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New asset for analyzing and talking to financial documents with graphs and images
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‎ai/generative-ai-service/financial-analysis-chatbot/README.md

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# 📊 Document Analysis with Graphs
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A Streamlit-based application for extracting insights from financial documents by combining text and visual (chart/image) content using Oracle Generative AI.
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This tool enables semantic search, summarization, and financial Q&A by leveraging OCI GenAI services — providing rich context-aware answers grounded in both OCR-extracted text and chart images.
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Author: **Ali Ottoman**
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---
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## 🔧 Features
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### Multimodal Financial Document Processing
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- Upload PDFs or images of corporate financial documents.
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- Extract both **textual data** and **visual elements** (charts, tables, graphs).
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### Oracle GenAI-Powered Search & QA
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- Embed documents using **Cohere Embed v4.0** via OCI Generative AI.
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- Use **Llama 4 Maverick** to answer questions with visual + textual reasoning.
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- "Super Searcher" mode rewrites your query with **Command A** for enhanced semantic search.
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### Semantic Memory & Chat Interface
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- Context-aware responses based on prior conversation.
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- Semantic search across vectorized chunks using Qdrant.
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- Responses grounded in document context + image evidence.
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### Summary & Analytics View
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- Summarizes uploaded financial reports into key highlights.
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- Understand KPIs, trends, and performance across firm sizes and time periods.
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---
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## 👥 Who Can Use This
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**Finance & Strategy Teams**
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→ Analyze trends, ratios, and balance sheet insights across time with chart references.
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**Business Analysts**
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→ Automate exploration of complex PDF documents and balance sheets.
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**Developers & AI Engineers**
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→ Explore multimodal document Q&A using OCI’s latest GenAI capabilities.
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**Anyone using OCI AI Services**
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→ Seamlessly integrate this workflow into larger OCI-based analytics pipelines.
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---
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## 🗂️ Files & Structure
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```
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.
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├── doc_analysis_with_graphs.py # Main Streamlit app
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├── config.py # OCI config & model IDs (user-provided)
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├── requirements.txt # Python dependencies
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└── README.md # You're reading it
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```
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---
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## ⚙️ Setup & Installation
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### 1. Clone the Repository
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```bash
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git clone https://github.com/your-username/your-repo.git
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cd your-repo
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```
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### 2. Configure OCI Credentials
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Fill out the `config.py` file:
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```python
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# config.py
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COMPARTMENT_ID = "<your OCI Compartment OCID>"
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```
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Ensure you also have an OCI config file (usually at `~/.oci/config`) with proper credentials.
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### 3. Install Requirements
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```bash
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pip install -r requirements.txt
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```
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---
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## 🚀 Run the App
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```bash
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streamlit run doc_analysis_with_graphs.py
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```
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---
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## 📝 How to Use
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### 1. Upload your documents
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→ PDFs or images containing **financial reports, charts, balance sheets**
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### 2. Ask your question
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→ Examples:
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- “What is the change in ROA from 1990 to 2000?”
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- “Summarize the key liquidity trends in small firms.”
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- “Explain the data in Chart 2a on debt ratios.”
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### 3. View responses
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→ AI replies with:
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- Financially-grounded insights
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- Visual chart references (axes, values)
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- Source document images
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- NULL if data is unavailable
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---
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## 🛠️ Customization
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- **Enable/disable Super Searcher** to use Command-A for rephrased queries.
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- **Change model temperature or token limits** in `ChatOCIGenAI` constructor.
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- **Add custom logic** to extend analysis for ratios, ROE, gearing, sector comparison, etc.
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---
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## 🧠 Example Chat
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> **You**: What is the debt-to-assets ratio trend from 1990 to 2000?
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>
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> **AI**:
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> - Debt-to-assets ratio declined from **47% in 1990** to **39% in 2000**.
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> - As per **Chart 1a**, small firms saw the sharpest drop post-1997.
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> - The Y-axis shows the ratio (%) and the X-axis is the year.
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---
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## 🔧 OCI Services Used
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### 1. **OCI Generative AI – Embeddings**
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- Used for vector search on document content.
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```python
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from langchain_community.embeddings.oci_generative_ai import OCIGenAIEmbeddings
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```
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### 2. **OCI Generative AI – LLM (Llama 4 Maverick)**
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- Used to extract structured insights from text + images.
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```python
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from langchain_community.chat_models.oci_generative_ai import ChatOCIGenAI
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```
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---
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## 🔗 Docs & References
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- 📘 [OCI Generative AI Overview](https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm)
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- 📘 [OCI Document Understanding](https://docs.oracle.com/en-us/iaas/Content/document-understanding/using/home.htm)
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---
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## 📄 License
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MIT License — see [LICENSE](LICENSE) for details.

‎ai/generative-ai-service/financial-analysis-chatbot/config.py

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"""
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config file
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- Add the OCID of your compartment
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"""
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COMPARTMENT_ID = ""
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OTHER_MODELS = [
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"meta.llama-4-maverick-17b-128e-instruct-fp8",
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"meta.llama-4-scout-17b-16e-instruct"]
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MODEL_ID = "cohere.command-a-03-2025"

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