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MadhuvodMadhuvod
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fixes some issues
1 parent fc02a7f commit 68f300d

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‎ai_agent_tutorials/ai_legal_agent_team/legal_agent_team.py

Lines changed: 156 additions & 112 deletions
Original file line numberDiff line numberDiff line change
@@ -7,8 +7,8 @@
77
from agno.embedder.openai import OpenAIEmbedder
88
import tempfile
99
import os
10+
from agno.document.chunking.document import DocumentChunking
1011

11-
#initializing the session state variables
1212
def init_session_state():
1313
"""Initialize session state variables"""
1414
if 'openai_api_key' not in st.session_state:
@@ -23,55 +23,87 @@ def init_session_state():
2323
st.session_state.legal_team = None
2424
if 'knowledge_base' not in st.session_state:
2525
st.session_state.knowledge_base = None
26+
# Add a new state variable to track processed files
27+
if 'processed_files' not in st.session_state:
28+
st.session_state.processed_files = set()
29+
30+
COLLECTION_NAME = "legal_documents" # Define your collection name
2631

2732
def init_qdrant():
28-
"""Initialize Qdrant vector database"""
29-
if not st.session_state.qdrant_api_key:
30-
raise ValueError("Qdrant API key not provided")
31-
if not st.session_state.qdrant_url:
32-
raise ValueError("Qdrant URL not provided")
33-
34-
return Qdrant(
35-
collection="legal_knowledge",
36-
url=st.session_state.qdrant_url,
37-
api_key=st.session_state.qdrant_api_key,
38-
https=True,
39-
timeout=None,
40-
distance="cosine"
41-
)
33+
"""Initialize Qdrant client with configured settings."""
34+
if not all([st.session_state.qdrant_api_key, st.session_state.qdrant_url]):
35+
return None
36+
try:
37+
# Create Agno's Qdrant instance which implements VectorDb
38+
vector_db = Qdrant(
39+
collection=COLLECTION_NAME,
40+
url=st.session_state.qdrant_url,
41+
api_key=st.session_state.qdrant_api_key,
42+
embedder=OpenAIEmbedder(
43+
id="text-embedding-3-small",
44+
api_key=st.session_state.openai_api_key
45+
)
46+
)
47+
return vector_db
48+
except Exception as e:
49+
st.error(f"🔴 Qdrant connection failed: {str(e)}")
50+
return None
4251

4352
def process_document(uploaded_file, vector_db: Qdrant):
44-
"""Process document, create embeddings and store in Qdrant vector database"""
53+
"""
54+
Process document, create embeddings and store in Qdrant vector database
55+
56+
Args:
57+
uploaded_file: Streamlit uploaded file object
58+
vector_db (Qdrant): Initialized Qdrant instance from Agno
59+
60+
Returns:
61+
PDFKnowledgeBase: Initialized knowledge base with processed documents
62+
"""
4563
if not st.session_state.openai_api_key:
4664
raise ValueError("OpenAI API key not provided")
4765

4866
os.environ['OPENAI_API_KEY'] = st.session_state.openai_api_key
4967

50-
with tempfile.TemporaryDirectory() as temp_dir:
51-
52-
temp_file_path = os.path.join(temp_dir, uploaded_file.name)
53-
with open(temp_file_path, "wb") as f:
54-
f.write(uploaded_file.getbuffer())
55-
56-
try:
57-
58-
embedder = OpenAIEmbedder(
59-
model="text-embedding-3-small",
60-
api_key=st.session_state.openai_api_key
68+
try:
69+
# Save the uploaded file to a temporary location
70+
with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as temp_file:
71+
temp_file.write(uploaded_file.getvalue())
72+
temp_file_path = temp_file.name
73+
74+
st.info("Loading and processing document...")
75+
76+
# Create a PDFKnowledgeBase with the vector_db
77+
knowledge_base = PDFKnowledgeBase(
78+
path=temp_file_path, # Single string path, not a list
79+
vector_db=vector_db,
80+
reader=PDFReader(),
81+
chunking_strategy=DocumentChunking(
82+
chunk_size=1000,
83+
overlap=200
6184
)
85+
)
86+
87+
# Load the documents into the knowledge base
88+
with st.spinner('📤 Loading documents into knowledge base...'):
89+
try:
90+
knowledge_base.load(recreate=True, upsert=True)
91+
st.success("✅ Documents stored successfully!")
92+
except Exception as e:
93+
st.error(f"Error loading documents: {str(e)}")
94+
raise
95+
96+
# Clean up the temporary file
97+
try:
98+
os.unlink(temp_file_path)
99+
except Exception:
100+
pass
62101

