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  • #  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
    
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    #
    #  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.
    #
    
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    from flask import request
    
    from flask_login import login_required
    
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    from api.db.services.dialog_service import DialogService, ConversationService
    
    from api.db import LLMType
    
    from api.db.services.knowledgebase_service import KnowledgebaseService
    
    from api.db.services.llm_service import LLMService, LLMBundle, TenantLLMService
    
    from api.settings import access_logger, stat_logger, retrievaler, chat_logger
    
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    from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
    from api.utils import get_uuid
    from api.utils.api_utils import get_json_result
    
    from rag.app.resume import forbidden_select_fields4resume
    
    from rag.nlp.search import index_name
    
    from rag.utils import num_tokens_from_string, encoder, rmSpace
    
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    @manager.route('/set', methods=['POST'])
    @login_required
    
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        req = request.json
        conv_id = req.get("conversation_id")
        if conv_id:
            del req["conversation_id"]
            try:
                if not ConversationService.update_by_id(conv_id, req):
                    return get_data_error_result(retmsg="Conversation not found!")
                e, conv = ConversationService.get_by_id(conv_id)
                if not e:
                    return get_data_error_result(
                        retmsg="Fail to update a conversation!")
                conv = conv.to_dict()
                return get_json_result(data=conv)
            except Exception as e:
                return server_error_response(e)
    
        try:
            e, dia = DialogService.get_by_id(req["dialog_id"])
            if not e:
                return get_data_error_result(retmsg="Dialog not found")
            conv = {
                "id": get_uuid(),
                "dialog_id": req["dialog_id"],
    
                "name": req.get("name", "New conversation"),
    
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                "message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}]
            }
            ConversationService.save(**conv)
            e, conv = ConversationService.get_by_id(conv["id"])
            if not e:
                return get_data_error_result(retmsg="Fail to new a conversation!")
            conv = conv.to_dict()
            return get_json_result(data=conv)
        except Exception as e:
            return server_error_response(e)
    
    
    @manager.route('/get', methods=['GET'])
    @login_required
    def get():
        conv_id = request.args["conversation_id"]
        try:
            e, conv = ConversationService.get_by_id(conv_id)
            if not e:
                return get_data_error_result(retmsg="Conversation not found!")
            conv = conv.to_dict()
            return get_json_result(data=conv)
        except Exception as e:
            return server_error_response(e)
    
    
    @manager.route('/rm', methods=['POST'])
    @login_required
    def rm():
        conv_ids = request.json["conversation_ids"]
        try:
            for cid in conv_ids:
                ConversationService.delete_by_id(cid)
            return get_json_result(data=True)
        except Exception as e:
            return server_error_response(e)
    
    
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    @manager.route('/list', methods=['GET'])
    @login_required
    
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        dialog_id = request.args["dialog_id"]
        try:
    
            convs = ConversationService.query(
                dialog_id=dialog_id,
                order_by=ConversationService.model.create_time,
                reverse=True)
    
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            convs = [d.to_dict() for d in convs]
            return get_json_result(data=convs)
        except Exception as e:
            return server_error_response(e)
    
    
    def message_fit_in(msg, max_length=4000):
        def count():
            nonlocal msg
            tks_cnts = []
    
            for m in msg:
                tks_cnts.append(
                    {"role": m["role"], "count": num_tokens_from_string(m["content"])})
    
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            total = 0
    
            for m in tks_cnts:
                total += m["count"]
    
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            return total
    
        c = count()
    
        if c < max_length:
            return c, msg
    
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        msg_ = [m for m in msg[:-1] if m["role"] == "system"]
    
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        msg_.append(msg[-1])
        msg = msg_
        c = count()
    
        if c < max_length:
            return c, msg
    
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        ll = num_tokens_from_string(msg_[0].content)
        l = num_tokens_from_string(msg_[-1].content)
    
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            m = msg_[0].content
    
            m = encoder.decode(encoder.encode(m)[:max_length - l])
    
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            msg[0].content = m
            return max_length, msg
    
        m = msg_[1].content
    
        m = encoder.decode(encoder.encode(m)[:max_length - l])
    
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        msg[1].content = m
        return max_length, msg
    
    
    
    @manager.route('/completion', methods=['POST'])
    @login_required
    
    @validate_request("conversation_id", "messages")
    
    def completion():
        req = request.json
        msg = []
        for m in req["messages"]:
    
            if m["role"] == "system":
                continue
            if m["role"] == "assistant" and not msg:
                continue
    
            msg.append({"role": m["role"], "content": m["content"]})
        try:
    
            e, conv = ConversationService.get_by_id(req["conversation_id"])
            if not e:
                return get_data_error_result(retmsg="Conversation not found!")
            conv.message.append(msg[-1])
            e, dia = DialogService.get_by_id(conv.dialog_id)
    
            if not e:
                return get_data_error_result(retmsg="Dialog not found!")
    
