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import functools |
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import typing |
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import aiohttp |
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from langchain.docstore.document import Document |
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from langchain.utilities import SerpAPIWrapper |
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from src.utils_langchain import _chunk_sources, add_parser, _add_meta |
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from urllib.parse import urlparse |
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class H2OSerpAPIWrapper(SerpAPIWrapper): |
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def get_search_documents(self, query, |
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query_action=True, |
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chunk=True, chunk_size=512, |
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db_type='chroma', |
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headsize=50, |
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top_k_docs=-1): |
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docs = self.run(query, headsize) |
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chunk_sources = functools.partial(_chunk_sources, chunk=chunk, chunk_size=chunk_size, db_type=db_type) |
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docs = chunk_sources(docs) |
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if query_action: |
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docs = [x for x in docs if x.metadata['chunk_id'] >= 0] |
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else: |
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docs = [x for x in docs if x.metadata['chunk_id'] == -1] |
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delta = 0.05 |
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[x.metadata.update(score=0.1 + delta * x.metadata['chunk_id'] if x.metadata['chunk_id'] >= 0 else -1) for x in |
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docs] |
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if top_k_docs >= 1: |
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top_k_docs = max(top_k_docs, len(docs)) |
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return docs, top_k_docs |
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async def arun(self, query: str, headsize: int, **kwargs: typing.Any) -> list: |
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"""Run query through SerpAPI and parse result async.""" |
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return self._process_response(await self.aresults(query), query, headsize) |
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def run(self, query: str, headsize: int, **kwargs: typing.Any) -> list: |
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"""Run query through SerpAPI and parse result.""" |
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return self._process_response(self.results(query), query, headsize) |
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@staticmethod |
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def _process_response(res: dict, query: str, headsize: int) -> list: |
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try: |
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return H2OSerpAPIWrapper.__process_response(res, query, headsize) |
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except Exception as e: |
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print("SERP search failed: %s" % str(e)) |
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return [] |
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@staticmethod |
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def __process_response(res: dict, query: str, headsize: int) -> list: |
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docs = [] |
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res1 = SerpAPIWrapper._process_response(res) |
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if res1: |
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if isinstance(res1, str) and not res1.startswith('['): |
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docs += [Document(page_content='Web search result %s: ' % len(docs) + res1, |
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metadata=dict(source='Web Search %s for %s' % (len(docs), query), score=0.0))] |
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elif isinstance(res1, list): |
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for x in res1: |
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date = '' |
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content = '' |
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if 'source' in x: |
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source = x['source'] |
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content += '%s says' % source |
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else: |
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content = 'Web search result %s: ' % len(docs) |
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if 'date' in x: |
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date = x['date'] |
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content += ' %s' % date |
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if 'title' in x: |
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content += ': %s' % x['title'] |
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if 'snippet' in x: |
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content += ': %s' % x['snippet'] |
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if 'link' in x: |
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link = x['link'] |
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domain = urlparse(link).netloc |
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font_size = 2 |
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source_name = domain |
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http_content = """<font size="%s"><a href="%s" target="_blank" rel="noopener noreferrer">%s</a></font>""" % ( |
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font_size, link, source_name) |
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source = 'Web Search %s' % len(docs) + \ |
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' from Date: %s Domain: %s Link: %s' % (date, domain, http_content) |
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if date: |
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content += ' around %s' % date |
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content += ' according to %s' % domain |
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else: |
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source = 'Web Search %s for %s' % (len(docs), query) |
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docs += [Document(page_content=content, metadata=dict(source=source, score=0.0))] |
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if "knowledge_graph" in res.keys(): |
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knowledge_graph = res["knowledge_graph"] |
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title = knowledge_graph["title"] if "title" in knowledge_graph else "" |
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if "description" in knowledge_graph.keys(): |
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docs += [Document(page_content='Web search result %s: ' % len(docs) + knowledge_graph["description"], |
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metadata=dict(source='Web Search %s with knowledge_graph description for %s' % ( |
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len(docs), query), score=0.0))] |
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for key, value in knowledge_graph.items(): |
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if ( |
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type(key) == str |
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and type(value) == str |
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and key not in ["title", "description"] |
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and not key.endswith("_stick") |
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and not key.endswith("_link") |
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and not value.startswith("http") |
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): |
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docs += [Document(page_content='Web search result %s: ' % len(docs) + f"{title} {key}: {value}.", |
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metadata=dict( |
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source='Web Search %s with knowledge_graph for %s' % (len(docs), query), |
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score=0.0))] |
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if "organic_results" in res.keys(): |
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for org_res in res["organic_results"]: |
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keys_to_try = ['snippet', 'snippet_highlighted_words', 'rich_snippet', 'rich_snippet_table', 'link'] |
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for key in keys_to_try: |
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if key in org_res.keys(): |
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date = '' |
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domain = '' |
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link = '' |
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snippet1 = '' |
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if key != 'link': |
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snippet1 = org_res[key] |
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if 'date' in org_res.keys(): |
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date = org_res['date'] |
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snippet1 += ' on %s' % date |
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else: |
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date = 'unknown date' |
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if 'link' in org_res.keys(): |
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link = org_res['link'] |
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domain = urlparse(link).netloc |
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if key == 'link': |
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snippet1 += ' Link at %s: <a href="%s">%s</a>' % (domain, link, domain) |
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else: |
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snippet1 += ' according to %s' % domain |
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if snippet1: |
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font_size = 2 |
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source_name = domain |
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http_content = """<font size="%s"><a href="%s" target="_blank" rel="noopener noreferrer">%s</a></font>""" % ( |
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font_size, link, source_name) |
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source = 'Web Search %s' % len(docs) + \ |
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' from Date: %s Domain: %s Link: %s' % (date, domain, http_content) |
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domain_simple = domain.replace('www.', '').replace('.com', '') |
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snippet1 = '%s says on %s: %s' % (domain_simple, date, snippet1) |
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docs += [Document(page_content=snippet1, metadata=dict(source=source), score=0.0)] |
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break |
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if "buying_guide" in res.keys(): |
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docs += [Document(page_content='Web search result %s: ' % len(docs) + res["buying_guide"], |
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metadata=dict(source='Web Search %s with buying_guide for %s' % (len(docs), query)), |
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score=0.0)] |
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if "local_results" in res.keys() and "places" in res["local_results"].keys(): |
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docs += [Document(page_content='Web search result %s: ' % len(docs) + res["local_results"]["places"], |
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metadata=dict( |
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source='Web Search %s with local_results_places for %s' % (len(docs), query)), |
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score=0.0)] |
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add_meta = functools.partial(_add_meta, headsize=headsize, parser='SERPAPI') |
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add_meta(docs, query) |
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return docs |
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def results(self, query: str) -> dict: |
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"""Run query through SerpAPI and return the raw result.""" |
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params = self.get_params(query) |
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search = self.search_engine(params) |
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res = search.get_dict() |
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return res |
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