+
+            return response_data
+        except requests.exceptions.RequestException as e:
+            return {"error": str(e)}
+
+    def get_tools(self) -> List[FunctionTool]:
+        r"""Returns a list of FunctionTool objects representing the
+        functions in the toolkit.
+
+        Returns:
+            List[FunctionTool]: A list of FunctionTool objects
+                representing the functions in the toolkit.
+        """
+        return [
+            FunctionTool(self.fetch_paper_data_title),
+            FunctionTool(self.fetch_paper_data_id),
+            FunctionTool(self.fetch_bulk_paper_data),
+            FunctionTool(self.fetch_recommended_papers),
+            FunctionTool(self.fetch_author_data),
+        ]