Create agent.py

agent.py

@@ -0,0 +1,63 @@
+import pandas as pd
+import requests
+from pydantic import Field, BaseModel
+
+from omegaconf import OmegaConf
+
+from vectara_agentic.agent import Agent
+from vectara_agentic.tools import ToolsFactory, VectaraToolFactory
+
+def create_assistant_tools(cfg):
+    class QueryDocsArgs(BaseModel):
+        query: str = Field(..., description="The user query, always in the form of a question", 
+                           examples=["Based on uploaded documents, what are the top four challenges of the Fintech sector in Saudi Arabia? list them in bullet points."])        
+        
+    vec_factory = VectaraToolFactory(vectara_api_key=cfg.api_key,
+                                     vectara_corpus_key=cfg.corpus_key)
+    summarizer = 'mockingbird-1.0-2024-07-16'
+    ask_docs = vec_factory.create_rag_tool(
+        tool_name = "ask_docs",
+        tool_description = """
+        Responds to an user question about a particular analysis, based on the documentation provide.
+        """,
+        tool_args_schema = QueryDocsArgs,
+        reranker = "chain", rerank_k = 100, 
+        rerank_chain = [
+            {
+                "type": "multilingual_reranker_v1",
+#                "cutoff": 0.2
+            },
+            {
+                "type": "mmr",
+                "diversity_bias": 0.2,
+                "limit": 50
+            }
+        ],
+        n_sentences_before = 2, n_sentences_after = 2, lambda_val = 0.005,
+        summary_num_results = 15,
+        vectara_summarizer = summarizer,
+        include_citations = True,
+        #vectara_prompt_text=prompt,
+        save_history = True,
+        verbose=False
+    )
+    tools_factory = ToolsFactory()
+    return (
+            tools_factory.standard_tools() +
+            [ask_docs]
+    )
+
+def initialize_agent(_cfg, agent_progress_callback=None):
+    stc_bank_bot_instructions = """
+    - Call the the ask_docs tool to retrieve the information to answer the user query.
+    - Always summarize the response.
+    """
+
+    agent = Agent(
+        tools=create_assistant_tools(_cfg),
+        topic="STC Bank questions",
+        custom_instructions=stc_bank_bot_instructions,
+        agent_progress_callback=agent_progress_callback,
+    )
+    agent.report()
+    return agent