63-
# Creating knowledge base with explicit Qdrant configuration
64-
knowledge_base = PDFKnowledgeBase(
65-
path=temp_dir,
66-
vector_db=vector_db,
67-
reader=PDFReader(chunk=True),
68-
embedder=embedder,
69-
recreate_vector_db=True
70-
)
71-
knowledge_base.load()
72-
return knowledge_base
73-
except Exception as e:
74-
raise Exception(f"Error processing document: {str(e)}")
102+
return knowledge_base
103+
104+
except Exception as e:
105+
st.error(f"Document processing error: {str(e)}")
106+
raise Exception(f"Error processing document: {str(e)}")
75107

76108
def main():
77109
st.set_page_config(page_title="Legal Document Analyzer", layout="wide")
@@ -102,7 +134,7 @@ def main():
102134

103135
qdrant_url = st.text_input(
104136
"Qdrant URL",
105-
value=st.session_state.qdrant_url if st.session_state.qdrant_url else "https://f499085c-b4bf-4bda-a9a5-227f62a9ca20.us-west-2-0.aws.cloud.qdrant.io:6333",
137+
value=st.session_state.qdrant_url if st.session_state.qdrant_url else "",
106138
help="Enter your Qdrant instance URL"
107139
)
108140
if qdrant_url:
@@ -111,8 +143,10 @@ def main():
111143
if all([st.session_state.qdrant_api_key, st.session_state.qdrant_url]):
112144
try:
113145
if not st.session_state.vector_db:
146+
# Make sure we're initializing a QdrantClient here
114147
st.session_state.vector_db = init_qdrant()
115-
st.success("Successfully connected to Qdrant!")
148+
if st.session_state.vector_db:
149+
st.success("Successfully connected to Qdrant!")
116150
except Exception as e:
117151
st.error(f"Failed to connect to Qdrant: {str(e)}")
118152

@@ -123,80 +157,90 @@ def main():
123157
uploaded_file = st.file_uploader("Upload Legal Document", type=['pdf'])
124158

125159
if uploaded_file:
126-
with st.spinner("Processing document..."):
127-
try:
128-
knowledge_base = process_document(uploaded_file, st.session_state.vector_db)
129-
st.session_state.knowledge_base = knowledge_base
130-
131-
# Initialize agents
132-
legal_researcher = Agent(
133-
name="Legal Researcher",
134-
role="Legal research specialist",
135-
model=OpenAIChat(model="gpt-4o"),
136-
tools=[DuckDuckGoTools()],
137-
knowledge=st.session_state.knowledge_base,
138-
search_knowledge=True,
139-
instructions=[
140-
"Find and cite relevant legal cases and precedents",
141-
"Provide detailed research summaries with sources",
142-
"Reference specific sections from the uploaded document",
143-
"Always search the knowledge base for relevant information"
144-
],
145-
show_tool_calls=True,
146-
markdown=True
147-
)
160+
# Check if this file has already been processed
161+
if uploaded_file.name not in st.session_state.processed_files:
162+
with st.spinner("Processing document..."):
163+
try:
164+
# Process the document and get the knowledge base
165+
knowledge_base = process_document(uploaded_file, st.session_state.vector_db)
166+
167+
if knowledge_base:
168+
st.session_state.knowledge_base = knowledge_base
169+
# Add the file to processed files
170+
st.session_state.processed_files.add(uploaded_file.name)
171+
172+
# Initialize agents
173+
legal_researcher = Agent(
174+
name="Legal Researcher",
175+
role="Legal research specialist",
176+
model=OpenAIChat(id="gpt-4o"),
177+
tools=[DuckDuckGoTools()],
178+
knowledge=st.session_state.knowledge_base,
179+
search_knowledge=True,
180+
instructions=[
181+
"Find and cite relevant legal cases and precedents",
182+
"Provide detailed research summaries with sources",
183+
"Reference specific sections from the uploaded document",
184+
"Always search the knowledge base for relevant information"
185+
],
186+
show_tool_calls=True,
187+
markdown=True
188+
)
148189