            del req["conversation_id"]
    
            ans = chat(dia, msg, **req)
    
            if not conv.reference:
                conv.reference = []
    
            conv.reference.append(ans["reference"])
            conv.message.append({"role": "assistant", "content": ans["answer"]})
            ConversationService.update_by_id(conv.id, conv.to_dict())
            return get_json_result(data=ans)
    
        except Exception as e:
            return server_error_response(e)
    
    
    
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    def chat(dialog, messages, **kwargs):
        assert messages[-1]["role"] == "user", "The last content of this conversation is not from user."
        llm = LLMService.query(llm_name=dialog.llm_id)
        if not llm:
    
            llm = TenantLLMService.query(tenant_id=dialog.tenant_id, llm_name=dialog.llm_id)
            if not llm:
                raise LookupError("LLM(%s) not found" % dialog.llm_id)
            max_tokens = 1024
        else: max_tokens = llm[0].max_tokens
    
        questions = [m["content"] for m in messages if m["role"] == "user"]
    
        embd_mdl = LLMBundle(dialog.tenant_id, LLMType.EMBEDDING)
        chat_mdl = LLMBundle(dialog.tenant_id, LLMType.CHAT, dialog.llm_id)
    
        field_map = KnowledgebaseService.get_field_map(dialog.kb_ids)
    
        # try to use sql if field mapping is good to go
    
        if field_map:
    
            chat_logger.info("Use SQL to retrieval:{}".format(questions[-1]))
    
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            ans = use_sql(questions[-1], field_map, dialog.tenant_id, chat_mdl)
            if ans: return ans
    
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        prompt_config = dialog.prompt_config
        for p in prompt_config["parameters"]:
    
            if p["key"] == "knowledge":
                continue
            if p["key"] not in kwargs and not p["optional"]:
                raise KeyError("Miss parameter: " + p["key"])
    
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            if p["key"] not in kwargs:
    
                prompt_config["system"] = prompt_config["system"].replace(
                    "{%s}" % p["key"], " ")
    
        for _ in range(len(questions) // 2):
    
            questions.append(questions[-1])
    
        if "knowledge" not in [p["key"] for p in prompt_config["parameters"]]:
    
            kbinfos = {"total": 0, "chunks": [], "doc_aggs": []}
    
        else:
            kbinfos = retrievaler.retrieval(" ".join(questions), embd_mdl, dialog.tenant_id, dialog.kb_ids, 1, dialog.top_n,
    
                                            dialog.similarity_threshold,
                                            dialog.vector_similarity_weight, top=1024, aggs=False)
    
        knowledges = [ck["content_with_weight"] for ck in kbinfos["chunks"]]
    
        chat_logger.info(
            "{}->{}".format(" ".join(questions), "\n->".join(knowledges)))
    
        if not knowledges and prompt_config.get("empty_response"):
    
            return {
                "answer": prompt_config["empty_response"], "reference": kbinfos}
    
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        kwargs["knowledge"] = "\n".join(knowledges)
    
        gen_conf = dialog.llm_setting
    
        msg = [{"role": m["role"], "content": m["content"]}
               for m in messages if m["role"] != "system"]
    
        used_token_count, msg = message_fit_in(msg, int(max_tokens * 0.97))
    
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        if "max_tokens" in gen_conf:
    
            gen_conf["max_tokens"] = min(
                gen_conf["max_tokens"],
    
                max_tokens - used_token_count)
    
        answer = chat_mdl.chat(
            prompt_config["system"].format(
                **kwargs), msg, gen_conf)
        chat_logger.info("User: {}|Assistant: {}".format(
            msg[-1]["content"], answer))
    
            answer, idx = retrievaler.insert_citations(answer,
    
                                                       [ck["content_ltks"]
                                                           for ck in kbinfos["chunks"]],
                                                       [ck["vector"]
                                                           for ck in kbinfos["chunks"]],
                                                       embd_mdl,
                                                       tkweight=1 - dialog.vector_similarity_weight,
                                                       vtweight=dialog.vector_similarity_weight)
    
            idx = set([kbinfos["chunks"][int(i)]["doc_id"] for i in idx])
    
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            recall_docs = [
    
                d for d in kbinfos["doc_aggs"] if d["doc_id"] in idx]
    
