Upload app.py

app.py

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+import os
+import pandas as pd
+import gradio as gr
+from crewai import Agent, Task, Crew
+from langchain_openai import ChatOpenAI
+from crewai_tools import PDFSearchTool, FileReadTool, DOCXSearchTool, CSVSearchTool
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain.agents.agent_types import AgentType
+from langchain_experimental.agents.agent_toolkits import create_csv_agent
+from langchain_groq import ChatGroq
+
+# API keys-----------------move them to ENV 
+os.environ["OPENAI_API_KEY"] = "NA"
+os.environ["GOOGLE_API_KEY"] = "AIzaSyD7jKc5MdkRLakxcyhvrpie8XgbwY98NMo"
+
+# Load The Groq model for LLM
+llm = ChatGroq(
+    api_key="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",
+    model="llama3-70b-8192"
+)
+
+#<-----------------------------Tools----------------------------------->
+class tools:
+    def pdfRead(path):
+        PDFtool = PDFSearchTool(
+            config=dict(
+                llm=dict(
+                    provider="google",
+                    config=dict(
+                        model="gemini-1.5-flash-latest",
+                    ),
+                ),
+                embedder=dict(
+                    provider="huggingface",
+                    config=dict(
+                        model="sentence-transformers/msmarco-distilbert-base-v4"
+                        
+                    ),
+                ),
+            ),
+            pdf=path
+        )
+        return PDFtool
+    
+    def fileRead(path):
+        Filetool = FileReadTool(
+            config=dict(
+                llm=dict(
+                    provider="google",
+                    config=dict(
+                        model="gemini-1.5-flash-latest",
+                    ),
+                ),
+                embedder=dict(
+                    provider="huggingface",
+                    config=dict(
+                        model="sentence-transformers/msmarco-distilbert-base-v4"
+                        
+                    ),
+                ),
+            ),
+            file_path=path
+        )
+        return Filetool
+    
+    def docsRead(path):
+        Docstool = DOCXSearchTool(
+            config=dict(
+                llm=dict(
+                    provider="google",
+                    config=dict(
+                        model="gemini-1.5-flash-latest",
+                    ),
+                ),
+                embedder=dict(
+                    provider="huggingface",
+                    config=dict(
+                        model="sentence-transformers/msmarco-distilbert-base-v4"
+                        
+                    ),
+                ),
+            ),
+            docx=path
+        )
+        return Docstool
+#<-----------------------------Tools----------------------------------->
+
+#<------------------------------Agents START------------------------->
+
+class AgentLoader:
+
+    def csvReaderAgent(path):
+        agent = create_csv_agent(
+            ChatGoogleGenerativeAI(temperature=0.6, model="gemini-1.5-flash-latest"),
+            path,
+            verbose=True,
+            agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION
+        )
+        return agent
+
+    def fileReaderAgent(path):
+        FileReader = Agent(
+            role='File searcher',
+            goal='To analyse and generate optimal and reliable results',
+            backstory="""You are a File specialist and can handle multiple file formats like .txt, .csv, .json etc.
+            You are responsible to analyse the file to find the relevant content that solves the problem of the user and generate high quality and reliable results.
+            You should also provide the results of your analysis and searching.""",
+            llm=llm,
+            verbose=True,
+            tools=[tools.fileRead(path)],
+            allow_delegation=False
+        )
+        return FileReader
+    
+    def PdfReaderAgent(path):
+        PdfReader = Agent(
+            role='PDF searcher',
+            goal='To analyse and generate optimal and reliable results',
+            backstory="""You are a PDF specialist and content writer.
+            You are responsible to analyse the pdf to find the relevant content that solves the problem of the user and generate high quality and reliable results.
+            You should also provide the results of your analysis and searching.""",
+            llm=llm,
+            verbose=True,
+            tools=[tools.pdfRead(path)],
+            allow_delegation=False
+        )
+        return PdfReader
+    
+    def DocsReaderAgent(path):
+        DocsReader = Agent(
+            role='Docs searcher',
+            goal='To analyse and generate optimal and reliable results',
+            backstory="""You are a Docs specialist and content writer.
+            You are responsible to analyse the pdf to find the relevant content that solves the problem of the user and generate high quality and reliable results.
+            You should also provide the results of your analysis and searching.""",
+            llm=llm,
+            verbose=True,
+            tools=[tools.docsRead(path)],
+            allow_delegation=False
+        )
+        return DocsReader
+    
+    def writerAgent():
+        writer=Agent(
+            role='Content Writer',
+            goal='To provide QUICK and reliable output',
+            backstory="""You are content specialist.
+            You are responsible to generate high quality results in the required format very quickly as soon as data is available.
+            You are very accurate and fast at the same time.""",
+            verbose=True,
+            llm=llm,
+            max_iter=5
+        )
+        return writer
+
+#<------------------------------Agents END------------------------->
+
+#<-------------------------------Tasks---------------------------->
+def getTasks(query, agent, exp):
+    task_read=Task(
+        description=f'{query}',
+        agent=agent,
+        expected_output=f'A detailed information on {query}'
+    )
+
+    task_write=Task(
+        description=f'{query}',
+        agent=AgentLoader.writerAgent(),
+        expected_output=exp
+    )
+
+    return [task_read, task_write]
+
+# Gradio interface function
+def process_file(file, query, expected_output):
+    path = file.name
+    
+    if path.endswith(".pdf"):
+        agent = AgentLoader.PdfReaderAgent(path)
+    elif path.endswith(".docx"):
+        agent = AgentLoader.DocsReaderAgent(path)
+    elif path.endswith(".json") or path.endswith(".txt"):
+        agent = AgentLoader.fileReaderAgent(path)
+    elif path.endswith(".csv"):
+        agent = AgentLoader.csvReaderAgent(path)
+        results = agent.run(query)
+    else:
+        return 'File NOT supported'
+    
+    if not path.endswith(".csv"):
+        task1 = getTasks(query, agent, expected_output)
+        mycrew = Crew(
+            agents=[agent, AgentLoader.writerAgent()],
+            tasks=task1,
+            verbose=True
+        )
+        results = mycrew.kickoff()
+    
+    return results
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=process_file,
+    inputs=[
+        gr.File(label="Upload File"),
+        gr.Textbox(label="Query"),
+        gr.Textbox(label="Expected Output")
+    ],
+    outputs="text",
+    title="File Analyzer",
+    description="Upload a file (CSV, PDF, DOCX, TXT, JSON) and enter your query to get detailed information."
+)
+
+# Launch the Gradio interface
+interface.launch()