149-
contract_analyst = Agent(
150-
name="Contract Analyst",
151-
role="Contract analysis specialist",
152-
model=OpenAIChat(model="gpt-4o"),
153-
knowledge=knowledge_base,
154-
search_knowledge=True,
155-
instructions=[
156-
"Review contracts thoroughly",
157-
"Identify key terms and potential issues",
158-
"Reference specific clauses from the document"
159-
],
160-
markdown=True
161-
)
190+
contract_analyst = Agent(
191+
name="Contract Analyst",
192+
role="Contract analysis specialist",
193+
model=OpenAIChat(id="gpt-4o"),
194+
knowledge=st.session_state.knowledge_base,
195+
search_knowledge=True,
196+
instructions=[
197+
"Review contracts thoroughly",
198+
"Identify key terms and potential issues",
199+
"Reference specific clauses from the document"
200+
],
201+
markdown=True
202+
)
162203

163-
legal_strategist = Agent(
164-
name="Legal Strategist",
165-
role="Legal strategy specialist",
166-
model=OpenAIChat(model="gpt-4o"),
167-
knowledge=knowledge_base,
168-
search_knowledge=True,
169-
instructions=[
170-
"Develop comprehensive legal strategies",
171-
"Provide actionable recommendations",
172-
"Consider both risks and opportunities"
173-
],
174-
markdown=True
175-
)
204+
legal_strategist = Agent(
205+
name="Legal Strategist",
206+
role="Legal strategy specialist",
207+
model=OpenAIChat(id="gpt-4o"),
208+
knowledge=st.session_state.knowledge_base,
209+
search_knowledge=True,
210+
instructions=[
211+
"Develop comprehensive legal strategies",
212+
"Provide actionable recommendations",
213+
"Consider both risks and opportunities"
214+
],
215+
markdown=True
216+
)
176217

177-
# Legal Agent Team
178-
st.session_state.legal_team = Agent(
179-
name="Legal Team Lead",
180-
role="Legal team coordinator",
181-
model=OpenAIChat(model="gpt-4o"),
182-
team=[legal_researcher, contract_analyst, legal_strategist],
183-
knowledge=st.session_state.knowledge_base,
184-
search_knowledge=True,
185-
instructions=[
186-
"Coordinate analysis between team members",
187-
"Provide comprehensive responses",
188-
"Ensure all recommendations are properly sourced",
189-
"Reference specific parts of the uploaded document",
190-
"Always search the knowledge base before delegating tasks"
191-
],
192-
show_tool_calls=True,
193-
markdown=True
194-
)
195-
196-
st.success("✅ Document processed and team initialized!")
197-
198-
except Exception as e:
199-
st.error(f"Error processing document: {str(e)}")
218+
# Legal Agent Team
219+
st.session_state.legal_team = Agent(
220+
name="Legal Team Lead",
221+
role="Legal team coordinator",
222+
model=OpenAIChat(id="gpt-4o"),
223+
team=[legal_researcher, contract_analyst, legal_strategist],
224+
knowledge=st.session_state.knowledge_base,
225+
search_knowledge=True,
226+
instructions=[
227+
"Coordinate analysis between team members",
228+
"Provide comprehensive responses",
229+
"Ensure all recommendations are properly sourced",
230+
"Reference specific parts of the uploaded document",
231+
"Always search the knowledge base before delegating tasks"
232+
],
233+
show_tool_calls=True,
234+
markdown=True
235+
)
236+
237+
st.success("✅ Document processed and team initialized!")
238+
239+
except Exception as e:
240+
st.error(f"Error processing document: {str(e)}")
241+
else:
242+
# File already processed, just show a message
243+
st.success("✅ Document already processed and team ready!")
200244

201245
st.divider()
202246
st.header("🔍 Analysis Options")

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