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            if not recall_docs: recall_docs = kbinfos["doc_aggs"]
            kbinfos["doc_aggs"] = recall_docs
    
        for c in kbinfos["chunks"]:
    
            if c.get("vector"):
                del c["vector"]
    
        if answer.lower().find("invalid key") >= 0 or answer.lower().find("invalid api")>=0:
            answer += " Please set LLM API-Key in 'User Setting -> Model Providers -> API-Key'"
    
        return {"answer": answer, "reference": kbinfos}
    
    def use_sql(question, field_map, tenant_id, chat_mdl):
    
        sys_prompt = "你是一个DBA。你需要这对以下表的字段结构,根据用户的问题列表,写出最后一个问题对应的SQL。"
    
        user_promt = """
    表名:{};
    数据库表字段说明如下:
    {}
    
    
    请写出SQL, 且只要SQL,不要有其他说明及文字。
    
    """.format(
            index_name(tenant_id),
    
            "\n".join([f"{k}: {v}" for k, v in field_map.items()]),
    
        def get_table():
            nonlocal sys_prompt, user_promt, question, tried_times
    
            sql = chat_mdl.chat(sys_prompt, [{"role": "user", "content": user_promt}], {
                                "temperature": 0.06})
    
            print(user_promt, sql)
            chat_logger.info(f"{question}”==>{user_promt} get SQL: {sql}")
            sql = re.sub(r"[\r\n]+", " ", sql.lower())
            sql = re.sub(r".*select ", "select ", sql.lower())
            sql = re.sub(r" +", " ", sql)
            sql = re.sub(r"([;;]|```).*", "", sql)
            if sql[:len("select ")] != "select ":
                return None, None
            if not re.search(r"((sum|avg|max|min)\(|group by )", sql.lower()):
                if sql[:len("select *")] != "select *":
                    sql = "select doc_id,docnm_kwd," + sql[6:]
                else:
                    flds = []
                    for k in field_map.keys():
    
                        if k in forbidden_select_fields4resume:
                            continue
                        if len(flds) > 11:
                            break
    
                        flds.append(k)
                    sql = "select doc_id,docnm_kwd," + ",".join(flds) + sql[8:]
    
            print(f"{question}” get SQL(refined): {sql}")
    
            chat_logger.info(f"{question}” get SQL(refined): {sql}")
            tried_times += 1
            return retrievaler.sql_retrieval(sql, format="json"), sql
    
        tbl, sql = get_table()
    
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        if tbl is None:
    
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            return None
    
        if tbl.get("error") and tried_times <= 2:
            user_promt = """
            表名:{};
            数据库表字段说明如下:
            {}
    
            问题如下:
            {}
    
            你上一次给出的错误SQL如下:
            {}
    
            请纠正SQL中的错误再写一遍,且只要SQL,不要有其他说明及文字。
            """.format(
                index_name(tenant_id),
                "\n".join([f"{k}: {v}" for k, v in field_map.items()]),
                question, sql, tbl["error"]
            )
            tbl, sql = get_table()
            chat_logger.info("TRY it again: {}".format(sql))
    
        chat_logger.info("GET table: {}".format(tbl))
        print(tbl)
    
        if tbl.get("error") or len(tbl["rows"]) == 0:
    
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            return None
    
        docid_idx = set([ii for ii, c in enumerate(
            tbl["columns"]) if c["name"] == "doc_id"])
        docnm_idx = set([ii for ii, c in enumerate(
            tbl["columns"]) if c["name"] == "docnm_kwd"])
        clmn_idx = [ii for ii in range(
            len(tbl["columns"])) if ii not in (docid_idx | docnm_idx)]
    
        # compose markdown table
    
        clmns = "|" + "|".join([re.sub(r"(/.*|([^()]+))", "", field_map.get(tbl["columns"][i]["name"],
                               tbl["columns"][i]["name"])) for i in clmn_idx]) + ("|Source|" if docid_idx and docid_idx else "|")
        line = "|" + "|".join(["------" for _ in range(len(clmn_idx))]) + \
            ("|------|" if docid_idx and docid_idx else "")
        rows = ["|" +
                "|".join([rmSpace(str(r[i])) for i in clmn_idx]).replace("None", " ") +
                "|" for r in tbl["rows"]]
    
        if not docid_idx or not docnm_idx:
    
            chat_logger.warning("SQL missing field: " + sql)
    
            return "\n".join([clmns, line, "\n".join(rows)]), []
    
    
        rows = "\n".join([r + f" ##{ii}$$ |" for ii, r in enumerate(rows)])
    
        rows = re.sub(r"T[0-9]{2}:[0-9]{2}:[0-9]{2}(\.[0-9]+Z)?\|", "|", rows)
    
        docid_idx = list(docid_idx)[0]
        docnm_idx = list(docnm_idx)[0]
    
        doc_aggs = {}
        for r in tbl["rows"]:
            if r[docid_idx] not in doc_aggs:
                doc_aggs[r[docid_idx]] = {"doc_name": r[docnm_idx], "count": 0}
            doc_aggs[r[docid_idx]]["count"] += 1
    
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        return {
            "answer": "\n".join([clmns, line, rows]),
            "reference": {"chunks": [{"doc_id": r[docid_idx], "docnm_kwd": r[docnm_idx]} for r in tbl["rows"]],
    
                          "doc_aggs": [{"doc_id": did, "doc_name": d["doc_name"], "count": d["count"]} for did, d in doc_aggs.items()]}